Volume 13, Issue 2, December 2015 - IMS Unison …pragyaanmanagement.iuu.ac/upload_dynamic_content/2015...Professor T. J. Kamlanabhan DMS IIT, Madras Dr. S. P. Kala Professor (Retd.),

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Members of Advisory Board

Professor Narendra K. SharmaProfessor Pulin B. NayakHead, Department of Industrial & Management Delhi school of EconomicsEngineeringDelhiIIT, Kanpur

Professor T. J. KamlanabhanDr. S. P. KalaDMS IIT, MadrasProfessor (Retd.), HNB Garhwal University, Srinagar

Professor P. K. ChaubeyProfessor V. K. NangiaIndian Institute of Public AdministrationDepartment of Management StudiesNew DelhiIIT, Roorkee

Professor M. AkbarProfessor D. P. GoyalIIM, LucknowChairperson, Computer CentreMDI, GurgaonProfessor D. L. Sunder

IIM, IndoreProfessor Bhagwati PrasadFormer Director, KIMSProfessor Vipin GuptaDharwad Ros Jaffe Chair Professor of Strategy

Simmons School of Management,Simmons College, Boston, USA

Pragyaan: Journal of Management

Volume 13, Issue 2, December 2015

Patron: Dr. D. K. BandyopadhyayVice ChancellorIMS Unison University, Dehradun

Chief Editor: Dr. Pawan K. AggarwalAssociate Pro Vice ChancellorIMS Unison University, Dehradun

Editor: Dr. K. Ajay Singh HOD, School of Management IMS Unison University, Dehradun

Associate Editor: Mr. Raghav Upadhyai Assistant ProfessorSchool of ManagementIMS Unison University, Dehradun

Panel of Referees

Prof. Prof.

Prof.

Prof.

Prof.

Prof.

Prof. Bobby W. LyallDepartment of ManagementShri Ram Swaroop Memorial Group of Professional CollegesLucknow- 227105

Prof. Timira ShuklaJaganath International Management SchoolKalkaji, New Delhi - 110019

Prof. B. B.TiwariShri Ramswaroop Memorial College of Engineering and Management,Lucknow - 227105

Prof. Anu Singh LatherUniversity School of Management Studies, GGS Indraprastha UniversityDwarka, Delhi 110078

Prof. Prof. Vidya SekhriInstitute of Management Studies,Ghaziabad- 201009

Prof. Simmi AgrawalFinancial Consultant and Visiting Faculty

Prof. Institute of Management & Technology, Ghaziabad- 201001International Management Institute, New Delhi- 110016

Prof. Arvind Kumar Jain College of Management and Economic Studies UPES Dehradun - 248007

Prof. Raju Ganesh SunderCollege of Management and Economic Studies Prof. UPES Dehradun - 248007

Prof. Anita SinghInstitute of Management Studies,Ghaziabad- 201009

V. P. S. AroraRudra Prakash PradhanCollege of Agribusiness ManagementVinod Gupta School of ManagementG B Pant University of Agriculture and TechnologyIIT, Kharagpur- 721302Pantnagar- 263145Dist. Udham Singh NagarHimanshu RaiUttarakhand (India)Indian Institute of Management

Prabandh Nagar, Off Sitapur RoadS. K. Dubey

Lucknow- 226013.Faculty of Management StudiesBanaras Hindu University

GeetikaVaranasi- 221005

School of Management StudiesUttar Pradesh (India)

Motilal Nehru National Institute of TechnologyAllahabad- 211004 Dr. Neeraj Kaushik

Department of Business AdministrationSusmita Mukhopadhyay National Institute of Technology

Vinod Gupta School of Management Kurukshetra- 136117IIT, Kharagpur- 721302 Haryana (India)

Prof. R. K. PandeyFMS, Banaras Hindu UniversityVaranasi- 221005

Prof. Sita MishraInstitute of Management TechnologyRaj Nagar, Post Box No. 137Ghaziabad- 201001, India

Prof. V. K. NangiaIndian Institute of Technology, RoorkeeNH 58, Roorkee, UttarakhandIndia- 247667

Prof. R. C. MishraSchool of Management Studies & CommerceUttarakhand Open UniversityHaldwani-263139

Zillur RahmanDepartment of Management StudiesIndian Institute of Technology, RoorkeeNH 58, Roorkee, UttarakhandIndia- 247667

Sheeba KapilIndian Institute of Foreign TradeIIFT Bhawan

B-21, Qutab Institutional AreaNew Delhi- 110016

Ram SinghIndian Institute of Foreign TradeIIFT BhawanB-21, Qutab Institutional AreaNew Delhi- 110016

From the Chief Editor

It is with much joy and anticipation that we present the December 2015 issue of our journal, Pragyaan: Journal of Management (Pragyaan: JOM). It continues to gain appreciation and accolades as it provides a platform that stimulates and guides the intellectual quest of Management scholars and practitioners.

Pragyaan: JOM is a bi-annual, peer reviewed, open access Journal that brings to the readers high quality stresearch in Management that should help to address the challenges of the 21 century. It is committed to rapid

dissemination of high quality research, and priority is given to the contributions that demonstrate practical usefulness.

This issue of Pragyaan: JOM presents articles that deal with real world problems that are complex in nature.

These cover the areas like balanced scorecard and organisational sustainability , behavior of users of social

networking sites, forecasting generation and utilization of fly ash, influence of retail infrastructure on customer,

impact of green marketing tools on buying behavior, online shopping convenience, cost implications of

business process re-engineering, acquisition and financial performance, entrepreneurial support in

Jharkhand and pre and post acquisition performance of select pharmaceutical companies.

We are thankful to the authors for their scholarly contributions to the Journal. We express our gratitude to our panel of referees for the time and thought invested by them into the papers and for giving us sufficient insights to ensure selection of quality papers. Thanks are also due to Dr. Vijayan Immanuel (Pro VC), Dr. Dilip K. Bandyopadhyay (VC), Dr. M. P. Jain (Chancellor), the members of the Editorial Board, and the members of the Board of Management for their constant guidance and support.

We would like to acknowledge the contribution of Dr. K. Ajay Singh (Editor), Mr. Raghav Upadhyai (Associate

Editor) and all the other faculty members of School of Management for their contribution in preparing the

reader friendly manuscript for the Press.

We invite contributions from the scholars, scientific community and industry practitioners to ensure a continued success of the journal.

We hope our readers find the contents, findings and suggestions contained in this issue of Pragyaan: JOM as informative, stimulating, and of practical relevance. We welcome comments and suggestions for further improvement in the quality of our Journal.

Dr. Pawan K AggarwalAssociate Pro Vice ChancellorIMS Unison University, Dehradun

Panel of Referees

Prof. Prof.

Prof.

Prof.

Prof.

Prof.

Prof. Bobby W. LyallDepartment of ManagementShri Ram Swaroop Memorial Group of Professional CollegesLucknow- 227105

Prof. Timira ShuklaJaganath International Management SchoolKalkaji, New Delhi - 110019

Prof. B. B.TiwariShri Ramswaroop Memorial College of Engineering and Management,Lucknow - 227105

Prof. Anu Singh LatherUniversity School of Management Studies, GGS Indraprastha UniversityDwarka, Delhi 110078

Prof. Prof. Vidya SekhriInstitute of Management Studies,Ghaziabad- 201009

Prof. Simmi AgrawalFinancial Consultant and Visiting Faculty

Prof. Institute of Management & Technology, Ghaziabad- 201001International Management Institute, New Delhi- 110016

Prof. Arvind Kumar Jain College of Management and Economic Studies UPES Dehradun - 248007

Prof. Raju Ganesh SunderCollege of Management and Economic Studies Prof. UPES Dehradun - 248007

Prof. Anita SinghInstitute of Management Studies,Ghaziabad- 201009

V. P. S. AroraRudra Prakash PradhanCollege of Agribusiness ManagementVinod Gupta School of ManagementG B Pant University of Agriculture and TechnologyIIT, Kharagpur- 721302Pantnagar- 263145Dist. Udham Singh NagarHimanshu RaiUttarakhand (India)Indian Institute of Management

Prabandh Nagar, Off Sitapur RoadS. K. Dubey

Lucknow- 226013.Faculty of Management StudiesBanaras Hindu University

GeetikaVaranasi- 221005

School of Management StudiesUttar Pradesh (India)

Motilal Nehru National Institute of TechnologyAllahabad- 211004 Dr. Neeraj Kaushik

Department of Business AdministrationSusmita Mukhopadhyay National Institute of Technology

Vinod Gupta School of Management Kurukshetra- 136117IIT, Kharagpur- 721302 Haryana (India)

Prof. R. K. PandeyFMS, Banaras Hindu UniversityVaranasi- 221005

Prof. Sita MishraInstitute of Management TechnologyRaj Nagar, Post Box No. 137Ghaziabad- 201001, India

Prof. V. K. NangiaIndian Institute of Technology, RoorkeeNH 58, Roorkee, UttarakhandIndia- 247667

Prof. R. C. MishraSchool of Management Studies & CommerceUttarakhand Open UniversityHaldwani-263139

Zillur RahmanDepartment of Management StudiesIndian Institute of Technology, RoorkeeNH 58, Roorkee, UttarakhandIndia- 247667

Sheeba KapilIndian Institute of Foreign TradeIIFT Bhawan

B-21, Qutab Institutional AreaNew Delhi- 110016

Ram SinghIndian Institute of Foreign TradeIIFT BhawanB-21, Qutab Institutional AreaNew Delhi- 110016

From the Chief Editor

It is with much joy and anticipation that we present the December 2015 issue of our journal, Pragyaan: Journal of Management (Pragyaan: JOM). It continues to gain appreciation and accolades as it provides a platform that stimulates and guides the intellectual quest of Management scholars and practitioners.

Pragyaan: JOM is a bi-annual, peer reviewed, open access Journal that brings to the readers high quality stresearch in Management that should help to address the challenges of the 21 century. It is committed to rapid

dissemination of high quality research, and priority is given to the contributions that demonstrate practical usefulness.

This issue of Pragyaan: JOM presents articles that deal with real world problems that are complex in nature.

These cover the areas like balanced scorecard and organisational sustainability , behavior of users of social

networking sites, forecasting generation and utilization of fly ash, influence of retail infrastructure on customer,

impact of green marketing tools on buying behavior, online shopping convenience, cost implications of

business process re-engineering, acquisition and financial performance, entrepreneurial support in

Jharkhand and pre and post acquisition performance of select pharmaceutical companies.

We are thankful to the authors for their scholarly contributions to the Journal. We express our gratitude to our panel of referees for the time and thought invested by them into the papers and for giving us sufficient insights to ensure selection of quality papers. Thanks are also due to Dr. Vijayan Immanuel (Pro VC), Dr. Dilip K. Bandyopadhyay (VC), Dr. M. P. Jain (Chancellor), the members of the Editorial Board, and the members of the Board of Management for their constant guidance and support.

We would like to acknowledge the contribution of Dr. K. Ajay Singh (Editor), Mr. Raghav Upadhyai (Associate

Editor) and all the other faculty members of School of Management for their contribution in preparing the

reader friendly manuscript for the Press.

We invite contributions from the scholars, scientific community and industry practitioners to ensure a continued success of the journal.

We hope our readers find the contents, findings and suggestions contained in this issue of Pragyaan: JOM as informative, stimulating, and of practical relevance. We welcome comments and suggestions for further improvement in the quality of our Journal.

Dr. Pawan K AggarwalAssociate Pro Vice ChancellorIMS Unison University, Dehradun

1. Introduction

The banking industry in UAE is the biggest by the investment value in the Gulf Cooperation Council (GCC) business. As on 2014, UAE banking industry is dominated by twenty three local national banks, which account for more than seventy five percent of total banking investments and assets, whereas twenty eight overseas banks account for the rest (emiratesnbd.com, 2014). Dubai is considered as one of the key international financial hubs in the world. As on 2013, ten UAE based banks rank among the top 500 strongest banks worldwide and additionally four other banks have found their place in the first half of this list (thebanker.com,2014). Emirates NBD has the highest position between UAE banks, which is considered the best bank in UAE and Middle East. (dubanks.com, 2014). Currently, Emirates NBD has more than 9,000 people, representing 70 nationalities, which is considered as one of the top biggest and multicultural diversified organizations in the UAE, and is delivering a continuous high value to its shareholders, customers and employees year over year (emiratesnbd.com, 2014). Since August 2009 till June 2014, the bank has witnessed an average annual growth of around 12% in terms of bank deposits and around 14% in loans disbursement (centralbank.ae, 2014). By third quarter of 2014, Emirates NBD total assets have reached to AED 353.9 billion (US$ 96.4 billion). The Group is running its activities in the UAE, Kingdom of Saudi Arabia, Qatar,

Egypt, United Kingdom, Singapore, India, Indonesia and China. As socially responsible corporation (SRC), Emirates NBD is involved in many SRC functions, concentrating on important foundations in the UAE, in fields of the charity, environment, culture, education, sport and art (emiratesnbd.com 2014).

In 1990, Nolan Norton Institute (the research arm of KPMG) conducted a study suggested a multiple stakeholders' based performance measurement model for an organization. Thus, concept of balanced scorecard was born, which revolutionized the overall perspectives of organizational performance measurement orientation. The new model linked the concept to all major stakeholders of business by redefining KPIs of business through financial, customer, operations/internal business process and employees involvement. Such approach of measurement enhanced the legitimacy of the initiatives as a better tool for sustainable business as it was an improvement from the traditional financial based process towards entire business focus integration and strategic design implementation.

The present research intends to measure the organizational sustainability through adopting the Balanced Scorecard, which is being used in the Retail Banking section of Emirates NBD Bank, Dubai head quarter, since 2007. The retail section is managing three portfolios (individual, small and medium enterprises,

1

ABSTRACT

Measurement of performance of an organization has become a challenging task in the context of constant evolution of business. The issue becomes more complicated, when the organizational structure seems to be complicated, spread across different autonomous, semi-autonomous and cross functional divisions. Emirates NBD Bank, one of the leading banking organization in the middle east has been undergoing the same challenges of evolution and managing sustainability. Moreover, the organization is bound to manage the performance in the emerging organizational complexity and role transformations. As per the decision of top management, retail banking division has been chosen in the exclusive functional divisions for balanced scorecard intervention and the middle management executives have been made responsible for the entire process since last few years. For the purpose of the present study, analysis has been done of data collected through survey based questionnaire from 25 middle management executives of the retail banking division. The analysis has revealed mixed opinions and identified the areas on which, further improvement is required for sustainable growth and improvement in the selected performance indicators from stakeholders' perspectives in the process of implementation of balanced scorecard.

Key Words: Balanced Scorecard, Organizational Sustainability, Emirates NBD Bank

Balanced Scorecard and Organizational Sustainability: An empirical Study from the Perspectives of Middle Management Executives of Retail Banking Division of Emirates NBD Bank, UAE

"Pragyaan: Journal of Management" Volume 13, Issue 2, December 2015

Dr. Indranil Bose *Sredharran Sampath **

*Dean Business Studies, Western International College-Off shore campus of University of Bolton (UAE)**Associate Dean, Westford School of Management (UAE)


CONTENTS

Research Papers/Articles

1. Balanced Scorecard and Organizational Sustainability: An empirical Study from 1the Perspectives of Middle Management Executives of retail banking division of Emirates NBD Bank, UAE Dr. Indranil Bose, Sredharran Sampath

2. Understanding Behavior of the Users of Social Networking Sites 7 Dr. Tripti Barthwal, Dr. Akansha Srivastava

3. Forecasting Generation and Utilization of Fly Ash in India 12M. I. M. Loya, A. M. Rawani

4. Influence of Retail Infrastructure Stimuli on In-Store Customer Experience 18Raghav Upadhyai, Dr. H.S. Grewal

5. Impact of Green Marketing Tools on Buying Behaviour of Indian Consumer 23Trilok Pratap Singh, Dr. Somesh Dhamija, Krishanveer Singh

6. Why Customers Buy Online: Measuring the Underlying Dimensions of 29Online Shopping ConvenienceHarsandaldeep Kaur, Nidhi Sabharwal

7. Entrepreneurial Support in the SSI Sector: A Case Study of Jharkhand 36Dr. Tarak Nath Shaw

8. Pre and Post Acquisition Performance of Select Indian Pharmaceutical Companies 47Reddy Y V, Mayuresh Natekar


1. Introduction

The banking industry in UAE is the biggest by the investment value in the Gulf Cooperation Council (GCC) business. As on 2014, UAE banking industry is dominated by twenty three local national banks, which account for more than seventy five percent of total banking investments and assets, whereas twenty eight overseas banks account for the rest (emiratesnbd.com, 2014). Dubai is considered as one of the key international financial hubs in the world. As on 2013, ten UAE based banks rank among the top 500 strongest banks worldwide and additionally four other banks have found their place in the first half of this list (thebanker.com,2014). Emirates NBD has the highest position between UAE banks, which is considered the best bank in UAE and Middle East. (dubanks.com, 2014). Currently, Emirates NBD has more than 9,000 people, representing 70 nationalities, which is considered as one of the top biggest and multicultural diversified organizations in the UAE, and is delivering a continuous high value to its shareholders, customers and employees year over year (emiratesnbd.com, 2014). Since August 2009 till June 2014, the bank has witnessed an average annual growth of around 12% in terms of bank deposits and around 14% in loans disbursement (centralbank.ae, 2014). By third quarter of 2014, Emirates NBD total assets have reached to AED 353.9 billion (US$ 96.4 billion). The Group is running its activities in the UAE, Kingdom of Saudi Arabia, Qatar,

Egypt, United Kingdom, Singapore, India, Indonesia and China. As socially responsible corporation (SRC), Emirates NBD is involved in many SRC functions, concentrating on important foundations in the UAE, in fields of the charity, environment, culture, education, sport and art (emiratesnbd.com 2014).

In 1990, Nolan Norton Institute (the research arm of KPMG) conducted a study suggested a multiple stakeholders' based performance measurement model for an organization. Thus, concept of balanced scorecard was born, which revolutionized the overall perspectives of organizational performance measurement orientation. The new model linked the concept to all major stakeholders of business by redefining KPIs of business through financial, customer, operations/internal business process and employees involvement. Such approach of measurement enhanced the legitimacy of the initiatives as a better tool for sustainable business as it was an improvement from the traditional financial based process towards entire business focus integration and strategic design implementation.

The present research intends to measure the organizational sustainability through adopting the Balanced Scorecard, which is being used in the Retail Banking section of Emirates NBD Bank, Dubai head quarter, since 2007. The retail section is managing three portfolios (individual, small and medium enterprises,

1

ABSTRACT

Measurement of performance of an organization has become a challenging task in the context of constant evolution of business. The issue becomes more complicated, when the organizational structure seems to be complicated, spread across different autonomous, semi-autonomous and cross functional divisions. Emirates NBD Bank, one of the leading banking organization in the middle east has been undergoing the same challenges of evolution and managing sustainability. Moreover, the organization is bound to manage the performance in the emerging organizational complexity and role transformations. As per the decision of top management, retail banking division has been chosen in the exclusive functional divisions for balanced scorecard intervention and the middle management executives have been made responsible for the entire process since last few years. For the purpose of the present study, analysis has been done of data collected through survey based questionnaire from 25 middle management executives of the retail banking division. The analysis has revealed mixed opinions and identified the areas on which, further improvement is required for sustainable growth and improvement in the selected performance indicators from stakeholders' perspectives in the process of implementation of balanced scorecard.

Key Words: Balanced Scorecard, Organizational Sustainability, Emirates NBD Bank

Balanced Scorecard and Organizational Sustainability: An empirical Study from the Perspectives of Middle Management Executives of Retail Banking Division of Emirates NBD Bank, UAE


Dr. Indranil Bose *Sredharran Sampath **

*Dean Business Studies, Western International College-Off shore campus of University of Bolton (UAE)**Associate Dean, Westford School of Management (UAE)


CONTENTS

Research Papers/Articles

1. Balanced Scorecard and Organizational Sustainability: An empirical Study from 1the Perspectives of Middle Management Executives of retail banking division of Emirates NBD Bank, UAE Dr. Indranil Bose, Sredharran Sampath

2. Understanding Behavior of the Users of Social Networking Sites 7 Dr. Tripti Barthwal, Dr. Akansha Srivastava

3. Forecasting Generation and Utilization of Fly Ash in India 12M. I. M. Loya, A. M. Rawani

4. Influence of Retail Infrastructure Stimuli on In-Store Customer Experience 18Raghav Upadhyai, Dr. H.S. Grewal

5. Impact of Green Marketing Tools on Buying Behaviour of Indian Consumer 23Trilok Pratap Singh, Dr. Somesh Dhamija, Krishanveer Singh

6. Why Customers Buy Online: Measuring the Underlying Dimensions of 29Online Shopping ConvenienceHarsandaldeep Kaur, Nidhi Sabharwal

7. Entrepreneurial Support in the SSI Sector: A Case Study of Jharkhand 36Dr. Tarak Nath Shaw

8. Pre and Post Acquisition Performance of Select Indian Pharmaceutical Companies 47Reddy Y V, Mayuresh Natekar


2

wealth management) with customer base exceeding one million customers.

1.1 Research Objectives

The retail banking division of Emirates NDB Bank is using balanced scorecard since 2007. In this context, the present research paper attempts:

To understand the level of executive engagement at the designing and the implementation of balanced scorecard in the retail banking division of Emirates NBD bank

To evaluate the level of compliance of balanced scorecard perspectives by respective departments under retail banking division of Emirates NBD bank

To study the level of agreeableness of the managerial executives with different achievements as claimed to be attained by implementing balanced scorecard in the retail banking division of Emirates NBD bank

To observe strengths and weaknesses of the practice of implementation of balanced scorecard in the present format in the retail banking division of Emirates NBD bank

To suggest improvements to make balanced scorecard as sustainable instrument for the Emirates NBD bank

2. Review of Literature

Though there are several studies on the Balanced Scorecard, but only few have been found to be establishing the principal model of the Scorecard at the stage of implementation. The availability of research literature is found to be more limited, while coming to the research on banking industry. A study on Austrian, German and Swiss banking organizations (Speckbacher et al. 2003) has revealed that almost sixty percent of the banking organizations in these countries have somehow implemented balanced scorecard in their organizations. Another study by Soderberg (2012), has revealed that none of the banking and financial organizations implemented balanced scorecard across all the divisions and adopted at a limited scale. However, the study has acknowledged that all the surveyed organizations have complied with the original purposes and methods of balanced scorecard implementation as suggested by Kaplan like linking the same with strategic objectives, maintaining functional balanced, understanding cause-effect relations and clear policies about incentives for successful implementation of balanced scorecard. Over the period of time, different measurement metrics have been developed by different scholars in the process of implementation of balanced scorecard in industry. Ahmed Al-Baidhani (2010), in his study has identified bonus scorecard, personal scorecard, process scorecard, KPI

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scorecard, stakeholder scorecard, strategy scorecard, enterprise scorecard, board scorecard, and executive scorecard. Ralph (2011) in his research work based on almost two hundred manufacturing organizations based in Europe, has recommended that for effective implementation of balanced scorecard, each stakeholder's interest must be taken care of separately and separate metrics must be developed. Mehta (2012) has also developed a comprehensive performance measurement metrics related to balanced scorecard implementation in the hospitality industry of South Asia. Though the ideal applicability of different dimensions of balanced scorecard at different stages of business has been categorically described by Kaplan, yet, many subsequent studies have revealed that such structured pattern is not universally followed across different industries. Daniel (2011) has shown in his research that in the banking industry in north America, especially in USA and Canada, balanced scorecard dimensions are chosen collectively according to the demand in the situation. Same phenomenon has been found to be applicable in the research by the same author (Daniel, 2011) regarding implementation method of balanced scorecard. Here also, the researcher has found that instead of rigidly following the recommended steps, almost 60% of the banking organizations create their own mechanisms of implementation. Regarding barriers of implementation of balanced scorecard, different observations have been made by different scholars. Niven (2012) has cited the observation of report, published in the Fortune Magazine and expressed his support with the observations made therein. He has conducted an empirical research on sixty organizations of Greater New York area and found that 70% of the surveyed organizations failed to attain the successful implementation level of balanced scorecard due to vision barriers. Ratnam (2012) has however identified management barrier as the key significant reason in failing proper implementation of balanced scorecard. Ratnam has conducted a study on the failure of implementation of balanced scorecard on twenty six organizations located across different free trade zones in UAE. In that sense, his work is a unique study. Regarding the role of balanced scorecard in ensuring organizational sustainability, different studies have been found in different industries. Kathley (2013) has conducted a significant study on airlines industries in western Europe and has found that top management of most of the companies are quite sure about that, but have remained sceptical on the issue. Rodger and Prince (2014) have found that in the manufacturing and engineering industries in Europe, balanced scorecard as a sustainability tool has been well accepted in many service industries.

However, no such landmark research has come to the knowledge of the researcher, which has been carried out either in the banking industry in UAE or in a retail banking

3

sector, anywhere across the globe. This can be identified as significant research gap in the domain of retail banking and the present study is intended to fill this gap

3. Implementation of Balanced Scorecard at Emirates NBD Bank- An Overview

Regarding the applicability of balanced scorecard, it has been found that Emirates NBD Bank has been using Balanced Scorecard at two levels, i.e., at the business unit level and at the support unit level. At the business unit level, the sustainability of business performance is measured in terms of revenue generation by the branches, product teams, segment teams and direct sales teams. Whereas, at the support units levels, the same is measured through control and service efficiency in terms of major functional processes like HR, finance, accounting, procurement etc. It was also found that as a policy issue, 15% weightage is distributed each to financial perspective, customer perspective, business process perspective and learning and growth perspective. Remaining 40% is dedicated to strategic perspectives (Emirates NBD Bank, 2014).

4. Research Methodology

The present research has been conducted on the basis of the analysis of data collected through structured questionnaire survey from twenty five managerial employees employed in the retail banking division of Emirates NBD Bank, located in UAE. As the bank is one of the fastest growing and largest banking organizations in the region and the researcher found it convenient to administer questionnaire survey and feedback, due to personal acquaintance, the same has been chosen for the present study. The present study is a good example of quantitative and descriptive study, as the same has been conducted on the basis of collected primary data and interpretation of analysis of primary data through standard statistical tools. As Emirates NBD bank uses two types of Balanced Scorecard structure, the researcher has incorporated the same in the questionnaire also. However, the structured questionnaire has emphasised more on the level of executive engagements in implementing the mechanism (as per the perception of the respondents), compliance of balanced scorecard perspectives by the respective departments, level of agreeableness with different achievement as claimed to be attained by implementing balanced scorecard, strengths and weaknesses of the practice of implementation of balanced card in the present format etc. A total number of 25 middle management executives have been surveyed through structured questionnaire across retail business divisions of the bank. As, the survey was done on one to one basis, 100% response could be generated. It took, almost 45 days to complete the survey. The questionnaire had four sections and total 20 questions were asked. On the issues

of level of executive engagements in implementing balanced scorecard (Section 1), 2 questions have been asked; and, on the issues of compliance of balanced scorecard perspectives by respective departments (Section 2) 2 questions have been placed. However, regarding the level of agreeableness with different achievements as claimed to be attained by implementing balanced scorecard (Section 3) 6 questions have been asked. Finally, strengths and weaknesses of the practice of implementation of balanced card in the present format (Section 4) have been reviewed through 10 questions. To analyse the data, standard statistical tools like mean and standard deviations have been applied.

5. Data Analysis and Interpretation

The data analysis shows diverse trends of opinion on different issues. On the issue of level of executive engagement in implementing balanced scorecard, two questions have been asked. The question was asked on 5 point likert scale, indicating 1= never, 2=rarely, 3= some times, 4= regularly and 5= always). Following are the results found on these issues.

Table 1: Level of Executive Engagements in Implementing Balanced Scorecard

Statement/Question Mean Standard Deviation

Level of engagement at the stage 2.3. 043of designing balanced scorecard mechanism for your unit

Level of engagement at the time 4.6 .37of regular implementation of balanced scorecard

On the issue of compliance of balanced scorecard perspectives by respective departments , a standard pattern of response was recorded through 5 point likert scale (indicating 1 as strongly disagreed, 2 disagreed, 3 as neither agreed or disagreed, 4 as agreed and 5 as strongly agreed). The analysis of response pattern shows the following trends:

Table 2: Compliance of Balanced Scorecard Perspectives by Perspective Departments


All functional measurements are 4.3 .23done in compliance with balanced scorecard requirement

All functional targets are set 4.1 . 27according to balanced scorecard objectives

Balanced Scorecard and Organizational Sustainability: An empirical Study.... Balanced Scorecard and Organizational Sustainability: An empirical Study....

"Pragyaan: Journal of Management" Volume 13, Issue 2, December 2015"Pragyaan: Journal of Management" Volume 13, Issue 2, December 2015

2

wealth management) with customer base exceeding one million customers.

1.1 Research Objectives

The retail banking division of Emirates NDB Bank is using balanced scorecard since 2007. In this context, the present research paper attempts:

To understand the level of executive engagement at the designing and the implementation of balanced scorecard in the retail banking division of Emirates NBD bank

To evaluate the level of compliance of balanced scorecard perspectives by respective departments under retail banking division of Emirates NBD bank

To study the level of agreeableness of the managerial executives with different achievements as claimed to be attained by implementing balanced scorecard in the retail banking division of Emirates NBD bank

To observe strengths and weaknesses of the practice of implementation of balanced scorecard in the present format in the retail banking division of Emirates NBD bank

To suggest improvements to make balanced scorecard as sustainable instrument for the Emirates NBD bank


Though there are several studies on the Balanced Scorecard, but only few have been found to be establishing the principal model of the Scorecard at the stage of implementation. The availability of research literature is found to be more limited, while coming to the research on banking industry. A study on Austrian, German and Swiss banking organizations (Speckbacher et al. 2003) has revealed that almost sixty percent of the banking organizations in these countries have somehow implemented balanced scorecard in their organizations. Another study by Soderberg (2012), has revealed that none of the banking and financial organizations implemented balanced scorecard across all the divisions and adopted at a limited scale. However, the study has acknowledged that all the surveyed organizations have complied with the original purposes and methods of balanced scorecard implementation as suggested by Kaplan like linking the same with strategic objectives, maintaining functional balanced, understanding cause-effect relations and clear policies about incentives for successful implementation of balanced scorecard. Over the period of time, different measurement metrics have been developed by different scholars in the process of implementation of balanced scorecard in industry. Ahmed Al-Baidhani (2010), in his study has identified bonus scorecard, personal scorecard, process scorecard, KPI

!

!

!

!

!

scorecard, stakeholder scorecard, strategy scorecard, enterprise scorecard, board scorecard, and executive scorecard. Ralph (2011) in his research work based on almost two hundred manufacturing organizations based in Europe, has recommended that for effective implementation of balanced scorecard, each stakeholder's interest must be taken care of separately and separate metrics must be developed. Mehta (2012) has also developed a comprehensive performance measurement metrics related to balanced scorecard implementation in the hospitality industry of South Asia. Though the ideal applicability of different dimensions of balanced scorecard at different stages of business has been categorically described by Kaplan, yet, many subsequent studies have revealed that such structured pattern is not universally followed across different industries. Daniel (2011) has shown in his research that in the banking industry in north America, especially in USA and Canada, balanced scorecard dimensions are chosen collectively according to the demand in the situation. Same phenomenon has been found to be applicable in the research by the same author (Daniel, 2011) regarding implementation method of balanced scorecard. Here also, the researcher has found that instead of rigidly following the recommended steps, almost 60% of the banking organizations create their own mechanisms of implementation. Regarding barriers of implementation of balanced scorecard, different observations have been made by different scholars. Niven (2012) has cited the observation of report, published in the Fortune Magazine and expressed his support with the observations made therein. He has conducted an empirical research on sixty organizations of Greater New York area and found that 70% of the surveyed organizations failed to attain the successful implementation level of balanced scorecard due to vision barriers. Ratnam (2012) has however identified management barrier as the key significant reason in failing proper implementation of balanced scorecard. Ratnam has conducted a study on the failure of implementation of balanced scorecard on twenty six organizations located across different free trade zones in UAE. In that sense, his work is a unique study. Regarding the role of balanced scorecard in ensuring organizational sustainability, different studies have been found in different industries. Kathley (2013) has conducted a significant study on airlines industries in western Europe and has found that top management of most of the companies are quite sure about that, but have remained sceptical on the issue. Rodger and Prince (2014) have found that in the manufacturing and engineering industries in Europe, balanced scorecard as a sustainability tool has been well accepted in many service industries.

However, no such landmark research has come to the knowledge of the researcher, which has been carried out either in the banking industry in UAE or in a retail banking

3

sector, anywhere across the globe. This can be identified as significant research gap in the domain of retail banking and the present study is intended to fill this gap

3. Implementation of Balanced Scorecard at Emirates NBD Bank- An Overview

Regarding the applicability of balanced scorecard, it has been found that Emirates NBD Bank has been using Balanced Scorecard at two levels, i.e., at the business unit level and at the support unit level. At the business unit level, the sustainability of business performance is measured in terms of revenue generation by the branches, product teams, segment teams and direct sales teams. Whereas, at the support units levels, the same is measured through control and service efficiency in terms of major functional processes like HR, finance, accounting, procurement etc. It was also found that as a policy issue, 15% weightage is distributed each to financial perspective, customer perspective, business process perspective and learning and growth perspective. Remaining 40% is dedicated to strategic perspectives (Emirates NBD Bank, 2014).


The present research has been conducted on the basis of the analysis of data collected through structured questionnaire survey from twenty five managerial employees employed in the retail banking division of Emirates NBD Bank, located in UAE. As the bank is one of the fastest growing and largest banking organizations in the region and the researcher found it convenient to administer questionnaire survey and feedback, due to personal acquaintance, the same has been chosen for the present study. The present study is a good example of quantitative and descriptive study, as the same has been conducted on the basis of collected primary data and interpretation of analysis of primary data through standard statistical tools. As Emirates NBD bank uses two types of Balanced Scorecard structure, the researcher has incorporated the same in the questionnaire also. However, the structured questionnaire has emphasised more on the level of executive engagements in implementing the mechanism (as per the perception of the respondents), compliance of balanced scorecard perspectives by the respective departments, level of agreeableness with different achievement as claimed to be attained by implementing balanced scorecard, strengths and weaknesses of the practice of implementation of balanced card in the present format etc. A total number of 25 middle management executives have been surveyed through structured questionnaire across retail business divisions of the bank. As, the survey was done on one to one basis, 100% response could be generated. It took, almost 45 days to complete the survey. The questionnaire had four sections and total 20 questions were asked. On the issues

of level of executive engagements in implementing balanced scorecard (Section 1), 2 questions have been asked; and, on the issues of compliance of balanced scorecard perspectives by respective departments (Section 2) 2 questions have been placed. However, regarding the level of agreeableness with different achievements as claimed to be attained by implementing balanced scorecard (Section 3) 6 questions have been asked. Finally, strengths and weaknesses of the practice of implementation of balanced card in the present format (Section 4) have been reviewed through 10 questions. To analyse the data, standard statistical tools like mean and standard deviations have been applied.


The data analysis shows diverse trends of opinion on different issues. On the issue of level of executive engagement in implementing balanced scorecard, two questions have been asked. The question was asked on 5 point likert scale, indicating 1= never, 2=rarely, 3= some times, 4= regularly and 5= always). Following are the results found on these issues.

Table 1: Level of Executive Engagements in Implementing Balanced Scorecard


Level of engagement at the stage 2.3. 043of designing balanced scorecard mechanism for your unit

Level of engagement at the time 4.6 .37of regular implementation of balanced scorecard

On the issue of compliance of balanced scorecard perspectives by respective departments , a standard pattern of response was recorded through 5 point likert scale (indicating 1 as strongly disagreed, 2 disagreed, 3 as neither agreed or disagreed, 4 as agreed and 5 as strongly agreed). The analysis of response pattern shows the following trends:

Table 2: Compliance of Balanced Scorecard Perspectives by Perspective Departments


All functional measurements are 4.3 .23done in compliance with balanced scorecard requirement

All functional targets are set 4.1 . 27according to balanced scorecard objectives



On the issue of agreeableness with different achievements as claimed to be attained by implementing balanced scorecard (Section 3), the questions were asked through 5 point likert scale (indicating 1 as strongly disagreed, 2 as disagreed, 3 as neither disagreed or agreed, 4 as agreed and 5 as strongly agreed).

Table 3: Agreeableness with Different Achievements


Improved the market position due 3.9 .07to effective implementation of balanced scorecard

Improved the communication of 4.1 .18 strategy across the organization due to effective implementation of balanced scorecard

Improved accomplishment of 2.9 .37 strategic goals due to effective implementation of balanced scorecard

Improved Efficiency in Operations 3.1 .38 due to effective implementation of balanced scorecard

Improved Financial Performance 3.8 .23due to effective implementation of balanced scorecard

Improved HR process delivery 3.9 .22due to effective implementation of balanced scorecard

On the issue of strengths and weaknesses of the practice of implementation of balanced card in the present format, following trend of observations have been found to be made by the respondents on the basis of 5 point likert scale questionnaire (indicating 1 as strongly disagree, 2 as little agreed, 3 as neither disagreed nor agreed, 4 as agreed and 5 as strongly agreed).

Table 4: Strengths and Weaknesses of the Practice of Implementation of Balanced Scorecard in the Present Format


Current balanced scorecard 3.9 .06format reflects the bank's overall strategy effectively

Current balanced scorecard 3.7 .14format balanceds between financial and non-financial aspects properly

Current balanced scorecard 3.8 .19format has cascaded from senior to middle to junior executives effectively

Current balanced scorecard 2.9 .25format is based on historical data of the bank

Current balanced scorecard is 3.9 .11comprehensive enough

Current balanced scorecard 3.2 .14format is capable enough to develop manpower on sustainable basis

Current balanced scorecard 3.7 .12format has the problem of too many Key Performance Indicators (KPIs)

Current balanced scorecard 2.7 .23format is not effective in tracking data (on time data/real time data)

Current balanced scorecard 2.1 .21format is not effective in measuring process setting

Current balanced scorecard 2.6 .17 format has not covered effectively some quantitative KPIs

6. Findings and Observations

It has been found that more than the design stage, the managerial employees have been involved at the regular implementation of balanced scorecard in the organization.

On the issues of compliance of balanced scorecard perspectives by respective departments, it is also found that almost same level of positive effectiveness has been experienced by the respondents on both the functional measurements and functional goal settings through balanced scorecard.

On the issues of agreeableness with different achievements as claimed to be attained by implementing balanced scorecard, least positive trends in opinion has been observed on the question regarding the improvement of the accomplishment of strategic goals due to effective implementation of balanced scorecard, whereas most positive trend in opinion has been found on the question of improvement in communication of strategy across the organization by effective implementation of balanced scorecard. Improvement in efficiency in operations seems to have been perceived in a less positive manner, yet, on the other issues like improvement in

4

market position, financial performance and HR performance, almost same time of positive temperament has been witnessed.

On the issues of strengths and weaknesses of the practice of implementation of balanced card in the present format, a mixed trend of opinions has been found. On of most the issues evaluated under this section, almost uniform pattern of positive patterns of opinion has been found. However, it has been also recorded that the ability of the current balanced scorecard format to track on time/real time data, in measuring process setting and addressing all aspects of quantitative KPIs has not been perceived so positively.

Moreover, it is to be stated here that maximum division of opinion has been reflected on the issues like improved efficiency in operations due to effective implementation of balanced scorecard and improved accomplishment of strategic goals due to effective implementation of balanced scorecard. Maximum unanimity of opinion is however has been observed on the issue of the reflection of bank's overall strategy effectively through current format of balanced scorecard.

7. Suggestions and Recommendations

Based on the observations in the previous sections, following suggestions and recommendations can be made:

As it has been found that, the current format of balanced scorecard has somehow failed to meet the expectations in terms of tracking on-time/real-time data, which is an important requirement in the process of operational monitoring on continuous basis, the required changes in the format, design and implementation should be incorporated, which not only provides the required data on different business and functional domains, but also will help the organization in cross checking of data across different units of the organization.

It has been also found that the involvement of the managerial employees at the stage of designing of the present format of balanced scorecard was limited. Balanced scorecard format design must be updated on regular intervals and the involvement of executives in the process needs to be more rigorous and participative.

Though, it has been found that most of the respondents have given their positive opinions on most of the functional improvements through balanced scorecard, yet the concern remained as relatively less positive trend is visible on the issue of improvement in attaining strategic goals through balanced scorecard. It somehow indicates that at the functional level, the format is working at a satisfactory

!

!

!

level; though at the strategic level more emphasis should be given in finding the relational links between strategic goal attainment and functional and process integration.

Though, Emirates NBD Bank, set up a task force to initiate the process, back in 2007 and a wide spread training and familiarity programmes have been conducted involving almost 600 operational staffs and 82 managerial staffs at the initial stages, yet a monitoring committee should have been set up to keep tracking the regular developments and understanding system change requirements.

8. Limitations and Future Scope of Research

The limitations of the present study and scope of further research are indicted below.

The present study has been restricted to only 25 respondents and more detailed picture might have been captured by extending the study to a larger number of respondents.

The study could have been more comprehensive by making a comparison, between the managerial employees of retail banking division and other divisions.

A future study can also be done on comparing the perceptions of the managerial employees and non-managerial employees involved in the process of the Emirates NBD Bank.

An inter-organizational level comparative study between Emirates NBD Bank and its competitor which has also implemented balanced scorecard as the tool for business sustainability can also be done to derive key lessons of effectiveness of such practice in the banking industry in UAE.

A more detailed analysis can also be done in future, where the study can be conducted on whether the perceptions on different issues addressed in the present study significantly vary across age groups, experiences and nationalities. The same research approach can be adopted on the comparative basis at the industry level in UAE.

9. Conclusion

It has been understood that balanced scorecard is a comprehensive tool, which can affect entire business dynamics of an organization. However, the system format must be continuously modified, updated and made relevant in the ever changing business scenario. Integrating the same with the organizational culture, strategy and policy will ensure its effectiveness at a higher scale.

!

!

!

!

!

!

5



On the issue of agreeableness with different achievements as claimed to be attained by implementing balanced scorecard (Section 3), the questions were asked through 5 point likert scale (indicating 1 as strongly disagreed, 2 as disagreed, 3 as neither disagreed or agreed, 4 as agreed and 5 as strongly agreed).

Table 3: Agreeableness with Different Achievements


Improved the market position due 3.9 .07to effective implementation of balanced scorecard

Improved the communication of 4.1 .18 strategy across the organization due to effective implementation of balanced scorecard

Improved accomplishment of 2.9 .37 strategic goals due to effective implementation of balanced scorecard

Improved Efficiency in Operations 3.1 .38 due to effective implementation of balanced scorecard

Improved Financial Performance 3.8 .23due to effective implementation of balanced scorecard

Improved HR process delivery 3.9 .22due to effective implementation of balanced scorecard

On the issue of strengths and weaknesses of the practice of implementation of balanced card in the present format, following trend of observations have been found to be made by the respondents on the basis of 5 point likert scale questionnaire (indicating 1 as strongly disagree, 2 as little agreed, 3 as neither disagreed nor agreed, 4 as agreed and 5 as strongly agreed).

Table 4: Strengths and Weaknesses of the Practice of Implementation of Balanced Scorecard in the Present Format


Current balanced scorecard 3.9 .06format reflects the bank's overall strategy effectively

Current balanced scorecard 3.7 .14format balanceds between financial and non-financial aspects properly

Current balanced scorecard 3.8 .19format has cascaded from senior to middle to junior executives effectively

Current balanced scorecard 2.9 .25format is based on historical data of the bank

Current balanced scorecard is 3.9 .11comprehensive enough

Current balanced scorecard 3.2 .14format is capable enough to develop manpower on sustainable basis

Current balanced scorecard 3.7 .12format has the problem of too many Key Performance Indicators (KPIs)

Current balanced scorecard 2.7 .23format is not effective in tracking data (on time data/real time data)

Current balanced scorecard 2.1 .21format is not effective in measuring process setting

Current balanced scorecard 2.6 .17 format has not covered effectively some quantitative KPIs

6. Findings and Observations

It has been found that more than the design stage, the managerial employees have been involved at the regular implementation of balanced scorecard in the organization.

On the issues of compliance of balanced scorecard perspectives by respective departments, it is also found that almost same level of positive effectiveness has been experienced by the respondents on both the functional measurements and functional goal settings through balanced scorecard.

On the issues of agreeableness with different achievements as claimed to be attained by implementing balanced scorecard, least positive trends in opinion has been observed on the question regarding the improvement of the accomplishment of strategic goals due to effective implementation of balanced scorecard, whereas most positive trend in opinion has been found on the question of improvement in communication of strategy across the organization by effective implementation of balanced scorecard. Improvement in efficiency in operations seems to have been perceived in a less positive manner, yet, on the other issues like improvement in

4

market position, financial performance and HR performance, almost same time of positive temperament has been witnessed.

On the issues of strengths and weaknesses of the practice of implementation of balanced card in the present format, a mixed trend of opinions has been found. On of most the issues evaluated under this section, almost uniform pattern of positive patterns of opinion has been found. However, it has been also recorded that the ability of the current balanced scorecard format to track on time/real time data, in measuring process setting and addressing all aspects of quantitative KPIs has not been perceived so positively.

Moreover, it is to be stated here that maximum division of opinion has been reflected on the issues like improved efficiency in operations due to effective implementation of balanced scorecard and improved accomplishment of strategic goals due to effective implementation of balanced scorecard. Maximum unanimity of opinion is however has been observed on the issue of the reflection of bank's overall strategy effectively through current format of balanced scorecard.

7. Suggestions and Recommendations

Based on the observations in the previous sections, following suggestions and recommendations can be made:

As it has been found that, the current format of balanced scorecard has somehow failed to meet the expectations in terms of tracking on-time/real-time data, which is an important requirement in the process of operational monitoring on continuous basis, the required changes in the format, design and implementation should be incorporated, which not only provides the required data on different business and functional domains, but also will help the organization in cross checking of data across different units of the organization.

It has been also found that the involvement of the managerial employees at the stage of designing of the present format of balanced scorecard was limited. Balanced scorecard format design must be updated on regular intervals and the involvement of executives in the process needs to be more rigorous and participative.

Though, it has been found that most of the respondents have given their positive opinions on most of the functional improvements through balanced scorecard, yet the concern remained as relatively less positive trend is visible on the issue of improvement in attaining strategic goals through balanced scorecard. It somehow indicates that at the functional level, the format is working at a satisfactory

!

!

!

level; though at the strategic level more emphasis should be given in finding the relational links between strategic goal attainment and functional and process integration.

Though, Emirates NBD Bank, set up a task force to initiate the process, back in 2007 and a wide spread training and familiarity programmes have been conducted involving almost 600 operational staffs and 82 managerial staffs at the initial stages, yet a monitoring committee should have been set up to keep tracking the regular developments and understanding system change requirements.

8. Limitations and Future Scope of Research

The limitations of the present study and scope of further research are indicted below.

The present study has been restricted to only 25 respondents and more detailed picture might have been captured by extending the study to a larger number of respondents.

The study could have been more comprehensive by making a comparison, between the managerial employees of retail banking division and other divisions.

A future study can also be done on comparing the perceptions of the managerial employees and non-managerial employees involved in the process of the Emirates NBD Bank.

An inter-organizational level comparative study between Emirates NBD Bank and its competitor which has also implemented balanced scorecard as the tool for business sustainability can also be done to derive key lessons of effectiveness of such practice in the banking industry in UAE.

A more detailed analysis can also be done in future, where the study can be conducted on whether the perceptions on different issues addressed in the present study significantly vary across age groups, experiences and nationalities. The same research approach can be adopted on the comparative basis at the industry level in UAE.

9. Conclusion

It has been understood that balanced scorecard is a comprehensive tool, which can affect entire business dynamics of an organization. However, the system format must be continuously modified, updated and made relevant in the ever changing business scenario. Integrating the same with the organizational culture, strategy and policy will ensure its effectiveness at a higher scale.

!

!

!

!

!

!

5



References

Al-Baidhani, A. (2010). The Use of Balanced Scorecard as a Tool for Performance Management and Planning, International Journal of Quality Science, Vol.16(3), pp. 56-67.

Daniel, P. (2011). Balanced Scorecard and profit centre management: A study on selected banks in North America, Journal of Business and Economics, Vol. 3(2), pp. 23-36.

dubanks.com (2014). [Online], http://dubanks.com/ [Accessed December 2014].

emiratesnbd.com (2014). [Online], http://www. emiratesnbd.com/Aboutus/ [Accessed December 2014].

Emirates NBD Bank (2014). Training Manual for retail managers, pp. 45-59.

Kathley, R. (2013). Performance indicator and Balanced Scorecard in aviation industry in Western market, Journal of Business Sustainability, Vol.18(4), pp. 37-52.

Mehta, C. (2012). How to measure service quality through balanced scorecard: a study on hospitality industry in selected SARRC countries, International Journal of Science, Commerce and Management, Vol.12(4), pp.70-1103.

Niven, P. R. (2012). Balanced Scorecard: Step-by- step,. John Wiley & Sons, New York, USA, pp. 67-83.

Ralph, D. (2011). Innovation, Sustainability and measurements: Study from manufacturing industry in Europe and America (2000-2010), Journal of Innovation and Sustainability, Vol. 56(2), pp. 30-58.

Ratnam, C. K. (2012). Functional barrier to leadership challenge, a comparative study in middle east, Journal of Leadership and Performance, Vol. 5(1), pp. 67-82.

Rodger, D. & Prince, A. (2014). Balanced scorecard and industrial growth: a sustainability study in European manufacturing industry, International Journal of Management Research and Theories, Vol. 30(3), pp. 189-230.

Soderberg, M. (2013). The Balanced Scorecard: structure and use in Canadian organizations, International Journal of Business, Commerce and education, Vol. 5(1), pp. 23-35.

Speckbacher, T., Francis, K. & George, S. (2003). A study on Balanced Scorecard implementation in banking sector: a comprehensive study on selected European banking institutions, International Journal of Financial Economics and Monetary Policy, Vol. 29(1), pp. 567-591.

6

1. Introduction

A few years ago, the idea of an online social network was not only unheard of but was also unthinkable. But, internet which in itself has been a marvelous invention of mankind is in itself a creator of new trends and technological advancements with each passing day. While the web has always provided a way for people to make connections with one another, social networking sites made it easier than ever to find old friends and make new ones. Today, we hardly find any educated person who has not heard of Facebook, MySpace, Twitter,.Linkedin or other social networks. With the introduction of smart phone, the social networking sites are now at just a thumb's press away.

Social Networking Sites (SNS) is the phrase used to describe any website that enables users to create public profiles within that Website and form relationships with other users of the same website who access their profiles. It is simply a way to use our computer with an internet connection to connect with people all around the world. These sites allow a person to connect both on a personal & professional level. According to Boyd & Ellison (2008), SNSs are web-based services that allow individuals to

(i) construct a public or semi-public profile within a bounded system,

(ii) articulate a list of other users with whom they share a connection, and

(iii) view and traverse their list of connections and those made by others within the system.

1.1 Literature Review

Studies of human conversation have documented that 30–40% of everyday speech is used to relay information to others about one's private experiences or personal relationships (Dunbar, Duncan & Mariott, 1997). Through

ABSTRACT

Online social networks have emerged as the new way in which people connect socially. Social networking websites connect users to familiar and new people through mutual acquaintances and common interests. Today, use of Social Networking Sites (SNS) is a major activity for internet users from a wide range of demographic groups. The present study aims to understand the behavior of SNS users, and whether usage of SNS gives them pleasure or not. It is based on the survey of respondents from across different regions.

Key Words: Neutral Operants, Reinforcers, Punishers.

Understanding Behavior of the Users of Social Networking Sites

a series of experiments, the researchers at Harvard University (Diana, Tamir & Jason), learned that the act of disclosing information about oneself activates the same part of the brain that is associated with the sensation of pleasure, the same pleasure that we get from eating food, getting money or having sex. In the experiments, the Harvard researchers asked test subjects a series of questions about their and others' opinions while hooked up to an MRI machine. The researchers found that the regions of the brain associated with reward were strongly engaged when people were talking about themselves, and less engaged when they were talking about someone else.

Test subjects indicated that they would turn down money (a few cents) to talk about someone else, preferring to talk about themselves instead. Also, researchers performed a secondary experiment that was geared to help them learn how important having an audience to listen is to a person's self-disclosure. Through the secondary experiment, researchers found that when people got to share their thoughts with a friend or family member, there was a larger amount of activity in the reward region of their brain, and less of a reward sensation when they were told their thoughts would be kept private.

Nauert (2010) had a similar response when students expressed hatred for the loss of personal connections. The students felt that the strength of these relationships was based entirely on their use of social media. Ultimately, both studies arrived at similar conclusions where students felt that they were isolated from their friends and family in the absence of text messaging or Facebook.

According to McQuail (1994), there are four main motivational needs within a person: (i) information, (ii) entertainment, (iii) social interaction, and (iv) personal identity. An article published in the Times of India, dated June 14, 2012 mentions that Shashank Kapur,

7

Dr. Tripti Barthwal *Dr. Akansha Srivastava **

* Professor, LBS Institute of Management & Development Studies, Lucknow**Associate Professor, LBS Institute of Management & Development Studies, Lucknow

Balanced Scorecard and Organizational Sustainability: An empirical Study....


References

Al-Baidhani, A. (2010). The Use of Balanced Scorecard as a Tool for Performance Management and Planning, International Journal of Quality Science, Vol.16(3), pp. 56-67.

Daniel, P. (2011). Balanced Scorecard and profit centre management: A study on selected banks in North America, Journal of Business and Economics, Vol. 3(2), pp. 23-36.

dubanks.com (2014). [Online], http://dubanks.com/ [Accessed December 2014].

emiratesnbd.com (2014). [Online], http://www. emiratesnbd.com/Aboutus/ [Accessed December 2014].

Emirates NBD Bank (2014). Training Manual for retail managers, pp. 45-59.

Kathley, R. (2013). Performance indicator and Balanced Scorecard in aviation industry in Western market, Journal of Business Sustainability, Vol.18(4), pp. 37-52.

Mehta, C. (2012). How to measure service quality through balanced scorecard: a study on hospitality industry in selected SARRC countries, International Journal of Science, Commerce and Management, Vol.12(4), pp.70-1103.

Niven, P. R. (2012). Balanced Scorecard: Step-by- step,. John Wiley & Sons, New York, USA, pp. 67-83.

Ralph, D. (2011). Innovation, Sustainability and measurements: Study from manufacturing industry in Europe and America (2000-2010), Journal of Innovation and Sustainability, Vol. 56(2), pp. 30-58.

Ratnam, C. K. (2012). Functional barrier to leadership challenge, a comparative study in middle east, Journal of Leadership and Performance, Vol. 5(1), pp. 67-82.

Rodger, D. & Prince, A. (2014). Balanced scorecard and industrial growth: a sustainability study in European manufacturing industry, International Journal of Management Research and Theories, Vol. 30(3), pp. 189-230.

Soderberg, M. (2013). The Balanced Scorecard: structure and use in Canadian organizations, International Journal of Business, Commerce and education, Vol. 5(1), pp. 23-35.

Speckbacher, T., Francis, K. & George, S. (2003). A study on Balanced Scorecard implementation in banking sector: a comprehensive study on selected European banking institutions, International Journal of Financial Economics and Monetary Policy, Vol. 29(1), pp. 567-591.

6

1. Introduction

A few years ago, the idea of an online social network was not only unheard of but was also unthinkable. But, internet which in itself has been a marvelous invention of mankind is in itself a creator of new trends and technological advancements with each passing day. While the web has always provided a way for people to make connections with one another, social networking sites made it easier than ever to find old friends and make new ones. Today, we hardly find any educated person who has not heard of Facebook, MySpace, Twitter,.Linkedin or other social networks. With the introduction of smart phone, the social networking sites are now at just a thumb's press away.

Social Networking Sites (SNS) is the phrase used to describe any website that enables users to create public profiles within that Website and form relationships with other users of the same website who access their profiles. It is simply a way to use our computer with an internet connection to connect with people all around the world. These sites allow a person to connect both on a personal & professional level. According to Boyd & Ellison (2008), SNSs are web-based services that allow individuals to

(i) construct a public or semi-public profile within a bounded system,

(ii) articulate a list of other users with whom they share a connection, and

(iii) view and traverse their list of connections and those made by others within the system.

1.1 Literature Review

Studies of human conversation have documented that 30–40% of everyday speech is used to relay information to others about one's private experiences or personal relationships (Dunbar, Duncan & Mariott, 1997). Through

ABSTRACT

Online social networks have emerged as the new way in which people connect socially. Social networking websites connect users to familiar and new people through mutual acquaintances and common interests. Today, use of Social Networking Sites (SNS) is a major activity for internet users from a wide range of demographic groups. The present study aims to understand the behavior of SNS users, and whether usage of SNS gives them pleasure or not. It is based on the survey of respondents from across different regions.

Key Words: Neutral Operants, Reinforcers, Punishers.

Understanding Behavior of the Users of Social Networking Sites

a series of experiments, the researchers at Harvard University (Diana, Tamir & Jason), learned that the act of disclosing information about oneself activates the same part of the brain that is associated with the sensation of pleasure, the same pleasure that we get from eating food, getting money or having sex. In the experiments, the Harvard researchers asked test subjects a series of questions about their and others' opinions while hooked up to an MRI machine. The researchers found that the regions of the brain associated with reward were strongly engaged when people were talking about themselves, and less engaged when they were talking about someone else.

Test subjects indicated that they would turn down money (a few cents) to talk about someone else, preferring to talk about themselves instead. Also, researchers performed a secondary experiment that was geared to help them learn how important having an audience to listen is to a person's self-disclosure. Through the secondary experiment, researchers found that when people got to share their thoughts with a friend or family member, there was a larger amount of activity in the reward region of their brain, and less of a reward sensation when they were told their thoughts would be kept private.

Nauert (2010) had a similar response when students expressed hatred for the loss of personal connections. The students felt that the strength of these relationships was based entirely on their use of social media. Ultimately, both studies arrived at similar conclusions where students felt that they were isolated from their friends and family in the absence of text messaging or Facebook.

According to McQuail (1994), there are four main motivational needs within a person: (i) information, (ii) entertainment, (iii) social interaction, and (iv) personal identity. An article published in the Times of India, dated June 14, 2012 mentions that Shashank Kapur,

7

Dr. Tripti Barthwal *Dr. Akansha Srivastava **

* Professor, LBS Institute of Management & Development Studies, Lucknow**Associate Professor, LBS Institute of Management & Development Studies, Lucknow

Balanced Scorecard and Organizational Sustainability: An empirical Study....


behavioural psychologist, explains that such online behaviour takes root in American psychologist Abraham Maslow's theory on the three basic human psychological needs — love, affection and a sense of belonging and the constant updates, photo albums and profile stalking is an attempt to seek attention and a sense of belonging.

The behavior underlying usage of Social Networking Sites can also be explained by B. F. Skinner's theory of operant conditioning (McLeod, 2007). Operant conditioning can be described as a process that attempts to modify behavior through the use of positive and negative reinforcement. Through operant conditioning, an individual makes an association between a particular behavior and a consequence. Skinner believed that the best way to understand behavior is to look at the causes of an action and its consequences. Skinner identified three types of responses or operant that can follow behavior.

• Neutral operants: Responses from the environment that neither increase nor decrease the probability of a behavior being repeated.

• Reinforcers: Responses from the environment that increase the probability of a behavior being repeated. Reinforcers can be either positive or negative.

• Punishers: Responses from the environment that decrease the likelihood of a behavior being repeated. Punishment weakens behavior.

2. Objectives & Methodology

The study has been designed with the following objectives:

! Understanding the behaviour of SNS users.

! Finding out whether people are comfortable in disclosing information about self.

! Assessing to what extent people enjoy getting information about others.

! To ascertain whether accessing SNS satisfies social needs of users.

! Identifying what makes accessing SNS a pleasurable experience for SNS users.

Keeping into view the above objectives, the research was conducted using exploratory research design. For collection of primary data, a questionnaire containing 20 statements based on the objectives was constructed on a 5 point Likert scale. Secondary data was collected through journals & internet. The universe of the study is India & the researchers have drawn 200 respondents trying to cover the different regions. The analysis was done on SPSS by applying Descriptive Statistics & Cross Tabulation.

3. Data Analysis & Interpretation

Objective 1: Understanding the behaviour of SNS users.

For understanding the behaviour of SNS users researcher has to analyse every statement of the questionnaire. There are a few positive statements and a few negative statements in the questionnaire (Refer Table1: which is generated by using Frequencies under Descriptive Statistics in SPSS).

Interpretation: From Table1 (Row 14) it is clear that in India about 38% people use SNS for satisfying their social need of remaining connected. Majority of respondents have accepted that they do not feel uncomfortable when they find that others have more online friends than them (Row 2). They agree that online relationship is of poorer quality than face-to-face relationship (Row 12). Respondents do not love to share information about themselves with others (Row 17). Most of the respondents feel delighted in receiving favourable comments (Row18). The lesser is the time gap between posting something & getting a favourable comment on it, the happier they feel (Row 19).

Objective 2: Finding out whether people are comfortable in disclosing information about self.

From Table1 it is clear that about 49% respondents are comfortable in disclosing information about self. Now this is analysed on the basis of age, gender and marital status of the respondents. For this Crosstab under Descriptive Statistics in SPSS has been used. The processed information is given in Table 2.

Interpretation: From Table 2, it is clear that younger respondents (below 20 years), those between 40-50 years, male respondents and single respondents are more comfortable in disclosing about themselves through SNS in comparison to respondents of older age group, female respondents and married respondents.

Objective 3: Assessing to what extent people enjoy getting information about others.

From Table1 (Row 6), it is clear that about 48% respondents feel that getting information about activities of others gives pleasure. Now, this is analysed with reference to age, gender and marital status of the respondents. For this Crosstabs under Descriptive Statistics in SPSS has been used. The processed information is given in Table 3.

Interpretation: From Table 3, it is clearly seen about 50% respondents feel that getting information about activities of others gives more pleasure to the respondents of each age group except the age group between 40-50 years probably because of more work pressure and higher accountability towards their personal & professional roles. Female and single respondents are more interested in getting information about other's activities in comparison to male and married respondents.

Objective 4: To ascertain whether accessing SNS satisfies social needs of users.

8

AppendixTable1: Behaviour of SNS Users

S No. Statements Respondents RespondentAgreement Disagreement

1 I deliberately give favourable comments to others to avoid unnecessary 33.3% 50%conflicts.

2 It bothers me when I find that others have more friends on SNS than me. 14.3% 73.8%

3 I hate unfavourable comments. 42.8% 41.7%

4 I actually like all the people with whom i am Friends on SNS. 40.4% 35.7%

5 I am comfortable in disclosing about myself through SNS. 48.8% 41.7%

6 Getting information about activities of others gives me pleasure. 48% 28.6%

7 I access SNS because everybody does it & if i don't i will be called 29.8% 59.5%outdated.

8 I put in a lot of effort to keep relationships created through SNS going. 30.9% 46.2%

9 If I do not get comments on my post my eagerness to post the next time decreases. 33.3% 56%

10 I withdraw & never post something similar again if i get lots of negative 33.3% 47.6%comments on it.

11 I make sure to give even a fake favourable comment to someone who 32.1% 53.6%has given me a favourable comment in the past so that i receive a positive comment in future as well.

12 Online relationship is of better quality than face to face relationships. 20.2% 60.7%

13 SNS help me to escape the daily frustrations & low phases. 39.3% 44.1%

14 After connecting with SNS, i feel that my social needs have been satisfied. 38.1% 44.1%

15 SNS gives me the convenience of connecting with people at my 44.1% 35.7%convenience without bothering about time or physical distances.

16 I always get genuine comments from others. 51.1% 11.9%

17 I love to share about my day to day activities with others. 23.8% 61.9%

18 I feel delighted to receive a favourable comment 86.9% 6%

19 The lesser the gap between posting a comment & getting a favourable 64.3% 14.3%response, the better I feel

20 I often talk to my friends more online than offline 53% 37.4%

Understanding Behavior of the Users of Social Networking SitesUnderstanding Behavior of the Users of Social Networking Sites


Table1 (Row 14) clearly shows that 38.1% of respondents agree while 44.1% disagree with the statement that after connecting with SNS, their social needs have been satisfied. Now their responses have been analysed with reference to their age, gender and marital status. The processed information given in Table 4.

Interpretation: From Table 4, it is clear that after connecting with SNS, the social needs of younger age group are more satisfied and this satisfaction level decreases with increase in age. There is a very minute

difference in this satisfaction between males and females. Social needs of single respondents are more satisfied than married respondents.

Objective 5: Identifying what makes accessing SNS a pleasurable experience for SNS users.

From Table 1, it is found that there are 5 major factors which make a SNS a pleasurable experience for SNS users. These are given in Table 5.

(Insert Table 5 from Appendix)

9

behavioural psychologist, explains that such online behaviour takes root in American psychologist Abraham Maslow's theory on the three basic human psychological needs — love, affection and a sense of belonging and the constant updates, photo albums and profile stalking is an attempt to seek attention and a sense of belonging.

The behavior underlying usage of Social Networking Sites can also be explained by B. F. Skinner's theory of operant conditioning (McLeod, 2007). Operant conditioning can be described as a process that attempts to modify behavior through the use of positive and negative reinforcement. Through operant conditioning, an individual makes an association between a particular behavior and a consequence. Skinner believed that the best way to understand behavior is to look at the causes of an action and its consequences. Skinner identified three types of responses or operant that can follow behavior.

• Neutral operants: Responses from the environment that neither increase nor decrease the probability of a behavior being repeated.

• Reinforcers: Responses from the environment that increase the probability of a behavior being repeated. Reinforcers can be either positive or negative.

• Punishers: Responses from the environment that decrease the likelihood of a behavior being repeated. Punishment weakens behavior.

2. Objectives & Methodology

The study has been designed with the following objectives:

! Understanding the behaviour of SNS users.

! Finding out whether people are comfortable in disclosing information about self.

! Assessing to what extent people enjoy getting information about others.

! To ascertain whether accessing SNS satisfies social needs of users.

! Identifying what makes accessing SNS a pleasurable experience for SNS users.

Keeping into view the above objectives, the research was conducted using exploratory research design. For collection of primary data, a questionnaire containing 20 statements based on the objectives was constructed on a 5 point Likert scale. Secondary data was collected through journals & internet. The universe of the study is India & the researchers have drawn 200 respondents trying to cover the different regions. The analysis was done on SPSS by applying Descriptive Statistics & Cross Tabulation.


Objective 1: Understanding the behaviour of SNS users.

For understanding the behaviour of SNS users researcher has to analyse every statement of the questionnaire. There are a few positive statements and a few negative statements in the questionnaire (Refer Table1: which is generated by using Frequencies under Descriptive Statistics in SPSS).

Interpretation: From Table1 (Row 14) it is clear that in India about 38% people use SNS for satisfying their social need of remaining connected. Majority of respondents have accepted that they do not feel uncomfortable when they find that others have more online friends than them (Row 2). They agree that online relationship is of poorer quality than face-to-face relationship (Row 12). Respondents do not love to share information about themselves with others (Row 17). Most of the respondents feel delighted in receiving favourable comments (Row18). The lesser is the time gap between posting something & getting a favourable comment on it, the happier they feel (Row 19).

Objective 2: Finding out whether people are comfortable in disclosing information about self.

From Table1 it is clear that about 49% respondents are comfortable in disclosing information about self. Now this is analysed on the basis of age, gender and marital status of the respondents. For this Crosstab under Descriptive Statistics in SPSS has been used. The processed information is given in Table 2.

Interpretation: From Table 2, it is clear that younger respondents (below 20 years), those between 40-50 years, male respondents and single respondents are more comfortable in disclosing about themselves through SNS in comparison to respondents of older age group, female respondents and married respondents.

Objective 3: Assessing to what extent people enjoy getting information about others.

From Table1 (Row 6), it is clear that about 48% respondents feel that getting information about activities of others gives pleasure. Now, this is analysed with reference to age, gender and marital status of the respondents. For this Crosstabs under Descriptive Statistics in SPSS has been used. The processed information is given in Table 3.

Interpretation: From Table 3, it is clearly seen about 50% respondents feel that getting information about activities of others gives more pleasure to the respondents of each age group except the age group between 40-50 years probably because of more work pressure and higher accountability towards their personal & professional roles. Female and single respondents are more interested in getting information about other's activities in comparison to male and married respondents.

Objective 4: To ascertain whether accessing SNS satisfies social needs of users.

8

AppendixTable1: Behaviour of SNS Users

S No. Statements Respondents RespondentAgreement Disagreement

1 I deliberately give favourable comments to others to avoid unnecessary 33.3% 50%conflicts.

2 It bothers me when I find that others have more friends on SNS than me. 14.3% 73.8%

3 I hate unfavourable comments. 42.8% 41.7%

4 I actually like all the people with whom i am Friends on SNS. 40.4% 35.7%

5 I am comfortable in disclosing about myself through SNS. 48.8% 41.7%

6 Getting information about activities of others gives me pleasure. 48% 28.6%

7 I access SNS because everybody does it & if i don't i will be called 29.8% 59.5%outdated.

8 I put in a lot of effort to keep relationships created through SNS going. 30.9% 46.2%

9 If I do not get comments on my post my eagerness to post the next time decreases. 33.3% 56%

10 I withdraw & never post something similar again if i get lots of negative 33.3% 47.6%comments on it.

11 I make sure to give even a fake favourable comment to someone who 32.1% 53.6%has given me a favourable comment in the past so that i receive a positive comment in future as well.

12 Online relationship is of better quality than face to face relationships. 20.2% 60.7%

13 SNS help me to escape the daily frustrations & low phases. 39.3% 44.1%

14 After connecting with SNS, i feel that my social needs have been satisfied. 38.1% 44.1%

15 SNS gives me the convenience of connecting with people at my 44.1% 35.7%convenience without bothering about time or physical distances.

16 I always get genuine comments from others. 51.1% 11.9%

17 I love to share about my day to day activities with others. 23.8% 61.9%

18 I feel delighted to receive a favourable comment 86.9% 6%

19 The lesser the gap between posting a comment & getting a favourable 64.3% 14.3%response, the better I feel

20 I often talk to my friends more online than offline 53% 37.4%



Table1 (Row 14) clearly shows that 38.1% of respondents agree while 44.1% disagree with the statement that after connecting with SNS, their social needs have been satisfied. Now their responses have been analysed with reference to their age, gender and marital status. The processed information given in Table 4.

Interpretation: From Table 4, it is clear that after connecting with SNS, the social needs of younger age group are more satisfied and this satisfaction level decreases with increase in age. There is a very minute

difference in this satisfaction between males and females. Social needs of single respondents are more satisfied than married respondents.

Objective 5: Identifying what makes accessing SNS a pleasurable experience for SNS users.

From Table 1, it is found that there are 5 major factors which make a SNS a pleasurable experience for SNS users. These are given in Table 5.

(Insert Table 5 from Appendix)

9

10

Interpretation: Table 5, shows top 5 reasons which makes accessing SNS a pleasurable experience for SNS users. These factors are as follows:

! Receiving a favourable comment.

! Lesser gap between posting a message & getting a favourable comment for it.

! Facility of communicating with friends online.

! Belief that comments from others are genuine.

! High comfort level & pleasure in disclosing about self through SNS.

4. Conclusions

The study led to the following conclusions:

Social Networking Sites satisfy social needs of younger, male & single users.

Respondents, particularly under 20 years & between 40-50 years, males & singles are very comfortable in disclosing information about self to others.

The lesser the gap between posting a message & getting favorable comments, the more is the pleasure of users.

Receiving information about the activities of others gives immense pleasure.

Though online relations are of poorer quality than face-to-face relationships but they provide the convenience of connecting with others whenever the user wants without bothering for physical distances.

Respondents feel that they get genuine comments from others.

References

Boyd D. M., Ellison N. B. (2008). Social Network Sites: Definition, History, and Scholarship. J Comput Mediat Comm., Vol. 13, pp. 210–230.

Dunbar, R., Duncan, N. & Marriot (1997). A: Human Conversational Behaviour, Human Nature, Volume 8, Issue 3, pp. 231-246.

Diana, I., Tamir and Jason, P. Mitchell., Disclosing Information about the Self is Intrinsically Rewarding. http://wjh.harvard.edu/~dtamir/Tamir-PNAS-2012.pdf

Nauert, R. (2010), College Students 'Addicted' to Social Med ia . L i ve Sc i ence , Ap r i l 23 , 2010 http://www.livescience.com, accessed on March 21, 2014

McQuail, D. (1994). Mass Communication Theory: An Introduction. Sage, London.

McLeod, S. A. (2007). B. F. Skinner | Operant Conditioning - Simply Psychology. Retrieved from ht tp://www.s implypsychology.org/operant-conditioning.html

h t t p : / / t i m e s o f i n d i a . i n d i a t i m e s . c o m / l i f e -style/fashion/style-guide/Addicted-to-Social-Network/articleshow/10968618.cms accessed on March 21, 2014

11

Table 3: Extent to which Information About Others is Enjoyable

Statement Pattern Parameters Respondents Agreement

Getting information about activities

of others gives pleasure 20-30 years 49.1%

30-40 years 50%

40-50 years 33.3%

More than 50 years 50%

Gender Male 45.8%

Female 52.8%

Marital Status Single 50.9%

Married 44.8%

Table 4: SNS Satisfy Social Needs


After connecting with SNS, Age Up to 20 years 50%

I feel that my social needs 20-30 years 45.9%

have been satisfied 30-40 years 18.7%

40-50 years 0%


Gender Male 37.5%

Female 38.9%


Married 27.5%

Age Up to 20 years 50%

Table 5: Reasons Making SNS a Pleasurable Experience

S. No. Factors Respondents Agreement

1. I feel delighted to receive a favourable comment 86.9%

2. The lesser the gap between posting a comment & getting a favourable 64.3%response, the better I feel

3. I often talk to my friends more online than offline 53%

4. I always get genuine comments from others. 51.1%

5. I am comfortable in disclosing about myself through SNS. 48.8%



Table 2: Comfort Level in Disclosing Information About Self


I am comfortable in disclosing

about myself through SNS 20-30 years 37.7%

30-40 years 25%

40-50 years 66.7%


Gender Male 37.5%

Female 33.3%


Married 20.6%


10

Interpretation: Table 5, shows top 5 reasons which makes accessing SNS a pleasurable experience for SNS users. These factors are as follows:

! Receiving a favourable comment.

! Lesser gap between posting a message & getting a favourable comment for it.

! Facility of communicating with friends online.

! Belief that comments from others are genuine.

! High comfort level & pleasure in disclosing about self through SNS.

4. Conclusions

The study led to the following conclusions:

Social Networking Sites satisfy social needs of younger, male & single users.

Respondents, particularly under 20 years & between 40-50 years, males & singles are very comfortable in disclosing information about self to others.

The lesser the gap between posting a message & getting favorable comments, the more is the pleasure of users.

Receiving information about the activities of others gives immense pleasure.

Though online relations are of poorer quality than face-to-face relationships but they provide the convenience of connecting with others whenever the user wants without bothering for physical distances.

Respondents feel that they get genuine comments from others.

References

Boyd D. M., Ellison N. B. (2008). Social Network Sites: Definition, History, and Scholarship. J Comput Mediat Comm., Vol. 13, pp. 210–230.

Dunbar, R., Duncan, N. & Marriot (1997). A: Human Conversational Behaviour, Human Nature, Volume 8, Issue 3, pp. 231-246.

Diana, I., Tamir and Jason, P. Mitchell., Disclosing Information about the Self is Intrinsically Rewarding. http://wjh.harvard.edu/~dtamir/Tamir-PNAS-2012.pdf

Nauert, R. (2010), College Students 'Addicted' to Social Med ia . L i ve Sc i ence , Ap r i l 23 , 2010 http://www.livescience.com, accessed on March 21, 2014

McQuail, D. (1994). Mass Communication Theory: An Introduction. Sage, London.

McLeod, S. A. (2007). B. F. Skinner | Operant Conditioning - Simply Psychology. Retrieved from ht tp://www.s implypsychology.org/operant-conditioning.html

h t t p : / / t i m e s o f i n d i a . i n d i a t i m e s . c o m / l i f e -style/fashion/style-guide/Addicted-to-Social-Network/articleshow/10968618.cms accessed on March 21, 2014

11

Table 3: Extent to which Information About Others is Enjoyable


Getting information about activities

of others gives pleasure 20-30 years 49.1%

30-40 years 50%

40-50 years 33.3%


Gender Male 45.8%

Female 52.8%


Married 44.8%

Table 4: SNS Satisfy Social Needs


After connecting with SNS, Age Up to 20 years 50%

I feel that my social needs 20-30 years 45.9%

have been satisfied 30-40 years 18.7%

40-50 years 0%


Gender Male 37.5%

Female 38.9%


Married 27.5%


Table 5: Reasons Making SNS a Pleasurable Experience

S. No. Factors Respondents Agreement

1. I feel delighted to receive a favourable comment 86.9%

2. The lesser the gap between posting a comment & getting a favourable 64.3%response, the better I feel

3. I often talk to my friends more online than offline 53%

4. I always get genuine comments from others. 51.1%

5. I am comfortable in disclosing about myself through SNS. 48.8%



Table 2: Comfort Level in Disclosing Information About Self


I am comfortable in disclosing

about myself through SNS 20-30 years 37.7%

30-40 years 25%

40-50 years 66.7%


Gender Male 37.5%

Female 33.3%


Married 20.6%


ABSTRACT

Fly ash is an industrial waste generated at coal/lignite based thermal power plants. This waste material is utilized in numerous innovative applications across the world. In India, Ministry of Environment & Forests notification 2009 mandates to achieve 100% utilization of fly ash generated in a phased manner within five years. Various initiatives have been taken in the country to promote safe utilization of fly ash. As a result, utilization has increased from 1 million tonnes in 1994 to 100 million tonnes in 2013. Despite this impressive increase, the target of cent-percent utilization is not achieved and 73 million tonnes of fly ash remained unutilized in 2013. It leads to the following questions. Will the target of cent-percent utilization be achieved in near future if the existing trend continues? If not, what will be the gap between the generation and utilization of fly ash? An attempt is made in this study to answer these questions. For this, annual time series data of generation and utilization obtained from CEA are subjected to regression analysis to identify the underlying trend. Regression models for generation and utilization of fly ash are developed. Forecasts obtained by using the developed regression models show that if the existing trend continues, cent-percent utilization is unlikely to be achieved in near future. Thus, there is an urgent need to escalate utilization efforts in order to achieve cent-percent utilization of fly ash.

Key Words: Time series analysis, Forecasting, Regression models, Fly ash utilization, Technology management, Decision making and planning

Forecasting Generation and Utilization of Fly Ash in India

1. Introduction

Fly ash is an industrial waste and an environmental challenge because it is known to pollute air, water and soil. Fly ash is generated during the combustion of coal/lignite for generation of electricity at thermal power plants across the world (Blissett and Rowson, 2012). Fly ash is also recognized as a valuable resource material (Kumar et al., 2005). This is because it can be utilized in numerous innovative products and applications. According to Central Electricity Authority (CEA) to promote safe utilization of fly ash Government of India commissioned a Technology Project in Mission Mode called Fly Ash Mission (FAM) in 1994 (CEA, 2014). After its approved period, i.e. 31st March 2002 it was renamed as Fly Ash Utilization Programme (FAUP), and thereafter, it was renamed as

Fly Ash Unit (FAU) providing new focus and thrust under Department of Science and Technology (DST) since May 2007 (DST, 2013). Continuous progress in research and development clubbed with continuous effort of various government and private agencies, resulted in increased utilization of fly ash year after year. Utilization of fly ash has increased from 1 million tonnes (MT) in 1994 (DST, 2013) to about 100 MT in financial year (FY) 2013 (CEA, 2014). This denotes about 10000% increase in utilization in about 19 years. Despite this impressive increase in utilization, the target of cent-percent utilization could not be achieved, and there remains over 73 MT of unutilized fly ash in FY

2013. This is because, though the utilization of fly ash has increased, the generation of fly ash has also increased from 40 MT in the year 1994 (DST, 2013) to about 173 MT in FY 2013(CEA, 2014).

According to Ministry of Environment & Forests (MoEF) notification vide Gazette of India Notification No. 2804(E) dated 3rd Nov 2009, all coal/lignite based thermal power stations and/or expansion units in operation on or before the date of MoEF's notification, are required to achieve 100% utilization of fly ash generated in a phased manner within five years from the date of notice (CEA, 2014; MoEF, 2013), i.e. by November 2014. Relating it with the data published by CEA (2014), utilization level for FY 2013 is 58% of generation. Though utilization data for November 2014 is not published yet, it is highly unlikely that cent-percent utilization could be achieved by the target schedule. It leads to the following questions. Will the target of cent-percent utilization be achieved in near future if the existing trend continues? If not, what will be the gap between the generation and utilization of fly ash? Answers of these questions are vital for strategy formulation and timely execution of action plans in order to effectively manage the problem of unutilized fly ash. Estimating the gap between generation and utilization is the first step towards strategy formulation for maximizing the utilization of fly ash (Loya and Rawani, 2015). Haque (2013a), citing World Business Council for Sustainable Development / Cement Sustainability Initiative, mentions forecast of fly

12

ash utilization by cement sector in India, but forecast of collective utilization incorporating multiple applications is not provided. Haque (2013b), on the basis of India Energy Book's forecast of coal consumption, argues that generation of fly ash will increase tremendously but quantity of generation is not predicted. Referring to FAUP and Technology Information, Forecasting & Assessment Council (TIFAC), Kumar et al., (2005) mention fly ash generation is estimated to increase to about 170 MT by 2012 and 225 MT by 2017, however the basis of estimation is not shared. Bhattacharjee and Kandpal (2002) presented a 13 years forecast of fly ash generation and utilization. The results predicted the fly ash utilisation to be less than 25% of generation. The paper highlighted the need (at that time) of developing a much more aggressive strategy for fly ash utilisation. However the forecast period covered in the above study was from 1999 to 2012. There seems to be no other literature forecasting quantum of fly ash generation and utilization. Hence the above mentioned questions remain unanswered in the present scenario.

As it is highly unlikely that cent-percent utilization will be achieved within the target schedule set by MoEF, there is a need to revise the target schedule. And also there is an urgent need of suitable strategies and actions to bridge the gap between the generation and utilization. To bridge the gap between the generation and utilization of fly ash either the generation has to decrease or the utilization has to increase. Fly ash is a by-product and volume of its generation depends on production of electricity by coal based thermal power plants. Given the ever increasing demand for electricity and dependency on coal for electricity production, the generation of fly ash is highly unlikely to decrease. Thus, bridging the gap can be achieved only by increasing the utilization of fly ash. Though the quantity of fly ash generated cannot be controlled it can be predicted. Further, based on this predicted quantum of generation, utilization quantity could be planned and suitable strategies could be formulated and executed to achieve cent-percent utilization. Accordingly, to assist informed decision making and planning, the aim of this study is to forecast generation and utilization of fly ash and to compute the gap between the two.

2. Methodology and Data Analysis

In order to forecast generation and utilization of fly ash data are obtained from secondary source. Generation and utilization of fly ash in the country is monitored and reported by CEA on behalf of Ministry of Power (MOP) (CEA, 2014; MOP, 2013). The latest report of CEA, dated August 2014, on fly ash generation at coal/lignite based thermal power stations and its utilization, presents annual time series data of generation and utilization for 18 years'

period, starting from the FY 1996 to FY 2013 as shown in Table 1.

Table 1 Time Series Data of Fly Ash Generation and Utilization

FY Time Period Generation (MT) Utilization (MT)

1996 1 68.66 6.64

1997 2 78.06 8.43

1998 3 78.99 9.22

1999 4 74.03 8.91

2000 5 86.29 13.54

2001 6 82.81 15.57

2002 7 91.65 20.79

2003 8 96.28 28.29

2004 9 98.57 37.49

2005 10 98.97 45.22

2006 11 108.15 55.01

2007 12 116.94 61.98

2008 13 116.69 66.64

2009 14 123.54 77.33

2010 15 131.09 73.13

2011 16 145.41 85.05

2012 17 163.56 100.37

2013 18 172.87 99.62

(Source: CEA, 2014)

A time series is defined as a chronological sequence of observations on a variable of interest (Montgomery et al., 2008). Time series forecasting generally assumes that the same underlying causal relationship that existed in the past will continue to prevail in the future (Shim, 2009). Consequently time series forecasting methods are based on the concept that when an underlying pattern exists in a data series, it can be identified and decomposed, for better understanding the behaviour, which in turn facilitates improved accuracy in forecasting (Makridakis et al., 1998). The four commonly recognized components are trend, seasonal, cyclical, and irregular variation (Shim, 2009). Based on these components an additive decomposed model of time series can be mathematically represented as follows.

Y = T + S + C + E (1)t t t t t

Where Y is the time series value (actual data) at time period t,t

T is the trend component at time period t, t

13

M. I. M. Loya *A. M. Rawani **

*Research Scholar, Mechanical Engineering Department, NIT Raipur

**Professor, Mechanical Engineering Department, NIT Raipur



ABSTRACT

Fly ash is an industrial waste generated at coal/lignite based thermal power plants. This waste material is utilized in numerous innovative applications across the world. In India, Ministry of Environment & Forests notification 2009 mandates to achieve 100% utilization of fly ash generated in a phased manner within five years. Various initiatives have been taken in the country to promote safe utilization of fly ash. As a result, utilization has increased from 1 million tonnes in 1994 to 100 million tonnes in 2013. Despite this impressive increase, the target of cent-percent utilization is not achieved and 73 million tonnes of fly ash remained unutilized in 2013. It leads to the following questions. Will the target of cent-percent utilization be achieved in near future if the existing trend continues? If not, what will be the gap between the generation and utilization of fly ash? An attempt is made in this study to answer these questions. For this, annual time series data of generation and utilization obtained from CEA are subjected to regression analysis to identify the underlying trend. Regression models for generation and utilization of fly ash are developed. Forecasts obtained by using the developed regression models show that if the existing trend continues, cent-percent utilization is unlikely to be achieved in near future. Thus, there is an urgent need to escalate utilization efforts in order to achieve cent-percent utilization of fly ash.

Key Words: Time series analysis, Forecasting, Regression models, Fly ash utilization, Technology management, Decision making and planning


1. Introduction

Fly ash is an industrial waste and an environmental challenge because it is known to pollute air, water and soil. Fly ash is generated during the combustion of coal/lignite for generation of electricity at thermal power plants across the world (Blissett and Rowson, 2012). Fly ash is also recognized as a valuable resource material (Kumar et al., 2005). This is because it can be utilized in numerous innovative products and applications. According to Central Electricity Authority (CEA) to promote safe utilization of fly ash Government of India commissioned a Technology Project in Mission Mode called Fly Ash Mission (FAM) in 1994 (CEA, 2014). After its approved period, i.e. 31st March 2002 it was renamed as Fly Ash Utilization Programme (FAUP), and thereafter, it was renamed as

Fly Ash Unit (FAU) providing new focus and thrust under Department of Science and Technology (DST) since May 2007 (DST, 2013). Continuous progress in research and development clubbed with continuous effort of various government and private agencies, resulted in increased utilization of fly ash year after year. Utilization of fly ash has increased from 1 million tonnes (MT) in 1994 (DST, 2013) to about 100 MT in financial year (FY) 2013 (CEA, 2014). This denotes about 10000% increase in utilization in about 19 years. Despite this impressive increase in utilization, the target of cent-percent utilization could not be achieved, and there remains over 73 MT of unutilized fly ash in FY

2013. This is because, though the utilization of fly ash has increased, the generation of fly ash has also increased from 40 MT in the year 1994 (DST, 2013) to about 173 MT in FY 2013(CEA, 2014).

According to Ministry of Environment & Forests (MoEF) notification vide Gazette of India Notification No. 2804(E) dated 3rd Nov 2009, all coal/lignite based thermal power stations and/or expansion units in operation on or before the date of MoEF's notification, are required to achieve 100% utilization of fly ash generated in a phased manner within five years from the date of notice (CEA, 2014; MoEF, 2013), i.e. by November 2014. Relating it with the data published by CEA (2014), utilization level for FY 2013 is 58% of generation. Though utilization data for November 2014 is not published yet, it is highly unlikely that cent-percent utilization could be achieved by the target schedule. It leads to the following questions. Will the target of cent-percent utilization be achieved in near future if the existing trend continues? If not, what will be the gap between the generation and utilization of fly ash? Answers of these questions are vital for strategy formulation and timely execution of action plans in order to effectively manage the problem of unutilized fly ash. Estimating the gap between generation and utilization is the first step towards strategy formulation for maximizing the utilization of fly ash (Loya and Rawani, 2015). Haque (2013a), citing World Business Council for Sustainable Development / Cement Sustainability Initiative, mentions forecast of fly

12

ash utilization by cement sector in India, but forecast of collective utilization incorporating multiple applications is not provided. Haque (2013b), on the basis of India Energy Book's forecast of coal consumption, argues that generation of fly ash will increase tremendously but quantity of generation is not predicted. Referring to FAUP and Technology Information, Forecasting & Assessment Council (TIFAC), Kumar et al., (2005) mention fly ash generation is estimated to increase to about 170 MT by 2012 and 225 MT by 2017, however the basis of estimation is not shared. Bhattacharjee and Kandpal (2002) presented a 13 years forecast of fly ash generation and utilization. The results predicted the fly ash utilisation to be less than 25% of generation. The paper highlighted the need (at that time) of developing a much more aggressive strategy for fly ash utilisation. However the forecast period covered in the above study was from 1999 to 2012. There seems to be no other literature forecasting quantum of fly ash generation and utilization. Hence the above mentioned questions remain unanswered in the present scenario.

As it is highly unlikely that cent-percent utilization will be achieved within the target schedule set by MoEF, there is a need to revise the target schedule. And also there is an urgent need of suitable strategies and actions to bridge the gap between the generation and utilization. To bridge the gap between the generation and utilization of fly ash either the generation has to decrease or the utilization has to increase. Fly ash is a by-product and volume of its generation depends on production of electricity by coal based thermal power plants. Given the ever increasing demand for electricity and dependency on coal for electricity production, the generation of fly ash is highly unlikely to decrease. Thus, bridging the gap can be achieved only by increasing the utilization of fly ash. Though the quantity of fly ash generated cannot be controlled it can be predicted. Further, based on this predicted quantum of generation, utilization quantity could be planned and suitable strategies could be formulated and executed to achieve cent-percent utilization. Accordingly, to assist informed decision making and planning, the aim of this study is to forecast generation and utilization of fly ash and to compute the gap between the two.

2. Methodology and Data Analysis

In order to forecast generation and utilization of fly ash data are obtained from secondary source. Generation and utilization of fly ash in the country is monitored and reported by CEA on behalf of Ministry of Power (MOP) (CEA, 2014; MOP, 2013). The latest report of CEA, dated August 2014, on fly ash generation at coal/lignite based thermal power stations and its utilization, presents annual time series data of generation and utilization for 18 years'

period, starting from the FY 1996 to FY 2013 as shown in Table 1.

Table 1 Time Series Data of Fly Ash Generation and Utilization

FY Time Period Generation (MT) Utilization (MT)

1996 1 68.66 6.64

1997 2 78.06 8.43

1998 3 78.99 9.22

1999 4 74.03 8.91

2000 5 86.29 13.54

2001 6 82.81 15.57

2002 7 91.65 20.79

2003 8 96.28 28.29

2004 9 98.57 37.49

2005 10 98.97 45.22

2006 11 108.15 55.01

2007 12 116.94 61.98

2008 13 116.69 66.64

2009 14 123.54 77.33

2010 15 131.09 73.13

2011 16 145.41 85.05

2012 17 163.56 100.37

2013 18 172.87 99.62

(Source: CEA, 2014)

A time series is defined as a chronological sequence of observations on a variable of interest (Montgomery et al., 2008). Time series forecasting generally assumes that the same underlying causal relationship that existed in the past will continue to prevail in the future (Shim, 2009). Consequently time series forecasting methods are based on the concept that when an underlying pattern exists in a data series, it can be identified and decomposed, for better understanding the behaviour, which in turn facilitates improved accuracy in forecasting (Makridakis et al., 1998). The four commonly recognized components are trend, seasonal, cyclical, and irregular variation (Shim, 2009). Based on these components an additive decomposed model of time series can be mathematically represented as follows.

Y = T + S + C + E (1)t t t t t

Where Y is the time series value (actual data) at time period t,t

T is the trend component at time period t, t

13

M. I. M. Loya *A. M. Rawani **

*Research Scholar, Mechanical Engineering Department, NIT Raipur

**Professor, Mechanical Engineering Department, NIT Raipur



S is the seasonal component at time period t,t

C is the cyclical component at time period t, andt

E is the irregular variation component at time period t.t

Shim (2009) defines these components as follows. Trend component (Tt) is the general upward or downward movement of the average, over time. The seasonal component (St) is a recurring fluctuation of data points above or below the trend value that repeats with a usual frequency of one year, e.g., Christmas sales. Cyclical components (Ct) is recurrent upward or downward movement that repeats with a frequency that is longer than a year. This movement is attributed to business cycles (such as recession, inflation, unemployment, and prosperity), so the periodicity (recurrent rate) of such cycles does not have to be constant. The irregular variation component (Et) is a series of short, erratic movements that follow no discernible pattern.

A time series covering 18 years of period is not long enough to identify business cycle, because to capture business cycles a long time series is needed (Armstrong, 2002). As available data are annual data, hence they do not include seasonality. The type of data (yearly, quarterly, monthly, weekly, daily, etc.) relates to the characteristics of the time series, in general randomness diminishes as the level of aggregation increases. In daily data randomness dominates while trend is insignificant, contrasting this in yearly data averaging 12 months eliminates most of the randomness, in such a case trend fitting is recommended as it ignores random and seasonal fluctuations and concentrates on the long-term increase or decline instead, thus can correctly identify and extrapolate the trend in the data pattern for long forecasting horizons (Makridakis et al., 1998). Accordingly, for the time series data in consideration the equation 1 can be modified as

Y = T + E . (2)t t t

Typically, two types of trend fitting are used for business forecasting, namely, linear and nonlinear (Shim, 2009). In order to identify the type of trend in the time series data presented in (Table 1) a sequential chart is prepared with the help of statistical software package SPSS Version 20.0. The sequential chart is illustrated in Figure 1, where for FY 1996 the corresponding time period, t, is equal to 1. The chart reveals that the movements are upward and reasonably linear. Accordingly the trend can be assumed to be linear. Armstrong (2002) recommends a simple representation of trend unless there is strong evidence to the contrary. Supplementing this, in case a nonlinear trend is erroneously attempted to fit into a linear equation, it would not give a good fit and can be identified using t-value and R2 statistics (Shim, 2009). The t-test is extensively used in regression analysis (Makridakis et al., 1998) to statistically test the hypothesis if there is a linear

relationship between the response variable and predictor variables (Montgomery et al., 2008). The coefficient of determination R2 measures the proportion of variance in the observed data that can be explained by the estimated regression model (Anderson et al., 2011).

Figure 1 Sequential Chart of Generation and

Utilization of Fly Ash

In light of the above rationales, this study hypothesizes existence of linear trend in data of generation and utilization of fly ash with respect to time (financial year). The null hypothesis (H0) is that the slope of the population regression line is zero (there is no linear trend). The alternative hypothesis (H1) is that the slope of the population regression line is different from zero (there is a linear trend). A linear relationship can be modelled using statistical method of simple linear regression analysis. The method has inherent strengths as well as limitations. Strengths of the method are noted here and the limitations of the method are acknowledged in conclusion section. A great advantage of regression method is that it is easy to comprehend and can be represented & understood graphically (Deng and Song, 2013). Simplicity minimises mistakes and also facilitates decision makers' understanding and implementation (Armstrong, 2001). A linear trend can be represented by an equation

T = a + bt; (3)t

where the two parameters, a and b, represent the intercept and slope respectively (Makridakis et al., 1998). Parameter values of the regression equation can be estimated using method of least-squares. The method of least square is robust to violations of the underlying assumptions to which other methods are more sensitive, wins for simplicity (Armstrong, 2001) and widely used (Shim, 2009).

14

Accordingly, the statistical technique of simple linear regression analysis is carried out to identify the underlying trend of the time series data of generation and utilization of fly ash (Table 1). In order to test the hypotheses of existence of linear relationship between dependent variables and independent variable, parametric t-tests are performed to access the statistical significance of the slopes of the regression equations. Analysis is conducted with the help of statistical software package SPSS Version 20.0. The method of least square is used for estimation of

2parameters. Goodness of fit is assessed using R statistics. Using the estimated parameters regression models of generation and utilization of fly ash are developed. Based on the developed regression models, utilization and generation of fly ash are forecasted separately, and then the gap between the two is computed.

3. Result and Discussion

The result of the data analysis is shown in Table 2. The calculated p-value represents the probability of obtaining a value of t as large as the one calculated for the data. A p-value smaller than 0.05, provides the evidence for rejecting the null hypothesis. Accordingly, if a p-value is smaller than 0.05 it is concluded that the result is significant (Montgomery et al., 2008). In this study hypotheses of linear trend in generation and utilization of fly ash with respect to time are supported at 0.001 significant levels. Histograms of residue are included in the

2 appendix. The R statistics indicate that about 91% variance in fly ash generation and about 96% variance in fly ash utilization are explained. Thus, regression models for fly ash generation and utilization indicate good fit.

The above estimated parameters of regression models are used in this study for mid range forecast. For this regression models of generation and utilization of fly ash are formulated as follows:

Gt = 55.599 + 5.449.t (4)

Ut = -12.442 + 6.065.t (5)

Where Gt is generation of fly ash in MT for time period t

Ut is utilization of fly ash in MT for time period t

t is time period for which forecast is being calculated (for the given regression models, t is determined by subtracting 1995 for financial year being forecasted, e.g. for FY 2014, t = 19)

Using the above regression models, a forecast for generation and utilization of fly ash for 10 years starting from FY 2014 to FY 2023 is determined, and then the gap between the generation and utilization of fly ash is computed and shown in Table 3.

The above forecast is subject to continuity of trend. Forecast shows that in 10 years utilization of fly ash will increase to about 157.38 MT, however the generation of fly ash will also increase significantly. In context of the target schedule set by MoEF for cent-percent utilization of fly ash, i.e. November 2014, interpretation of the forecast is done as follows. It is predicted that the MoEF's target schedule for achieving cent-percent utilization will not be achieved. Further if the existing trend continues, i.e. no new strategy is formulated and no new action is taken, cent-percent utilization is unlikely to be achieved in near future. Likewise, if the existing trend continues, the gap between generation and utilization is predicted to be over 50 MT. As fly ash is a by-product, its generation is difficult to control. Thus, the logical approach to bridge the gap between generation and utilization is to increase utilization of fly ash. The existing strategies and efforts are resulting in an increasing trend of utilization of fly ash; however this increase is not enough in context of ambition of cent-percent utilization. So there is an urgent need to escalate utilization of fly ash. Several public and private funded R&D in last five decades has enabled numerous innovative applications of fly ash (Loya and Rawani, 2013). For example fly ash can be utilized in cement, concrete, brick, tile, mine-filling, land-filling, road-construction, fertilizer, pesticide, paint, synthetic wood, ceramic, glass, geopolimer, catalysts, zeolites, as adsorbents in pollution control applications such as industrial waste waters treatment, recovery of magnetic microspheres, cenospheres, carbon & several precious metals, etc. Large scale utilization of fly ash in such applications can assist in bridging the gap between generation and utilization.

15

Table 2 Parameter Estimation of Regression Models and t-test Results

2Model Unstandardized Standardized t-value p-value R

Coefficients Coefficients

B Std. Error Beta

Generation (Constant) 55.599 4.521 12.297 .000 0.914

FY 5.449 0.418 0.956 13.045 .000

Utilization (Constant) -12.442 3.231 -3.851 .001 0.963

FY 6.065 0.298 0.981 20.321 .000


Forecasting Generation and Utilization of Fly Ash in IndiaForecasting Generation and Utilization of Fly Ash in India


S is the seasonal component at time period t,t

C is the cyclical component at time period t, andt

E is the irregular variation component at time period t.t

Shim (2009) defines these components as follows. Trend component (Tt) is the general upward or downward movement of the average, over time. The seasonal component (St) is a recurring fluctuation of data points above or below the trend value that repeats with a usual frequency of one year, e.g., Christmas sales. Cyclical components (Ct) is recurrent upward or downward movement that repeats with a frequency that is longer than a year. This movement is attributed to business cycles (such as recession, inflation, unemployment, and prosperity), so the periodicity (recurrent rate) of such cycles does not have to be constant. The irregular variation component (Et) is a series of short, erratic movements that follow no discernible pattern.

A time series covering 18 years of period is not long enough to identify business cycle, because to capture business cycles a long time series is needed (Armstrong, 2002). As available data are annual data, hence they do not include seasonality. The type of data (yearly, quarterly, monthly, weekly, daily, etc.) relates to the characteristics of the time series, in general randomness diminishes as the level of aggregation increases. In daily data randomness dominates while trend is insignificant, contrasting this in yearly data averaging 12 months eliminates most of the randomness, in such a case trend fitting is recommended as it ignores random and seasonal fluctuations and concentrates on the long-term increase or decline instead, thus can correctly identify and extrapolate the trend in the data pattern for long forecasting horizons (Makridakis et al., 1998). Accordingly, for the time series data in consideration the equation 1 can be modified as

Y = T + E . (2)t t t

Typically, two types of trend fitting are used for business forecasting, namely, linear and nonlinear (Shim, 2009). In order to identify the type of trend in the time series data presented in (Table 1) a sequential chart is prepared with the help of statistical software package SPSS Version 20.0. The sequential chart is illustrated in Figure 1, where for FY 1996 the corresponding time period, t, is equal to 1. The chart reveals that the movements are upward and reasonably linear. Accordingly the trend can be assumed to be linear. Armstrong (2002) recommends a simple representation of trend unless there is strong evidence to the contrary. Supplementing this, in case a nonlinear trend is erroneously attempted to fit into a linear equation, it would not give a good fit and can be identified using t-value and R2 statistics (Shim, 2009). The t-test is extensively used in regression analysis (Makridakis et al., 1998) to statistically test the hypothesis if there is a linear

relationship between the response variable and predictor variables (Montgomery et al., 2008). The coefficient of determination R2 measures the proportion of variance in the observed data that can be explained by the estimated regression model (Anderson et al., 2011).

Figure 1 Sequential Chart of Generation and

Utilization of Fly Ash

In light of the above rationales, this study hypothesizes existence of linear trend in data of generation and utilization of fly ash with respect to time (financial year). The null hypothesis (H0) is that the slope of the population regression line is zero (there is no linear trend). The alternative hypothesis (H1) is that the slope of the population regression line is different from zero (there is a linear trend). A linear relationship can be modelled using statistical method of simple linear regression analysis. The method has inherent strengths as well as limitations. Strengths of the method are noted here and the limitations of the method are acknowledged in conclusion section. A great advantage of regression method is that it is easy to comprehend and can be represented & understood graphically (Deng and Song, 2013). Simplicity minimises mistakes and also facilitates decision makers' understanding and implementation (Armstrong, 2001). A linear trend can be represented by an equation

T = a + bt; (3)t

where the two parameters, a and b, represent the intercept and slope respectively (Makridakis et al., 1998). Parameter values of the regression equation can be estimated using method of least-squares. The method of least square is robust to violations of the underlying assumptions to which other methods are more sensitive, wins for simplicity (Armstrong, 2001) and widely used (Shim, 2009).

14

Accordingly, the statistical technique of simple linear regression analysis is carried out to identify the underlying trend of the time series data of generation and utilization of fly ash (Table 1). In order to test the hypotheses of existence of linear relationship between dependent variables and independent variable, parametric t-tests are performed to access the statistical significance of the slopes of the regression equations. Analysis is conducted with the help of statistical software package SPSS Version 20.0. The method of least square is used for estimation of

2parameters. Goodness of fit is assessed using R statistics. Using the estimated parameters regression models of generation and utilization of fly ash are developed. Based on the developed regression models, utilization and generation of fly ash are forecasted separately, and then the gap between the two is computed.

3. Result and Discussion

The result of the data analysis is shown in Table 2. The calculated p-value represents the probability of obtaining a value of t as large as the one calculated for the data. A p-value smaller than 0.05, provides the evidence for rejecting the null hypothesis. Accordingly, if a p-value is smaller than 0.05 it is concluded that the result is significant (Montgomery et al., 2008). In this study hypotheses of linear trend in generation and utilization of fly ash with respect to time are supported at 0.001 significant levels. Histograms of residue are included in the

2 appendix. The R statistics indicate that about 91% variance in fly ash generation and about 96% variance in fly ash utilization are explained. Thus, regression models for fly ash generation and utilization indicate good fit.

The above estimated parameters of regression models are used in this study for mid range forecast. For this regression models of generation and utilization of fly ash are formulated as follows:

Gt = 55.599 + 5.449.t (4)

Ut = -12.442 + 6.065.t (5)

Where Gt is generation of fly ash in MT for time period t

Ut is utilization of fly ash in MT for time period t

t is time period for which forecast is being calculated (for the given regression models, t is determined by subtracting 1995 for financial year being forecasted, e.g. for FY 2014, t = 19)

Using the above regression models, a forecast for generation and utilization of fly ash for 10 years starting from FY 2014 to FY 2023 is determined, and then the gap between the generation and utilization of fly ash is computed and shown in Table 3.

The above forecast is subject to continuity of trend. Forecast shows that in 10 years utilization of fly ash will increase to about 157.38 MT, however the generation of fly ash will also increase significantly. In context of the target schedule set by MoEF for cent-percent utilization of fly ash, i.e. November 2014, interpretation of the forecast is done as follows. It is predicted that the MoEF's target schedule for achieving cent-percent utilization will not be achieved. Further if the existing trend continues, i.e. no new strategy is formulated and no new action is taken, cent-percent utilization is unlikely to be achieved in near future. Likewise, if the existing trend continues, the gap between generation and utilization is predicted to be over 50 MT. As fly ash is a by-product, its generation is difficult to control. Thus, the logical approach to bridge the gap between generation and utilization is to increase utilization of fly ash. The existing strategies and efforts are resulting in an increasing trend of utilization of fly ash; however this increase is not enough in context of ambition of cent-percent utilization. So there is an urgent need to escalate utilization of fly ash. Several public and private funded R&D in last five decades has enabled numerous innovative applications of fly ash (Loya and Rawani, 2013). For example fly ash can be utilized in cement, concrete, brick, tile, mine-filling, land-filling, road-construction, fertilizer, pesticide, paint, synthetic wood, ceramic, glass, geopolimer, catalysts, zeolites, as adsorbents in pollution control applications such as industrial waste waters treatment, recovery of magnetic microspheres, cenospheres, carbon & several precious metals, etc. Large scale utilization of fly ash in such applications can assist in bridging the gap between generation and utilization.

15


2Model Unstandardized Standardized t-value p-value R

Coefficients Coefficients

B Std. Error Beta

Generation (Constant) 55.599 4.521 12.297 .000 0.914

FY 5.449 0.418 0.956 13.045 .000

Utilization (Constant) -12.442 3.231 -3.851 .001 0.963

FY 6.065 0.298 0.981 20.321 .000




However many of these applications are not yet commercialized utilized to their full potential. In light of this, the study recommends to escalate commercialization of fly ash innovations and technologies, developed by various government and private funded research, for achieving cent percent utilization of fly ash.

4. Conclusions

In this paper generation and utilization of fly ash in India is forecasted and then gap between the two is computed. For this annual time series data of generation and utilization starting from the FY 1996 to FY 2013 are analyzed. Regression models for generation and utilization of fly ash are developed and a forecast for 10 years starting from FY 2014 to FY 2023 is obtained. The gap between the generation and utilization is computed. The result shows that if the existing trend continues, cent percent utilization is unlikely to be achieved in near future. Thus, there is an urgent need for more aggressive utilization efforts in order to achieve cent percent utilization of fly ash. Subsequently it is recommended to escalate commercialization of fly ash innovations and technologies developed by various government and private funded research. The findings of the study are expected to assist in informed decision making, planning and managing fly ash utilization.

The statistical technique of simple linear regression analysis is used in this study consequently the study possesses all the inherent limitations of the methodology chosen. The limitation includes assumption that the relationship is linear. The prediction of future is based on identification of pattern in the historical data series and assumption that the identified patter will continue to prevail in the future. The result is based on the latest data published by CEA dated August 2014. The data includes

143 coal/lignite based thermal power plants' electricity generation capacity that was operational during 2013-14. Thus the growth trend of past is incorporated; however any aggressive or sluggish growth in production capacity deviating from past trend of growth would require a revision in forecast of generation of fly ash. The methods of forecasting based on identified trend in past treat the system as a black box and make no attempt to discover the factors affecting its behaviour. These limitations can provide directions for further studies. Accordingly future study may use alternative methods such as explanatory models, ARIMA models, qualitative techniques etc. As each forecasting method has its own strengths and limitations, such studies using alternative methods would complement the strength of this study and also serve in overcoming the limitations of this study.

16

References

Anderson, D. R., Sweeney, D. J., & Williams, T. A. (2011). Essentials of Statistics for Business and Economics. OH, USA: South-Western Cengage Learning.

Armstrong, J. S. (2002). Principles of forecasting: A Handbook for Researchers and Practitioners. New York: Kluwer Academic Publishers.

Bhattacharjee, U., & Kandpal, T. C. (2002). Potential of Fly Ash Utilisation in India. Energy, 27, 151–166.

Blissett, R. S., & Rowson, N. A. (2012). A Review of the Multi-component Utilisation of Coal Fly Ash. Fuel, 97, 1–23.

Central Electricity Authority. (2014). Report on Fly Ash Generation at Coal/Lignite Based Thermal Power Stations and its Utilization in the Country for 2013-14.

Deng, H., & Song, X. (2013). The Theory and Practice of Linear Regression. World Transactions on Engineering and Technology Education, 11(4), 382–387.

Department of Science & Technology. (2013). Annual report 2012-13. Ministry of Power, Government of India, New Delhi.

Haque, M. E. (2013a). Enablers and Barriers for Utilization of Fly-Ash in Indian Cement Industry. International Journal of Advance Industrial Engineering, 1(1), 31–35.

Haque, M. E. (2013b). Indian Fly-Ash: Production and Consumption Scenario. International Journal of Waste Resources, 3(1), 22–25.

Kumar, V., Mathur, M., & Sinha, S. S. (2005). A Case Study: Manifold Increase in Fly Ash. Fly Ash India, 1–8.

Loya, M. I. M., & Rawani, A. M. (2013). Criteria for Evaluating Innovative Fly Ash Applications. Proceedings of GLOGIFT-13, the 13th Global Conference on Flexible Systems Management, held on 13-15 December, 2013 at New Delhi, India, convened by Department of Management Studies, IIT Delhi, and co-hosted by International Federation for Systems Research.

Loya, M. I. M., & Rawani, A. M. (2015). Strategic Framework for Commercialisation of Fly Ash Innovations. Technology Analysis & Strategic Management, 1-13.

Makridakis, S. G., Wheelwright, S. C., & Hyndman, R. J. (1998). Forecasting: Methods and Applications (3rd ed.). New York: John Wiley & Sons, Inc.

Ministry of Environment and Forests. (2013). Annual report 2012-13. Ministry of Environment and Forests, Government of India, New Delhi.

Ministry of Power. (2013). Annual report 2012-13. Ministry of Power, Government of India, New Delhi.

Montgomery, D. C., Jennings, C. L., & Kulahci, M. (2008). Introduction to Time Series Analysis and Forecasting. New Jersey: John & Wiley & Sons. Inc.

Shim, J. K. (2009). Strategic Business Forecasting. Kent: Global Professional Publishing.

17

Table 3 Forecast Using the Regression Models

FY Time period Generation (MT) Utilization (MT) Gap (MT)

2014 19 159.13 102.79 56.34

2015 20 164.58 108.86 55.72

2016 21 170.03 114.92 55.11

2017 22 175.48 120.99 54.49

2018 23 180.93 127.05 53.87

2019 24 186.38 133.12 53.26

2020 25 191.82 139.18 52.64

2021 26 197.27 145.25 52.03

2022 27 202.72 151.31 51.41

2023 28 208.17 157.38 50.79

Appendix



However many of these applications are not yet commercialized utilized to their full potential. In light of this, the study recommends to escalate commercialization of fly ash innovations and technologies, developed by various government and private funded research, for achieving cent percent utilization of fly ash.

4. Conclusions

In this paper generation and utilization of fly ash in India is forecasted and then gap between the two is computed. For this annual time series data of generation and utilization starting from the FY 1996 to FY 2013 are analyzed. Regression models for generation and utilization of fly ash are developed and a forecast for 10 years starting from FY 2014 to FY 2023 is obtained. The gap between the generation and utilization is computed. The result shows that if the existing trend continues, cent percent utilization is unlikely to be achieved in near future. Thus, there is an urgent need for more aggressive utilization efforts in order to achieve cent percent utilization of fly ash. Subsequently it is recommended to escalate commercialization of fly ash innovations and technologies developed by various government and private funded research. The findings of the study are expected to assist in informed decision making, planning and managing fly ash utilization.

The statistical technique of simple linear regression analysis is used in this study consequently the study possesses all the inherent limitations of the methodology chosen. The limitation includes assumption that the relationship is linear. The prediction of future is based on identification of pattern in the historical data series and assumption that the identified patter will continue to prevail in the future. The result is based on the latest data published by CEA dated August 2014. The data includes

143 coal/lignite based thermal power plants' electricity generation capacity that was operational during 2013-14. Thus the growth trend of past is incorporated; however any aggressive or sluggish growth in production capacity deviating from past trend of growth would require a revision in forecast of generation of fly ash. The methods of forecasting based on identified trend in past treat the system as a black box and make no attempt to discover the factors affecting its behaviour. These limitations can provide directions for further studies. Accordingly future study may use alternative methods such as explanatory models, ARIMA models, qualitative techniques etc. As each forecasting method has its own strengths and limitations, such studies using alternative methods would complement the strength of this study and also serve in overcoming the limitations of this study.

16

References

Anderson, D. R., Sweeney, D. J., & Williams, T. A. (2011). Essentials of Statistics for Business and Economics. OH, USA: South-Western Cengage Learning.

Armstrong, J. S. (2002). Principles of forecasting: A Handbook for Researchers and Practitioners. New York: Kluwer Academic Publishers.

Bhattacharjee, U., & Kandpal, T. C. (2002). Potential of Fly Ash Utilisation in India. Energy, 27, 151–166.

Blissett, R. S., & Rowson, N. A. (2012). A Review of the Multi-component Utilisation of Coal Fly Ash. Fuel, 97, 1–23.

Central Electricity Authority. (2014). Report on Fly Ash Generation at Coal/Lignite Based Thermal Power Stations and its Utilization in the Country for 2013-14.

Deng, H., & Song, X. (2013). The Theory and Practice of Linear Regression. World Transactions on Engineering and Technology Education, 11(4), 382–387.

Department of Science & Technology. (2013). Annual report 2012-13. Ministry of Power, Government of India, New Delhi.

Haque, M. E. (2013a). Enablers and Barriers for Utilization of Fly-Ash in Indian Cement Industry. International Journal of Advance Industrial Engineering, 1(1), 31–35.

Haque, M. E. (2013b). Indian Fly-Ash: Production and Consumption Scenario. International Journal of Waste Resources, 3(1), 22–25.

Kumar, V., Mathur, M., & Sinha, S. S. (2005). A Case Study: Manifold Increase in Fly Ash. Fly Ash India, 1–8.

Loya, M. I. M., & Rawani, A. M. (2013). Criteria for Evaluating Innovative Fly Ash Applications. Proceedings of GLOGIFT-13, the 13th Global Conference on Flexible Systems Management, held on 13-15 December, 2013 at New Delhi, India, convened by Department of Management Studies, IIT Delhi, and co-hosted by International Federation for Systems Research.

Loya, M. I. M., & Rawani, A. M. (2015). Strategic Framework for Commercialisation of Fly Ash Innovations. Technology Analysis & Strategic Management, 1-13.

Makridakis, S. G., Wheelwright, S. C., & Hyndman, R. J. (1998). Forecasting: Methods and Applications (3rd ed.). New York: John Wiley & Sons, Inc.

Ministry of Environment and Forests. (2013). Annual report 2012-13. Ministry of Environment and Forests, Government of India, New Delhi.

Ministry of Power. (2013). Annual report 2012-13. Ministry of Power, Government of India, New Delhi.

Montgomery, D. C., Jennings, C. L., & Kulahci, M. (2008). Introduction to Time Series Analysis and Forecasting. New Jersey: John & Wiley & Sons. Inc.

Shim, J. K. (2009). Strategic Business Forecasting. Kent: Global Professional Publishing.

17

Table 3 Forecast Using the Regression Models

FY Time period Generation (MT) Utilization (MT) Gap (MT)

2014 19 159.13 102.79 56.34

2015 20 164.58 108.86 55.72

2016 21 170.03 114.92 55.11

2017 22 175.48 120.99 54.49

2018 23 180.93 127.05 53.87

2019 24 186.38 133.12 53.26

2020 25 191.82 139.18 52.64

2021 26 197.27 145.25 52.03

2022 27 202.72 151.31 51.41

2023 28 208.17 157.38 50.79

Appendix



18

1. Introduction

In 2012-13 retail in India was Rs 25286 billion Industry. Organized retail contributed 7% of total retail standing at Rs 1,767 billion. Online retail contributed Rs 139 billion to the overall retail trade which is 7.9 % of the organized retail and 0.5% of the overall retail. (Crisil, 2014). While food and grocery contributed 60% of the total organized and unorganized trade followed by 11% and 8% of the total organized trade in India in footwear and apparels. It is projected that the organized retail would contribute approx 20% of the retail trade by 2020 (Delloite, 2013).

Although India has slipped down to 14th rank in 2013 from 1st in 2009 yet, it was ranked 5th worldwide for the foreign direct investment confidence in 2013 (AT Kearney, 2013).

Various online retailers like Flipkart, Snapdeal, Myntra, Jabong and International players like ebay, amazon etc. are creating a dent to the brick and mortar outlets. With the advent of internet complimented by mobile telephony the online retail platforms of shopping are getting popularity. This has eroded the sales per square feet and conversion ratio of the footfall in the conventional retail outlets. Accenture's study revealed that 78 percent of the U.S. shoppers had webroomed (browsing online and then going to store to make their purchase). The touch and feel benefit which the pure play retailers provided was no longer important for the buyers. Still we look for recommendations and customer reviews for booking a hotel online. Customers look for seamless shopping experience which is effortless and on their own terms.

Physical stores do not identify shopper as frequent shopper and further does not track the shopping patterns. Even the loyalty programs/cards do provide patronage. If the shopping process offers benefits other than exposure to products, the retail innovations that attempt to reduce “shopping effort” (vending machines, mail orders or home

delivery) may have a dim future for some product categories. Retailers need to re examine and reconfigure their talent, physical space and store operations to meet or exceed customer expectations. Shopper's Stop in 2008 went online to become multi channel retailer. I-phone owners can select and buy the items online and pick them from the nearest Apple store. Retailers are combining e commerce with in-store shipping to create connected retail customer experience. Thus, the aim should not be to think online or offline but seamless customer experience. IT infrastructure can make stores as efficient fulfillment centers while the in-store customer experience can be improved by making stores as social destinations. The goal of the in-store customer shopping experience should be to inspire customer to dream. Consumer having a good store experience have significantly more favorable shopping intentions that those having a bad shopping experience (Swinyard, 1993). “Internal Store Environment” relates to all the elements playing part in an agreeable shopping atmosphere. These elements include the shop's layout, aisle to facilitate movement, the store's cleanliness, uncluttered product displays and interior decoration (Terblanche, 2006). For making in-store customer experience more intuitive, retail infrastructure strategy needs to be reworked for the joy of shopping.

2. Theoretical Background and Hypothesis

The growth of research on leisure, entertainment and the arts reflects the shift of attention toward the experimental side (Holbrook, 1982). As the lifestyle changes in terms of travel, clothing, hygiene etc shopping environments have created new expectations even at the points of shopping. Such expectations generate interest in doing shopping in various categories and format of outlets. (Sathish & Venkatesakumar, 2011). Multichannel shopping behavior has posed a challenge for effective knowledge management for enhancing customer experience (Chakravorti, 2011). Many companies excel in individual

ABSTRACT

Under competition from e-retailers, the conventional brick and mortar stores are coming up with various retail strategies. In-store shopping infrastructure offers retailers with a differentiation tool which can be used to drive and enhance customer's shopping experience. Since the in-store infrastructure is a controllable factor, various influencing stimuli are being researched along with their impact on sales or intention to shop. Selected stimuli or the physical environment in general had been studied by various researches in particular retail settings and formats. This paper aims at studying selected in-store controllable retail infrastructure stimuli and their influence on customer experience in three different product categories. Further, within the product categories variation in in-store customer experience between demographic compositions of the population has been studied.

Key Words: In-store customer experience, Retail infrastructure stimuli, Physical environment, Atmospherics.

19

Influence of Retail Infrastructure Stimuli on In-Store Customer Experience

Raghav Upadhyai *Dr. H.S. Grewal **

*Assistant Professor, IMS Unison University, Dehradun** Professor, Omkarananda Institute of Management and Technology, Rishikesh

etc. We propose to study the overall in-store customer experience created by these stimuli in three different product categories namely, consumer electronics, groceries and fashion apparels being top three retail categories in terms of sales in Indian market . Further, we studied how in-store customer experience stimuli influence certain demographic variables. The following hypotheses are designed to serve the purpose of the study.

H0a: Overall in-store customer experience is same across all three product categories.

H0b: Overall in-store customer experience does not vary between genders across three product categories.

H0c: Overall in-store customer experience does not vary between married and singles across three product categories

H0d: Overall in-store customer experience does not vary between education level of shoppers across three product categories.

H0e: Overall in-store customer experience does not vary between age groups across three product categories

H0f: Overall in-store customer experience does not vary between income level of shoppers across three product categories.

3. Methodology

The data has been collected using self administered questionnaire to the residents of Dehradun city who had exposure to shopping across these product categories. The sampling is purely judgmental with a sample size of 98 respondents. In all, total of 110 questionnaires were being circulated out of which 105 completely filled questionnaires were received. Seven questionnaires were rejected due to incomplete information leading to overall response rate of 89%. In all 68.4% of the respondents were male and 31.6% were females with mean age of respondents being 31.6 years.

Responses of the influence of individual stimuli were measured on a scale of 1 to 10 where 1 being very unpleasant and 10 being highly pleasant. Adding the individual score of all stimuli under each product category a composite score for each respondent was calculated for responses given to consumer electronics, groceries and fashion apparels. .

interactions with customers, but they fail to apply adequate attention to the customer's complete experience on way to purchase and after. (Rawson et. al. 2013)

The term “consumption experience” given by Holbrook in 1982, signifies that the conventional research where the information processing model of the consumer behavior was studied in detail needs to be re evaluated. Customer experience is the internal and subjective response customers have to any direct or indirect contact with a company. The expectations of the customers in terms of what they require need to be assessed in terms of the hedonic aspects as well. Customer experience management locates places to add offerings in the gaps between expectations and experience. (Meyer and Shwager, 2007). Store shopping experience emerges from a consumer's interaction with a store's physical surrounding, personnel and customer related policies and practices (Kerin, 1992). Superior customer experience is increasingly becoming a differentiator not to mention an important factor in generating customer loyalty. (Chakravorti, 2011).The retailers should define their businesses around social and recreational appeals (Tauber, 1972).

Ever since atmospherics (Kotler 1973) became an important point for discussion in the academic literature, various attempts have been made to study underlying motives of customer shopping experience and the retail strategy. Customer experience encompasses facets like atmospherics, facilities, information, sounds, lighting, music and so on (Sathish & Venkatesakumar, 2011). The strategic view of retail environment (figure 1) classifies atmospheric design in five categories: exterior, general interiors, layout and design, POP and decorations, and human factors as a key element of atmospheric design (Turley and Chebat, 2002). They further stressed that the small changes in the retail environment can have an impact on sales and shopping behavior. Further, these are controllable factors and can be modified to suite the requirements of the general customers as a whole.

For this research we considered certain controllable atmospheric design stimuli which were earlier researched upon and having influence on in-store customer experience like Music (Milliman,1982; Milliman,1986; Areni & Kim, 1993; Matilla & Wirtz, 2001; Eroglu, Machleit & Chebat 2005), Product display and Shelf space (Cox,1970; Gagnon & Osterhans, 1985; Bawa, Landwehr and Krishna, 1989; Kotzan & Evanson, 1996; Chandon, Hutchinson, Bradlow and Young, 2009), In-store signage (Chevalier 1975; Woodside and Waddle 1975), Atmospheric color (Bellizz & Hite, 1992; Brogman, 2004), Window display (Edwards & Shackley, 1992), Odour (Hirsch, 1995; Matilla & Wirtz, 2001; Teller & Dennis, 2012; Vaccaro, Ahlawat, Yucetepe and Lee, 2012), Design and décor (Wakefeild & Blodgett, 1999)



18

1. Introduction

In 2012-13 retail in India was Rs 25286 billion Industry. Organized retail contributed 7% of total retail standing at Rs 1,767 billion. Online retail contributed Rs 139 billion to the overall retail trade which is 7.9 % of the organized retail and 0.5% of the overall retail. (Crisil, 2014). While food and grocery contributed 60% of the total organized and unorganized trade followed by 11% and 8% of the total organized trade in India in footwear and apparels. It is projected that the organized retail would contribute approx 20% of the retail trade by 2020 (Delloite, 2013).

Although India has slipped down to 14th rank in 2013 from 1st in 2009 yet, it was ranked 5th worldwide for the foreign direct investment confidence in 2013 (AT Kearney, 2013).

Various online retailers like Flipkart, Snapdeal, Myntra, Jabong and International players like ebay, amazon etc. are creating a dent to the brick and mortar outlets. With the advent of internet complimented by mobile telephony the online retail platforms of shopping are getting popularity. This has eroded the sales per square feet and conversion ratio of the footfall in the conventional retail outlets. Accenture's study revealed that 78 percent of the U.S. shoppers had webroomed (browsing online and then going to store to make their purchase). The touch and feel benefit which the pure play retailers provided was no longer important for the buyers. Still we look for recommendations and customer reviews for booking a hotel online. Customers look for seamless shopping experience which is effortless and on their own terms.

Physical stores do not identify shopper as frequent shopper and further does not track the shopping patterns. Even the loyalty programs/cards do provide patronage. If the shopping process offers benefits other than exposure to products, the retail innovations that attempt to reduce “shopping effort” (vending machines, mail orders or home

delivery) may have a dim future for some product categories. Retailers need to re examine and reconfigure their talent, physical space and store operations to meet or exceed customer expectations. Shopper's Stop in 2008 went online to become multi channel retailer. I-phone owners can select and buy the items online and pick them from the nearest Apple store. Retailers are combining e commerce with in-store shipping to create connected retail customer experience. Thus, the aim should not be to think online or offline but seamless customer experience. IT infrastructure can make stores as efficient fulfillment centers while the in-store customer experience can be improved by making stores as social destinations. The goal of the in-store customer shopping experience should be to inspire customer to dream. Consumer having a good store experience have significantly more favorable shopping intentions that those having a bad shopping experience (Swinyard, 1993). “Internal Store Environment” relates to all the elements playing part in an agreeable shopping atmosphere. These elements include the shop's layout, aisle to facilitate movement, the store's cleanliness, uncluttered product displays and interior decoration (Terblanche, 2006). For making in-store customer experience more intuitive, retail infrastructure strategy needs to be reworked for the joy of shopping.

2. Theoretical Background and Hypothesis

The growth of research on leisure, entertainment and the arts reflects the shift of attention toward the experimental side (Holbrook, 1982). As the lifestyle changes in terms of travel, clothing, hygiene etc shopping environments have created new expectations even at the points of shopping. Such expectations generate interest in doing shopping in various categories and format of outlets. (Sathish & Venkatesakumar, 2011). Multichannel shopping behavior has posed a challenge for effective knowledge management for enhancing customer experience (Chakravorti, 2011). Many companies excel in individual

ABSTRACT

Under competition from e-retailers, the conventional brick and mortar stores are coming up with various retail strategies. In-store shopping infrastructure offers retailers with a differentiation tool which can be used to drive and enhance customer's shopping experience. Since the in-store infrastructure is a controllable factor, various influencing stimuli are being researched along with their impact on sales or intention to shop. Selected stimuli or the physical environment in general had been studied by various researches in particular retail settings and formats. This paper aims at studying selected in-store controllable retail infrastructure stimuli and their influence on customer experience in three different product categories. Further, within the product categories variation in in-store customer experience between demographic compositions of the population has been studied.

Key Words: In-store customer experience, Retail infrastructure stimuli, Physical environment, Atmospherics.

19


Raghav Upadhyai *Dr. H.S. Grewal **

*Assistant Professor, IMS Unison University, Dehradun** Professor, Omkarananda Institute of Management and Technology, Rishikesh

etc. We propose to study the overall in-store customer experience created by these stimuli in three different product categories namely, consumer electronics, groceries and fashion apparels being top three retail categories in terms of sales in Indian market . Further, we studied how in-store customer experience stimuli influence certain demographic variables. The following hypotheses are designed to serve the purpose of the study.

H0a: Overall in-store customer experience is same across all three product categories.

H0b: Overall in-store customer experience does not vary between genders across three product categories.

H0c: Overall in-store customer experience does not vary between married and singles across three product categories

H0d: Overall in-store customer experience does not vary between education level of shoppers across three product categories.

H0e: Overall in-store customer experience does not vary between age groups across three product categories

H0f: Overall in-store customer experience does not vary between income level of shoppers across three product categories.

3. Methodology

The data has been collected using self administered questionnaire to the residents of Dehradun city who had exposure to shopping across these product categories. The sampling is purely judgmental with a sample size of 98 respondents. In all, total of 110 questionnaires were being circulated out of which 105 completely filled questionnaires were received. Seven questionnaires were rejected due to incomplete information leading to overall response rate of 89%. In all 68.4% of the respondents were male and 31.6% were females with mean age of respondents being 31.6 years.

Responses of the influence of individual stimuli were measured on a scale of 1 to 10 where 1 being very unpleasant and 10 being highly pleasant. Adding the individual score of all stimuli under each product category a composite score for each respondent was calculated for responses given to consumer electronics, groceries and fashion apparels. .

interactions with customers, but they fail to apply adequate attention to the customer's complete experience on way to purchase and after. (Rawson et. al. 2013)

The term “consumption experience” given by Holbrook in 1982, signifies that the conventional research where the information processing model of the consumer behavior was studied in detail needs to be re evaluated. Customer experience is the internal and subjective response customers have to any direct or indirect contact with a company. The expectations of the customers in terms of what they require need to be assessed in terms of the hedonic aspects as well. Customer experience management locates places to add offerings in the gaps between expectations and experience. (Meyer and Shwager, 2007). Store shopping experience emerges from a consumer's interaction with a store's physical surrounding, personnel and customer related policies and practices (Kerin, 1992). Superior customer experience is increasingly becoming a differentiator not to mention an important factor in generating customer loyalty. (Chakravorti, 2011).The retailers should define their businesses around social and recreational appeals (Tauber, 1972).

Ever since atmospherics (Kotler 1973) became an important point for discussion in the academic literature, various attempts have been made to study underlying motives of customer shopping experience and the retail strategy. Customer experience encompasses facets like atmospherics, facilities, information, sounds, lighting, music and so on (Sathish & Venkatesakumar, 2011). The strategic view of retail environment (figure 1) classifies atmospheric design in five categories: exterior, general interiors, layout and design, POP and decorations, and human factors as a key element of atmospheric design (Turley and Chebat, 2002). They further stressed that the small changes in the retail environment can have an impact on sales and shopping behavior. Further, these are controllable factors and can be modified to suite the requirements of the general customers as a whole.

For this research we considered certain controllable atmospheric design stimuli which were earlier researched upon and having influence on in-store customer experience like Music (Milliman,1982; Milliman,1986; Areni & Kim, 1993; Matilla & Wirtz, 2001; Eroglu, Machleit & Chebat 2005), Product display and Shelf space (Cox,1970; Gagnon & Osterhans, 1985; Bawa, Landwehr and Krishna, 1989; Kotzan & Evanson, 1996; Chandon, Hutchinson, Bradlow and Young, 2009), In-store signage (Chevalier 1975; Woodside and Waddle 1975), Atmospheric color (Bellizz & Hite, 1992; Brogman, 2004), Window display (Edwards & Shackley, 1992), Odour (Hirsch, 1995; Matilla & Wirtz, 2001; Teller & Dennis, 2012; Vaccaro, Ahlawat, Yucetepe and Lee, 2012), Design and décor (Wakefeild & Blodgett, 1999)



20

4. Hypothesis Testing & Findings

Shapiro-Wilk test is used to test the normality of the data as it is the most sensitive normality test, this rejects the null hypothesis of normality at the smallest sample sizes compared to other tests, at all levels of skewness and kurtosis (Ahad et.al. 2011). Table 1 shows the result of test it is significant for consumer electronic category (W(98)=0.963, p<0.05), grocery (W(98)=0.954, p<0.05) and for fashion apparels (W(98)=0.21, p<0.05). Table 2 shows the result of Levene's test, it shows that the variances were equal for consumer electronics (F(1,96)=1.226, p>0.05), groceries (F(1,96=2.469, p>0.05) and fashion apparels (F(1,96)=0.902, p>0.05) product categories. As such, these data are not normally distributed, and the groups have homogeneous variances.

Table 1: Tests of NormalityaKolmogorov-Smirnov Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

CE .070 98 .200* .963 98 .007

Groc .056 98 .200* .954 98 .002

FA .416 98 .000 .210 98 .000

*. This is a lower bound of the true significance.a. Lilliefors Significance Correction

Table 2: Test of Homogeneity of Variances

Levene Statistic df1 df2 Sig.

CE 1.226 1 96 .271

Groc 2.469 1 96 .119

FA .902 1 96 .345

4.1 Product Categories Hypothesis

Friedman two way ANOVA was used to compare the mean ranks of the product categories to check the significance at α=0.05. The test statistics (Table 3) show that overall in-store customer experience varies significantly across the

2three product categories x 2)= 82.52, p<0.05. aTable 3: Test Statistics

N 98

Chi-Square 82.548

Df 2

Asymp. Sig. .000

Exact Sig. .000

Point Probability .000

a. Friedman Test

4.2 Gender Hypothesis

Mann Whitney U test was conducted to statistically check the H0b. As shown in table 4, in-store customer experience in male and female respondents did not differ significantly in case of consumer electronics U= 907.5, z=-1.001,

5. Discussion and Implications

5.1Discussion

The results of the study show that the in-store customer experience as its influence on the shopping behavior and in term on the sales outcome. Further, it can be noted from the study that the influence of various stimuli of in-store infrastructure in not same across the different product categories under the study namely consumer electronics, groceries and fashion apparels. The difference in the customer experiences can not be attributed to the differences in the demographic variables like gender, age, income, education and marital status.

5.2 Implications

The researchers and marketers need to understand that the brick and mortar retailers need to restrategise in terms of the customer experiences that they offer to the customer in various retail categories and hence the controllable physical environment can not be generalized. Further, it should be noted from the study that there must be some influencing variables specific to product category, to attract the customers.

Future research may be conducted in the field of understanding the interaction of retail infrastructure and the in-store customer experience amongst the various types of shoppers like economic, personalizing, ethical, recreational, apathetic etc. Further, the degree to which a particular stimuli, and its relative weightage in building the atmospherics of the store could be explored across more product categories. Apart from retailers' private in-store infrastructure, the influence of the public infrastructure like transport and travel on the customer experience can also be studied. This study is limited to Dehradun and s small sample, covering more cities and with a large sample a comprehensive study could be carried.

Refrences

Areni, C. S., Kim, D. (1993). The influence of background music on shopping behavior: Classical versus Top –Forty Music in Wine Store; Advances in Consumer Research, 19, 336-340.

Ahad, N. A., Yin, S.T., Othman, A.R., Yaacob, C.R. (2011). Sensitivity of normality to non normal data, Sains Malaysiana, 40(6), 637-641.

Bawa, K., Landwehr, J. T., Krishna (1989). A., Consumer response to retailer's marketing environments: An analysis of coffee purchase data, Journal of Retailing, 65(4), 471-495.

Bellizzi, J. A., & Hite, R. E. (1992). Environmental color, consumer feelings, and purchase likelihood. Psychology & marketing, 9(5), 347-363.

4.5 Age Group Hypothesis

The respondents were classified in five age groups namely, less than 20yrs (7), 21 to 30 yrs(45), . 31 to 40 yrs(34), 41-50 yrs (7) and greater than 50 years (5).There is no difference in the in-store customer experience of customers of different age groups in all three product categories (Table 7) namely consumer electronics (H4)=3.915, p>0.05, groceries (H4)=3.68, p>0.05 and fashion apparels H(4)=5.864, p>0.05.

a,bTable 7: Test Statistics

CE Groc FA

Chi-Square 3.915 3.680 5.864

Df 4 4 4

Asymp. Sig. .418 .451 .210c c cSig. .421 .463 .204

Monte Carlo Sig. Lower Bound .408 .450 .194

99% Confidence IntervalUpper Bound .434 .476 .214

a. Kruskal Wallis Testb. Grouping Variable: Age Groupc. Based on 10000 sampled tables with starting seed 2000000.

4.6 Monthly Family Income Hypothesis

Monthly family income groups have been divided in four groups with range of less than Rs 30000, Rs 30001 to 45000, Rs 45001 to 50000 and Rs 50001 and above. There is no difference in the in-store customer experience across the family income category in all three product categories (Table 8) namely consumer electronics (H3)=0.67, p>0.05, groceries (H3)=2.52, p>0.05, and fashion apparels H(3)=0.507, p>0.05.


CE Groc FA

Chi-Square .670 2.518 .507

Df 3 3 3

Asymp. Sig. .880 .472 .917

Monte Carlo Sig.c c cSig. .880 .477 .917

99% Confidence IntervalLower Bound .872 .464 .909

Upper Bound .889 .490 .924

a. Kruskal Wallis Test

b. Grouping Variable: Monthly family income

c. Based on 10000 sampled tables with starting seed 1314643744.

21

p>0.05, groceries U=984.5, z=-0.413, p>0.05, and fashion apparels U=901.5, z=-1.047, p>0.05,

aTable 4: Test Statistics

CE Groc FA

Mann-Whitney U 907.500 984.500 901.500

Wilcoxon W 1403.500 3262.500 3179.500

Z -1.001 -.413 -1.047

Asymp. Sig. (2-tailed) .317 .680 .295

Exact Sig. (2-tailed) .319 .683 .298

Exact Sig. (1-tailed) .160 .341 .149

Point Probability .001 .001 .001

a. Grouping Variable: Gender

4.3 Marital Status Hypothesis

Mann Whitney U test was conducted to statistically check the H0c. As shown in table 5, in-store customer experience between married and unmarried respondents did not differ significantly in case of consumer electronics U= 1057.5, z=-0.933, p>0.05, groceries U=1009, z= -1.279, p>0.05, and fashion apparels U=953, z=-1.68, p>0.05.


CE Groc FA

Mann-Whitney U 1057.500 1009.000 953.000

Wilcoxon W 2542.500 2494.000 2438.000

Z -.933 -1.279 -1.680

Asymp. Sig. (2-tailed) .351 .201 .093

Exact Sig. (2-tailed) .354 .202 .093

Exact Sig. (1-tailed) .177 .101 .047


a. Grouping Variable: M_Status

4.4 Education Level Hypothesis

The respondents were classified as graduates (25) and post graduates (73). Mann Whitney U test was conducted to statistically check the H0d. As shown in Table 6, in-store customer experience between married and unmarried respondents did not differ significantly in case of consumer electronics U= 859, z=-0.436, p>0.05, groceries U=752, z= -1.309, p>0.05, and fashion apparels U=790, z=-0.995, p>0.05.


CE Groc FA

Mann-Whitney U 859.000 752.000 790.500

Wilcoxon W 1184.000 1077.000 3491.500

Z -.436 -1.309 -.995

Asymp. Sig. (2-tailed) .663 .191 .320

Exact Sig. (2-tailed) .666 .193 .323

Exact Sig. (1-tailed) .333 .096 .161


a. Grouping Variable: Education

Influence of Retail Infrastructure Stimuli on In-Store Customer ExperienceInfluence of Retail Infrastructure Stimuli on In-Store Customer Experience


20

4. Hypothesis Testing & Findings

Shapiro-Wilk test is used to test the normality of the data as it is the most sensitive normality test, this rejects the null hypothesis of normality at the smallest sample sizes compared to other tests, at all levels of skewness and kurtosis (Ahad et.al. 2011). Table 1 shows the result of test it is significant for consumer electronic category (W(98)=0.963, p<0.05), grocery (W(98)=0.954, p<0.05) and for fashion apparels (W(98)=0.21, p<0.05). Table 2 shows the result of Levene's test, it shows that the variances were equal for consumer electronics (F(1,96)=1.226, p>0.05), groceries (F(1,96=2.469, p>0.05) and fashion apparels (F(1,96)=0.902, p>0.05) product categories. As such, these data are not normally distributed, and the groups have homogeneous variances.

Table 1: Tests of NormalityaKolmogorov-Smirnov Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

CE .070 98 .200* .963 98 .007

Groc .056 98 .200* .954 98 .002

FA .416 98 .000 .210 98 .000

*. This is a lower bound of the true significance.a. Lilliefors Significance Correction

Table 2: Test of Homogeneity of Variances

Levene Statistic df1 df2 Sig.

CE 1.226 1 96 .271

Groc 2.469 1 96 .119

FA .902 1 96 .345

4.1 Product Categories Hypothesis

Friedman two way ANOVA was used to compare the mean ranks of the product categories to check the significance at α=0.05. The test statistics (Table 3) show that overall in-store customer experience varies significantly across the

2three product categories x 2)= 82.52, p<0.05. aTable 3: Test Statistics

N 98

Chi-Square 82.548

Df 2

Asymp. Sig. .000

Exact Sig. .000

Point Probability .000

a. Friedman Test

4.2 Gender Hypothesis

Mann Whitney U test was conducted to statistically check the H0b. As shown in table 4, in-store customer experience in male and female respondents did not differ significantly in case of consumer electronics U= 907.5, z=-1.001,


5.1Discussion

The results of the study show that the in-store customer experience as its influence on the shopping behavior and in term on the sales outcome. Further, it can be noted from the study that the influence of various stimuli of in-store infrastructure in not same across the different product categories under the study namely consumer electronics, groceries and fashion apparels. The difference in the customer experiences can not be attributed to the differences in the demographic variables like gender, age, income, education and marital status.

5.2 Implications

The researchers and marketers need to understand that the brick and mortar retailers need to restrategise in terms of the customer experiences that they offer to the customer in various retail categories and hence the controllable physical environment can not be generalized. Further, it should be noted from the study that there must be some influencing variables specific to product category, to attract the customers.

Future research may be conducted in the field of understanding the interaction of retail infrastructure and the in-store customer experience amongst the various types of shoppers like economic, personalizing, ethical, recreational, apathetic etc. Further, the degree to which a particular stimuli, and its relative weightage in building the atmospherics of the store could be explored across more product categories. Apart from retailers' private in-store infrastructure, the influence of the public infrastructure like transport and travel on the customer experience can also be studied. This study is limited to Dehradun and s small sample, covering more cities and with a large sample a comprehensive study could be carried.

Refrences

Areni, C. S., Kim, D. (1993). The influence of background music on shopping behavior: Classical versus Top –Forty Music in Wine Store; Advances in Consumer Research, 19, 336-340.

Ahad, N. A., Yin, S.T., Othman, A.R., Yaacob, C.R. (2011). Sensitivity of normality to non normal data, Sains Malaysiana, 40(6), 637-641.

Bawa, K., Landwehr, J. T., Krishna (1989). A., Consumer response to retailer's marketing environments: An analysis of coffee purchase data, Journal of Retailing, 65(4), 471-495.

Bellizzi, J. A., & Hite, R. E. (1992). Environmental color, consumer feelings, and purchase likelihood. Psychology & marketing, 9(5), 347-363.

4.5 Age Group Hypothesis

The respondents were classified in five age groups namely, less than 20yrs (7), 21 to 30 yrs(45), . 31 to 40 yrs(34), 41-50 yrs (7) and greater than 50 years (5).There is no difference in the in-store customer experience of customers of different age groups in all three product categories (Table 7) namely consumer electronics (H4)=3.915, p>0.05, groceries (H4)=3.68, p>0.05 and fashion apparels H(4)=5.864, p>0.05.


CE Groc FA

Chi-Square 3.915 3.680 5.864

Df 4 4 4

Asymp. Sig. .418 .451 .210c c cSig. .421 .463 .204

Monte Carlo Sig. Lower Bound .408 .450 .194

99% Confidence IntervalUpper Bound .434 .476 .214

a. Kruskal Wallis Testb. Grouping Variable: Age Groupc. Based on 10000 sampled tables with starting seed 2000000.

4.6 Monthly Family Income Hypothesis

Monthly family income groups have been divided in four groups with range of less than Rs 30000, Rs 30001 to 45000, Rs 45001 to 50000 and Rs 50001 and above. There is no difference in the in-store customer experience across the family income category in all three product categories (Table 8) namely consumer electronics (H3)=0.67, p>0.05, groceries (H3)=2.52, p>0.05, and fashion apparels H(3)=0.507, p>0.05.


CE Groc FA

Chi-Square .670 2.518 .507

Df 3 3 3

Asymp. Sig. .880 .472 .917

Monte Carlo Sig.c c cSig. .880 .477 .917

99% Confidence IntervalLower Bound .872 .464 .909

Upper Bound .889 .490 .924

a. Kruskal Wallis Test

b. Grouping Variable: Monthly family income

c. Based on 10000 sampled tables with starting seed 1314643744.

21

p>0.05, groceries U=984.5, z=-0.413, p>0.05, and fashion apparels U=901.5, z=-1.047, p>0.05,


CE Groc FA

Mann-Whitney U 907.500 984.500 901.500

Wilcoxon W 1403.500 3262.500 3179.500

Z -1.001 -.413 -1.047

Asymp. Sig. (2-tailed) .317 .680 .295

Exact Sig. (2-tailed) .319 .683 .298

Exact Sig. (1-tailed) .160 .341 .149


a. Grouping Variable: Gender

4.3 Marital Status Hypothesis

Mann Whitney U test was conducted to statistically check the H0c. As shown in table 5, in-store customer experience between married and unmarried respondents did not differ significantly in case of consumer electronics U= 1057.5, z=-0.933, p>0.05, groceries U=1009, z= -1.279, p>0.05, and fashion apparels U=953, z=-1.68, p>0.05.


CE Groc FA

Mann-Whitney U 1057.500 1009.000 953.000

Wilcoxon W 2542.500 2494.000 2438.000

Z -.933 -1.279 -1.680

Asymp. Sig. (2-tailed) .351 .201 .093

Exact Sig. (2-tailed) .354 .202 .093

Exact Sig. (1-tailed) .177 .101 .047


a. Grouping Variable: M_Status

4.4 Education Level Hypothesis

The respondents were classified as graduates (25) and post graduates (73). Mann Whitney U test was conducted to statistically check the H0d. As shown in Table 6, in-store customer experience between married and unmarried respondents did not differ significantly in case of consumer electronics U= 859, z=-0.436, p>0.05, groceries U=752, z= -1.309, p>0.05, and fashion apparels U=790, z=-0.995, p>0.05.


CE Groc FA

Mann-Whitney U 859.000 752.000 790.500

Wilcoxon W 1184.000 1077.000 3491.500

Z -.436 -1.309 -.995

Asymp. Sig. (2-tailed) .663 .191 .320

Exact Sig. (2-tailed) .666 .193 .323

Exact Sig. (1-tailed) .333 .096 .161


a. Grouping Variable: Education

Influence of Retail Infrastructure Stimuli on In-Store Customer ExperienceInfluence of Retail Infrastructure Stimuli on In-Store Customer Experience


Brady, M. K., Joseph C. Jr. (2001). Some new thoughts on conceptualizing perceived service quality: A

22 23

1. Introduction

Since 1980, responsibility and worries of the society for the environment had drawn attention of the society to marketing. Green marketing and environment protection has become an area of interest for the researchers in the present scenario. Most of the European economies have shown a sharp increase in their interest in conserving the society with the development of green-friendly products.

The main reason for the environment awareness in the society is that the maximum countries in the world are promoting those plan and policies which are green-friendly in nature and educating the common people to create the image of green trust in the minds of customers (Charter and Polonsky, 2009). In the last few years, the Asian countries also made an effort to promote green marketing and societal protection in their economies (Chan, 2004). Indian economy also promotes and uses the same concept and tools to protect the society from harmful impact of pollution (Jain and Kaur, 2014). But maximum work related to the tools of green marketing is from the west and from Asian continent (Martenson, 2007). The studies on green marketing show that the customers from these economies have also become aware about the concept of green marketing. These customers are more attentive and cautious towards the emerging global business problems and issues. On the other side, the marketers are taking this as a new business opportunity for good profit. Recently government of Hong Kong have focused and stated the importance of these green issues in their policy (Chan,2004).There is lack of studies about the impact of green marketing tools on Indian consumers. This

Impact of Green Marketing Tools on Buying Behaviour of Indian Consumer

Trilok Pratap Singh *Dr. Somesh Dhamija **

Krishanveer Singh ***

ABSTRACTGreen marketing tools such as eco-label, eco-brand and eco-advertisement play an important role in creating perception

and awareness about attributes and characteristics of green products and promoting demand for environmentally friendly

products. Green marketing tools can be used by marketer for re-marketing, promoting and packaging their products and

services for the satisfaction of the customers in a green way. On the other side the modern concept of green marketing

tools provides new guidelines which have opened the new chance and favorable environment to the companies. In this

research paper, we attempt to study the impact of green marketing tools on buying behavior of Indian consumers by

observing and examining their buying habits of the green products and the factors affecting them.

Key Words: Green marketing tools,Eco-label, Eco-brand, Eco-advertising, Re-marketing.

*Research Scholar, Department of Management, Jiwaji University, Gwalior**Professor, Institute of Business Management, GLA University, Mathura***Assistant Professor, Institute of Business Management, GLA University, Mathura

research, therefore, tries to fullfll the research gap by studying and examining the behaviors of Indian consumers towards green product and the factors which affect them.

2. Literature Review

In the late 1980s, for the very first time, the concept of “green marketing” was originated and promoted in the market (Peattie and Crane, 2005). Some of the researchers identified three levels of green marketing. The first level since the 1980s, second level in the 1990s, and the third level from 2000 onwards. Green marketing focuses on societal issues and strategies which enhance the knowledge of the customer and involvement of the marketer in these green-friendly activities Green marketing is defined as marketing to find the solution to the customer problem without any harmful effect on society (O'Dwyer and Carson, 2009). Green marketing is the green promotion and green development of product which is green-friendly in nature (Chatterjee, 2009). Since late-1990s, the consumers have become more cautious and aware about the concept of green marketing (Sammer, 2006). Now consumers expect critical care from the companies and from other concerned personnel on these green issues (Roe, 2011). Green customers are those customers who dislike those products and services which are harmful for the society (Sammer, 2006). Some of the researchers report that the environment problems consist of the customers worries (Wustenhagen and Bilharz, 2014). Companies all over the world have started implementing green strategies to protect the problem to the environment (Ottaman and Hartman, 2006). As



Brady, M. K., Joseph C. Jr. (2001). Some new thoughts on conceptualizing perceived service quality: A

22 23

1. Introduction

Since 1980, responsibility and worries of the society for the environment had drawn attention of the society to marketing. Green marketing and environment protection has become an area of interest for the researchers in the present scenario. Most of the European economies have shown a sharp increase in their interest in conserving the society with the development of green-friendly products.

The main reason for the environment awareness in the society is that the maximum countries in the world are promoting those plan and policies which are green-friendly in nature and educating the common people to create the image of green trust in the minds of customers (Charter and Polonsky, 2009). In the last few years, the Asian countries also made an effort to promote green marketing and societal protection in their economies (Chan, 2004). Indian economy also promotes and uses the same concept and tools to protect the society from harmful impact of pollution (Jain and Kaur, 2014). But maximum work related to the tools of green marketing is from the west and from Asian continent (Martenson, 2007). The studies on green marketing show that the customers from these economies have also become aware about the concept of green marketing. These customers are more attentive and cautious towards the emerging global business problems and issues. On the other side, the marketers are taking this as a new business opportunity for good profit. Recently government of Hong Kong have focused and stated the importance of these green issues in their policy (Chan,2004).There is lack of studies about the impact of green marketing tools on Indian consumers. This


Trilok Pratap Singh *Dr. Somesh Dhamija **

Krishanveer Singh ***

ABSTRACTGreen marketing tools such as eco-label, eco-brand and eco-advertisement play an important role in creating perception

and awareness about attributes and characteristics of green products and promoting demand for environmentally friendly

products. Green marketing tools can be used by marketer for re-marketing, promoting and packaging their products and

services for the satisfaction of the customers in a green way. On the other side the modern concept of green marketing

tools provides new guidelines which have opened the new chance and favorable environment to the companies. In this

research paper, we attempt to study the impact of green marketing tools on buying behavior of Indian consumers by

observing and examining their buying habits of the green products and the factors affecting them.

Key Words: Green marketing tools,Eco-label, Eco-brand, Eco-advertising, Re-marketing.

*Research Scholar, Department of Management, Jiwaji University, Gwalior**Professor, Institute of Business Management, GLA University, Mathura***Assistant Professor, Institute of Business Management, GLA University, Mathura

research, therefore, tries to fullfll the research gap by studying and examining the behaviors of Indian consumers towards green product and the factors which affect them.


In the late 1980s, for the very first time, the concept of “green marketing” was originated and promoted in the market (Peattie and Crane, 2005). Some of the researchers identified three levels of green marketing. The first level since the 1980s, second level in the 1990s, and the third level from 2000 onwards. Green marketing focuses on societal issues and strategies which enhance the knowledge of the customer and involvement of the marketer in these green-friendly activities Green marketing is defined as marketing to find the solution to the customer problem without any harmful effect on society (O'Dwyer and Carson, 2009). Green marketing is the green promotion and green development of product which is green-friendly in nature (Chatterjee, 2009). Since late-1990s, the consumers have become more cautious and aware about the concept of green marketing (Sammer, 2006). Now consumers expect critical care from the companies and from other concerned personnel on these green issues (Roe, 2011). Green customers are those customers who dislike those products and services which are harmful for the society (Sammer, 2006). Some of the researchers report that the environment problems consist of the customers worries (Wustenhagen and Bilharz, 2014). Companies all over the world have started implementing green strategies to protect the problem to the environment (Ottaman and Hartman, 2006). As



compared to the developing economies, the firms from the west are observed too be more concerned and are willing to start their operations for green marketing (Mathur and Mathur, 2010). Slowly and steadily, the concept of green marketing is gaining the momentum (Suman and Suparna, 2010). Green marketing is an important tool in the hands of the marketers which plays an important role in attending and creating consumer awareness by making organizations green-friendly in the India (Cohen,2012).

2.1 Tools of Green Marketing

Three green marketing tools are studied in this research work to make customers aware about the green friendly products. These tools include green-brand (eco-brand), green-label (eco-label) and green advertisement (eco advertising) and will change the perception of people and make the people aware towards the greenly-friendly products (Cohen, 2012).

2.2 Green-Labeling

The concept of green label was introduced first time in Germany in late seventies (Kumar, 2014). Green label is an important green tool mainly used by marketers in order to promote green marketing and awareness among the society for particular product (D'Souza et al., 2006). The Green labels mainly provide the identification about the green product with two important aspects: value function and information function (Sammer and Wustenhagen, 2006). Rex and Baumann (2007) explained the concept of green-label as a tool for facilitating the green awareness and selection of green products. Many researchers explain green –label as a tool to give an idea to the customer about the safe product (D'Souza et. al., 2006). It is found that green labeling also act as a important tool which will affects the decision of the customer while making the purchase (Chen, 2011, Sammer and Stenhagen, 2006). Green label acts as a positive bridge in order to move the customer for the final purchase about the green product and service (Rashid, 2009). Some of the research studies explain the linkage between customer buying motive and green label ((D'Souza, 2004). According to some of the researchers the concept of green label in marketing is not focused yet, but if the marketer pays full attention to it then the outcomes could be much better as compared to the present scenario ( D'Souza (2004). One main reason that is hindering the impact of green label is trust of the customer on this concept (Stafford, 2003).

2.3 Green-Brand

A green brand is a brand that consumers associate with environmental conservation and sustainable business practices. Such a brand appeals to the consumers who are conscious about protection of environment. A green-

brand is a combination of sign, symbol, design and name to reflect on the environmental-friendly characters of the product. A green brand can add unique selling point to a product and can enhance corporate credibility (Chatterjee, 2009). Green branding tends to attract customers as it facilitated identification of eco freiendly quality products which are less harmful to the environment. The concept of green-brand is used to position the product in the mind of the customer and also used as a tool for the promotion. All these factors play an important role in actual purchase behavior and alter it with significant impact (Hartmann et al., 2005). There are certain category of products which the customer want eco-friendly and non-hazardous at any cost such as plastic and pesticides (Rahbar and Abdul Wahid, 2010). As compared to the Asian economies the western markets are more advance and friendly towards these green products (Wustenhagen and Bilharz, 2014).

2.4 Green-Advertisements

Green-advertising is the advertising focused on creating awareness about green products and promoting the sale of such products. Green-advertising is one of the techniques used by the companies to attract the customer and to enhance the market share. Often the companies that use green advertising also use eco-friendly operations and packaging. Throughout the globe, many organizations are using the concept of green advertising to get the attention of the customers and find solution of the ecological problems (Dasgupta, 2013). The main aim of green-advertising is to motivate the customers to green products to earn reasonable profit. Companies are attracted towards the green advertising because of three reasons: (i) concern of society about environment, (ii) support of society to companies showing support too environment, and (iii) to enhance sales and profit. Green-advertising develops the positive synergy and induces customers to buy green products (Bakewell, 2012). In green-advertisements an indirect message is conveyed to the society and things are presented in such a way that they in f luence the consumer purchase in tent ion (Vasanthakumar, 2008).

2.5 Purchase Behavior of Consumers

Green marketing of the activities focused by most of the countries and slowly changing the attitude towards green products. This is motivating the customers to buy green products. As compared to the developing economies, the firms from the developed economies (from the west) are more attracted and are willing to start their operations in these Asian economies in order to capture the market share of the demand for green products (Gurau and Ranchhod, 2005, Sekaran, 2006). Marketers are very

24

focused towards marketing of green products to capture the market and to satisfy the customer needs and wants with eco-friendly environment (Ahmad et. al. , 2010).

2.6 Objectives and Hypothesis

As would be noted from the literature review, there is lot of research work done on the impact of green marketing tools on customers' buying behaviour in the context of developed countries, but not much has been done in context of developing nations. Therefore, this study intends to test the following hypothesis in regard to Indian customers:

H1. Green marketing tools are positively associated with customers' buying behavior.

H1a. Green-labeling is positively associated with customers' buying behavior.

H1b. Green-branding is positively associated with customers' buying behavior.

H1c. Green-advertising is positively associated with customers' buying behavior.


The study is based primary data on responsiveness of customers to green marketing tools (green-labeling, green branding and green-advertising) collected through a questionnaire. Data are analysed by using factor analysis and multiple regression. Following the data analysis, findings, implications and limitations of the study are discussed.

3.1 Sample and Procedure

Most of the customers studied here are Indian consumers. The age range is between 35-65 years, the reason behind selecting this age group is that the people in this age group are more involved in the purchasing activities and are having the power to make decision according to their convenience. Data are collected through a structured questionnaire. The scale used for the study is five-point Likert scale (1 = Strongly Disagree, 5 = Strongly Disagree). With the help of this scale we try to study the impact of green marketing tools on customers' buying behavior. Study is based on the actual data as shared by the customers personally on green marketing concept. Customers are selected from the major shopping areas from metros (NCR Region, Jaipur, Indore and Pune) and non-metros (Agra, Gwalior, Aligarh, Jhansi) in India. Sample size from metros is 250 (NCR Region, Jaipur, Indore and Pune) and from non-metros is 250 (Agra, Gwalior, Alighar, Jhansi) and the total sample size of 500 customers.

3.2 Measures and Data Collection

The structured questionnaire consists of five parts, as shown below in Table 1.

Table 1: Five Parts of Questionnaire

Part Area Covered

I Demographic Features

II Idea and perception of green marketing.

III Idea and perception of green-label

IV Idea and perception of green-brand

V Idea and perception of green-advertising

The scale used for the study is five-point Likert scale (1 = Strongly Disagree, 5 = Strongly Disagree). With the help of this scale we try to study the impact of green marketing tools on customer buying behavior. Questionnaires were filled personally through interaction with the respondents as per convenience sample of customers from the cities sited above. The respondents were requested to share their perceptions and preferences about green products vis-à-vis non green products. Green products are taken to be energy saving products and non green products to be energy consuming.


Factor analysis was done of three variables for all the variables to get knowledge about the importance of each utilized variables and sub variables.To study the impact of green marketing tools on actual buying behavior, the green marketing tools are used as independent variables namely, green-advertising, green-label and green-brand. These all three variables are used for factor analysis. A factor analysis of all the items was done ( the composition of all the items is as follows, green-brand, items of green advertisement and items of green-label) appropriately named as green advertisement, green-label, green-brand

Loading factors of all the items lie between 0.63 to 0.91 and eigenvalue of 2.79, 1.82, 1.54, and 1.11 respectively. The value of variance in all three factors is 71.66 percent the value of KMO is 0.66 ,Bartlett's Test of Sphercity is with significant value. The value of Cronbach alpha for the entire four dimensions is 0.79, 0.71, 0.83 and 0.55 respectively for green advertisement, green-brand, and green-label.

To analyze the relationship between the dependent variable and independent variable the multiple regression analysis was performed with a addressed hypothesis. Mean and standard deviation are used for descriptive analysis of all variables.

25

Impact of Green Marketing Tools on Buying Behaviour of Indian ConsumerImpact of Green Marketing Tools on Buying Behaviour of Indian Consumer


compared to the developing economies, the firms from the west are observed too be more concerned and are willing to start their operations for green marketing (Mathur and Mathur, 2010). Slowly and steadily, the concept of green marketing is gaining the momentum (Suman and Suparna, 2010). Green marketing is an important tool in the hands of the marketers which plays an important role in attending and creating consumer awareness by making organizations green-friendly in the India (Cohen,2012).

2.1 Tools of Green Marketing

Three green marketing tools are studied in this research work to make customers aware about the green friendly products. These tools include green-brand (eco-brand), green-label (eco-label) and green advertisement (eco advertising) and will change the perception of people and make the people aware towards the greenly-friendly products (Cohen, 2012).

2.2 Green-Labeling

The concept of green label was introduced first time in Germany in late seventies (Kumar, 2014). Green label is an important green tool mainly used by marketers in order to promote green marketing and awareness among the society for particular product (D'Souza et al., 2006). The Green labels mainly provide the identification about the green product with two important aspects: value function and information function (Sammer and Wustenhagen, 2006). Rex and Baumann (2007) explained the concept of green-label as a tool for facilitating the green awareness and selection of green products. Many researchers explain green –label as a tool to give an idea to the customer about the safe product (D'Souza et. al., 2006). It is found that green labeling also act as a important tool which will affects the decision of the customer while making the purchase (Chen, 2011, Sammer and Stenhagen, 2006). Green label acts as a positive bridge in order to move the customer for the final purchase about the green product and service (Rashid, 2009). Some of the research studies explain the linkage between customer buying motive and green label ((D'Souza, 2004). According to some of the researchers the concept of green label in marketing is not focused yet, but if the marketer pays full attention to it then the outcomes could be much better as compared to the present scenario ( D'Souza (2004). One main reason that is hindering the impact of green label is trust of the customer on this concept (Stafford, 2003).

2.3 Green-Brand

A green brand is a brand that consumers associate with environmental conservation and sustainable business practices. Such a brand appeals to the consumers who are conscious about protection of environment. A green-

brand is a combination of sign, symbol, design and name to reflect on the environmental-friendly characters of the product. A green brand can add unique selling point to a product and can enhance corporate credibility (Chatterjee, 2009). Green branding tends to attract customers as it facilitated identification of eco freiendly quality products which are less harmful to the environment. The concept of green-brand is used to position the product in the mind of the customer and also used as a tool for the promotion. All these factors play an important role in actual purchase behavior and alter it with significant impact (Hartmann et al., 2005). There are certain category of products which the customer want eco-friendly and non-hazardous at any cost such as plastic and pesticides (Rahbar and Abdul Wahid, 2010). As compared to the Asian economies the western markets are more advance and friendly towards these green products (Wustenhagen and Bilharz, 2014).

2.4 Green-Advertisements

Green-advertising is the advertising focused on creating awareness about green products and promoting the sale of such products. Green-advertising is one of the techniques used by the companies to attract the customer and to enhance the market share. Often the companies that use green advertising also use eco-friendly operations and packaging. Throughout the globe, many organizations are using the concept of green advertising to get the attention of the customers and find solution of the ecological problems (Dasgupta, 2013). The main aim of green-advertising is to motivate the customers to green products to earn reasonable profit. Companies are attracted towards the green advertising because of three reasons: (i) concern of society about environment, (ii) support of society to companies showing support too environment, and (iii) to enhance sales and profit. Green-advertising develops the positive synergy and induces customers to buy green products (Bakewell, 2012). In green-advertisements an indirect message is conveyed to the society and things are presented in such a way that they in f luence the consumer purchase in tent ion (Vasanthakumar, 2008).

2.5 Purchase Behavior of Consumers

Green marketing of the activities focused by most of the countries and slowly changing the attitude towards green products. This is motivating the customers to buy green products. As compared to the developing economies, the firms from the developed economies (from the west) are more attracted and are willing to start their operations in these Asian economies in order to capture the market share of the demand for green products (Gurau and Ranchhod, 2005, Sekaran, 2006). Marketers are very

24

focused towards marketing of green products to capture the market and to satisfy the customer needs and wants with eco-friendly environment (Ahmad et. al. , 2010).

2.6 Objectives and Hypothesis

As would be noted from the literature review, there is lot of research work done on the impact of green marketing tools on customers' buying behaviour in the context of developed countries, but not much has been done in context of developing nations. Therefore, this study intends to test the following hypothesis in regard to Indian customers:

H1. Green marketing tools are positively associated with customers' buying behavior.

H1a. Green-labeling is positively associated with customers' buying behavior.

H1b. Green-branding is positively associated with customers' buying behavior.

H1c. Green-advertising is positively associated with customers' buying behavior.


The study is based primary data on responsiveness of customers to green marketing tools (green-labeling, green branding and green-advertising) collected through a questionnaire. Data are analysed by using factor analysis and multiple regression. Following the data analysis, findings, implications and limitations of the study are discussed.

3.1 Sample and Procedure

Most of the customers studied here are Indian consumers. The age range is between 35-65 years, the reason behind selecting this age group is that the people in this age group are more involved in the purchasing activities and are having the power to make decision according to their convenience. Data are collected through a structured questionnaire. The scale used for the study is five-point Likert scale (1 = Strongly Disagree, 5 = Strongly Disagree). With the help of this scale we try to study the impact of green marketing tools on customers' buying behavior. Study is based on the actual data as shared by the customers personally on green marketing concept. Customers are selected from the major shopping areas from metros (NCR Region, Jaipur, Indore and Pune) and non-metros (Agra, Gwalior, Aligarh, Jhansi) in India. Sample size from metros is 250 (NCR Region, Jaipur, Indore and Pune) and from non-metros is 250 (Agra, Gwalior, Alighar, Jhansi) and the total sample size of 500 customers.

3.2 Measures and Data Collection

The structured questionnaire consists of five parts, as shown below in Table 1.

Table 1: Five Parts of Questionnaire

Part Area Covered

I Demographic Features

II Idea and perception of green marketing.

III Idea and perception of green-label

IV Idea and perception of green-brand

V Idea and perception of green-advertising

The scale used for the study is five-point Likert scale (1 = Strongly Disagree, 5 = Strongly Disagree). With the help of this scale we try to study the impact of green marketing tools on customer buying behavior. Questionnaires were filled personally through interaction with the respondents as per convenience sample of customers from the cities sited above. The respondents were requested to share their perceptions and preferences about green products vis-à-vis non green products. Green products are taken to be energy saving products and non green products to be energy consuming.


Factor analysis was done of three variables for all the variables to get knowledge about the importance of each utilized variables and sub variables.To study the impact of green marketing tools on actual buying behavior, the green marketing tools are used as independent variables namely, green-advertising, green-label and green-brand. These all three variables are used for factor analysis. A factor analysis of all the items was done ( the composition of all the items is as follows, green-brand, items of green advertisement and items of green-label) appropriately named as green advertisement, green-label, green-brand

Loading factors of all the items lie between 0.63 to 0.91 and eigenvalue of 2.79, 1.82, 1.54, and 1.11 respectively. The value of variance in all three factors is 71.66 percent the value of KMO is 0.66 ,Bartlett's Test of Sphercity is with significant value. The value of Cronbach alpha for the entire four dimensions is 0.79, 0.71, 0.83 and 0.55 respectively for green advertisement, green-brand, and green-label.

To analyze the relationship between the dependent variable and independent variable the multiple regression analysis was performed with a addressed hypothesis. Mean and standard deviation are used for descriptive analysis of all variables.

25



Table 3: Description of Variables

S.No. Variable (Green Mean Standard Marketing Tools) Deviation

1 Green-label 2.90 0.78

2 Green-brand 3.18 0.61

3 Green-advertisement 3.71 0.62

4 Actual purchase behavior 3.62 0.81

It may be noted from Table 3 that most of the respondents admit that green advertisement is one of the effective tools to attract customer attract and educate them about the benefits of green marketing and eco-friendly brands. The mean value of actual purchase behaviour is 3.62. Here the mean value of green advertisement is (3.71), the mean value of green-brand is (3.18), and the mean value of green label is (2.90).

Table 4: Result of Multiple Regression Analysis

S.No. Variable ß Sig.

1 Green-label -0.08 0.17


3 Green-advertisement. 0.05 0.52

Multiple regression analysis was carried out in order to identify the significant factors related to the consumer purchase behavior and the formulated hypotheses are tested. The results in Table 4 indicate that, green-brand (β= 0:16, p < 0.01) are absolutely and definitely associated with buying behavior of customer, accordingly, H1b is accepted. The impact of green-label and green advertisement is not significant on actual purchase behavior with (β = -0.08, p > 0.01) and (β= 0:05, p > 0.01) Hypotheses H1a and H1c are rejected.

5. Findings

! The Indian consumers are found to be more attentive and influenced by the green brand and commercially this concept is more beneficial for the marketer for creating positive image and enhancing the market share.

! Most of the Indians found to be very cautious for the environment and they provide the full support to the concept of green marketing.

! Green marketing seems to be motivating the customers to purchase the green product and services and increase the awareness in the Indian market.

! Many customers those are not purchasing the green

26

product in India because they are not aware about the green marketing benefits and outcomes.

! Most of the customers believed that green advertising increases awareness of customers about green products and finally affects their purchase decision.

! One thing which does not support green marketing in India is trust of the customer on green advertisement and their perception that the companies in the market are for profit making not for taking care of the society (Kilbourne, 1995). Most of the consumers who are not satisfied with the green marketing efforts of the marketer are so due to the promotion style which these marketer are adopting, which is not fruitful (Davis, 1993). In Indian market the marketers are using mass media for the promotion of green marketing and the main medium is television and Internet.

For the proper convincing and satisfaction of the customer it is noticed that the green brand tools should satisfy the customer in every way what hay want for their satisfaction and the marketer should develop the policy in such a way that make the whole environment green friendly. At the end we can say that the green brand tools plays an very important role in the purchase decision of the Indian consumer. Apart from the industries the government of the India is also paying attention towards the concept of green brand and giving importance to the green manufacturing process and creating the green environment.

6. Limitations

The study has a few limitations. Due to time constraint, many areas have not been covered. The literature review for this study focused on the theoretical fields of green marketing and consumer buying habits. Convenience sampling is used, which is non-probability sampling technique and fail to provide real scene of the society. The sample is too small to draw conclusive implications. This research covers only general green brands and not specific green brands and Customers are less aware about the concept of green marketing. So they were nor very clear while responding.

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Gurau, C. and Ranchhod, A. (2005). International Green Marketing: A Comparative Study of British and Romanian Firms, International Marketing Review, Vol. 22 No. 5, pp. 547-61.

Hartmann, P. and Ibań˜ez, V. A. (2006). Green Value Added, Marketing Intelligence & Planning, Vol. 24 No. 7, pp. 673-80.

Hartmann, P., Ibań˜ez, V. A. and Sainz, F. J. (2005). Green Branding Effects on Attitude: Functional versus Emotional Positioning Strategies, Marketing Intelligence & Planning, Vol. 23 No. 1, pp. 9-29.

Jain, S. K. and G. Kaur (2014). Green Marketing: An Indian Perspective, Decision 31(2), 168–209.

Kumar, P. (2014). Greening Retail: An Indian Experience, International Journal of Retail and Distribution Management, Vol. 42 No. 7, pp. 613-625.

27

Table 2: Result of Factor Analysis

S.No. ITEMS 1 2 3 4

IV Eigenvalue 2.79 1.82 1.54 1.11

V Percentage of variance 28.02 15.59 18.12 11.01

VI Bartlett's test of sphericity 0.00

VII Kaiser-Meyer-Olkin 0.65

VIII Extraction Method: Principle component analysis Reliability 0.79 0.71 0.83 0.55

II Green-label

A I am aware of green-label 0.01 0.14 0.91 0.03

B The green label is best recognized to me. 0.06 0.13 0.90 0.004

III Green-brand

A I am aware of green-brand 0.09 0.63 0.33 0.10

B I know green-brand is useful. 0.15 0.88 0.02 0.04

III Green-advertisement

A Green-advertisement improve awareness about green

Products 0.87 0.03 0.007 0.10

B I like green-advertisement 0.82 0.13 0.10 0.05

C Green-advertisement influence consumer purchase behavior 0.79 0.16 0.009 0.13



Table 3: Description of Variables

S.No. Variable (Green Mean Standard Marketing Tools) Deviation

1 Green-label 2.90 0.78


3 Green-advertisement 3.71 0.62

4 Actual purchase behavior 3.62 0.81

It may be noted from Table 3 that most of the respondents admit that green advertisement is one of the effective tools to attract customer attract and educate them about the benefits of green marketing and eco-friendly brands. The mean value of actual purchase behaviour is 3.62. Here the mean value of green advertisement is (3.71), the mean value of green-brand is (3.18), and the mean value of green label is (2.90).

Table 4: Result of Multiple Regression Analysis

S.No. Variable ß Sig.

1 Green-label -0.08 0.17


3 Green-advertisement. 0.05 0.52

Multiple regression analysis was carried out in order to identify the significant factors related to the consumer purchase behavior and the formulated hypotheses are tested. The results in Table 4 indicate that, green-brand (β= 0:16, p < 0.01) are absolutely and definitely associated with buying behavior of customer, accordingly, H1b is accepted. The impact of green-label and green advertisement is not significant on actual purchase behavior with (β = -0.08, p > 0.01) and (β= 0:05, p > 0.01) Hypotheses H1a and H1c are rejected.

5. Findings

! The Indian consumers are found to be more attentive and influenced by the green brand and commercially this concept is more beneficial for the marketer for creating positive image and enhancing the market share.

! Most of the Indians found to be very cautious for the environment and they provide the full support to the concept of green marketing.

! Green marketing seems to be motivating the customers to purchase the green product and services and increase the awareness in the Indian market.

! Many customers those are not purchasing the green

26

product in India because they are not aware about the green marketing benefits and outcomes.

! Most of the customers believed that green advertising increases awareness of customers about green products and finally affects their purchase decision.

! One thing which does not support green marketing in India is trust of the customer on green advertisement and their perception that the companies in the market are for profit making not for taking care of the society (Kilbourne, 1995). Most of the consumers who are not satisfied with the green marketing efforts of the marketer are so due to the promotion style which these marketer are adopting, which is not fruitful (Davis, 1993). In Indian market the marketers are using mass media for the promotion of green marketing and the main medium is television and Internet.

For the proper convincing and satisfaction of the customer it is noticed that the green brand tools should satisfy the customer in every way what hay want for their satisfaction and the marketer should develop the policy in such a way that make the whole environment green friendly. At the end we can say that the green brand tools plays an very important role in the purchase decision of the Indian consumer. Apart from the industries the government of the India is also paying attention towards the concept of green brand and giving importance to the green manufacturing process and creating the green environment.

6. Limitations

The study has a few limitations. Due to time constraint, many areas have not been covered. The literature review for this study focused on the theoretical fields of green marketing and consumer buying habits. Convenience sampling is used, which is non-probability sampling technique and fail to provide real scene of the society. The sample is too small to draw conclusive implications. This research covers only general green brands and not specific green brands and Customers are less aware about the concept of green marketing. So they were nor very clear while responding.

References

Ahmad, H., Shah, I. A. and Ahmad, K. (2010). Factors in Environmental Advertising Influencing Consumer's Purchase Intention. European Journal of Scientific Research, 48(2), 217-226

Bakewell, C. and Mitchell, V. (2012). Generation Y Female Consumer Decision-Making Styles, Journal of Retail & Distribution Management, Vol. 31 No. 2, pp. 95-106.

Bleda, M. and Valente, M. (2008). Graded Green-Labels: A Demand-Oriented Approach to Reduce Pollution'',

Technological Forecasting and Social Change, TFS-17065, p. 13.

Charter, M. and Polonsky, M. J. (2009). Green Marketing: A Global Perspective on Green Marketing Practices, Greenleaf Publications, Sheffield.

Chen, Y. S. (2011). Green Organizational Identity: Sources and Consequence, Management Decision, Vol. 49 No. 3, pp. 384-404.

Chan, R. Y. K. (2004). Consumer Responses to Green Advertising in China, Marketing Intelligence & Planning, Vol. 22 No. 4, pp. 427-37.

Chatterjee, P. (2009). Green Brand Extension Strategy and Online Communities, Journal of Systems and Information Technology, Vol. 11 No. 4, pp. 367-84.

Coakes, S. J. and Steed, L. G. (2001). SPSS for Windows: Analysis without Anguish, John Wiley & Sons, Brisbane.

Cohen, M. R. (2012). Green Information versus Green Attitudes, Journal of Green Education, Vol. 3 No. 2, pp. 5-8.

D'Souza, C. (2004). Green labels Programmes: A Stakeholder (consumer) Perspective, Corporate Communication: An International Journal, Vol. 9 No. 3, pp. 179-88.

D'Souza, C., Taghian, M. and Lamb, P. (2006). ''An Empirical Study on the Influence of Green Labels on Consumers, Corporate Communication: An International Journal, Vol. 11 No. 2, pp. 162-73.

Dasgupta, N. (2013). Environmental Enforcement and Small Industries in India: Reworking the Problem in the Poverty Context, World Development, Vol. 28 No. 5, pp. 945-967.

Gurau, C. and Ranchhod, A. (2005). International Green Marketing: A Comparative Study of British and Romanian Firms, International Marketing Review, Vol. 22 No. 5, pp. 547-61.

Hartmann, P. and Ibań˜ez, V. A. (2006). Green Value Added, Marketing Intelligence & Planning, Vol. 24 No. 7, pp. 673-80.

Hartmann, P., Ibań˜ez, V. A. and Sainz, F. J. (2005). Green Branding Effects on Attitude: Functional versus Emotional Positioning Strategies, Marketing Intelligence & Planning, Vol. 23 No. 1, pp. 9-29.

Jain, S. K. and G. Kaur (2014). Green Marketing: An Indian Perspective, Decision 31(2), 168–209.

Kumar, P. (2014). Greening Retail: An Indian Experience, International Journal of Retail and Distribution Management, Vol. 42 No. 7, pp. 613-625.

27

Table 2: Result of Factor Analysis

S.No. ITEMS 1 2 3 4

IV Eigenvalue 2.79 1.82 1.54 1.11

V Percentage of variance 28.02 15.59 18.12 11.01

VI Bartlett's test of sphericity 0.00

VII Kaiser-Meyer-Olkin 0.65

VIII Extraction Method: Principle component analysis Reliability 0.79 0.71 0.83 0.55

II Green-label

A I am aware of green-label 0.01 0.14 0.91 0.03

B The green label is best recognized to me. 0.06 0.13 0.90 0.004

III Green-brand

A I am aware of green-brand 0.09 0.63 0.33 0.10

B I know green-brand is useful. 0.15 0.88 0.02 0.04

III Green-advertisement

A Green-advertisement improve awareness about green

Products 0.87 0.03 0.007 0.10

B I like green-advertisement 0.82 0.13 0.10 0.05

C Green-advertisement influence consumer purchase behavior 0.79 0.16 0.009 0.13



Martenson, R. (2007). Corporate Trust Image, Satisfaction and Store Loyalty; A Study of the Store as a Trust, Store Trusts and Manufacturer Trusts”, Inter-national Journal of Retail & Distribution Management 35(7), 544–555.

Mat Said, A., Ahmadun, F.-R., Hj Paim, L. and Masud, J. (2003). Green Concerns, Knowledge and Practices Gap among Malaysian Teachers, International Journal of Sustainability in Higher Education, Vol. 4 No. 4, pp. 305-13.

Mathur, L. K., and Mathur, I., (2010). An analysis of the Wealth Effects of Green Market Strategies. Journal of Business Research, 50, 193-200.

O'Dwyer, M., Gilmore, A. and Carson, D. (2009). Innovative Marketing in SMEs, European Journal of Marketing, Vol. 43 Nos 1/2, pp. 46-61.

Ottman, J. A., Stafford, E. R. and Hartman, C. L. (2006). Avoiding Green Marketing Myopia: Ways to Improve Consumer Appeal for Environmentally Preferable Products, Environment, Vol. 48 No. 5, pp. 22-36.

Parliamentary Office of Science and Technology (2004). Green Policy and Innovation, Report No. 212, Parliamentary Office of Science and Technology.

Peattie, K. and Crane, A. (2005). Green Marketing: Legend, Myth, Farce or Prophesy? Qualitative Market Research: An International Journal, Vol. 8 No. 4, pp. 357-70.

Rahbar, E. and Abdul Wahid, N. (2010). Consumers' Perception of Green Products Category: Implication of SMEs, paper presented at the SME and Marketing Mini Conference, Penang.

Roe, B., Teisl, M. F., Rong, H. and Levy, A. S. (2011). Characteristic of Consumer-Preferred Labeling Policies: Experimental Evidence from Price and Green Disclosure for Deregulated Electricity Services, Journal of Consumer Affairs, Vol. 35 No. 1, pp. 1-26.

Sammer, K. and Wustenhagen, R. (2006), The Influence of Green-labelling on Consumer Behaviour – Results of a Discrete Choice Analysis for Washing Machines, Business Strategy and the Environment, Vol. 15 No. 3, pp. 185-99.

Stafford, E. R. (2003). Energy Efficiency and the New Green Marketing, Environment, March, pp. 8-10.

Sekaran, U. (2006). Research Methods for Business, A Skill Building Approach, Ar Emm International, New Dehli.

Suman Kumar Dawn and Suparna Biswas (2010). Employer Branding: A New Strategic Dimension of Indian Corporations, Asian Journal of management Research, Retrieved from http://ipublishing.co.in /ajmrvol1no1/sped12011/AJMRSP1003.pdf

Vasanthakumar N . Bhatt (2008). Green Marketing Begins with Green Designs, Journal of Business industrial marketing, Vol;8.Issue 4.

Wustenhagen, R. and Bilharz, M. (2014), Green Energy Market Development in Germany: Effective Public Policy and Emerging Customer Demand, Energy Policy, Vol. 34, pp. 1681-96.

28

1. Introduction

The changing lifestyle of the urban population has also resulted in many people relying on the internet for their shopping needs. One of the key reasons for using the Internet for shopping is convenience. The convenience of shopping from the comfort of one's home while having a broader selection of merchandise to choose from, competitive prices and more access to information has brought about an increased reliance on the online medium. Online retail is the fastest growing channel globally (Planet Retail 2014). The Indian online market is growing rapidly. A joint study by Assocham and Grant Thornton (2015) has indicated that, online shoppers are expected to increase from 20 million in 2013 to 40 million in 2016, with majority of them coming online through smartphones According to Accel Partners Report (2014), 35 percent of online sales in 2016 will be influenced by women, a growth of 24X compared to 2012 levels.

2. Need of Study

Since convenience is a context-based concept, consumers' perceptions of convenience vary from one setting to another (Jiang, Yamg and Jun 2013). Prior research has investigated the multidimensional view of service convenience within a brick-and-mortar service setting (Berry et. al., 2002; Seiders 2000; Seiders et. al., 2007; Colwell et. al., (2008)). Beauchamp and Ponder (2010) report different perceptions of retail convenience for both in-store and online shoppers. The growing importance of convenience construct necessitates the need to have new business models to deliver hassle-free service and maintain loyal customer base. According to KPMG (2104)

.

Report on Emerging Consumer Segments in India, successful e-retailers have to transform their brand into a lifestyle focused on catering to the needs, desires and whims of customers, wherever and whenever they are.

Much research on the measurement of service convenience, its antecedents and outcomes has been carried out in Western countries. Despite the increased significance of e-retail in India, not much research has been done in this field. The studies conducted have focused on understanding consumers' attitude towards online shopping. There is lack of research in the Indian context specifically examining the dimensions of service convenience in online shopping. Thus, empirical investigation aimed at measuring and validating dimensions of service convenience is of utmost importance for online retailers to develop strategies to increase margins. The purpose of this study is to propose online service convenience as a multidimensional construct that is conceptualized by the six dimensions: access, search, transaction, evaluation, possession and post-benefit. The purpose of this study is to describe the development and refinement of a scale for measuring online shopping convenience. Specifically, our key objectives are (a) to provide a conceptualization of online shopping and its dimensions, (b) to develop a scale for measuring service convenience and its dimensions and (c) to assess reliability of the measures.

The paper is organized as follows. First, we provide the theoretical background of the convenience construct. Next we briefly discuss the construct of online shopping convenience. Then the research methodology for the

29

Why Customers Buy Online: Measuring the Underlying Dimensions of Online Shopping Convenience

Harsandaldeep Kaur *Nidhi Sabharwal **

ABSTRACTConsumers increasingly make use of online shopping for benefits such as saving time and energy, convenience,

competitive prices, broader selection of merchandise and more access to information. Convenience is the greatest

motivator for online shopping. Researchers define convenience as the consumer's time and effort perceptions related to

buying or using a service. Service convenience is often thought of as a means of adding value to consumers, by decreasing

the amount of time and effort a consumer must expend on the service. Keeping this in mind, the purpose of this study is to

report on the development and validation of service convenience scale in the online retailing context in India. The study

identifies six dimensions of online shopping convenience in India using exploratory and confirmatory factor analysis. The

multidimensional scale (23 items) evidenced reliability and convergent validity. Results of the study, managerial

implications and future research directions are discussed.

Key Words: Internet, Online Shopping, Service Convenience, India

*Assistant Professor, Department of Commerce, Guru Nanak Dev University, Amristsar**Assistant Professor, PG Department of Commerce and Business Administration, Khalsa College, Amritsar



Martenson, R. (2007). Corporate Trust Image, Satisfaction and Store Loyalty; A Study of the Store as a Trust, Store Trusts and Manufacturer Trusts”, Inter-national Journal of Retail & Distribution Management 35(7), 544–555.

Mat Said, A., Ahmadun, F.-R., Hj Paim, L. and Masud, J. (2003). Green Concerns, Knowledge and Practices Gap among Malaysian Teachers, International Journal of Sustainability in Higher Education, Vol. 4 No. 4, pp. 305-13.

Mathur, L. K., and Mathur, I., (2010). An analysis of the Wealth Effects of Green Market Strategies. Journal of Business Research, 50, 193-200.

O'Dwyer, M., Gilmore, A. and Carson, D. (2009). Innovative Marketing in SMEs, European Journal of Marketing, Vol. 43 Nos 1/2, pp. 46-61.

Ottman, J. A., Stafford, E. R. and Hartman, C. L. (2006). Avoiding Green Marketing Myopia: Ways to Improve Consumer Appeal for Environmentally Preferable Products, Environment, Vol. 48 No. 5, pp. 22-36.

Parliamentary Office of Science and Technology (2004). Green Policy and Innovation, Report No. 212, Parliamentary Office of Science and Technology.

Peattie, K. and Crane, A. (2005). Green Marketing: Legend, Myth, Farce or Prophesy? Qualitative Market Research: An International Journal, Vol. 8 No. 4, pp. 357-70.

Rahbar, E. and Abdul Wahid, N. (2010). Consumers' Perception of Green Products Category: Implication of SMEs, paper presented at the SME and Marketing Mini Conference, Penang.

Roe, B., Teisl, M. F., Rong, H. and Levy, A. S. (2011). Characteristic of Consumer-Preferred Labeling Policies: Experimental Evidence from Price and Green Disclosure for Deregulated Electricity Services, Journal of Consumer Affairs, Vol. 35 No. 1, pp. 1-26.

Sammer, K. and Wustenhagen, R. (2006), The Influence of Green-labelling on Consumer Behaviour – Results of a Discrete Choice Analysis for Washing Machines, Business Strategy and the Environment, Vol. 15 No. 3, pp. 185-99.

Stafford, E. R. (2003). Energy Efficiency and the New Green Marketing, Environment, March, pp. 8-10.

Sekaran, U. (2006). Research Methods for Business, A Skill Building Approach, Ar Emm International, New Dehli.

Suman Kumar Dawn and Suparna Biswas (2010). Employer Branding: A New Strategic Dimension of Indian Corporations, Asian Journal of management Research, Retrieved from http://ipublishing.co.in /ajmrvol1no1/sped12011/AJMRSP1003.pdf

Vasanthakumar N . Bhatt (2008). Green Marketing Begins with Green Designs, Journal of Business industrial marketing, Vol;8.Issue 4.

Wustenhagen, R. and Bilharz, M. (2014), Green Energy Market Development in Germany: Effective Public Policy and Emerging Customer Demand, Energy Policy, Vol. 34, pp. 1681-96.

28

1. Introduction

The changing lifestyle of the urban population has also resulted in many people relying on the internet for their shopping needs. One of the key reasons for using the Internet for shopping is convenience. The convenience of shopping from the comfort of one's home while having a broader selection of merchandise to choose from, competitive prices and more access to information has brought about an increased reliance on the online medium. Online retail is the fastest growing channel globally (Planet Retail 2014). The Indian online market is growing rapidly. A joint study by Assocham and Grant Thornton (2015) has indicated that, online shoppers are expected to increase from 20 million in 2013 to 40 million in 2016, with majority of them coming online through smartphones According to Accel Partners Report (2014), 35 percent of online sales in 2016 will be influenced by women, a growth of 24X compared to 2012 levels.

2. Need of Study

Since convenience is a context-based concept, consumers' perceptions of convenience vary from one setting to another (Jiang, Yamg and Jun 2013). Prior research has investigated the multidimensional view of service convenience within a brick-and-mortar service setting (Berry et. al., 2002; Seiders 2000; Seiders et. al., 2007; Colwell et. al., (2008)). Beauchamp and Ponder (2010) report different perceptions of retail convenience for both in-store and online shoppers. The growing importance of convenience construct necessitates the need to have new business models to deliver hassle-free service and maintain loyal customer base. According to KPMG (2104)

.

Report on Emerging Consumer Segments in India, successful e-retailers have to transform their brand into a lifestyle focused on catering to the needs, desires and whims of customers, wherever and whenever they are.

Much research on the measurement of service convenience, its antecedents and outcomes has been carried out in Western countries. Despite the increased significance of e-retail in India, not much research has been done in this field. The studies conducted have focused on understanding consumers' attitude towards online shopping. There is lack of research in the Indian context specifically examining the dimensions of service convenience in online shopping. Thus, empirical investigation aimed at measuring and validating dimensions of service convenience is of utmost importance for online retailers to develop strategies to increase margins. The purpose of this study is to propose online service convenience as a multidimensional construct that is conceptualized by the six dimensions: access, search, transaction, evaluation, possession and post-benefit. The purpose of this study is to describe the development and refinement of a scale for measuring online shopping convenience. Specifically, our key objectives are (a) to provide a conceptualization of online shopping and its dimensions, (b) to develop a scale for measuring service convenience and its dimensions and (c) to assess reliability of the measures.

The paper is organized as follows. First, we provide the theoretical background of the convenience construct. Next we briefly discuss the construct of online shopping convenience. Then the research methodology for the

29

Why Customers Buy Online: Measuring the Underlying Dimensions of Online Shopping Convenience

Harsandaldeep Kaur *Nidhi Sabharwal **

ABSTRACTConsumers increasingly make use of online shopping for benefits such as saving time and energy, convenience,

competitive prices, broader selection of merchandise and more access to information. Convenience is the greatest

motivator for online shopping. Researchers define convenience as the consumer's time and effort perceptions related to

buying or using a service. Service convenience is often thought of as a means of adding value to consumers, by decreasing

the amount of time and effort a consumer must expend on the service. Keeping this in mind, the purpose of this study is to

report on the development and validation of service convenience scale in the online retailing context in India. The study

identifies six dimensions of online shopping convenience in India using exploratory and confirmatory factor analysis. The

multidimensional scale (23 items) evidenced reliability and convergent validity. Results of the study, managerial

implications and future research directions are discussed.

Key Words: Internet, Online Shopping, Service Convenience, India

*Assistant Professor, Department of Commerce, Guru Nanak Dev University, Amristsar**Assistant Professor, PG Department of Commerce and Business Administration, Khalsa College, Amritsar



paper is described, followed by the discussion of study results and limitations of the study.


The concept of convenience has been discussed in the marketing and consumer behavior literature over the last century. In the marketing literature, the concept of convenience was introduced by Copeland (1923), who initiated the classification of convenience goods. Copeland (1923) defines convenience goods as “intensively distributed products that require minimal time and physical and mental effort to purchase” (Berry et. al. 2000). Most of the early studies in marketing have used the convenience construct as product classification schema, focused only on convenience goods (Bucklin, 1963; Murphy and Enis, 1986). Brown (1990) suggested that convenience consists of the time and efforts used in purchasing a product rather than a characteristic or attribute of a product. The early marketing usage of convenience has revealed that consumers' time and effort costs are important in purchasing a product or service (Kotler and Zaltman, 1971, Etgar, 1978; Yale and Venkatesh, 1986).

Recent research in the conceptualization and measurement of convenience represent service convenience as multi-dimensional construct (Berry et al., 2002; Seiders et. al., 2007). In a retailing context, Seiders (2000) developed a convenience framework for retail. They defined retail convenience as the ease and speed of shopping. Berry et. al. (2002) coined the term “service convenience” and defined it as time and effort perception of customers related to their purchase and usage of service. In a conceptual study they proposed five types of service convenience viz. decision convenience, access convenience, transaction convenience, benefit convenience and post benefit convenience. They further suggested that the above service convenience types will have a significant positive impact on positive outcomes viz. service quality, service fairness and customer satisfaction. Seiders et. al. (2007) developed the SERVCON scale and empirically validated the service convenience construct in the context of traditional service consumption. Colwell et. al. (2008) developed and validated scale for the measurement of service convenience in the personal cellular telephone and internet usage context. Furthermore, Moeller, Fassnacht and Ettinger (2009) found that service convenience types has a significant positive impact on customers' behavioural loyalty (share of wallet and share of visits) and a significant negative impact on their exit intentions. In the Indian context, Aagja, Mammen and Sraswat (2011) have found that access, benefit, and decision convenience dimensions are more important whereas dimensions like transaction and post-benefit convenience are less relevant.

4. Online Shopping Convenience

Prior literature on online shopping has focused on measuring the quality of website. Online shopping convenience is the speed and ease with which buyers can do shopping on the internet. Very few studies have examined the convenience construct in the online context. Beauchamp and Ponder (2010) empirically examined consumer perceptions of retail convenience for in-store and online shoppers. They found that online shoppers have more favorable perceptions of access convenience, search convenience, and transaction convenience than in-store shoppers. Jiang, Yang and Jun (2013) identified key dimensions of convenience and their associated sub-dimensions specific in the context of online shopping. The reported five dimensions of online shopping convenience are: access, search, evaluation, transaction, and possession/post-purchase convenience.


The empirical phase of the study is aimed at identifying the dimensions of online shopping convenience in the Indian context. The research method is explained in detail below.

5.1 Measurement Instrument

The survey instrument for the study was developed after following recommendations of Churchill (1979), Gerbing and Anderson (1988) and Saxe & Weitz (1982) for measure development. An extensive literature survey was carried out and all the dimensions of online shopping convenience were conceptually defined and their domain was specified. To generate a large pool of items for measurement of various constructs, we carried out an extensive literature survey and conducted interviews with several customers. This process resulted in generation of 35 items. The selected items are shown in the Annexure I. A questionnaire was developed in which each item was measured on a 7-point Likert Scale ranging from “very strongly agree” to “very strongly disagree”.

5.2 Assessment of Content Validity

The assessment of content validity serves as a pretest, permitting the deletion of items that are deemed to be conceptually inconsistent (Hinkin 1998). Content validity is ensured to the extent that expert judges agree that these items are reflective of the overall construct and are representative of the domain and facets of the construct (Netemeyer et. al., 2003). A panel of three marketing judges evaluated the items for content validity and suggested the removal of some items they considered to be redundant, double-barreled and ambiguous. This process resulted in elimination of 8 items, leaving a pool of 27 items for further analysis.

30

5.3 Sample and Data Collection

Respondents selected for the study were screened with a criterion of having buying experience online of at least six months. The study sample consisted of students studying in a major university of Punjab. Data was collected using self-administered questionnaire. Respondents were selected randomly. Of the 235 completed questionnaires, 203 were usable, resulting in a response rate of 86%. Respondents were mostly male (67%) and were dominantly in the age group of 20-24 years (75%). About 48% of the respondents had total monthly family income greater than Rs. 25,000.

6. Data Analysis and Results

Data analysis proceeds in three stages. The first stage is to conduct initial item analyses to determine which items are to be eliminated from or retained in the item pool (Clark and Watson 1995). Next an exploratory factor analysis was performed using the principal component analysis with Varimax rotation. In the third stage, confirmatory factor analysis was performed to confirm that factor structure.

6.1 Item Analysis

We used item-total correlation and corrected item-to-total correlation for item analysis. First, the correlation of each item with the total score for each construct was computed and items with low correlations with the total score were eliminated from the scale (Ruekert and Churchill, 1984). In the second stage, items in each construct were correlated with total score of other constructs. Items that did not have statistically higher correlations with the dimension to which they were hypothesized to belong in comparison with item correlations with remaining dimensions total scores were deleted (Ruekert and Churchill, 1984; Bearden, Netemeyer and Teel, 1989). Thirdly, corrected item-to-total correlations were examined for each construct. Items with high corrected item-to-total correlation have more variance relating to what the items have in common and add more to the test's reliablilty than items with low corrected item-to-total correlation (Nunnally and Bernstein, 1994). Items that had corrected item-to-total correlations more than or equal to 0.35 were retained and rest were deleted (Saxe and Weitz, 1982). These analyses resulted in a reduced scale with 23 items to measure various dimension of online shopping convenience.

6.2 Exploratory Factor Analysis

Exploratory factor analysis was conducted. We used principle component factor analysis followed by Varimax rotation to identify the number of dimensions. Six components with eigen values greater than one were extracted from the data. Together, these six components

explain 67.66 percent of the total variance. Reliability of the factors was calculated using Cronbach alpha. Table 1 depicts the reliability alphas for various constructs. As can be seen, the coefficient alphas for all the six dimensions are above .60 which is an acceptable limit for early stages of basic research (Nunnally and Bernstein, 1994).

6.3 Confirmatory Factor Analysis

Confirmatory Factor Analysis (CFA) was employed to assess the latent factor structure. Confirmatory factor analysis using AMOS 18.0 was used to test the measurement model.

6.4 Model Fit

Model fit determines the degree to which the structural model fits the sample data. AMOS output yielded a Chi-square value (χ2) of 276.725 with 215 degrees of freedom. The CMIN/DF (minimum discrepancy divided by degrees of freedom) ratio was 1.287, which is within the recommended range of less than 5, which are indicative of an acceptable fit between the hypothetical model and the sample data (Carmines and McIver, 1981). The root mean square error of approximation (RMSEA) was .030, which falls within cutoff value of 0.06 (Hu and Bentler, 1999). The Tucker-Lewis Index (TLI) was .972 while the Comparative Fit Index (CFI) was .976. The Bentler-Bonett normed fit index (NFI) was .903 and Bollen's incremental fit index (IFI) was .916. The values for fit indices are shown in Table 1 and all exceed the recommended level of 0.90, suggesting that the hypothesized model represented an adequate fit to the data.

6.5 Composite Reliability

Composite reliability is a measure of the internal consistency of the construct indicators, which depicts the degree to which the items indicate the common latent (unobserved) construct (Hair et. al., 1998). Even a perfectly unidimensional scale will be of little practical use if the resultant composite score has unacceptably low reliability (Anderson and Gerbing, 1988). Highly reliable constructs are those in which the indicators are highly inter correlated, indicating that they are all measuring the same latent construct (Koufteros, 1999; Lu, Lai and Cheng, 2007). Table 1 shows the composite reliability for various dimenions. All constructs had composite reliability above the recommended level of 0.70 (Hair et. al., 1998).

6.6 Scale Validation

Once the reliability and the structure of the scale are supported, the validity of the instrument has to be assessed.

Convergent Validity

A measure is said to possess convergent validity if independent measures of the same construct converge, or

31

Why Customers Buy Online: Measuring the Underlying Dimensions of Online Shopping ConvenienceWhy Customers Buy Online: Measuring the Underlying Dimensions of Online Shopping Convenience


paper is described, followed by the discussion of study results and limitations of the study.


The concept of convenience has been discussed in the marketing and consumer behavior literature over the last century. In the marketing literature, the concept of convenience was introduced by Copeland (1923), who initiated the classification of convenience goods. Copeland (1923) defines convenience goods as “intensively distributed products that require minimal time and physical and mental effort to purchase” (Berry et. al. 2000). Most of the early studies in marketing have used the convenience construct as product classification schema, focused only on convenience goods (Bucklin, 1963; Murphy and Enis, 1986). Brown (1990) suggested that convenience consists of the time and efforts used in purchasing a product rather than a characteristic or attribute of a product. The early marketing usage of convenience has revealed that consumers' time and effort costs are important in purchasing a product or service (Kotler and Zaltman, 1971, Etgar, 1978; Yale and Venkatesh, 1986).

Recent research in the conceptualization and measurement of convenience represent service convenience as multi-dimensional construct (Berry et al., 2002; Seiders et. al., 2007). In a retailing context, Seiders (2000) developed a convenience framework for retail. They defined retail convenience as the ease and speed of shopping. Berry et. al. (2002) coined the term “service convenience” and defined it as time and effort perception of customers related to their purchase and usage of service. In a conceptual study they proposed five types of service convenience viz. decision convenience, access convenience, transaction convenience, benefit convenience and post benefit convenience. They further suggested that the above service convenience types will have a significant positive impact on positive outcomes viz. service quality, service fairness and customer satisfaction. Seiders et. al. (2007) developed the SERVCON scale and empirically validated the service convenience construct in the context of traditional service consumption. Colwell et. al. (2008) developed and validated scale for the measurement of service convenience in the personal cellular telephone and internet usage context. Furthermore, Moeller, Fassnacht and Ettinger (2009) found that service convenience types has a significant positive impact on customers' behavioural loyalty (share of wallet and share of visits) and a significant negative impact on their exit intentions. In the Indian context, Aagja, Mammen and Sraswat (2011) have found that access, benefit, and decision convenience dimensions are more important whereas dimensions like transaction and post-benefit convenience are less relevant.

4. Online Shopping Convenience

Prior literature on online shopping has focused on measuring the quality of website. Online shopping convenience is the speed and ease with which buyers can do shopping on the internet. Very few studies have examined the convenience construct in the online context. Beauchamp and Ponder (2010) empirically examined consumer perceptions of retail convenience for in-store and online shoppers. They found that online shoppers have more favorable perceptions of access convenience, search convenience, and transaction convenience than in-store shoppers. Jiang, Yang and Jun (2013) identified key dimensions of convenience and their associated sub-dimensions specific in the context of online shopping. The reported five dimensions of online shopping convenience are: access, search, evaluation, transaction, and possession/post-purchase convenience.


The empirical phase of the study is aimed at identifying the dimensions of online shopping convenience in the Indian context. The research method is explained in detail below.

5.1 Measurement Instrument

The survey instrument for the study was developed after following recommendations of Churchill (1979), Gerbing and Anderson (1988) and Saxe & Weitz (1982) for measure development. An extensive literature survey was carried out and all the dimensions of online shopping convenience were conceptually defined and their domain was specified. To generate a large pool of items for measurement of various constructs, we carried out an extensive literature survey and conducted interviews with several customers. This process resulted in generation of 35 items. The selected items are shown in the Annexure I. A questionnaire was developed in which each item was measured on a 7-point Likert Scale ranging from “very strongly agree” to “very strongly disagree”.

5.2 Assessment of Content Validity

The assessment of content validity serves as a pretest, permitting the deletion of items that are deemed to be conceptually inconsistent (Hinkin 1998). Content validity is ensured to the extent that expert judges agree that these items are reflective of the overall construct and are representative of the domain and facets of the construct (Netemeyer et. al., 2003). A panel of three marketing judges evaluated the items for content validity and suggested the removal of some items they considered to be redundant, double-barreled and ambiguous. This process resulted in elimination of 8 items, leaving a pool of 27 items for further analysis.

30

5.3 Sample and Data Collection

Respondents selected for the study were screened with a criterion of having buying experience online of at least six months. The study sample consisted of students studying in a major university of Punjab. Data was collected using self-administered questionnaire. Respondents were selected randomly. Of the 235 completed questionnaires, 203 were usable, resulting in a response rate of 86%. Respondents were mostly male (67%) and were dominantly in the age group of 20-24 years (75%). About 48% of the respondents had total monthly family income greater than Rs. 25,000.

6. Data Analysis and Results

Data analysis proceeds in three stages. The first stage is to conduct initial item analyses to determine which items are to be eliminated from or retained in the item pool (Clark and Watson 1995). Next an exploratory factor analysis was performed using the principal component analysis with Varimax rotation. In the third stage, confirmatory factor analysis was performed to confirm that factor structure.

6.1 Item Analysis

We used item-total correlation and corrected item-to-total correlation for item analysis. First, the correlation of each item with the total score for each construct was computed and items with low correlations with the total score were eliminated from the scale (Ruekert and Churchill, 1984). In the second stage, items in each construct were correlated with total score of other constructs. Items that did not have statistically higher correlations with the dimension to which they were hypothesized to belong in comparison with item correlations with remaining dimensions total scores were deleted (Ruekert and Churchill, 1984; Bearden, Netemeyer and Teel, 1989). Thirdly, corrected item-to-total correlations were examined for each construct. Items with high corrected item-to-total correlation have more variance relating to what the items have in common and add more to the test's reliablilty than items with low corrected item-to-total correlation (Nunnally and Bernstein, 1994). Items that had corrected item-to-total correlations more than or equal to 0.35 were retained and rest were deleted (Saxe and Weitz, 1982). These analyses resulted in a reduced scale with 23 items to measure various dimension of online shopping convenience.

6.2 Exploratory Factor Analysis

Exploratory factor analysis was conducted. We used principle component factor analysis followed by Varimax rotation to identify the number of dimensions. Six components with eigen values greater than one were extracted from the data. Together, these six components

explain 67.66 percent of the total variance. Reliability of the factors was calculated using Cronbach alpha. Table 1 depicts the reliability alphas for various constructs. As can be seen, the coefficient alphas for all the six dimensions are above .60 which is an acceptable limit for early stages of basic research (Nunnally and Bernstein, 1994).

6.3 Confirmatory Factor Analysis

Confirmatory Factor Analysis (CFA) was employed to assess the latent factor structure. Confirmatory factor analysis using AMOS 18.0 was used to test the measurement model.

6.4 Model Fit

Model fit determines the degree to which the structural model fits the sample data. AMOS output yielded a Chi-square value (χ2) of 276.725 with 215 degrees of freedom. The CMIN/DF (minimum discrepancy divided by degrees of freedom) ratio was 1.287, which is within the recommended range of less than 5, which are indicative of an acceptable fit between the hypothetical model and the sample data (Carmines and McIver, 1981). The root mean square error of approximation (RMSEA) was .030, which falls within cutoff value of 0.06 (Hu and Bentler, 1999). The Tucker-Lewis Index (TLI) was .972 while the Comparative Fit Index (CFI) was .976. The Bentler-Bonett normed fit index (NFI) was .903 and Bollen's incremental fit index (IFI) was .916. The values for fit indices are shown in Table 1 and all exceed the recommended level of 0.90, suggesting that the hypothesized model represented an adequate fit to the data.

6.5 Composite Reliability

Composite reliability is a measure of the internal consistency of the construct indicators, which depicts the degree to which the items indicate the common latent (unobserved) construct (Hair et. al., 1998). Even a perfectly unidimensional scale will be of little practical use if the resultant composite score has unacceptably low reliability (Anderson and Gerbing, 1988). Highly reliable constructs are those in which the indicators are highly inter correlated, indicating that they are all measuring the same latent construct (Koufteros, 1999; Lu, Lai and Cheng, 2007). Table 1 shows the composite reliability for various dimenions. All constructs had composite reliability above the recommended level of 0.70 (Hair et. al., 1998).

6.6 Scale Validation

Once the reliability and the structure of the scale are supported, the validity of the instrument has to be assessed.

Convergent Validity

A measure is said to possess convergent validity if independent measures of the same construct converge, or

31



Table1: Online Shopping Convenience Scale Results are highly correlated (Netemeyer et. al. 2003). Convergent validity can be examined from the measurement model by determining whether each indicator's estimated pattern coefficient on its posited underlying factor is significant or not (Anderson and Gerbing, 1988). In the AMOS output file, the t-value is the critical ratio, which represents the parameter estimate divided by its standard error (Netemeyer et al. 2003). As can be seen in Table 1 all the factor loadings are significant at 0.05 significance level, which supports the convergent validity.


In the long term, the most successful online retailers will be those that continually strive to enhance the quality of their customers' interactions with their Web sites, and the outcome of their retail transactions and successful resolution of problems when they occur (Collier and Bienstock 2006). This study contributed to the existing literature by studying the online shopping convenience construct in the Indian context. The second contribution of this study is empiricl validation of online shopping convenience as a multidimensional construct including access convenience, search convenience, transaction convenience, evaluation convenience, possession and post-benefit convenience.

Catering to the specific requirements of time-starved consumers requires a different level of service delivery and supply chain scalabil i ty (KPMG 2014). The multidimensional view of service convenience will help online retailers to identify which dimensions of service convenience are more important and accordingly develop strategies to enhance loyalty and hence profits. By better understanding the forms of convenience and how they work together, retailers can formulate convenience strategies that support lasting customer relationships and raise their competitiveness to new levels (Seiders, Berry and Gresham 2000). The e-retailers generally focus on the product features, price, and delivery in their marketing strategy. Since the scope for product differentiation is limited in online shopping, an understanding of factors which drive customer loyalty is beneficial for customer relationship managers to develop and reinforce marketing strategies to increase retention. Therefore, providing convenience to time starved consumers may enable a competitive advantage. The dimensions of online shopping convenience can be used to identify segments based on the consumers 'perceptions of service convenience towards an online retailer.

8. Limitations

Since the study has been carried out using student sample

only from one Indian city, so the generalizability of the study is a issue of concern. Future research may test dimensions of online shopping convenience for the different online retailers. Another research direction could be the examination of linkage between dimensions of online shopping convenience on one side, and satisfaction on the other.

References

Aagja, J.P ., Mammen, T., and Saraswat, A. (2011). Validating Service Convenience Scale and Profiling Customers: A Study in the Indian Retail Context. Vikalpa, Vol. 36, No. 4, pp. 25-49.

Accel Partners (2014). How Indian E-Commerce Industry is Shaping Up. pp 1-33.

Assocham and Grant Thornton (2015). Law and Technology: Evolving Challenges as a Result of Fraud in E-commerce Sector, pp. 1-24.

Bearden, W. O., Netemeyer, R. G., and Teel, J. E. (1989). Measurement of Consumer Susceptibility to Interpersonal Influence. Journal of consumer research, pp. 473-481.

Beauchamp, M. B. and Ponder, N. (2010). Perceptions of Retail Convenience for In-Store and Online Shoppers. Marketing Management Journal, Vol. 20, No1, pp.

Berry, L. L., Seiders, K. and Grewal, D. (2002). Understanding Service Convenience. Journal of Marketing, Vol. 66, No. 3, pp. 1-17.

Brown, L. G. (1990). Convenience in Services Marketing. Journal of Services Marketing, Vol. 4, No.1, pp. 53-59.

Bucklin, L. P. (1963). Retail Strategy and the Classification of Consumer Goods. Journal of Marketing, pp. 50-55.

Carmines, E. G., and McIver, J. P. (1981). Analyzing Models with Unobserved Variables: Analysis of Covariance Structures. Social Measurement: Current Issues, pp. 65-115.

Churchill Jr, G. A. (1979). A Paradigm for Developing Better Measures of Marketing Constructs. Journal of Marketing Research, pp. 64-73.

Clark, L. A., and Watson, D. (1995). Constructing Validity: Basic Issues in Objective Scale Development. Psychological Assessment, Vol. 7, No. 3, pp. 309-319.

Colwell, S. R., Aung, M., Kanetkar, V., and Holden, A. L. (2008). Toward a Measure of Service Convenience: Multiple-Item Scale Development and Empirical Test.


3332 "Pragyaan: Journal of Management" Volume 13, Issue 2, December 2015"Pragyaan: Journal of Management" Volume 13, Issue 2, December 2015

Item Alpha Component CFA Results

1 2 3 4 5 6 Standar Critical Composite-dized Ratiob ReliabilityFactor Loading

aAC1 .765 .682 .556 – .775

AC2 .836 .835 7.328

AC3 .837 .796 7.320

AC4 .690 .508 5.632

aSC1 .682 .531 .532 – .714

SC2 .828 .661 5.931

SC3 .628 .615 5.731

SC4 .654 .594 5.628

aTC1 .829 .870 .871 – .836

TC2 .741 .643 9.260

TC3 .824 .762 11.149

TC4 .812 .705 10.297

aEC1 .801 .966 .998 – .943

EC2 .967 .997 20.046

EC3 .600 .638 20.046

aPC1 .901 .840 .768 – .901

PC2 .888 .843 12.550

PC3 .896 .879 13.109

PC4 .878 .843 12.543

aPBC1 .862 .798 .683 – .863

PBC2 .794 .800 9.923

PBC4 .817 .837 10.265

PBC5 .799 .805 9.968

Variance Extracted = 67.66% Overall Fit StatisticsKMO Statistic = .737 X2=276.725, 215df, p=0.00;Varimax Rotation CMIN/DF = 1.287

RMSEA=0.03; NFI=0.903,TLI=0.972 CFI=0.976, IFI = .961

n = 203a Indicates a parameter fixed at 1.0 in the measurement model.b All Critical Ratios (t-values) are significant at 0.05.

Table1: Online Shopping Convenience Scale Results are highly correlated (Netemeyer et. al. 2003). Convergent validity can be examined from the measurement model by determining whether each indicator's estimated pattern coefficient on its posited underlying factor is significant or not (Anderson and Gerbing, 1988). In the AMOS output file, the t-value is the critical ratio, which represents the parameter estimate divided by its standard error (Netemeyer et al. 2003). As can be seen in Table 1 all the factor loadings are significant at 0.05 significance level, which supports the convergent validity.


In the long term, the most successful online retailers will be those that continually strive to enhance the quality of their customers' interactions with their Web sites, and the outcome of their retail transactions and successful resolution of problems when they occur (Collier and Bienstock 2006). This study contributed to the existing literature by studying the online shopping convenience construct in the Indian context. The second contribution of this study is empiricl validation of online shopping convenience as a multidimensional construct including access convenience, search convenience, transaction convenience, evaluation convenience, possession and post-benefit convenience.

Catering to the specific requirements of time-starved consumers requires a different level of service delivery and supply chain scalabil i ty (KPMG 2014). The multidimensional view of service convenience will help online retailers to identify which dimensions of service convenience are more important and accordingly develop strategies to enhance loyalty and hence profits. By better understanding the forms of convenience and how they work together, retailers can formulate convenience strategies that support lasting customer relationships and raise their competitiveness to new levels (Seiders, Berry and Gresham 2000). The e-retailers generally focus on the product features, price, and delivery in their marketing strategy. Since the scope for product differentiation is limited in online shopping, an understanding of factors which drive customer loyalty is beneficial for customer relationship managers to develop and reinforce marketing strategies to increase retention. Therefore, providing convenience to time starved consumers may enable a competitive advantage. The dimensions of online shopping convenience can be used to identify segments based on the consumers 'perceptions of service convenience towards an online retailer.

8. Limitations

Since the study has been carried out using student sample

only from one Indian city, so the generalizability of the study is a issue of concern. Future research may test dimensions of online shopping convenience for the different online retailers. Another research direction could be the examination of linkage between dimensions of online shopping convenience on one side, and satisfaction on the other.

References

Aagja, J.P ., Mammen, T., and Saraswat, A. (2011). Validating Service Convenience Scale and Profiling Customers: A Study in the Indian Retail Context. Vikalpa, Vol. 36, No. 4, pp. 25-49.

Accel Partners (2014). How Indian E-Commerce Industry is Shaping Up. pp 1-33.

Assocham and Grant Thornton (2015). Law and Technology: Evolving Challenges as a Result of Fraud in E-commerce Sector, pp. 1-24.

Bearden, W. O., Netemeyer, R. G., and Teel, J. E. (1989). Measurement of Consumer Susceptibility to Interpersonal Influence. Journal of consumer research, pp. 473-481.

Beauchamp, M. B. and Ponder, N. (2010). Perceptions of Retail Convenience for In-Store and Online Shoppers. Marketing Management Journal, Vol. 20, No1, pp.

Berry, L. L., Seiders, K. and Grewal, D. (2002). Understanding Service Convenience. Journal of Marketing, Vol. 66, No. 3, pp. 1-17.

Brown, L. G. (1990). Convenience in Services Marketing. Journal of Services Marketing, Vol. 4, No.1, pp. 53-59.

Bucklin, L. P. (1963). Retail Strategy and the Classification of Consumer Goods. Journal of Marketing, pp. 50-55.

Carmines, E. G., and McIver, J. P. (1981). Analyzing Models with Unobserved Variables: Analysis of Covariance Structures. Social Measurement: Current Issues, pp. 65-115.

Churchill Jr, G. A. (1979). A Paradigm for Developing Better Measures of Marketing Constructs. Journal of Marketing Research, pp. 64-73.

Clark, L. A., and Watson, D. (1995). Constructing Validity: Basic Issues in Objective Scale Development. Psychological Assessment, Vol. 7, No. 3, pp. 309-319.

Colwell, S. R., Aung, M., Kanetkar, V., and Holden, A. L. (2008). Toward a Measure of Service Convenience: Multiple-Item Scale Development and Empirical Test.



Item Alpha Component CFA Results

1 2 3 4 5 6 Standar Critical Composite-dized Ratiob ReliabilityFactor Loading

aAC1 .765 .682 .556 – .775

AC2 .836 .835 7.328

AC3 .837 .796 7.320

AC4 .690 .508 5.632

aSC1 .682 .531 .532 – .714

SC2 .828 .661 5.931

SC3 .628 .615 5.731

SC4 .654 .594 5.628

aTC1 .829 .870 .871 – .836

TC2 .741 .643 9.260

TC3 .824 .762 11.149

TC4 .812 .705 10.297

aEC1 .801 .966 .998 – .943

EC2 .967 .997 20.046

EC3 .600 .638 20.046

aPC1 .901 .840 .768 – .901

PC2 .888 .843 12.550

PC3 .896 .879 13.109

PC4 .878 .843 12.543

aPBC1 .862 .798 .683 – .863

PBC2 .794 .800 9.923

PBC4 .817 .837 10.265

PBC5 .799 .805 9.968

Variance Extracted = 67.66% Overall Fit StatisticsKMO Statistic = .737 X2=276.725, 215df, p=0.00;Varimax Rotation CMIN/DF = 1.287

RMSEA=0.03; NFI=0.903,TLI=0.972 CFI=0.976, IFI = .961

n = 203a Indicates a parameter fixed at 1.0 in the measurement model.b All Critical Ratios (t-values) are significant at 0.05.

Journal of Services Marketing, Vol. 22, No. 2, pp. 160-169.

Copeland, M. T. (1923). Relation of Consumers' Buying Habits to Marketing Methods. Harvard Business Review, Vol. 1, No. 3, pp. 282-289.

Etgar, M. (1978). The Household as a Production Unit. Research in Marketing, Vol. 1, pp. 79-98.

Gerbing, D. W., and Anderson, J. C. (1988). An Updated Paradigm for Scale Development Incorporating Unidimensionality and its Assessment. Journal of Marketing Research, pp. 186-192.

Hair, J. F., Anderson, R. E., Tatham, R. L., and William, C. (1998). Black (1998), Multivariate Data Analysis. New Jersey: Prentice-Hall.

Hinkin, T. R. (1998). A Brief Tutorial on the Development of Measures for Use in Survey Questionnaires. Organizational Research Methods, Vol. 1, No. 1, pp. 104-121.

Jiang, L., Yang, Z., and Jun, M. (2013). Measuring Consumer Perceptions of Online Shopping Convenience. Journal of Service Management, Vol. 24, No. 2, pp. 191-214.

Kotler, P., and Zaltman, G. (1971). Social Marketing: An Approach to Planned Social Change. Journal of Marketing, pp. 3-12.

Koufteros, X. A. (1999). Testing a Model of Pull Production: A Paradigm for Manufacturing Research Using Structural Equation Modeling. Journal of Operations Management, Vol. 17, No. 4, pp. 467-488.

Lu, C. S., Lai, K. H., and Cheng, T. E. (2007). Application of Structural Equation Modeling to Evaluate the Intention of Shippers to Use Internet Services in Liner Shipping. European Journal of Operational Research, Vol. 180, No. 2, pp. 845-867.

Moeller, S., Fassnacht, M., and Ettinger, A. (2009). Retaining Customers with Shopping Convenience. Journal of Relationship Marketing, Vol. 8, No. 4, pp. 313-329.

Murphy, P. E., and Enis, B. M. (1986). Classifying Products Strategically. Journal of Marketing, pp. 24-42.

Netemeyer, R. G., Bearden, W. O., and Sharma, S. (2003). Scaling Procedures: Issues and Applications. Sage Publications.

Nunnally, J. C., and Bernstein, I. H. (1994). Psychometric Theory, New York MCGraw-Hill.

Planet Retail, Deloitte (2014). Online Retail in India Clicking Towards Growth, pp. 1-15.

Ruekert, R. W., and Churcill Jr, G. A. (1984). Reliability and Validity of Alternative Measures of Channel Member Satisfaction. Journal of Marketing Research, 226-233.

Saxe, R., and Weitz, B. A. (1982). The SOCO Scale: A Measure of the Customer Orientation of Salespeople. Journal of Marketing Research, pp. 343-351.

Seiders, K., Berry, L. L., and Gresham, L. G. (2000). Attention, Retailers! How Convenient is Your Convenience Strategy? MIT Sloan Management Review, Vol. 41, No.3, pp. 79.

Seiders, K., Voss, G. B., Godfrey, A. L., and Grewal, D. (2007). SERVCON: Development and Validation of a Multidimensional Service Convenience Scale. Journal of the Academy of Marketing Science, Vol. 35, No. 1, pp. 144-156.

Yale, L., and Venkatesh, A. (1986). Toward the Construct of Convenience in Consumer Research. Advances in Consumer Research, Vol. 13, No.1, pp. 403-408.

Dimension Item ItemLabel

Access Convenience AC1 I could shop anytime I wanted.

AC2 I could order products wherever I am.

AC3 I was able to find the website quickly.

AC4 The website is always accessible.

Search Convenience SC1 It was easy to navigate the website.

SC2 The product classification on website was easy to follow.

SC3 The website provided useful information.

SC4 The website provides variety of search options to find the same product.

SC5 It was easy to get information I needed to make my purchase decision.

SC6 I could find what I wanted without having to look elsewhere.

Transaction Convenience TC1 The checkout process was fast.

TC2 My purchase was completed easily.

TC3 The online payment method was simple.

TC4 The online retailer provides flexible payment options.

TC5 It didn't take a long time to complete the purchase process.

Evaluation Convenience EC1 The online retailer provides product specifics.

EC2 The website uses both text and graphics of product information.

EC3 The online retailer provides sufficient information to identify differentproducts.

Possession Convenience PC1 I was delivered undamaged goods.

PC2 I got exactly what I wanted.

PC3 My order was delivered on time.

PC4 I was properly notified of my order status.

Post-Benefit Convenience PBC1 It was easy to return unwanted goods.

PBC2 Prices were identical to those on the order form.

PBC3 I received all the items I ordered.

PBC4 The online retailer provides liberal exchange policy

PBC5 After purchase problems are resolved quickly.

Annexure

Dimensions of Online Shopping



Journal of Services Marketing, Vol. 22, No. 2, pp. 160-169.

Copeland, M. T. (1923). Relation of Consumers' Buying Habits to Marketing Methods. Harvard Business Review, Vol. 1, No. 3, pp. 282-289.

Etgar, M. (1978). The Household as a Production Unit. Research in Marketing, Vol. 1, pp. 79-98.

Gerbing, D. W., and Anderson, J. C. (1988). An Updated Paradigm for Scale Development Incorporating Unidimensionality and its Assessment. Journal of Marketing Research, pp. 186-192.

Hair, J. F., Anderson, R. E., Tatham, R. L., and William, C. (1998). Black (1998), Multivariate Data Analysis. New Jersey: Prentice-Hall.

Hinkin, T. R. (1998). A Brief Tutorial on the Development of Measures for Use in Survey Questionnaires. Organizational Research Methods, Vol. 1, No. 1, pp. 104-121.

Jiang, L., Yang, Z., and Jun, M. (2013). Measuring Consumer Perceptions of Online Shopping Convenience. Journal of Service Management, Vol. 24, No. 2, pp. 191-214.

Kotler, P., and Zaltman, G. (1971). Social Marketing: An Approach to Planned Social Change. Journal of Marketing, pp. 3-12.

Koufteros, X. A. (1999). Testing a Model of Pull Production: A Paradigm for Manufacturing Research Using Structural Equation Modeling. Journal of Operations Management, Vol. 17, No. 4, pp. 467-488.

Lu, C. S., Lai, K. H., and Cheng, T. E. (2007). Application of Structural Equation Modeling to Evaluate the Intention of Shippers to Use Internet Services in Liner Shipping. European Journal of Operational Research, Vol. 180, No. 2, pp. 845-867.

Moeller, S., Fassnacht, M., and Ettinger, A. (2009). Retaining Customers with Shopping Convenience. Journal of Relationship Marketing, Vol. 8, No. 4, pp. 313-329.

Murphy, P. E., and Enis, B. M. (1986). Classifying Products Strategically. Journal of Marketing, pp. 24-42.

Netemeyer, R. G., Bearden, W. O., and Sharma, S. (2003). Scaling Procedures: Issues and Applications. Sage Publications.

Nunnally, J. C., and Bernstein, I. H. (1994). Psychometric Theory, New York MCGraw-Hill.

Planet Retail, Deloitte (2014). Online Retail in India Clicking Towards Growth, pp. 1-15.

Ruekert, R. W., and Churcill Jr, G. A. (1984). Reliability and Validity of Alternative Measures of Channel Member Satisfaction. Journal of Marketing Research, 226-233.

Saxe, R., and Weitz, B. A. (1982). The SOCO Scale: A Measure of the Customer Orientation of Salespeople. Journal of Marketing Research, pp. 343-351.

Seiders, K., Berry, L. L., and Gresham, L. G. (2000). Attention, Retailers! How Convenient is Your Convenience Strategy? MIT Sloan Management Review, Vol. 41, No.3, pp. 79.

Seiders, K., Voss, G. B., Godfrey, A. L., and Grewal, D. (2007). SERVCON: Development and Validation of a Multidimensional Service Convenience Scale. Journal of the Academy of Marketing Science, Vol. 35, No. 1, pp. 144-156.

Yale, L., and Venkatesh, A. (1986). Toward the Construct of Convenience in Consumer Research. Advances in Consumer Research, Vol. 13, No.1, pp. 403-408.

Dimension Item ItemLabel

Access Convenience AC1 I could shop anytime I wanted.

AC2 I could order products wherever I am.

AC3 I was able to find the website quickly.

AC4 The website is always accessible.

Search Convenience SC1 It was easy to navigate the website.

SC2 The product classification on website was easy to follow.

SC3 The website provided useful information.

SC4 The website provides variety of search options to find the same product.

SC5 It was easy to get information I needed to make my purchase decision.

SC6 I could find what I wanted without having to look elsewhere.

Transaction Convenience TC1 The checkout process was fast.

TC2 My purchase was completed easily.

TC3 The online payment method was simple.

TC4 The online retailer provides flexible payment options.

TC5 It didn't take a long time to complete the purchase process.

Evaluation Convenience EC1 The online retailer provides product specifics.

EC2 The website uses both text and graphics of product information.

EC3 The online retailer provides sufficient information to identify differentproducts.

Possession Convenience PC1 I was delivered undamaged goods.

PC2 I got exactly what I wanted.

PC3 My order was delivered on time.

PC4 I was properly notified of my order status.

Post-Benefit Convenience PBC1 It was easy to return unwanted goods.

PBC2 Prices were identical to those on the order form.

PBC3 I received all the items I ordered.

PBC4 The online retailer provides liberal exchange policy

PBC5 After purchase problems are resolved quickly.

Annexure

Dimensions of Online Shopping



ABSTRACT

The lack of an enabling business framework and scarcity of support structure can undermine the SSI entrepreneurial activity in any country. 15 variables under environmental forces were chosen, to examine, the entrepreneurial support being provided by Jharkhand government.

The study has revealed that the variables: chances of new business success, government encourages the promotion of SSI units, obtaining finance from Banks /SFCs is easy, interest rates on loans from Banks /SFCs is highly competitive, Inspector Raj does not exist in Jharkhand, getting licenses /approvals is easy and attitude of political parties towards entrepreneurship is healthy are having scores less than 3 on a 5 – point interval scale. ANOVA test has revealed that entrepreneurial support across the study locations (Ranchi, Jamshedpur and Bokaro) are significantly different.

It has been postulated in the research that entrepreneurial success is a function of entrepreneurial traits, attitude, business skills and environmental forces. The pooled multiple regression results reveal that β – coefficient has registered the highest value for entrepreneurial traits (0.5528) followed by business skills (0.4684), attitude (0.0841) and environmental forces (0.0784). A low – β coefficient for environmental forces (0.0784) suggests that the entrepreneurial support is not facilitating the growth of SSI units in Jharkhand state.

A high β – coefficient for environmental forces (0.2570) for the study location Jamshedpur suggests that AIADA is providing the necessary entrepreneurial support to the SSI entrepreneurs for their overall development, growth and success. The study for location Ranchi has registered a low β – coefficient (0.0937) and 62.32% of the Ranchi entrepreneurs are average performers indicating that RIADA is not providing any entrepreneurial support. It is a matter of grave concern that negative β – coefficient (- 0.2347) has been registered for study location Bokaro and 50.98% of the entrepreneurs are average performers suggesting that all the efforts of the Bokaro entrepreneurs are going in vain and the entrepreneurial support is totally dysfunctional and in shambles. SPSS 12.0 software was used to calculate the regression coefficients for the predictor variables.

Key Words: Entrepreneurial support, Effectiveness of SSI entrepreneurs, AIADA, BIADA, RIADA

1. Introduction

Small scale industries (SSI) occupy a place of strategic importance in the Indian economy in view of its contribution to employment, production and exports. They are extremely important for the health of any country. The small sector in India has now been identified by the government as one that can assist in generating additional employment, indigenising technology, leveraging cheap labour and flexibility of operations to create competitive advantage for Indian industry (Mitra R and Pingali V, 1999).

The SSI entrepreneur is the backbone of any economy, as an entrepreneur is regarded as fourth factor of production i.e. after land, labour and capital. Probably this is the lasting solution to the burning problem of unemployment in the country (Singh B M and Namboodri K V A, 2006).

The opportunities in the SSI sector are enormous due to the following factors: being less capital intensive, reservation of items to be manufactured by the small sector, ease of funding and subsidies provided to SSI entrepreneurs, help

in procuring machineries and raw materials, training manpower, providing technical and managerial skills to SSI entrepreneurs, reservation of items exclusively to be purchased by the government and growth in requirements for ancillary units due to the increase in number of green field units coming up in the large sector. This sector is ideally suited to build on the strengths of our traditional skills and knowledge, by infusion of technologies, capital and innovative marketing practices.

The characteristics of the Indian economy allow complementary existence for various diverse types of manufacturing units. The promotional and the protective policies of the government have ensured the presence of the SSI sector in an astonishing range of products, particularly in consumer goods. However, the bugbear of the sector has been the inadequacies in capital, technology and marketing (www.sidoonline.com).

Inspite of all these initiatives taken by the government and support institutions, the SSI sector in Jharkhand has not been performing well. Large number of SSI units are sick

with little scope of any improvement in the near future. Sickness in the industrial sector results in locking up of resources, wastage of capital assets, loss of production and rising unemployment in Jharkhand.

2. Problem Statement

The major reasons for the poor performance of the SSI sector in India and Jharkhand in particular has been attributed to: inadequacy of working capital, delay in sanction of working capital, time gap between sanction of term loan and working capital, poor and obsolete technology, problem related to availability of raw material, in - adequate demand and other marketing problems, erratic power supply, poor management, inadequate attention to R & D, diversion of resources and inability of the SSI units to face competition due to liberalisation and globalisation (www.smallindustryindia.com). As such, this study considered each of these problems of paramount importance.

1. The SSI entrepreneurs perceive that the environment is not conducive for growth and they are in the grip of negative influence that small business enterprises cannot flourish within Jharkhand state.

2. Because of the poor performance of the small business sector most entrepreneurs are leading a stressed life and it has an impact on their effectiveness.

3. The government and financial institutions are not extending the necessary support for growth of the small business enterprises in Jharkhand state.

4. Most of the SSI entrepreneurs are finding it difficult to market their products and the reasons could be catering to a single customer. The SSI units are ancillary to large organisations in the vicinity.

5. The industrial activity is located in places with very poor infrastructure and support facilities, accessibility of customers is difficult and procurement of inputs is from far off places. The location and physical infrastructure problems are significant issues with the SSI entrepreneurs.

2.1 Objectives of the study

Against this backdrop, the present study has made an attempt to understand the important determinants of success and effectiveness of SSI entrepreneurs with specific reference to the state of Jharkhand and the detailed objectives of the study are:

1. To study the facilitating role of supportive environment in the development of SSI entrepreneurs.

2. To find out the reasons and circumstances leading to success and failure of entrepreneurs in the study

locations.

3. To identify the contributing factors towards the effectiveness of SSI entrepreneurs.

4. To find out whether the impact of environmental forces is significantly different across the study locations.

2.2 Effectiveness of SSI Entrepreneurs

Till date, though a number of studies have evaluated the small scale entrepreneurial success on the basis of entrepreneurial traits, attitude and business skills, they are highly limited to the Indian context and environment. Further, a number of studies though have paid attention towards success of SSI units across India, but none of these studies have paid due attention to the combined effect of entrepreneurial traits, attitude, business skills and environmental forces on the effectiveness of SSI entrepreneurs. It has been postulated in the research that Effectiveness = f (entrepreneurial traits, attitude, business skills, environmental forces). Multiple Regression has been used to measure the effectiveness of SSI entrepreneurs on the basis of four predictor variables namely: entrepreneurial traits, attitude, business skills and environmental forces and the dependent variable being the health of the SSI units.

The health of the SSI enterprises were categorised under the heads: “closed”, “not viable”, “average”, “good” and “very good” on a scale of 1 – 5. Those entrepreneurs who have cited the health of their enterprises as “very good” and “good” were classified as “successful” entrepreneurs whereas those entrepreneurs who were of the opinion that their performances were “average” were classified under the category as “not so successful” entrepreneurs. Those SSI entrepreneurs who were of the opinion that their enterprises were “not viable” were considered as “unsuccessful” entrepreneurs. The closed SSI units were not considered in the study.

To be very particular no such studies have attempted to understand the success of SSI entrepreneurs in light of the above mentioned factors in Jharkhand. In this context, the main purpose of the study is to analyse the factors affecting Jharkhand entrepreneurs by critically examining the behavioural characteristics of the entrepreneur and also, examining and evaluating policies, programs, services and assistance related to SSI development and promotion. The study will generate conclusions, recommendations, some of which can be applied in the context of Jharkhand state and the same can be replicated across the country.


It has been long mooted that the environment in a country impinges on entrepreneurship intentions. Whilst it is generally believed that the environment in various

Dr. Tarak Nath Shaw *

Entrepreneurial Support in the SSI Sector: A Case Study of Jharkhand


*Associate Professor, IMS Unison University, Dehradun

37"Pragyaan: Journal of Management" Volume 13, Issue 2, December 2015"Pragyaan: Journal of Management" Volume 13, Issue 2, December 201536

ABSTRACT

The lack of an enabling business framework and scarcity of support structure can undermine the SSI entrepreneurial activity in any country. 15 variables under environmental forces were chosen, to examine, the entrepreneurial support being provided by Jharkhand government.

The study has revealed that the variables: chances of new business success, government encourages the promotion of SSI units, obtaining finance from Banks /SFCs is easy, interest rates on loans from Banks /SFCs is highly competitive, Inspector Raj does not exist in Jharkhand, getting licenses /approvals is easy and attitude of political parties towards entrepreneurship is healthy are having scores less than 3 on a 5 – point interval scale. ANOVA test has revealed that entrepreneurial support across the study locations (Ranchi, Jamshedpur and Bokaro) are significantly different.

It has been postulated in the research that entrepreneurial success is a function of entrepreneurial traits, attitude, business skills and environmental forces. The pooled multiple regression results reveal that β – coefficient has registered the highest value for entrepreneurial traits (0.5528) followed by business skills (0.4684), attitude (0.0841) and environmental forces (0.0784). A low – β coefficient for environmental forces (0.0784) suggests that the entrepreneurial support is not facilitating the growth of SSI units in Jharkhand state.

A high β – coefficient for environmental forces (0.2570) for the study location Jamshedpur suggests that AIADA is providing the necessary entrepreneurial support to the SSI entrepreneurs for their overall development, growth and success. The study for location Ranchi has registered a low β – coefficient (0.0937) and 62.32% of the Ranchi entrepreneurs are average performers indicating that RIADA is not providing any entrepreneurial support. It is a matter of grave concern that negative β – coefficient (- 0.2347) has been registered for study location Bokaro and 50.98% of the entrepreneurs are average performers suggesting that all the efforts of the Bokaro entrepreneurs are going in vain and the entrepreneurial support is totally dysfunctional and in shambles. SPSS 12.0 software was used to calculate the regression coefficients for the predictor variables.

Key Words: Entrepreneurial support, Effectiveness of SSI entrepreneurs, AIADA, BIADA, RIADA

1. Introduction

Small scale industries (SSI) occupy a place of strategic importance in the Indian economy in view of its contribution to employment, production and exports. They are extremely important for the health of any country. The small sector in India has now been identified by the government as one that can assist in generating additional employment, indigenising technology, leveraging cheap labour and flexibility of operations to create competitive advantage for Indian industry (Mitra R and Pingali V, 1999).

The SSI entrepreneur is the backbone of any economy, as an entrepreneur is regarded as fourth factor of production i.e. after land, labour and capital. Probably this is the lasting solution to the burning problem of unemployment in the country (Singh B M and Namboodri K V A, 2006).

The opportunities in the SSI sector are enormous due to the following factors: being less capital intensive, reservation of items to be manufactured by the small sector, ease of funding and subsidies provided to SSI entrepreneurs, help

in procuring machineries and raw materials, training manpower, providing technical and managerial skills to SSI entrepreneurs, reservation of items exclusively to be purchased by the government and growth in requirements for ancillary units due to the increase in number of green field units coming up in the large sector. This sector is ideally suited to build on the strengths of our traditional skills and knowledge, by infusion of technologies, capital and innovative marketing practices.

The characteristics of the Indian economy allow complementary existence for various diverse types of manufacturing units. The promotional and the protective policies of the government have ensured the presence of the SSI sector in an astonishing range of products, particularly in consumer goods. However, the bugbear of the sector has been the inadequacies in capital, technology and marketing (www.sidoonline.com).

Inspite of all these initiatives taken by the government and support institutions, the SSI sector in Jharkhand has not been performing well. Large number of SSI units are sick

with little scope of any improvement in the near future. Sickness in the industrial sector results in locking up of resources, wastage of capital assets, loss of production and rising unemployment in Jharkhand.

2. Problem Statement

The major reasons for the poor performance of the SSI sector in India and Jharkhand in particular has been attributed to: inadequacy of working capital, delay in sanction of working capital, time gap between sanction of term loan and working capital, poor and obsolete technology, problem related to availability of raw material, in - adequate demand and other marketing problems, erratic power supply, poor management, inadequate attention to R & D, diversion of resources and inability of the SSI units to face competition due to liberalisation and globalisation (www.smallindustryindia.com). As such, this study considered each of these problems of paramount importance.

1. The SSI entrepreneurs perceive that the environment is not conducive for growth and they are in the grip of negative influence that small business enterprises cannot flourish within Jharkhand state.

2. Because of the poor performance of the small business sector most entrepreneurs are leading a stressed life and it has an impact on their effectiveness.

3. The government and financial institutions are not extending the necessary support for growth of the small business enterprises in Jharkhand state.

4. Most of the SSI entrepreneurs are finding it difficult to market their products and the reasons could be catering to a single customer. The SSI units are ancillary to large organisations in the vicinity.

5. The industrial activity is located in places with very poor infrastructure and support facilities, accessibility of customers is difficult and procurement of inputs is from far off places. The location and physical infrastructure problems are significant issues with the SSI entrepreneurs.

2.1 Objectives of the study

Against this backdrop, the present study has made an attempt to understand the important determinants of success and effectiveness of SSI entrepreneurs with specific reference to the state of Jharkhand and the detailed objectives of the study are:

1. To study the facilitating role of supportive environment in the development of SSI entrepreneurs.

2. To find out the reasons and circumstances leading to success and failure of entrepreneurs in the study

locations.

3. To identify the contributing factors towards the effectiveness of SSI entrepreneurs.

4. To find out whether the impact of environmental forces is significantly different across the study locations.

2.2 Effectiveness of SSI Entrepreneurs

Till date, though a number of studies have evaluated the small scale entrepreneurial success on the basis of entrepreneurial traits, attitude and business skills, they are highly limited to the Indian context and environment. Further, a number of studies though have paid attention towards success of SSI units across India, but none of these studies have paid due attention to the combined effect of entrepreneurial traits, attitude, business skills and environmental forces on the effectiveness of SSI entrepreneurs. It has been postulated in the research that Effectiveness = f (entrepreneurial traits, attitude, business skills, environmental forces). Multiple Regression has been used to measure the effectiveness of SSI entrepreneurs on the basis of four predictor variables namely: entrepreneurial traits, attitude, business skills and environmental forces and the dependent variable being the health of the SSI units.

The health of the SSI enterprises were categorised under the heads: “closed”, “not viable”, “average”, “good” and “very good” on a scale of 1 – 5. Those entrepreneurs who have cited the health of their enterprises as “very good” and “good” were classified as “successful” entrepreneurs whereas those entrepreneurs who were of the opinion that their performances were “average” were classified under the category as “not so successful” entrepreneurs. Those SSI entrepreneurs who were of the opinion that their enterprises were “not viable” were considered as “unsuccessful” entrepreneurs. The closed SSI units were not considered in the study.

To be very particular no such studies have attempted to understand the success of SSI entrepreneurs in light of the above mentioned factors in Jharkhand. In this context, the main purpose of the study is to analyse the factors affecting Jharkhand entrepreneurs by critically examining the behavioural characteristics of the entrepreneur and also, examining and evaluating policies, programs, services and assistance related to SSI development and promotion. The study will generate conclusions, recommendations, some of which can be applied in the context of Jharkhand state and the same can be replicated across the country.


It has been long mooted that the environment in a country impinges on entrepreneurship intentions. Whilst it is generally believed that the environment in various

Dr. Tarak Nath Shaw *



*Associate Professor, IMS Unison University, Dehradun


countries plays an important role in promoting entrepreneurship. There is a unanimous agreement that the psychological and traits model do not paint a complete picture of entrepreneurship, as they do not include the influence of environment variables on entrepreneurship activities.

According to Nazrul Islam et al. (1999), the researches found that the success factors of entrepreneurs before 90s differ from those after 90s. The success factors identified by researchers before 1990s emphasised on entrepreneurial traits and attitude of the entrepreneurs and did consider business skills of the entrepreneur and impact of environmental forces on entrepreneurial success.

On the other hand, studies after 1990, focussed mainly on market knowledge and well coordinated flexible persistent managerial action factors followed by risk taking capability, innovativeness, self motivation, moral attitudes, values and other environment etc. as the 'success' factors. These factors primarily focus on the managerial skills of the entrepreneur and the environmental forces affecting business success.

Most developing countries have come to realize the importance of SMEs in the process of economic development. The lack of an enabling business framework and scarcity of the support structure can undermine the entrepreneurial activity in any country. The role of the government and support institutions in the development and growth of SSI units cannot be overemphasized. The government's role in encouraging entrepreneurship is just not limited to providing an economic environment which is conducive for business and political stability. To stimulate the growth of entrepreneurship, the government must be able to provide the right combination of policies and incentives to attract individuals to become entrepreneurs and create congenial environment for growth.

Environmental Forces affecting entrepreneurship are: e n t r ep r eneu r i a l a c t i o n , k now l edge abou t en t repreneursh ip , soc ie ta l a t t i tude towards entrepreneurship, salary and taxation levels, availability of personnel and supporting services, accessibility of customers and universities, general economic conditions, government policies and availability of financial support (Vepa K R, 1984).

Commercial and industrial units established under the self employment category are important sources of income as government gets excise duty, sales tax, octroi and income tax from these units which boost national income. Establishment of self employed units requires infrastructural facilities viz transport, water, electricity, market, storage and communication. In absence of these infrastructural facilities entrepreneurship will not flourish. Apart from these bottle necks encountered by the entrepreneur, there does not exist any coordination among

the implementing agencies. Many institutions have been established to facilitate growth of entrepreneurship but there is a lack of coordination among them. Such institutions overlap in developing schemes and services and hence much of government's fund and efforts are wasted (Singh B M, Namboodri K V A, 2006).

According to Kumar M G (2005), the problems faced by SMEs may be classified into two types namely: internal problems and external problems. The internal problems are: the owners of SMEs lacking the ability to present a proper business case to potential financers, lacunae in the basic understanding of organizational structure and financing needs that are essential for sustainable growth, serious dearth of awareness, lack of information, knowledge of other possible opportunities among the SMEs and often ill formulated business plan.

The external problems are: the entrepreneur of the SMEs, often confronts a less than affable environment (a plethora of regulations and inspections of the state - Inspector Raj) that make them victims of corruption, experiences difficulties in accessing adequate finance from banks and other financial institutions, confronts a higher rate of interest because of the risk perception due to lack of well developed credit information sharing systems, faces difficulties in technological up-gradation because of lack of support services for technical know - how and access to long term finance, faces difficulties in weathering market fluctuations, experiences delays in the settlement of dues from large scale buyers and also, is more vulnerable to external shocks as the size of the enterprise may constrain him in weathering the stresses and strains.

To promote entrepreneurship in the country, what primarily is needed, is that all the government agencies, banks, universities, professional and technical institutions, corporate and non government organizations (NGOs) actively participate in setting up skill and entrepreneurial development institutes (EDIs) and not only provide skill development but also commit to their settlement and hand holding.

Apart from providing the necessary skills and hand holding exercise, post training contact with the trained entrepreneurs, is also desired which is acknowledged as the kingpin of good follow-up, which in practice is rarely attempted in a systematic manner. One of the major criteria to improve the results of entrepreneurship development program (EDP) is intensive and systematic follow-up of trained entrepreneurs (Singh B M, Namboodri K V A, 2006).

A survey conducted by Accenture (2000), (an international management consultancy firm), (published in the Economic Times, 6th July, 2001) concluded that 75% of the Indian executives see bureaucratic problems as one of the major hurdles of progress, 78% cited lack of incentives

and the government does not do enough to encourage entrepreneurship, 50% felt that the government had a negative attitude towards entrepreneurship and 68% felt that there was a lack of entrepreneurial role models in the country. Barriers to entrepreneurship include negative attitude towards success, reluctance to be seen as buckling the trend and aversion to risk and failure.

According to XLRI (2000), (published in Hindustan Times, 20th May, 2001), in the survey, the perception of industrialists outside Bihar/Jharkhand was explained: 100% of the entrepreneurs felt that the atmosphere was not conducive for industrialisation, 87% of the industrialist believed that the government does not understand the cost of delayed decisions, 83% of the entrepreneurs had the perception that the business community is a cash cow that can be milked as and when required, 82% felt that the exploitative ground reality of the police force and government officials was the root cause of all problems for the business and the industry, 78% felt that setting up a business was cumbersome, time consuming process and full of corruption, 75% felt that absence of a good social infrastructure was a big constraint in promoting industrialisation in Jharkhand state, 74% felt that too many corrupt inspectors and supervisors at ground level had made working very difficult, 68% of the respondents were of the opinion that industrialists from other states will be reluctant to invest in Jharkhand, 64% believed that most of the industries were sick unless revived potential investors will not come to Jharkhand and 50% had cited the problems of corruption, law and order and bad image of Jharkhand.

According the researcher's observation, the SSI entrepreneurs who have not succeeded in their endeavour are coined as failures and are seen as outcasts from their fraternity. The socio cultural barriers create negative impact on these SSI entrepreneurs who were not successful. Failure is often seen as the workings of the cruel, any opportunity to learn from past mistakes was lost in the quest to pin the blame.

Some of the views expressed by Jharkhand SSI entrepreneurs in a focus group study are as follows:

(1) Entrepreneurship is linked with group activities,

(2) Whether government subsidies will be of any help,

(3) Inconsistency in getting orders affects the enterprise,

(4) Climate of industrial activities needs to be conducive,

(5) Mindset of customers of treating “LOCAL UNITS” as inferior in comparison to units of other states,

(6) Performance of big enterprises in the vicinity affects the performance of SSI units,

(7) Unproductive time being spent mostly with various governmental departments and financial institutions,

(8) Treating smaller enterprises as reduction gear where efforts may not give higher returns proportionately,

(9) Lack of training facilities available with the entrepreneurs for their employees and self improvement,

(10) Lack of experience of first generation entrepreneurs,

(11) Lack of innovation to re-energise the enterprise,

(12) Carrying business with obsolete technology hampering business performance,

(13) Most of the entrepreneurs are managing different functional areas themselves and they are also, engaged in doing everything themselves (Prasad A, Shaw T, Haran H, 2003).

3.1 Profile of Study Area

Jharkhand is a state in eastern India carved out of the southern part of Bihar state on November 15, 2000, with 22 districts. Jharkhand is famous for its mineral, wealth and forestry products. The industrial city of Ranchi is its capital. Some other major cities and industrial centres are Jamshedpur, Bokaro and Dhanbad (which was once a part of West Bengal). Jharkhand shares its border with the states of Bihar to the north, Uttar Pradesh and Chattisgarh to the west, Odisha to the south and West Bengal to the east. Some of the other major cities and industrial centres are Sindri, Giridih, Gumla, Deogarh, Ramgarh and Hazaribagh.

3.2 Profile of Support Agencies

Ranchi Industrial Area Development Authority (RIADA): It is an autonomous body set-up by the erstwhile government of Bihar (now Jharkhand government) under Industrial Area Development Authority Act, 1974 to cater to the needs of industries set up in its control area. For the last thirty three years, it has been playing a progressive role in the industrial development of seven tribal districts.

RIADA has been entrusted fundamentally with the task of establishing industrial areas. It has also taken the responsibility of providing continued assistance to the units which come up in these industrial areas. It provides a total package of assistance at a single point to the entrepreneurs, be it selection of the project, location, providing developed land/sheds, arranging term loans and bank finance, power, water supply, technical know-how, market tie up and disbursement of incentives of the state government. Large engineering and mining industries and premier consultancy organizations like Central Coalfields Ltd. (CCL), Heavy Engineering Corporation Ltd. (HEC), Usha Martin Industries Ltd., Metallurgical and Engineering Consultants Ltd. (MECON) and Central Mining Planning & Design Institute Ltd. (CMPDIL) provide scope for ancillaries.

Adityapur Industrial Area Development Authority (AIADA): It caters to the needs of industries set-up in its controlled area in Adityapur (an industrial area in the study location Jamshedpur located at 130 kilometres from Ranchi), it is

Entrepreneurial Support in the SSI Sector: A Case Study of JharkhandEntrepreneurial Support in the SSI Sector: A Case Study of Jharkhand


countries plays an important role in promoting entrepreneurship. There is a unanimous agreement that the psychological and traits model do not paint a complete picture of entrepreneurship, as they do not include the influence of environment variables on entrepreneurship activities.

According to Nazrul Islam et al. (1999), the researches found that the success factors of entrepreneurs before 90s differ from those after 90s. The success factors identified by researchers before 1990s emphasised on entrepreneurial traits and attitude of the entrepreneurs and did consider business skills of the entrepreneur and impact of environmental forces on entrepreneurial success.

On the other hand, studies after 1990, focussed mainly on market knowledge and well coordinated flexible persistent managerial action factors followed by risk taking capability, innovativeness, self motivation, moral attitudes, values and other environment etc. as the 'success' factors. These factors primarily focus on the managerial skills of the entrepreneur and the environmental forces affecting business success.

Most developing countries have come to realize the importance of SMEs in the process of economic development. The lack of an enabling business framework and scarcity of the support structure can undermine the entrepreneurial activity in any country. The role of the government and support institutions in the development and growth of SSI units cannot be overemphasized. The government's role in encouraging entrepreneurship is just not limited to providing an economic environment which is conducive for business and political stability. To stimulate the growth of entrepreneurship, the government must be able to provide the right combination of policies and incentives to attract individuals to become entrepreneurs and create congenial environment for growth.

Environmental Forces affecting entrepreneurship are: e n t r ep r eneu r i a l a c t i o n , k now l edge abou t en t repreneursh ip , soc ie ta l a t t i tude towards entrepreneurship, salary and taxation levels, availability of personnel and supporting services, accessibility of customers and universities, general economic conditions, government policies and availability of financial support (Vepa K R, 1984).

Commercial and industrial units established under the self employment category are important sources of income as government gets excise duty, sales tax, octroi and income tax from these units which boost national income. Establishment of self employed units requires infrastructural facilities viz transport, water, electricity, market, storage and communication. In absence of these infrastructural facilities entrepreneurship will not flourish. Apart from these bottle necks encountered by the entrepreneur, there does not exist any coordination among

the implementing agencies. Many institutions have been established to facilitate growth of entrepreneurship but there is a lack of coordination among them. Such institutions overlap in developing schemes and services and hence much of government's fund and efforts are wasted (Singh B M, Namboodri K V A, 2006).

According to Kumar M G (2005), the problems faced by SMEs may be classified into two types namely: internal problems and external problems. The internal problems are: the owners of SMEs lacking the ability to present a proper business case to potential financers, lacunae in the basic understanding of organizational structure and financing needs that are essential for sustainable growth, serious dearth of awareness, lack of information, knowledge of other possible opportunities among the SMEs and often ill formulated business plan.

The external problems are: the entrepreneur of the SMEs, often confronts a less than affable environment (a plethora of regulations and inspections of the state - Inspector Raj) that make them victims of corruption, experiences difficulties in accessing adequate finance from banks and other financial institutions, confronts a higher rate of interest because of the risk perception due to lack of well developed credit information sharing systems, faces difficulties in technological up-gradation because of lack of support services for technical know - how and access to long term finance, faces difficulties in weathering market fluctuations, experiences delays in the settlement of dues from large scale buyers and also, is more vulnerable to external shocks as the size of the enterprise may constrain him in weathering the stresses and strains.

To promote entrepreneurship in the country, what primarily is needed, is that all the government agencies, banks, universities, professional and technical institutions, corporate and non government organizations (NGOs) actively participate in setting up skill and entrepreneurial development institutes (EDIs) and not only provide skill development but also commit to their settlement and hand holding.

Apart from providing the necessary skills and hand holding exercise, post training contact with the trained entrepreneurs, is also desired which is acknowledged as the kingpin of good follow-up, which in practice is rarely attempted in a systematic manner. One of the major criteria to improve the results of entrepreneurship development program (EDP) is intensive and systematic follow-up of trained entrepreneurs (Singh B M, Namboodri K V A, 2006).

A survey conducted by Accenture (2000), (an international management consultancy firm), (published in the Economic Times, 6th July, 2001) concluded that 75% of the Indian executives see bureaucratic problems as one of the major hurdles of progress, 78% cited lack of incentives

and the government does not do enough to encourage entrepreneurship, 50% felt that the government had a negative attitude towards entrepreneurship and 68% felt that there was a lack of entrepreneurial role models in the country. Barriers to entrepreneurship include negative attitude towards success, reluctance to be seen as buckling the trend and aversion to risk and failure.

According to XLRI (2000), (published in Hindustan Times, 20th May, 2001), in the survey, the perception of industrialists outside Bihar/Jharkhand was explained: 100% of the entrepreneurs felt that the atmosphere was not conducive for industrialisation, 87% of the industrialist believed that the government does not understand the cost of delayed decisions, 83% of the entrepreneurs had the perception that the business community is a cash cow that can be milked as and when required, 82% felt that the exploitative ground reality of the police force and government officials was the root cause of all problems for the business and the industry, 78% felt that setting up a business was cumbersome, time consuming process and full of corruption, 75% felt that absence of a good social infrastructure was a big constraint in promoting industrialisation in Jharkhand state, 74% felt that too many corrupt inspectors and supervisors at ground level had made working very difficult, 68% of the respondents were of the opinion that industrialists from other states will be reluctant to invest in Jharkhand, 64% believed that most of the industries were sick unless revived potential investors will not come to Jharkhand and 50% had cited the problems of corruption, law and order and bad image of Jharkhand.

According the researcher's observation, the SSI entrepreneurs who have not succeeded in their endeavour are coined as failures and are seen as outcasts from their fraternity. The socio cultural barriers create negative impact on these SSI entrepreneurs who were not successful. Failure is often seen as the workings of the cruel, any opportunity to learn from past mistakes was lost in the quest to pin the blame.

Some of the views expressed by Jharkhand SSI entrepreneurs in a focus group study are as follows:

(1) Entrepreneurship is linked with group activities,

(2) Whether government subsidies will be of any help,

(3) Inconsistency in getting orders affects the enterprise,

(4) Climate of industrial activities needs to be conducive,

(5) Mindset of customers of treating “LOCAL UNITS” as inferior in comparison to units of other states,

(6) Performance of big enterprises in the vicinity affects the performance of SSI units,

(7) Unproductive time being spent mostly with various governmental departments and financial institutions,

(8) Treating smaller enterprises as reduction gear where efforts may not give higher returns proportionately,

(9) Lack of training facilities available with the entrepreneurs for their employees and self improvement,

(10) Lack of experience of first generation entrepreneurs,

(11) Lack of innovation to re-energise the enterprise,

(12) Carrying business with obsolete technology hampering business performance,

(13) Most of the entrepreneurs are managing different functional areas themselves and they are also, engaged in doing everything themselves (Prasad A, Shaw T, Haran H, 2003).

3.1 Profile of Study Area

Jharkhand is a state in eastern India carved out of the southern part of Bihar state on November 15, 2000, with 22 districts. Jharkhand is famous for its mineral, wealth and forestry products. The industrial city of Ranchi is its capital. Some other major cities and industrial centres are Jamshedpur, Bokaro and Dhanbad (which was once a part of West Bengal). Jharkhand shares its border with the states of Bihar to the north, Uttar Pradesh and Chattisgarh to the west, Odisha to the south and West Bengal to the east. Some of the other major cities and industrial centres are Sindri, Giridih, Gumla, Deogarh, Ramgarh and Hazaribagh.

3.2 Profile of Support Agencies

Ranchi Industrial Area Development Authority (RIADA): It is an autonomous body set-up by the erstwhile government of Bihar (now Jharkhand government) under Industrial Area Development Authority Act, 1974 to cater to the needs of industries set up in its control area. For the last thirty three years, it has been playing a progressive role in the industrial development of seven tribal districts.

RIADA has been entrusted fundamentally with the task of establishing industrial areas. It has also taken the responsibility of providing continued assistance to the units which come up in these industrial areas. It provides a total package of assistance at a single point to the entrepreneurs, be it selection of the project, location, providing developed land/sheds, arranging term loans and bank finance, power, water supply, technical know-how, market tie up and disbursement of incentives of the state government. Large engineering and mining industries and premier consultancy organizations like Central Coalfields Ltd. (CCL), Heavy Engineering Corporation Ltd. (HEC), Usha Martin Industries Ltd., Metallurgical and Engineering Consultants Ltd. (MECON) and Central Mining Planning & Design Institute Ltd. (CMPDIL) provide scope for ancillaries.

Adityapur Industrial Area Development Authority (AIADA): It caters to the needs of industries set-up in its controlled area in Adityapur (an industrial area in the study location Jamshedpur located at 130 kilometres from Ranchi), it is



striving to excel as customer focused knowledge based organisation through its innovative practices. The total investment in infrastructure at Adityapur industrial area is to the tune of Rs. 30 billion, which is increasing every year with large number of units being set-up. Average turnover of the industrial area is about Rs. 35 billion. Uninterrupted power supply 24X 7 is made available to the industrial units located in its industrial area. There is no dearth of technical expertise in and around the industrial area – with well equipped National Metallurgical Laboratory (NML), sophisticated Indo Danish Tool Room & Training Centre (IDTR), National Institute of Technology (NIT), Xavier labour Relations Institute (XLRI), polytechnics and numerous private training outfits providing vocational courses in subjects ranging from technical level work like welder and fitter, training in design and drafting including CAD, IT education etc. (www.aiadaonline.com).

Majority of the SSI units in the study location Jamshedpur are ancillary to Tata group of companies and they are assured of regular flow of orders and large industries do the hand holding of the SSI entrepreneurs in product development and also, supply scarce raw materials which are difficult to procure from the open market. Majority of the large business houses located in Jamshedpur, utilise the full potential of the SSI units based on their capabilities.

Bokaro Industrial Area Development Authority (BIADA): To cater to the needs of industries set up in its controlled area, Bokaro Industrial Area Development Authority (BIADA), an autonomous body was set up by the erstwhile government of Bihar (now Jharkhand government) under Industrial Area Development Authority Act, 1974. Bokaro is known as steel city, because the largest steel plant of Asia is situated here. The giant public sector Steel Authority of India Ltd. (SAIL) has their steel plant situated at Bokaro Steel City known as Bokaro Steel Plant. About forty thousand people have been working in this plant day and night. The Coal India Ltd., a public sector has two of it's subsidiaries in Bokaro district i.e., Central Coalfields Ltd., and Bharat Coking Coal Ltd., respectively. Both of these subsidiaries have rich infrastructure in the area.

The private sector multinational Indian Explosives Ltd., has its explosives unit at Gomia which has a huge infrastructure. The Damodar Valley Corporation Ltd., has two big captive power plants situated at Bokaro and Chandrapura. Jharkhand State Electricity Board (JSEB) has one of their power captive plants located at Lalpania near Tenughat. This unit also has rich infrastructural support in the area (www.bokaro.nic.in). Several SSI units are situated in this industrial area and they are having infrastructural support from BIADA. Majority of the SSI units are ancillary units to Bokaro Steel Plant and they are heavily dependent upon the steel plant for their survival and sustenance.

5. Research Design

The study is empirical in nature and information has been gathered across three study locations, namely Ranchi, Jamshedpur and Bokaro districts of Jharkhand to understand entrepreneurial support being rendered by the government. These cities were selected because most of the SSIs are concentrated in these regions. In choosing the small scale units, those SSI units which are being encouraged, promoted and assisted in their growth and viability by the support agencies namely RIADA, AIADA and BIADA for promoting and overall development of the SSI units in their jurisdiction have been considered in the study.

5.1 Sampling Plan

While choosing the sample, a list of industries was prepared from the exhaustive list of the total number of SSI units existing in the study location, i.e., Ranchi, Jamshedpur and Bokaro. The list was obtained from the Directorate of Industries, government of Jharkhand. The list pertains to the period 2010 – 11.

5.2 Sample Size

In Ranchi, the number of operating SSI units was 346, in Jamshedpur it was 535 and in Bokaro it was 256 (Table - 1) and the total number of SSI units in these industrial areas was 1,137. A sample has been drawn from each study location, viz., Ranchi, Jamshedpur and Bokaro which constitutes about 20% of the total population. Thereby a total number of 227 sample SSI units were chosen under the study by adopting 'Simple Random Systematic Interval Sampling' technique.

Table 1: Distribution of Samples Across the Study Locations

Study Location Ranchi Jam Bokaro Totalshedpur

Operating units 346 535 256 1137

Sample size (20%) 69 107 51 227

Support Agency RIADA AIADA BIADA

5.3 Data Sources

The study had gathered quantitative information to meet the objectives of the study. The sources of the quantitative data are the sample entrepreneurs chosen under the study from the three study locations of Jharkhand state. The survey of entrepreneurs included only those SSI entrepreneurs who were from the manufacturing sector.

In gathering the quantitative information a structured closed ended questionnaire was used. The questionnaire used in the study constituted general profile of the entrepreneurs, entrepreneurial traits, attitude and business

skills of the entrepreneurs and the environmental forces that were influencing the success and failure of the sample business entrepreneurs. In gathering the information under different heads and sub-heads of the questionnaire, the statements were arranged on a 5- point Likert Scale. Each statement has 5 categories of responses: strongly agree, agree, undecided, disagree and strongly disagree. The weights given to strongly agree, agree, undecided, disagree and strongly disagree were 5, 4, 3, 2 and 1 respectively.

After finalisation of the questionnaire, a pilot study was undertaken to test the appropriateness and standard of the questions brought under the data gathering tools. As per the field reality, the questionnaire was redesigned and finalised for the study. The comments and suggestions of the respondents were incorporated in the final questionnaire.

Secondary data were also taken from brochures, pamphlets, reports, magazines and other government publications. These multiple sources of data collection were resorted to, for increasing the validity and reliability of the study. The detailed description of the different heads in the final questionnaire are as given below:

The 10 variables analysed under entrepreneurial traits were: drive and energy, responsibility, persistence, self – confidence, initiative, need for independence, tolerance for uncertainty, optimism, innovativeness, creativity and perseverance.

The 13 variables analysed under attitude were: long term commitment, persistence in problem solving, attitude to risk taking, dealing with failure, use of feedback, seeking assistance, flexibility, need for achievement, profit – orientedness, integrity, resolving issues without procrastination, positive influence and self – resolution of entrepreneurial stress.

The 12 variables chosen for analysis under business skills were: setting goals, developing business plans, delegating, dealing with work disputes, training subordinates, dealing with customers, dealing with government officials, keeping financial records, talent acquisition, marketing skills, catering to multiple customers and ethical competition.

The 15 variables chosen under the head Environmental Forces affecting growth of entrepreneurship in Jharkhand state were: necessary market information, training facility for employees within the state, necessary potential customers is available within the state, availability of business related services is of good quality, chances of new business success is very high within Jharkhand state, government encourages the promotion of SSI enterprises, labour force with necessary skills is easily available within the state, obtaining finance from banks/SFCs is easy,

interest rates on loans from banks /SFC is highly competitive, inspector raj does not exist in Jharkhand state, getting licenses/ approvals is easy, entrepreneurship is not linked with greed and self promotion, government and the investment community is encouraging entrepreneurship and attitude of political parties towards entrepreneurship is healthy.

5.4 Statistical Tools

Advanced statistical tools like ANOVA and Multiple Regression were used in the present study. In calculating ANOVA and the Regression Coefficients SPSS 12.0 package was used. Simple descriptive statistical tools like percentages and means to compare the variables under entrepreneurial traits, attitude, business skills and environmental forces were also used.


The environmental forces refer to the business environment in which the business units operate. Macro – forces are the broad factors in any society and business that have an effect on all businesses and industries. Some of the macro forces are socio cultural, demographic, economic, technological, political and natural environment, and they have profound effects on the business. It is important to keep track of these forces and their trends.

While it is not possible to change the forces, one can plan and adapt the business methods to meet the needs of a rapidly changing world. To stay longer in the business a constant monitoring of the macro environmental forces is essential. The study is aimed to pin point the macro environmental forces which have an impact on the performance and success of the SSI units in Jharkhand state. In this endeavour, the present study has made an attempt to identify and analyse the environmental forces which affect the chances of business success.

From Table 2, it is observed that the environmental forces has registered a high combined average for 3.11 for study location Jamshedpur followed by 2.99 for Bokaro and 2.87 for Ranchi. It is also, revealed from the above Table that the impact of environmental forces is varying across the study locations. The environment is highly conducive for the entrepreneurs from the study location Jamshedpur though the same is not for the entrepreneurs from Ranchi and Bokaro. Scrutiny has been resorted to those environmental variables which are having a combined average less than 3.00 and are affecting the business success of Jharkhand SSI entrepreneurs.

A high proportion of the new SSI units close down during the first year of their life and many SSI units are closing down every year indicating that these firms are not able to maintain the alignment with the environment. A change in the environment causes more uncertainty in the SSI units



striving to excel as customer focused knowledge based organisation through its innovative practices. The total investment in infrastructure at Adityapur industrial area is to the tune of Rs. 30 billion, which is increasing every year with large number of units being set-up. Average turnover of the industrial area is about Rs. 35 billion. Uninterrupted power supply 24X 7 is made available to the industrial units located in its industrial area. There is no dearth of technical expertise in and around the industrial area – with well equipped National Metallurgical Laboratory (NML), sophisticated Indo Danish Tool Room & Training Centre (IDTR), National Institute of Technology (NIT), Xavier labour Relations Institute (XLRI), polytechnics and numerous private training outfits providing vocational courses in subjects ranging from technical level work like welder and fitter, training in design and drafting including CAD, IT education etc. (www.aiadaonline.com).

Majority of the SSI units in the study location Jamshedpur are ancillary to Tata group of companies and they are assured of regular flow of orders and large industries do the hand holding of the SSI entrepreneurs in product development and also, supply scarce raw materials which are difficult to procure from the open market. Majority of the large business houses located in Jamshedpur, utilise the full potential of the SSI units based on their capabilities.

Bokaro Industrial Area Development Authority (BIADA): To cater to the needs of industries set up in its controlled area, Bokaro Industrial Area Development Authority (BIADA), an autonomous body was set up by the erstwhile government of Bihar (now Jharkhand government) under Industrial Area Development Authority Act, 1974. Bokaro is known as steel city, because the largest steel plant of Asia is situated here. The giant public sector Steel Authority of India Ltd. (SAIL) has their steel plant situated at Bokaro Steel City known as Bokaro Steel Plant. About forty thousand people have been working in this plant day and night. The Coal India Ltd., a public sector has two of it's subsidiaries in Bokaro district i.e., Central Coalfields Ltd., and Bharat Coking Coal Ltd., respectively. Both of these subsidiaries have rich infrastructure in the area.

The private sector multinational Indian Explosives Ltd., has its explosives unit at Gomia which has a huge infrastructure. The Damodar Valley Corporation Ltd., has two big captive power plants situated at Bokaro and Chandrapura. Jharkhand State Electricity Board (JSEB) has one of their power captive plants located at Lalpania near Tenughat. This unit also has rich infrastructural support in the area (www.bokaro.nic.in). Several SSI units are situated in this industrial area and they are having infrastructural support from BIADA. Majority of the SSI units are ancillary units to Bokaro Steel Plant and they are heavily dependent upon the steel plant for their survival and sustenance.

5. Research Design

The study is empirical in nature and information has been gathered across three study locations, namely Ranchi, Jamshedpur and Bokaro districts of Jharkhand to understand entrepreneurial support being rendered by the government. These cities were selected because most of the SSIs are concentrated in these regions. In choosing the small scale units, those SSI units which are being encouraged, promoted and assisted in their growth and viability by the support agencies namely RIADA, AIADA and BIADA for promoting and overall development of the SSI units in their jurisdiction have been considered in the study.

5.1 Sampling Plan

While choosing the sample, a list of industries was prepared from the exhaustive list of the total number of SSI units existing in the study location, i.e., Ranchi, Jamshedpur and Bokaro. The list was obtained from the Directorate of Industries, government of Jharkhand. The list pertains to the period 2010 – 11.

5.2 Sample Size

In Ranchi, the number of operating SSI units was 346, in Jamshedpur it was 535 and in Bokaro it was 256 (Table - 1) and the total number of SSI units in these industrial areas was 1,137. A sample has been drawn from each study location, viz., Ranchi, Jamshedpur and Bokaro which constitutes about 20% of the total population. Thereby a total number of 227 sample SSI units were chosen under the study by adopting 'Simple Random Systematic Interval Sampling' technique.

Table 1: Distribution of Samples Across the Study Locations

Study Location Ranchi Jam Bokaro Totalshedpur

Operating units 346 535 256 1137

Sample size (20%) 69 107 51 227

Support Agency RIADA AIADA BIADA

5.3 Data Sources

The study had gathered quantitative information to meet the objectives of the study. The sources of the quantitative data are the sample entrepreneurs chosen under the study from the three study locations of Jharkhand state. The survey of entrepreneurs included only those SSI entrepreneurs who were from the manufacturing sector.

In gathering the quantitative information a structured closed ended questionnaire was used. The questionnaire used in the study constituted general profile of the entrepreneurs, entrepreneurial traits, attitude and business

skills of the entrepreneurs and the environmental forces that were influencing the success and failure of the sample business entrepreneurs. In gathering the information under different heads and sub-heads of the questionnaire, the statements were arranged on a 5- point Likert Scale. Each statement has 5 categories of responses: strongly agree, agree, undecided, disagree and strongly disagree. The weights given to strongly agree, agree, undecided, disagree and strongly disagree were 5, 4, 3, 2 and 1 respectively.

After finalisation of the questionnaire, a pilot study was undertaken to test the appropriateness and standard of the questions brought under the data gathering tools. As per the field reality, the questionnaire was redesigned and finalised for the study. The comments and suggestions of the respondents were incorporated in the final questionnaire.

Secondary data were also taken from brochures, pamphlets, reports, magazines and other government publications. These multiple sources of data collection were resorted to, for increasing the validity and reliability of the study. The detailed description of the different heads in the final questionnaire are as given below:

The 10 variables analysed under entrepreneurial traits were: drive and energy, responsibility, persistence, self – confidence, initiative, need for independence, tolerance for uncertainty, optimism, innovativeness, creativity and perseverance.

The 13 variables analysed under attitude were: long term commitment, persistence in problem solving, attitude to risk taking, dealing with failure, use of feedback, seeking assistance, flexibility, need for achievement, profit – orientedness, integrity, resolving issues without procrastination, positive influence and self – resolution of entrepreneurial stress.

The 12 variables chosen for analysis under business skills were: setting goals, developing business plans, delegating, dealing with work disputes, training subordinates, dealing with customers, dealing with government officials, keeping financial records, talent acquisition, marketing skills, catering to multiple customers and ethical competition.

The 15 variables chosen under the head Environmental Forces affecting growth of entrepreneurship in Jharkhand state were: necessary market information, training facility for employees within the state, necessary potential customers is available within the state, availability of business related services is of good quality, chances of new business success is very high within Jharkhand state, government encourages the promotion of SSI enterprises, labour force with necessary skills is easily available within the state, obtaining finance from banks/SFCs is easy,

interest rates on loans from banks /SFC is highly competitive, inspector raj does not exist in Jharkhand state, getting licenses/ approvals is easy, entrepreneurship is not linked with greed and self promotion, government and the investment community is encouraging entrepreneurship and attitude of political parties towards entrepreneurship is healthy.

5.4 Statistical Tools

Advanced statistical tools like ANOVA and Multiple Regression were used in the present study. In calculating ANOVA and the Regression Coefficients SPSS 12.0 package was used. Simple descriptive statistical tools like percentages and means to compare the variables under entrepreneurial traits, attitude, business skills and environmental forces were also used.


The environmental forces refer to the business environment in which the business units operate. Macro – forces are the broad factors in any society and business that have an effect on all businesses and industries. Some of the macro forces are socio cultural, demographic, economic, technological, political and natural environment, and they have profound effects on the business. It is important to keep track of these forces and their trends.

While it is not possible to change the forces, one can plan and adapt the business methods to meet the needs of a rapidly changing world. To stay longer in the business a constant monitoring of the macro environmental forces is essential. The study is aimed to pin point the macro environmental forces which have an impact on the performance and success of the SSI units in Jharkhand state. In this endeavour, the present study has made an attempt to identify and analyse the environmental forces which affect the chances of business success.

From Table 2, it is observed that the environmental forces has registered a high combined average for 3.11 for study location Jamshedpur followed by 2.99 for Bokaro and 2.87 for Ranchi. It is also, revealed from the above Table that the impact of environmental forces is varying across the study locations. The environment is highly conducive for the entrepreneurs from the study location Jamshedpur though the same is not for the entrepreneurs from Ranchi and Bokaro. Scrutiny has been resorted to those environmental variables which are having a combined average less than 3.00 and are affecting the business success of Jharkhand SSI entrepreneurs.

A high proportion of the new SSI units close down during the first year of their life and many SSI units are closing down every year indicating that these firms are not able to maintain the alignment with the environment. A change in the environment causes more uncertainty in the SSI units



than in large companies. This is due to the inability of the SSI entrepreneur to acquire market information and make necessary changes.

The variable “Chances of new business success is very high in Jharkhand state” has registered a combined average of 2.75 suggests that the entrepreneurs are not able to adapt themselves with the environment due to which they have formed an opinion that the chances of new business success are very low in Jharkhand. It also, suggests that partial adaption to the environment could be one reason for their poor performances.

Success in business is never automatic and it is not based on luck but it primarily depends upon the entrepreneur's foresight and efficient management of the enterprises. The entrepreneur can be successful if he/she is patient, willing to work hard and take the necessary steps to promote the business and overcome obstacles in a proactive way. The obstacles seem insurmountable when the business is in the nascent stage.

The study has revealed that the variable “Government encourages the promotion of SSI units”, has registered a low combined mean score of 2.75. All categories of

entrepreneurs across the study locations are of the opinion that the government is not encouraging the promotion of SSI units within the state whole heartedly. Most of the promotional schemes are only on paper and the entrepreneurs are not able to tap the advantages due to the bottlenecks in the system such as rampant corruption, hurdles in getting approvals and sanctions from various government agencies.

Access to credit has been one of the main bottlenecks in SSI development. The problems of raising finance is an issue that to some extent applies in general and to the SSI sector as a whole and the SSI entrepreneur also, face additional discrimination from the finance providers. There is an inordinate delay from the Banks/SFCs to finance the SSI units in terms of term loan and working capital requirements. By the time the loan is sanctioned the project cost gets escalated and entrepreneur is under financed and in turn it affects his/her profitability.

In this context the variable “Obtaining finance from Banks/SFCs is easy”: the variable has registered a low combined average of 2.55 for all entrepreneurs across the study location. Even though the government recognises

the financial needs of the SSI units, very little has been done to mitigate the financial needs of this sector. The study has revealed that the difficulty in obtaining finance may be due to the following reasons: the SSI entrepreneurs are unable to furnish margin money, lack of collateral and instability of the SSI sector and the sector being highly unorganised.

From Table 2, it is observed that the variable “Interest rates on loans from Banks/SFCs is highly competitive” and has recorded low combined average score of 2.48 across all the three study locations. The study has revealed that high interest rates on loans affect the profitability of all categories of units. The study suggests that reduction in interest rates and offering floating rates of interest will help the SSI units to procure funds at lower costs and become more competitive.

On an average, a factory/establishment is subject to 37 inspections annually by government functionaries. In some factories there are 67 inspections in a single year. Anywhere between 9 and 24 different inspectors (15 officers, on an average), inspect a factory in a given year, with the maximum number of visits in a single year being those of the environment officer, state pollution control board officials and labour officer.

Some of these inspectors are vested with wide ranging powers, including order of imprisonment (which ranges between 6 months and 7 years), sealing the unit and stopping the operations of the unit. Other powers comprise imposing a penalty (which could be up –to Rs. 0.10 million), disconnecting water and electricity supply, filing a case in the court of law and denying renewal or cancelling the operating licence.

On examining the variable, “Inspector Raj does not exist within the state”: the variable has registered a low mean score of 2.69 across the study locations. The study has revealed that all categories of entrepreneurs were of the opinion that there is a wide prevalence of Inspector Raj within Jharkhand and it acts as a deterrent force towards the growth of SSI units.

Every SSI unit has to comply with various regulations in force. These include regulatory, taxation, environmental

and certain product specific clearances. In examining the variable, “Getting licences/approvals is easy”: the present study reveals that it has registered a low combined average of 2.49 for all entrepreneurs across the study locations. In this connection the study has revealed that all categories of entrepreneurs were of the opinion that getting licenses and approvals in Jharkhand was not an easy task. The study suggests that to remove these bottlenecks, the state government should set up a single window service aimed at providing the SSI entrepreneur a single point contact to meet all regulatory requirements and get approvals.

Creating a favourable environment for enterprises and businesses to flourish within the state, the attitude of the political leaders plays a very important role. The favourable environment leads to productivity, growth, job and wealth creation. In this connection, the variable “Attitude of political parties towards entrepreneurship is healthy” has recorded a low overall combined average of 2.79. The study suggests that the attitude of the political leaders was not supportive for promotion of small scale enterprise in Jharkhand.

Further to support the above descriptive statistical analysis on the environmental forces affecting business success of SSI units advanced statistical tool ANOVA has been resorted to: H0 : The effects of environmental forces are not significantly different across the study locations under investigation. The results of such tests in connection with the environmental forces affecting business success of SSI entrepreneurs have been furnished hereunder.

Please refer to Table 3 given below:

The value of F = 8.843, the variation between groups is 3.945 with 2 degrees of freedom and within groups it is 49.897 with 224 degrees of freedom, the resulting probability p = 0.000. Since the associated probability p is less than α = 0.05, the null hypothesis is getting rejected. Alternatively, it can be seen that Fcritical = 3.036 for 2 and 224 degrees of freedom and the calculated value of F = 8.843 is larger than the critical value, the null hypothesis is getting rejected.

The sample means with values of 2.973, 3.227 and 3.114

Table: 2 Statistical Values of Environmental Forces Affecting Business Success

Variables Study Locations

Ranchi Jamshedpur Bokaro CombinedAverage

Availability of Market Information 3.35 3.72 3.47 3.15

Training facility for employees are available within the state 3.52 3.61 2.90 3.55

Accessibility of customers is easy 3.45 3.58 3.57 3.53

Many potential customers exists within the state 2.85 3.58 3.03 3.15

Availability of business related services is of good quality 3.15 3.45 3.15 3.25

Chances of new business success is very high in Jharkhand 2.36 2.89 3.00 2.75

Government encourages the promotion of SSI enterprises 2.87 3.45 2.80 2.75

Labour force with necessary skills is available locally 3.00 3.08 2.50 3.05

Obtaining finance from Banks/SFCs is easy 2.51 2.68 2.45 2.55

Interest rates on loans from Banks/SFCs is highly competitive 2.41 2.39 2.64 2.48

Inspector Raj does not exist in Jharkhand 2.68 2.43 2.95 2.69

Getting licences/approvals is easy 2.28 2.59 2.60 2.49

Entrepreneurship is not linked with greed and self promotion 3.14 3.01 3.28 3.14

Government and investment community encourages 2.76 3.65 3.49 3.30entrepreneurship

Attitude of political leaders towards entrepreneurship is healthy 2.66 2.58 2.95 2.79

Overall Average 2.87 3.11 2.99 2.97

Table: 3 ANOVA Test for Environmental Forces affecting Business Success

Sources of variation SS df MS F p -value Fcritical

Between Groups 3.945 2 1.972 8.843 0.000 3.036

Within Groups 49.897 224 0.223

Total 53.842 226

Study Locations Ranchi Jamshedpur Bokaro

Mean 2.973 3.227 3.114

Variance 0.245 0.182 0.279



than in large companies. This is due to the inability of the SSI entrepreneur to acquire market information and make necessary changes.

The variable “Chances of new business success is very high in Jharkhand state” has registered a combined average of 2.75 suggests that the entrepreneurs are not able to adapt themselves with the environment due to which they have formed an opinion that the chances of new business success are very low in Jharkhand. It also, suggests that partial adaption to the environment could be one reason for their poor performances.

Success in business is never automatic and it is not based on luck but it primarily depends upon the entrepreneur's foresight and efficient management of the enterprises. The entrepreneur can be successful if he/she is patient, willing to work hard and take the necessary steps to promote the business and overcome obstacles in a proactive way. The obstacles seem insurmountable when the business is in the nascent stage.

The study has revealed that the variable “Government encourages the promotion of SSI units”, has registered a low combined mean score of 2.75. All categories of

entrepreneurs across the study locations are of the opinion that the government is not encouraging the promotion of SSI units within the state whole heartedly. Most of the promotional schemes are only on paper and the entrepreneurs are not able to tap the advantages due to the bottlenecks in the system such as rampant corruption, hurdles in getting approvals and sanctions from various government agencies.

Access to credit has been one of the main bottlenecks in SSI development. The problems of raising finance is an issue that to some extent applies in general and to the SSI sector as a whole and the SSI entrepreneur also, face additional discrimination from the finance providers. There is an inordinate delay from the Banks/SFCs to finance the SSI units in terms of term loan and working capital requirements. By the time the loan is sanctioned the project cost gets escalated and entrepreneur is under financed and in turn it affects his/her profitability.

In this context the variable “Obtaining finance from Banks/SFCs is easy”: the variable has registered a low combined average of 2.55 for all entrepreneurs across the study location. Even though the government recognises

the financial needs of the SSI units, very little has been done to mitigate the financial needs of this sector. The study has revealed that the difficulty in obtaining finance may be due to the following reasons: the SSI entrepreneurs are unable to furnish margin money, lack of collateral and instability of the SSI sector and the sector being highly unorganised.

From Table 2, it is observed that the variable “Interest rates on loans from Banks/SFCs is highly competitive” and has recorded low combined average score of 2.48 across all the three study locations. The study has revealed that high interest rates on loans affect the profitability of all categories of units. The study suggests that reduction in interest rates and offering floating rates of interest will help the SSI units to procure funds at lower costs and become more competitive.

On an average, a factory/establishment is subject to 37 inspections annually by government functionaries. In some factories there are 67 inspections in a single year. Anywhere between 9 and 24 different inspectors (15 officers, on an average), inspect a factory in a given year, with the maximum number of visits in a single year being those of the environment officer, state pollution control board officials and labour officer.

Some of these inspectors are vested with wide ranging powers, including order of imprisonment (which ranges between 6 months and 7 years), sealing the unit and stopping the operations of the unit. Other powers comprise imposing a penalty (which could be up –to Rs. 0.10 million), disconnecting water and electricity supply, filing a case in the court of law and denying renewal or cancelling the operating licence.

On examining the variable, “Inspector Raj does not exist within the state”: the variable has registered a low mean score of 2.69 across the study locations. The study has revealed that all categories of entrepreneurs were of the opinion that there is a wide prevalence of Inspector Raj within Jharkhand and it acts as a deterrent force towards the growth of SSI units.

Every SSI unit has to comply with various regulations in force. These include regulatory, taxation, environmental

and certain product specific clearances. In examining the variable, “Getting licences/approvals is easy”: the present study reveals that it has registered a low combined average of 2.49 for all entrepreneurs across the study locations. In this connection the study has revealed that all categories of entrepreneurs were of the opinion that getting licenses and approvals in Jharkhand was not an easy task. The study suggests that to remove these bottlenecks, the state government should set up a single window service aimed at providing the SSI entrepreneur a single point contact to meet all regulatory requirements and get approvals.

Creating a favourable environment for enterprises and businesses to flourish within the state, the attitude of the political leaders plays a very important role. The favourable environment leads to productivity, growth, job and wealth creation. In this connection, the variable “Attitude of political parties towards entrepreneurship is healthy” has recorded a low overall combined average of 2.79. The study suggests that the attitude of the political leaders was not supportive for promotion of small scale enterprise in Jharkhand.

Further to support the above descriptive statistical analysis on the environmental forces affecting business success of SSI units advanced statistical tool ANOVA has been resorted to: H0 : The effects of environmental forces are not significantly different across the study locations under investigation. The results of such tests in connection with the environmental forces affecting business success of SSI entrepreneurs have been furnished hereunder.

Please refer to Table 3 given below:

The value of F = 8.843, the variation between groups is 3.945 with 2 degrees of freedom and within groups it is 49.897 with 224 degrees of freedom, the resulting probability p = 0.000. Since the associated probability p is less than α = 0.05, the null hypothesis is getting rejected. Alternatively, it can be seen that Fcritical = 3.036 for 2 and 224 degrees of freedom and the calculated value of F = 8.843 is larger than the critical value, the null hypothesis is getting rejected.

The sample means with values of 2.973, 3.227 and 3.114

Table: 2 Statistical Values of Environmental Forces Affecting Business Success

Variables Study Locations

Ranchi Jamshedpur Bokaro CombinedAverage

Availability of Market Information 3.35 3.72 3.47 3.15

Training facility for employees are available within the state 3.52 3.61 2.90 3.55

Accessibility of customers is easy 3.45 3.58 3.57 3.53

Many potential customers exists within the state 2.85 3.58 3.03 3.15

Availability of business related services is of good quality 3.15 3.45 3.15 3.25

Chances of new business success is very high in Jharkhand 2.36 2.89 3.00 2.75

Government encourages the promotion of SSI enterprises 2.87 3.45 2.80 2.75

Labour force with necessary skills is available locally 3.00 3.08 2.50 3.05

Obtaining finance from Banks/SFCs is easy 2.51 2.68 2.45 2.55

Interest rates on loans from Banks/SFCs is highly competitive 2.41 2.39 2.64 2.48

Inspector Raj does not exist in Jharkhand 2.68 2.43 2.95 2.69

Getting licences/approvals is easy 2.28 2.59 2.60 2.49

Entrepreneurship is not linked with greed and self promotion 3.14 3.01 3.28 3.14

Government and investment community encourages 2.76 3.65 3.49 3.30entrepreneurship

Attitude of political leaders towards entrepreneurship is healthy 2.66 2.58 2.95 2.79

Overall Average 2.87 3.11 2.99 2.97

Table: 3 ANOVA Test for Environmental Forces affecting Business Success

Sources of variation SS df MS F p -value Fcritical

Between Groups 3.945 2 1.972 8.843 0.000 3.036

Within Groups 49.897 224 0.223

Total 53.842 226

Study Locations Ranchi Jamshedpur Bokaro

Mean 2.973 3.227 3.114

Variance 0.245 0.182 0.279



are quite different, it signifies that the impact of the environmental forces across the study locations is significantly different. The environment is more conducive for growth of the SSI sector in Jamshedpur followed by Bokaro and Ranchi. The major forces contributing to the success of Jamshedpur entrepreneurs could be due to the following: well established industrial base of companies like Tata group of companies, Timken and Cummins, industrial work force, excellent road and infrastructure, export advantage, logistical advantage catering to nearby markets and the role played by the support agency Adityapur Industrial Area Development Authority (AIADA) in promoting industrialisation in Jamshedpur district.

Effectiveness of Jharkhand SSI Entrepreneurs

To understand the effectiveness of SSI entrepreneurs across the study locations on an overall basis, multiple regression analysis has been conducted where the dependent variable is the effectiveness of the entrepreneurs and the predictor variables are entrepreneurial traits, attitude, business skills and environmental forces. The pooled multiple regression results reveal that β – coefficient has registered the highest value for entrepreneurial traits (0.5528), business skills (0.4684), attitude (0.0841) and environmental forces (0.0784). The study reveals that SSI entrepreneurs in Jharkhand are partly “successful” due to their entrepreneurial traits, attitude and business skills. A low – β coefficient (0.0784) for environmental forces

suggests that the supportive environment does not facilitate the growth of SSI units in Jharkhand state. The contribution of environmental forces towards effectiveness of SSI entrepreneurs is 7.84% (Table 4).

A high β – coefficient (0.2570) for environmental forces, for the study location Jamshedpur suggests that the supportive environment plays a positive role and it contributes to the success of Jamshedpur entrepreneurs. The Adityapur Industrial Area Development Authority (AIADA) is the regulator for industries up-coming in the study location Jamshedpur. The formal institutional environment in the study location Jamshedpur is highly supportive to the formation and growth of the SSI sector. A high β – coefficient reveals that AIADA is playing positive role and has tried to minimize regulations, red tapism in the promotion of entrepreneurship and is implementing the Jharkhand Industrial Policy in letter and spirit.

A low β – coefficient (0.0937) for environmental forces, for the study location Ranchi suggests that the supportive environment is not at all contributing to the success of Ranchi entrepreneurs. The contribution of environmental forces towards effectiveness of Ranchi SSI entrepreneurs is 9.37% only.

As per the study it has been found that Ranchi Industrial Area Development Authority (RIADA) is not playing any role for the growth and promotion of SSI units in the study location Ranchi. Most of the SSI units located in Ranchi are

ancillary units catering to public sector undertakings in the vicinity. No mentoring and no help in design and development of the products are provided by the PSUs which were quite evident in the case of Jamshedpur entrepreneurs. There is a dearth of supply orders for Ranch entrepreneurs since the PSUs in the study location Ranchi do not have sufficient businesses for themselves. Most of the Ranchi SSI units are having ancillary status with the PSUs. The health of the public sector undertaking determines the health of the ancillary units, if the public sector undertakings go sick so do the SSI entrepreneurs.

A negative β – coefficient (-) 0.2347 for environmental forces for the study location Bokaro suggests that Bokaro Industrial Area Development Authority (BIADA) is playing a negative role and is not at all contributing to the growth and success of the SSI entrepreneurs. The role of the supportive environment is totally dysfunctional and is in shambles and no entrepreneurial support is being provided to Bokaro SSI entrepreneurs.

The study has also, revealed that 62.32% of the SSI entrepreneurs in the study location Ranchi are average performers whereas 66.35% of the SSI entrepreneurs in the study location Jamshedpur are good performers (Table 5). A high percentage of average performers in the study location Ranchi amply speaks that the environmental forces are not very conducive to the development and promotion of Ranchi SSI entrepreneurs. The study on the health of the SSI units, in the study location Bokaro has revealed that 50.98% of the entrepreneurs are average performers and the situation is similar to the study location Ranchi. BIADA is not contributing towards the effectiveness of Bokaro entrepreneurs.

7. Conclusions

Based on the findings from the research it is clear that there is a need to take some corrective and effective measures at various levels such as the government, management institutions, medium and large enterprises and various association bodies to address the problems being faced by Jharkhand SSI entrepreneurs and to increase their effectiveness.

The study suggests that the supportive environment has to play a positive role for the promotion of entrepreneurship in the state. It is suggested that the government should ensure that the incentives and promotional schemes introduced by them from time to time are well known and understood by the SSI entrepreneurs for whom it is meant. The study has also, revealed that there are bottlenecks in the system such as hurdles in getting sanction and approvals from various government agencies. The government must weed out these, if it wants to attract investments in Jharkhand. It should simplify legislation, repeal restrictive laws and do away with Inspector Raj to help the SSI sector to grow to its full potential.

Access to credit has been one of the main bottlenecks to SSI development. There is an inordinate delay from Banks/ Financial Institutions to finance the SSI units. It is urgently needed that there should be speedy processing and disbursal of loans. Also, the interest rates on loans should be very competitive so that the SSI entrepreneurs can procure funds at low cost.

Lack of managerial know - how and business skills place significant constraints on the SSI development. The entrepreneur needs to possess a diverse range of skills which are functional or task based. It is suggested that the leading companies in Jharkhand should form a panel to provide business counselling on one to one basis to existing and potential entrepreneurs. By sharing know - how with smaller enterprises the large companies add a new dimension to the SSI enterprises. That is those who succeed in business should assist up-coming and less experienced SSI entrepreneurs by hand holding them and helping them in their settlement. The philosophy behind supporting the SSI units means that the SSI sector generates maximum job opportunities and contributes significantly to the government exchequer in terms of business volumes and exports.

The liberalisation of the Indian economy has generated more turbulence and competition in the business markets and it would be more challenging and difficult for the SSI sector in the coming times ahead. The organised sector is well equipped with resources to meet the competition in comparison to the SSI sector. The SSI sector is going to face

Table: 4 Effectiveness of Jharkhand SSI Entrepreneurs

2 Study Locations Variable R (*) β t Stat Lower 95% Upper 95%

Ranchi (n =69) Attitude 0.2426 2.4909 0.0480 0.43721

Business Skills 0.3057 2.8523 0.0196 0.5197 Environmental Forces 0.0937 1.1296 (-) 0.0720 0.2594

Jamshedpur Traits 0.7364 0.7186 8.1590 0.5439 0.8932 (n = 107) Attitude 0.0032 0.0352 (-) 0.1788 0.18532

Business Skills 0.4818 5.8034 0.3171 0.6465Environmental Forces 0.2570 3.2171 0.0985 0.4154

Bokaro Traits 0.6585 0.4619 5.2622 0.2865 0.6373(n = 51) Traits 0.4435 0.3740 2.1984 0.0316 0.71653

Attitude 0. 2112 0.8673 (-) 0.2790 0.7014 Business Skills 0.6391 2.9563 0.2040 1.0743 Environmental Forces (-) 0.2347 (-) 1.3640 (-) 0.5811 0.1117

Overall (n = 227) Traits 0.6584 0.5228 8.4995 0.4016 0.6441 Attitude 0.0841 1.3698 (-) 0.0369 0.2051 Business Skills 0.4684 7.0500 0.3374 0.5993 Environmental Forces 0.0784 1.3358 (-) 0.0373 0.1941

2 2 Note: Drawn from Field Survey Data, R (*) is R (adjusted)

Traits 0.6585 0.4619 5.2622 0.2865 0.6373

Table: 5 Health of the Sample Enterprises in the Study Locations

Health of the SSI Units Study Locations

Ranchi Jamshedpur Bokaro Total

Good (Successful) 21 (30.43%) 71 (66.35%) 13 (25.49%) 105 (46.25%)

Average (Not So Successful) 43 (62.32%) 27 (25.24%) 26 (50.98%) 96 (42.29%)

Not Viable (Unsuccessful) 05 (7.25%) 09 (8.41%) 12 (23.53%) 26 (11.46%)

Total 69 (100%) 107 100%) 51(100%) 227 (100%)



are quite different, it signifies that the impact of the environmental forces across the study locations is significantly different. The environment is more conducive for growth of the SSI sector in Jamshedpur followed by Bokaro and Ranchi. The major forces contributing to the success of Jamshedpur entrepreneurs could be due to the following: well established industrial base of companies like Tata group of companies, Timken and Cummins, industrial work force, excellent road and infrastructure, export advantage, logistical advantage catering to nearby markets and the role played by the support agency Adityapur Industrial Area Development Authority (AIADA) in promoting industrialisation in Jamshedpur district.

Effectiveness of Jharkhand SSI Entrepreneurs

To understand the effectiveness of SSI entrepreneurs across the study locations on an overall basis, multiple regression analysis has been conducted where the dependent variable is the effectiveness of the entrepreneurs and the predictor variables are entrepreneurial traits, attitude, business skills and environmental forces. The pooled multiple regression results reveal that β – coefficient has registered the highest value for entrepreneurial traits (0.5528), business skills (0.4684), attitude (0.0841) and environmental forces (0.0784). The study reveals that SSI entrepreneurs in Jharkhand are partly “successful” due to their entrepreneurial traits, attitude and business skills. A low – β coefficient (0.0784) for environmental forces

suggests that the supportive environment does not facilitate the growth of SSI units in Jharkhand state. The contribution of environmental forces towards effectiveness of SSI entrepreneurs is 7.84% (Table 4).

A high β – coefficient (0.2570) for environmental forces, for the study location Jamshedpur suggests that the supportive environment plays a positive role and it contributes to the success of Jamshedpur entrepreneurs. The Adityapur Industrial Area Development Authority (AIADA) is the regulator for industries up-coming in the study location Jamshedpur. The formal institutional environment in the study location Jamshedpur is highly supportive to the formation and growth of the SSI sector. A high β – coefficient reveals that AIADA is playing positive role and has tried to minimize regulations, red tapism in the promotion of entrepreneurship and is implementing the Jharkhand Industrial Policy in letter and spirit.

A low β – coefficient (0.0937) for environmental forces, for the study location Ranchi suggests that the supportive environment is not at all contributing to the success of Ranchi entrepreneurs. The contribution of environmental forces towards effectiveness of Ranchi SSI entrepreneurs is 9.37% only.

As per the study it has been found that Ranchi Industrial Area Development Authority (RIADA) is not playing any role for the growth and promotion of SSI units in the study location Ranchi. Most of the SSI units located in Ranchi are

ancillary units catering to public sector undertakings in the vicinity. No mentoring and no help in design and development of the products are provided by the PSUs which were quite evident in the case of Jamshedpur entrepreneurs. There is a dearth of supply orders for Ranch entrepreneurs since the PSUs in the study location Ranchi do not have sufficient businesses for themselves. Most of the Ranchi SSI units are having ancillary status with the PSUs. The health of the public sector undertaking determines the health of the ancillary units, if the public sector undertakings go sick so do the SSI entrepreneurs.

A negative β – coefficient (-) 0.2347 for environmental forces for the study location Bokaro suggests that Bokaro Industrial Area Development Authority (BIADA) is playing a negative role and is not at all contributing to the growth and success of the SSI entrepreneurs. The role of the supportive environment is totally dysfunctional and is in shambles and no entrepreneurial support is being provided to Bokaro SSI entrepreneurs.

The study has also, revealed that 62.32% of the SSI entrepreneurs in the study location Ranchi are average performers whereas 66.35% of the SSI entrepreneurs in the study location Jamshedpur are good performers (Table 5). A high percentage of average performers in the study location Ranchi amply speaks that the environmental forces are not very conducive to the development and promotion of Ranchi SSI entrepreneurs. The study on the health of the SSI units, in the study location Bokaro has revealed that 50.98% of the entrepreneurs are average performers and the situation is similar to the study location Ranchi. BIADA is not contributing towards the effectiveness of Bokaro entrepreneurs.

7. Conclusions

Based on the findings from the research it is clear that there is a need to take some corrective and effective measures at various levels such as the government, management institutions, medium and large enterprises and various association bodies to address the problems being faced by Jharkhand SSI entrepreneurs and to increase their effectiveness.

The study suggests that the supportive environment has to play a positive role for the promotion of entrepreneurship in the state. It is suggested that the government should ensure that the incentives and promotional schemes introduced by them from time to time are well known and understood by the SSI entrepreneurs for whom it is meant. The study has also, revealed that there are bottlenecks in the system such as hurdles in getting sanction and approvals from various government agencies. The government must weed out these, if it wants to attract investments in Jharkhand. It should simplify legislation, repeal restrictive laws and do away with Inspector Raj to help the SSI sector to grow to its full potential.

Access to credit has been one of the main bottlenecks to SSI development. There is an inordinate delay from Banks/ Financial Institutions to finance the SSI units. It is urgently needed that there should be speedy processing and disbursal of loans. Also, the interest rates on loans should be very competitive so that the SSI entrepreneurs can procure funds at low cost.

Lack of managerial know - how and business skills place significant constraints on the SSI development. The entrepreneur needs to possess a diverse range of skills which are functional or task based. It is suggested that the leading companies in Jharkhand should form a panel to provide business counselling on one to one basis to existing and potential entrepreneurs. By sharing know - how with smaller enterprises the large companies add a new dimension to the SSI enterprises. That is those who succeed in business should assist up-coming and less experienced SSI entrepreneurs by hand holding them and helping them in their settlement. The philosophy behind supporting the SSI units means that the SSI sector generates maximum job opportunities and contributes significantly to the government exchequer in terms of business volumes and exports.

The liberalisation of the Indian economy has generated more turbulence and competition in the business markets and it would be more challenging and difficult for the SSI sector in the coming times ahead. The organised sector is well equipped with resources to meet the competition in comparison to the SSI sector. The SSI sector is going to face

Table: 4 Effectiveness of Jharkhand SSI Entrepreneurs

2 Study Locations Variable R (*) β t Stat Lower 95% Upper 95%

Ranchi (n =69) Attitude 0.2426 2.4909 0.0480 0.43721

Business Skills 0.3057 2.8523 0.0196 0.5197 Environmental Forces 0.0937 1.1296 (-) 0.0720 0.2594

Jamshedpur Traits 0.7364 0.7186 8.1590 0.5439 0.8932 (n = 107) Attitude 0.0032 0.0352 (-) 0.1788 0.18532

Business Skills 0.4818 5.8034 0.3171 0.6465Environmental Forces 0.2570 3.2171 0.0985 0.4154

Bokaro Traits 0.6585 0.4619 5.2622 0.2865 0.6373(n = 51) Traits 0.4435 0.3740 2.1984 0.0316 0.71653

Attitude 0. 2112 0.8673 (-) 0.2790 0.7014 Business Skills 0.6391 2.9563 0.2040 1.0743 Environmental Forces (-) 0.2347 (-) 1.3640 (-) 0.5811 0.1117

Overall (n = 227) Traits 0.6584 0.5228 8.4995 0.4016 0.6441 Attitude 0.0841 1.3698 (-) 0.0369 0.2051 Business Skills 0.4684 7.0500 0.3374 0.5993 Environmental Forces 0.0784 1.3358 (-) 0.0373 0.1941

2 2 Note: Drawn from Field Survey Data, R (*) is R (adjusted)

Traits 0.6585 0.4619 5.2622 0.2865 0.6373

Table: 5 Health of the Sample Enterprises in the Study Locations

Health of the SSI Units Study Locations

Ranchi Jamshedpur Bokaro Total

Good (Successful) 21 (30.43%) 71 (66.35%) 13 (25.49%) 105 (46.25%)

Average (Not So Successful) 43 (62.32%) 27 (25.24%) 26 (50.98%) 96 (42.29%)

Not Viable (Unsuccessful) 05 (7.25%) 09 (8.41%) 12 (23.53%) 26 (11.46%)

Total 69 (100%) 107 100%) 51(100%) 227 (100%)



severe competition from the organised sector and hence management think – tanks, educators, policy makers and researchers should find out ways to save this vital sector from extinction.

The management of small scale enterprises differs significantly from the management of the organised sector primarily due to the background of the owner / manager and the promoters of organised companies. It is the need of the hour to introduce Small Business Management curriculum in business schools.

References

Hindustan Times, Xavier Labour Relations Institute Survey 2000, 20th May, 2001.

Kumar, M. G. (2005). Small and Medium Enterprises – Support for Higher Growth, Indian Bank Association, Kolkata.

Mitra, R. and Pingali, V. (1999). Analysis of Growth Stages in Small Firms: A Case Study of Automobile Ancillaries in India, Journal of Small Business Management, Vol

37, No 3, pp 62 – 75.

Nazrul, I. Muhammad, Z. M. and Jahiruddin, A. T. M. (1999). Success Factors of Small Farm – based Plant Nursery Entrepreneurs in Bangladesh: A Case Study, South Asian Journal of Management, Vol. 6, Number 3 & 4, pp 75 – 85.

Prasad, A. Shaw, T. and Haran, H. (2003). Developing Competitive Edge by SMEs, Proceedings of Eastern Regional Convention of ISTD Ranchi Chapter, April 18 – 19, pp 60 – 65.

Singh, B. M. and Namboodri, K. V. N. (2006). Unleashing Rural Entrepreneurship, 1st edition, The ICFAI University Press, Hyderabad.

The Economic Times, Accenture Survey 2000, 6th July, 2001.

Vepa, K. R. (1984). How to Succeed in Small Industry. 1st edition.Vikas Publishing House Pvt. Ltd., New Delhi.

Websites

www.aiadaonline.com

www.bokaro.nic.in

1. Introduction

Mergers and Acquisitions (M&A) are prevalent in India right from the post independence period, but due to Government regulations like Industrial Development and Regulation Act of 1951, MRTP Act, and FERA Act, only a very few M&A took place in India prior to 1990s. But policy of decontrol and liberalization coupled with globalization of the economy after 1980s, especially after liberalization in 1991 had exposed the corporate sector to severe domestic and global competition. In that context, Indian business houses increasingly resorted to M&A as a means to growth. With the increasing number of Indian companies opting for mergers and acquisitions as their growth strategy, India is now one of the leading nations in the world in terms of mergers and acquisitions. M&A volume is tremendously increasing with an estimated deal of worth more than $ 100 billion in the year 2007. This is known to be two times more than that of year 2002 and four times more than that of the deal in year 2000. Further to that, the percentage is continuously increasing with high end success in business operations. As for now the scenario has completely changed with increasing competition and globalization of business. It is believed that at present India has now emerged as one of the top countries entering into mergers and acquisitions.

Mergers and Acquisitions have become a common strategy to consolidate business. For many people, M&A simply mean sharing resources and costs. However, it is not as simple as it sounds. According to statistical reports, more than 64% of the times the M&A fail to accomplish the

promised results. The result is decline in the shareholders' wealth and due to conflicts in management and lack of efficient management to unite different organizational cultures. The most challenging task is to bring together people and make them work as a team. Establishing a new organizational structure that fits all the employees is also difficult. Today's competitive marketplace makes it nearly impossible for an organization to achieve its growth objectives through organic growth only. Mergers and Acquisitions is the strategy adopted by the companies to tackle the dynamic business environment. Mergers and Acquisitions have been a very important market entry strategy as well as expansion strategy. This present era is known as competition era. In this era, companies, to avoid the competition, go for Mergers and Acquisitions and enjoy sometimes, monopoly.

Indian Pharmaceutical Industry: An Overview:

Over the past 50 years, the Indian pharmaceutical industry has undergone a massive makeover. The Indian pharmaceutical industry is part of the top six global pharmaceutical producers. It is third largest in terms of volume. Currently there are 3000 pharmaceutical companies and 10500 manufacturing units, growing at high rate. About 70 percent patients in the developing countries receive medicine from India through various NGO's like UNCTD, Doctors without Borders etc. The burden of diseases, higher disposable income due to good growth rate, and improvement in healthcare infrastructure are some of the reasons for the growth of the pharmaceutical sector in India.



Pre and Post Acquisition Performance of Select Indian Pharmaceutical Companies

Reddy Y V *Mayuresh Natekar **

* Professor and Dean, Faculty of Commerce, Goa University, Goa-403206 **Mayuresh Natekar, PG Student, Department of Commerce, Goa University, Goa-403206

ABSTRACT

The main aim of any company is profitable growth and to maximize the wealth of its shareholders. Further to achieve profitable growth it is necessary for any company to limit competition, to gain economies of scale and thereby increase income with proportionally less investment to achieve diversification, enter new market and utilize underutilized market opportunities. In order to achieve goals, business needs to work towards its long term sustainability. Corporate restructuring is a strategy adopted by the companies to tackle dynamic business environment. This study aims to study the impact of acquisitions on the performance of Indian Pharmaceutical Industry by examining the pre and post financial performance of the companies. Also an attempt has been made to analyze and compare the impact of acquisition announcements on shareholders wealth using Event Study Methodology by calculating Cumulative Abnormal Return (CAR) and Buy and Hold out Abnormal Returns (BHAR). The results reveal that most of the companies did not show the improvement in financial health during the post acquisition period as compare to pre acquisition period. Also the study indicates that most of the companies were not able to generate wealth of their shareholders.

Key Words: Acquisition, Abnormal Return, Event Window, Profitability, Solvency

severe competition from the organised sector and hence management think – tanks, educators, policy makers and researchers should find out ways to save this vital sector from extinction.

The management of small scale enterprises differs significantly from the management of the organised sector primarily due to the background of the owner / manager and the promoters of organised companies. It is the need of the hour to introduce Small Business Management curriculum in business schools.

References

Hindustan Times, Xavier Labour Relations Institute Survey 2000, 20th May, 2001.

Kumar, M. G. (2005). Small and Medium Enterprises – Support for Higher Growth, Indian Bank Association, Kolkata.

Mitra, R. and Pingali, V. (1999). Analysis of Growth Stages in Small Firms: A Case Study of Automobile Ancillaries in India, Journal of Small Business Management, Vol

37, No 3, pp 62 – 75.

Nazrul, I. Muhammad, Z. M. and Jahiruddin, A. T. M. (1999). Success Factors of Small Farm – based Plant Nursery Entrepreneurs in Bangladesh: A Case Study, South Asian Journal of Management, Vol. 6, Number 3 & 4, pp 75 – 85.

Prasad, A. Shaw, T. and Haran, H. (2003). Developing Competitive Edge by SMEs, Proceedings of Eastern Regional Convention of ISTD Ranchi Chapter, April 18 – 19, pp 60 – 65.

Singh, B. M. and Namboodri, K. V. N. (2006). Unleashing Rural Entrepreneurship, 1st edition, The ICFAI University Press, Hyderabad.

The Economic Times, Accenture Survey 2000, 6th July, 2001.

Vepa, K. R. (1984). How to Succeed in Small Industry. 1st edition.Vikas Publishing House Pvt. Ltd., New Delhi.

Websites

www.aiadaonline.com

www.bokaro.nic.in

1. Introduction

Mergers and Acquisitions (M&A) are prevalent in India right from the post independence period, but due to Government regulations like Industrial Development and Regulation Act of 1951, MRTP Act, and FERA Act, only a very few M&A took place in India prior to 1990s. But policy of decontrol and liberalization coupled with globalization of the economy after 1980s, especially after liberalization in 1991 had exposed the corporate sector to severe domestic and global competition. In that context, Indian business houses increasingly resorted to M&A as a means to growth. With the increasing number of Indian companies opting for mergers and acquisitions as their growth strategy, India is now one of the leading nations in the world in terms of mergers and acquisitions. M&A volume is tremendously increasing with an estimated deal of worth more than $ 100 billion in the year 2007. This is known to be two times more than that of year 2002 and four times more than that of the deal in year 2000. Further to that, the percentage is continuously increasing with high end success in business operations. As for now the scenario has completely changed with increasing competition and globalization of business. It is believed that at present India has now emerged as one of the top countries entering into mergers and acquisitions.

Mergers and Acquisitions have become a common strategy to consolidate business. For many people, M&A simply mean sharing resources and costs. However, it is not as simple as it sounds. According to statistical reports, more than 64% of the times the M&A fail to accomplish the

promised results. The result is decline in the shareholders' wealth and due to conflicts in management and lack of efficient management to unite different organizational cultures. The most challenging task is to bring together people and make them work as a team. Establishing a new organizational structure that fits all the employees is also difficult. Today's competitive marketplace makes it nearly impossible for an organization to achieve its growth objectives through organic growth only. Mergers and Acquisitions is the strategy adopted by the companies to tackle the dynamic business environment. Mergers and Acquisitions have been a very important market entry strategy as well as expansion strategy. This present era is known as competition era. In this era, companies, to avoid the competition, go for Mergers and Acquisitions and enjoy sometimes, monopoly.

Indian Pharmaceutical Industry: An Overview:

Over the past 50 years, the Indian pharmaceutical industry has undergone a massive makeover. The Indian pharmaceutical industry is part of the top six global pharmaceutical producers. It is third largest in terms of volume. Currently there are 3000 pharmaceutical companies and 10500 manufacturing units, growing at high rate. About 70 percent patients in the developing countries receive medicine from India through various NGO's like UNCTD, Doctors without Borders etc. The burden of diseases, higher disposable income due to good growth rate, and improvement in healthcare infrastructure are some of the reasons for the growth of the pharmaceutical sector in India.



Pre and Post Acquisition Performance of Select Indian Pharmaceutical Companies

Reddy Y V *Mayuresh Natekar **

* Professor and Dean, Faculty of Commerce, Goa University, Goa-403206 **Mayuresh Natekar, PG Student, Department of Commerce, Goa University, Goa-403206

ABSTRACT

The main aim of any company is profitable growth and to maximize the wealth of its shareholders. Further to achieve profitable growth it is necessary for any company to limit competition, to gain economies of scale and thereby increase income with proportionally less investment to achieve diversification, enter new market and utilize underutilized market opportunities. In order to achieve goals, business needs to work towards its long term sustainability. Corporate restructuring is a strategy adopted by the companies to tackle dynamic business environment. This study aims to study the impact of acquisitions on the performance of Indian Pharmaceutical Industry by examining the pre and post financial performance of the companies. Also an attempt has been made to analyze and compare the impact of acquisition announcements on shareholders wealth using Event Study Methodology by calculating Cumulative Abnormal Return (CAR) and Buy and Hold out Abnormal Returns (BHAR). The results reveal that most of the companies did not show the improvement in financial health during the post acquisition period as compare to pre acquisition period. Also the study indicates that most of the companies were not able to generate wealth of their shareholders.

Key Words: Acquisition, Abnormal Return, Event Window, Profitability, Solvency


India has huge pool of scientists and engineers who have the capabilities to take high level. India's pharmaceutical export was US$ 15 billion in 2013-14.The Indian pharmaceutical industry is estimated to grow at 20 per cent annually over the next five years. Indian firms to market generics drugs to the US and other Western European countries. Indian drug manufacturers currently export their products to more than 65 countries worldwide.

Graph 1: Mergers and Acquisitions in the Pharmaceutical Sector for the period 2000-14

Source: Bloomberg Professional Services


There is enormous amount of literature available on impact of Mergers and Acquisitions on shareholders wealth, particularly in The United States. Many studies, analysing the stock prices around the announcement of acquisition report that acquired firms shareholders, gain significant positive excess returns, while the acquiring firm shareholders receive modest excess returns Jenson and Ruback, (1983); Asquith (1983); Jarell, Brickley and Netter (1988). However, research studies investigating accounting data show conflicting results. Some studies find no or negative impact on post acquisition earnings of the acquiring firms Hogarthy (1970); Bradford (1978); Raven Scraft and Scherer ( 1989). Some studies report positive impact on accounting profit of the acquiring firms Lev and Mandelker (1972); Smith (1990). The inconsistent results may be due to the different methodologies and sample periods adopted by the researchers.

McGowan and Zunaidah Sulong (2008) studied the impact of the effect of M&A completion announcements on the stock price behavior for two anchor banks in Malaysia and used event study show that the M&A completion announcements are treated as positive information by the market. Verma and Sharma (2014) studied the impact of mergers and acquisition on the

performance of Indian Telecom industry by examining some pre and post-merger financial and operating variables. Mahesh and Prasad (2012) analyzed whether the Indian Airline Companies have achieved financial performance efficiency during the post merger and acquisition period and specifically in the areas of profitability, leverage, liquidity, and capital market standards. Kumara and Satyanarayana (2013) showed that Mergers and Acquisition are concerning the determinations of the synergetic effect through which firms undertake their domestic and global strategies. Semir and Pontus (2011) examined if the relationship between a target and an acquiring company´s abnormal return prior the transaction can affect the outcome in the future. The present study examines the comparative difference between pre and post merger and acquisition in India in terms of financial analysis.

3. Objectives of the Study

! To evaluate financial performance of selected Pharmaceuticals companies before and after acquisition.

! To examine the impact of acquisition on shareholders wealth.

4. Methodology

The data is mainly based on secondary data collected from Bloomberg Database with focus on acquisition transactions of pharmaceuticals companies in India for the years 2005-14. During the period, 10 companies were selected based on high value deals which are listed in Table 1. The companies were selected on the basis of availability of the necessary data required for analysis. The companies which are involved in the multiple mergers or acquisition activities during the study period have not been considered. The share price data is also collected using Bloomberg database. For examining impact on financial performance various financial ratios as given in Table 2, have been obtained from moneycontrol.com, way2wealth.com. To examine the performance, tools like mean, standard deviation, t test are considered.

The following techniques are used for studying announcement returns and long term share price performance

! Cumulative Abnormal Returns (CAR)

! Buy and Hold Abnormal Returns (BHAR)

Table 2: Financial Ratios Utilized for Analysis

Category Ratios

Profitability Ratios Operating Profit Margin ( OPM)

Net Profit Margin (NPM)

Return on Net Worth (RONW)

Return on Capital Employed (ROCE)

Liquidity / Solvency Current Ratio (CR)

Ratios Quick Ratio (QR)

Debt- Equity Ratio (DER)

Efficiency & Asset Asset Turnover Ratio (ATR)utilization Ratios Return on Total Asset (ROTA)

5. Data Analysis

5.1 Profitability Ratios

Profitability ratios are the most popular metrics used in financial analysis. They are used to assess a company's ability to generate earnings as compared to its expenses and other relevant costs incurred. These include Operating Profit Margin, Net Profit Margin, Return on capital Employed and Return on Net Worth. The ratios for Pre and Post acquisition period for the 10 selected companies are given in Table 3.

From the Table 3 it can be observed that operating profit margin (OPM) ratio of four companies out of ten Cipla Ltd, Lupin Ltd, Bliss GVS Pharma Ltd and Ranbaxy Laboratories Ltd have shown mean operating profit margin increase of 5.39%, 31.19%, 59.58 and 12.51% respectively for post merger period. For Lupin Ltd

operating profit margin is significant at 5% level of significance. Whereas, Abbott Laboratories, Novartis India, Strides Arcolab Ltd, Primal Enterprises Ltd, Suven Life Sciences Ltd and Sun Pharmaceutical Industries Ltd have showed a decline in operating profit margin by 7.42%, 52 .68%, 34 .31%, 130 .51%, 40 .82% and 75.96%respectively. The major decrease came from Primal Enterprises of 130.51% and the result was at 5% level significant.

Net Profit Margin (NPM) ratio helps a company determine how much actual profit is made from its sales. Abbott Laboratories, Novartis India, Strides Arcolab Ltd ,Suven Life Sciences Ltd and Ranbaxy Laboratories have shown decline in the post acquisition NPM by 19.78%, 10.34%,44.98% and 67.06% respectively. Rest of the companies Cipla Ltd. , Primal Enterprises Ltd. , Bliss GVS Pharma Ltd and Sun Pharmaceutical Industries Ltd have positive post acquisition results and benefited from the event but statistically not significant.

Capital employed includes all the investment made by the company which includes fixed asset, current asset, capital reserves, revenue reserves etc. With regard to Return on capital employed only three companies have shown increase in the return on capital employed they are Lupin Ltd, Bliss GVS Pharma Ltd and Sun Pharmaceutical Industries Ltd. With increase in percentage mean by 19.76%, 74.30%,82.50% over the pre period mean. Primal Enterprises has shown the most decline of 94.43% for their post period compares to pre acquisition.

In case of Return on net worth, Piramal Enterprises Ltd., Lupin Ltd. and Bliss GVS Pharma Ltd. have resulted in increase in post acquisition mean RONW with increase as 53.98%,3.05% and 149.72% signifying net worth was added after taking over ownership. Abbott has shown

Target Name Acquirer Name Completion/Termination Date

Healthcare Solutions business Abbott Laboratories 9/8/2010

Meditab Specialties Pvt Ltd Cipla Ltd/India 10/1/2010

Chiron Behring Vaccines Pvt Ltd Novartis India 12/23/2010

Grandix Pharmaceuticals Ltd Strides Arcolab Ltd 6/11/2007

Intellectual ppty rights/i-pill brand Piramal Enterprises Ltd 3/31/2010

Rubamin Laboratories Ltd Lupin Ltd 9/27/2007

Asian Clinical Trials Ltd Suven Life Sciences Ltd 12/6/2006

GVS Labs Bliss GVS Pharma Ltd 5/2/2006

Zenotech Laboratories Ltd Ranbaxy Laboratories Ltd 1/15/2008

Phlox Pharmaceuticals Ltd Sun Pharmaceutical Industries Ltd 4/5/2005

Table 1: Acquisition Deals in the Pharmaceutical Sector Selected for Analysis

Pre and Post Acquisition Performance of Select Indian Pharmaceutical CompaniesPre and Post Acquisition Performance of Select Indian Pharmaceutical Companies


India has huge pool of scientists and engineers who have the capabilities to take high level. India's pharmaceutical export was US$ 15 billion in 2013-14.The Indian pharmaceutical industry is estimated to grow at 20 per cent annually over the next five years. Indian firms to market generics drugs to the US and other Western European countries. Indian drug manufacturers currently export their products to more than 65 countries worldwide.

Graph 1: Mergers and Acquisitions in the Pharmaceutical Sector for the period 2000-14

Source: Bloomberg Professional Services


There is enormous amount of literature available on impact of Mergers and Acquisitions on shareholders wealth, particularly in The United States. Many studies, analysing the stock prices around the announcement of acquisition report that acquired firms shareholders, gain significant positive excess returns, while the acquiring firm shareholders receive modest excess returns Jenson and Ruback, (1983); Asquith (1983); Jarell, Brickley and Netter (1988). However, research studies investigating accounting data show conflicting results. Some studies find no or negative impact on post acquisition earnings of the acquiring firms Hogarthy (1970); Bradford (1978); Raven Scraft and Scherer ( 1989). Some studies report positive impact on accounting profit of the acquiring firms Lev and Mandelker (1972); Smith (1990). The inconsistent results may be due to the different methodologies and sample periods adopted by the researchers.

McGowan and Zunaidah Sulong (2008) studied the impact of the effect of M&A completion announcements on the stock price behavior for two anchor banks in Malaysia and used event study show that the M&A completion announcements are treated as positive information by the market. Verma and Sharma (2014) studied the impact of mergers and acquisition on the

performance of Indian Telecom industry by examining some pre and post-merger financial and operating variables. Mahesh and Prasad (2012) analyzed whether the Indian Airline Companies have achieved financial performance efficiency during the post merger and acquisition period and specifically in the areas of profitability, leverage, liquidity, and capital market standards. Kumara and Satyanarayana (2013) showed that Mergers and Acquisition are concerning the determinations of the synergetic effect through which firms undertake their domestic and global strategies. Semir and Pontus (2011) examined if the relationship between a target and an acquiring company´s abnormal return prior the transaction can affect the outcome in the future. The present study examines the comparative difference between pre and post merger and acquisition in India in terms of financial analysis.

3. Objectives of the Study

! To evaluate financial performance of selected Pharmaceuticals companies before and after acquisition.

! To examine the impact of acquisition on shareholders wealth.

4. Methodology

The data is mainly based on secondary data collected from Bloomberg Database with focus on acquisition transactions of pharmaceuticals companies in India for the years 2005-14. During the period, 10 companies were selected based on high value deals which are listed in Table 1. The companies were selected on the basis of availability of the necessary data required for analysis. The companies which are involved in the multiple mergers or acquisition activities during the study period have not been considered. The share price data is also collected using Bloomberg database. For examining impact on financial performance various financial ratios as given in Table 2, have been obtained from moneycontrol.com, way2wealth.com. To examine the performance, tools like mean, standard deviation, t test are considered.

The following techniques are used for studying announcement returns and long term share price performance

! Cumulative Abnormal Returns (CAR)

! Buy and Hold Abnormal Returns (BHAR)

Table 2: Financial Ratios Utilized for Analysis

Category Ratios

Profitability Ratios Operating Profit Margin ( OPM)

Net Profit Margin (NPM)

Return on Net Worth (RONW)

Return on Capital Employed (ROCE)

Liquidity / Solvency Current Ratio (CR)

Ratios Quick Ratio (QR)

Debt- Equity Ratio (DER)

Efficiency & Asset Asset Turnover Ratio (ATR)utilization Ratios Return on Total Asset (ROTA)

5. Data Analysis

5.1 Profitability Ratios

Profitability ratios are the most popular metrics used in financial analysis. They are used to assess a company's ability to generate earnings as compared to its expenses and other relevant costs incurred. These include Operating Profit Margin, Net Profit Margin, Return on capital Employed and Return on Net Worth. The ratios for Pre and Post acquisition period for the 10 selected companies are given in Table 3.

From the Table 3 it can be observed that operating profit margin (OPM) ratio of four companies out of ten Cipla Ltd, Lupin Ltd, Bliss GVS Pharma Ltd and Ranbaxy Laboratories Ltd have shown mean operating profit margin increase of 5.39%, 31.19%, 59.58 and 12.51% respectively for post merger period. For Lupin Ltd

operating profit margin is significant at 5% level of significance. Whereas, Abbott Laboratories, Novartis India, Strides Arcolab Ltd, Primal Enterprises Ltd, Suven Life Sciences Ltd and Sun Pharmaceutical Industries Ltd have showed a decline in operating profit margin by 7.42%, 52 .68%, 34 .31%, 130 .51%, 40 .82% and 75.96%respectively. The major decrease came from Primal Enterprises of 130.51% and the result was at 5% level significant.

Net Profit Margin (NPM) ratio helps a company determine how much actual profit is made from its sales. Abbott Laboratories, Novartis India, Strides Arcolab Ltd ,Suven Life Sciences Ltd and Ranbaxy Laboratories have shown decline in the post acquisition NPM by 19.78%, 10.34%,44.98% and 67.06% respectively. Rest of the companies Cipla Ltd. , Primal Enterprises Ltd. , Bliss GVS Pharma Ltd and Sun Pharmaceutical Industries Ltd have positive post acquisition results and benefited from the event but statistically not significant.

Capital employed includes all the investment made by the company which includes fixed asset, current asset, capital reserves, revenue reserves etc. With regard to Return on capital employed only three companies have shown increase in the return on capital employed they are Lupin Ltd, Bliss GVS Pharma Ltd and Sun Pharmaceutical Industries Ltd. With increase in percentage mean by 19.76%, 74.30%,82.50% over the pre period mean. Primal Enterprises has shown the most decline of 94.43% for their post period compares to pre acquisition.

In case of Return on net worth, Piramal Enterprises Ltd., Lupin Ltd. and Bliss GVS Pharma Ltd. have resulted in increase in post acquisition mean RONW with increase as 53.98%,3.05% and 149.72% signifying net worth was added after taking over ownership. Abbott has shown

Target Name Acquirer Name Completion/Termination Date

Healthcare Solutions business Abbott Laboratories 9/8/2010

Meditab Specialties Pvt Ltd Cipla Ltd/India 10/1/2010

Chiron Behring Vaccines Pvt Ltd Novartis India 12/23/2010

Grandix Pharmaceuticals Ltd Strides Arcolab Ltd 6/11/2007

Intellectual ppty rights/i-pill brand Piramal Enterprises Ltd 3/31/2010

Rubamin Laboratories Ltd Lupin Ltd 9/27/2007

Asian Clinical Trials Ltd Suven Life Sciences Ltd 12/6/2006

GVS Labs Bliss GVS Pharma Ltd 5/2/2006

Zenotech Laboratories Ltd Ranbaxy Laboratories Ltd 1/15/2008

Phlox Pharmaceuticals Ltd Sun Pharmaceutical Industries Ltd 4/5/2005

Table 1: Acquisition Deals in the Pharmaceutical Sector Selected for Analysis



negative post acquisition mean of 19.23% significant at 5%. Other companies like Cipla, Novartis India, Strides Arcolab Ltd., Suven Life Sciences Ltd., Ranbaxy Laboratories Ltd. and Sun Pharmaceutical Industries Ltd. have shown decline in post azquisition RONW and the worst was for the Sun Pharmaceutical Industries ltd with the decline of 97.75% significant at 5%.

5.2 Efficiency and Asset Utilization Ratios

Efficiency and asset utilization ratios for the pre and post acquisition periods for the selected companies are given in Table 4.

The Table 3 shows the impact of deals on Efficiency and Asset Utilization ratios of the sample companies. It is observed that asset turnover ratio of seven companies have shown decline in the operating efficiency. Cipla, Novartis India Ltd. , Strides Arcolab Ltd, Piramal, Lupin Ltd, Ranbaxy Laboratories Ltd, Sun Pharmaceutical Industries Ltd over mean of pre period by-51.46%, 17.65%, 46.11%, 89.15%, 2.34%, 45.48% and 36.70% respectively. Piramal Enterprises Ltd has shown the highest decline of 89.15 % and is significant at 1%.

Abbott Laboratories, Suven Life Sciences Ltd and Bliss GVS Pharma Ltd has shown increase in the mean ratio

Table 4: Operational Efficiency and Asset Utilization Ratio of the Indian Pharmaceutical Companies

Name of the Company Mean

Ratio Pre PostAcquisition Acquisition Change(%) p-value t-statistic

Abbott Laboratories ATR 2.96 3.18 7.55 0.62 0.59 NSROTA 183.32 310.42 69.33 0.06 4.03 **

Cipla Ltd/India ATR 1.94 0.94 -51.46 0.00 -65.47***ROTA 48.63 96.83 99.12 0.01 11.00 ***

Novartis India Ltd. ATR 1.25 1.03 -17.65 0.01 -11.00 ***ROTA 162.34 279.46 72.14 0.00 66.59 ***

Strides Arcolab Ltd ATR 0.64 0.35 -46.11 0.07 -3.62 **ROTA 94.02 289.77 208.20 0.25 1.62 NS

Piramal Enterprises Ltd. ATR 1.26 0.14 -89.15 0.00 -19.42***ROTA 51.99 651.39 1152.91 0.00 22.73 ***

Lupin Ltd ATR 1.28 1.25 -2.34 0.10 -3.00*ROTA 131.90 173.75 31.73 0.47 0.88NS

Suven Life Sciences Ltd ATR 0.61 0.80 29.89 0.12 2.57 NSROTA 35.26 9.92 -71.87 0.00 -18.04***

Bliss GVS Pharma Ltd ATR 1.17 1.63 39.43 0.21 1.81NSROTA 12.87 10.65 -17.24 0.29 -1.42 NS

Ranbaxy Laboratories Ltd ATR 1.22 0.66 -45.48 0.08 -3.42 **ROTA 87.30 102.89 17.86 0.67 0.49 NS

Sun Pharmaceutical ATR 0.89 0.56 -36.70 0.33 -1.27 NSIndustries Ltd ROTA 20.56 192.82 837.67 0.02 7.24 **

Note: ***significant at the 0.01 level, **significant at the 0.05 level, *significant at the 0.1 level and NS- Not significant.


Table 3: Profitability Ratios of the Selected Pharmaceutical Companies


Acquisition Acquisition Change(%) p-value t-statistic

Abbott Laboratories OPM 12.12 11.22 -7.42 0.57 -0.68 NSNPM 9.56 8.25 -13.67 0.27 -1.52 NSROCE 42.34 34.27 -19.06 0.02 -7.37 **RONW 28.75 23.22 -19.23 0.04 -4.79**

Cipla Ltd/India OPM 22.57 23.78 5.39 0.58 0.65 NSNPM 16.42 16.53 0.71 0.96 0.06 NSROCE 22.83 20.00 -12.40 0.32 -1.33 NSRONW 19.06 15.65 -17.88 0.15 -2.26 NS

Novartis OPM 19.12 9.05 -52.68 0.23 -1.72 NSNPM 16.14 12.95 -19.78 0.23 -1.69 NSROCE 31.69 18.58 -41.37 0.11 -2.76 NSRONW 20.45 13.04 -36.25 0.02 -7.66 **

STRIDES OPM 22.53 14.80 -34.31 0.12 -2.59 NSNPM 10.28 9.22 -10.34 0.82 -0.26 NSROCE 14.07 6.18 -56.10 0.02 -6.80 **RONW 12.72 6.10 -52.03 0.07 -3.57 **OPM 19.94 -6.08 -130.51 0.05 -4.52**NPM 12.49 215.50 1624.89 0.45 0.93 NS

Piramal Enterprises Ltd ROCE 26.08 1.45 -94.43 0.02 -6.82 **RONW 23.64 36.41 53.98 0.78 0.32 NS

Lupin Ltd OPM 15.67 21.18 35.19 0.03 5.60 **NPM 11.02 58.79 433.48 0.38 1.11 NSROCE 22.83 27.34 19.76 0.43 0.98 NSRONW 26.41 27.21 3.05 0.91 0.12 NS

Suven Life Sciences Ltd OPM 19.20 11.36 -40.82 0.10 -3.00*NPM 10.62 5.84 -44.98 0.11 -2.70 NSROCE 8.67 6.36 -26.62 0.33 -1.27 NSRONW 7.36 6.88 -6.48 0.71 -0.42 NS

Bliss GVS Pharma Ltd OPM 21.00 33.51 59.58 0.30 1.37 NSNPM 13.08 28.53 118.09 0.13 2.53 NSROCE 23.22 40.47 74.30 0.29 1.42 NSRONW 14.79 41.41 179.92 0.13 2.44 NS

Ranbaxy Laboratories Ltd OPM 12.25 13.79 12.51 0.83 0.24 NSNPM 9.55 3.15 -67.06 0.71 -0.43 NSROCE 13.08 8.99 -31.31 0.66 -0.51NSRONW 12.38 2.45 -80.22 0.59 -0.63 NS

Sun Pharmaceutical OPM 11.11 2.67 -75.96 0.61 -0.60 NSIndustries Ltd NPM 26.35 29.71 12.75 0.36 1.18 NS

ROCE 11.98 21.87 82.50 0.57 0.68 NSRONW 29.63 0.67 -97.75 0.07 -3.53 **


Ratio Pre Post


negative post acquisition mean of 19.23% significant at 5%. Other companies like Cipla, Novartis India, Strides Arcolab Ltd., Suven Life Sciences Ltd., Ranbaxy Laboratories Ltd. and Sun Pharmaceutical Industries Ltd. have shown decline in post azquisition RONW and the worst was for the Sun Pharmaceutical Industries ltd with the decline of 97.75% significant at 5%.

5.2 Efficiency and Asset Utilization Ratios

Efficiency and asset utilization ratios for the pre and post acquisition periods for the selected companies are given in Table 4.

The Table 3 shows the impact of deals on Efficiency and Asset Utilization ratios of the sample companies. It is observed that asset turnover ratio of seven companies have shown decline in the operating efficiency. Cipla, Novartis India Ltd. , Strides Arcolab Ltd, Piramal, Lupin Ltd, Ranbaxy Laboratories Ltd, Sun Pharmaceutical Industries Ltd over mean of pre period by-51.46%, 17.65%, 46.11%, 89.15%, 2.34%, 45.48% and 36.70% respectively. Piramal Enterprises Ltd has shown the highest decline of 89.15 % and is significant at 1%.

Abbott Laboratories, Suven Life Sciences Ltd and Bliss GVS Pharma Ltd has shown increase in the mean ratio

Table 4: Operational Efficiency and Asset Utilization Ratio of the Indian Pharmaceutical Companies


Ratio Pre PostAcquisition Acquisition Change(%) p-value t-statistic

Abbott Laboratories ATR 2.96 3.18 7.55 0.62 0.59 NSROTA 183.32 310.42 69.33 0.06 4.03 **

Cipla Ltd/India ATR 1.94 0.94 -51.46 0.00 -65.47***ROTA 48.63 96.83 99.12 0.01 11.00 ***

Novartis India Ltd. ATR 1.25 1.03 -17.65 0.01 -11.00 ***ROTA 162.34 279.46 72.14 0.00 66.59 ***

Strides Arcolab Ltd ATR 0.64 0.35 -46.11 0.07 -3.62 **ROTA 94.02 289.77 208.20 0.25 1.62 NS

Piramal Enterprises Ltd. ATR 1.26 0.14 -89.15 0.00 -19.42***ROTA 51.99 651.39 1152.91 0.00 22.73 ***

Lupin Ltd ATR 1.28 1.25 -2.34 0.10 -3.00*ROTA 131.90 173.75 31.73 0.47 0.88NS

Suven Life Sciences Ltd ATR 0.61 0.80 29.89 0.12 2.57 NSROTA 35.26 9.92 -71.87 0.00 -18.04***

Bliss GVS Pharma Ltd ATR 1.17 1.63 39.43 0.21 1.81NSROTA 12.87 10.65 -17.24 0.29 -1.42 NS

Ranbaxy Laboratories Ltd ATR 1.22 0.66 -45.48 0.08 -3.42 **ROTA 87.30 102.89 17.86 0.67 0.49 NS

Sun Pharmaceutical ATR 0.89 0.56 -36.70 0.33 -1.27 NSIndustries Ltd ROTA 20.56 192.82 837.67 0.02 7.24 **



Table 3: Profitability Ratios of the Selected Pharmaceutical Companies



Abbott Laboratories OPM 12.12 11.22 -7.42 0.57 -0.68 NSNPM 9.56 8.25 -13.67 0.27 -1.52 NSROCE 42.34 34.27 -19.06 0.02 -7.37 **RONW 28.75 23.22 -19.23 0.04 -4.79**

Cipla Ltd/India OPM 22.57 23.78 5.39 0.58 0.65 NSNPM 16.42 16.53 0.71 0.96 0.06 NSROCE 22.83 20.00 -12.40 0.32 -1.33 NSRONW 19.06 15.65 -17.88 0.15 -2.26 NS

Novartis OPM 19.12 9.05 -52.68 0.23 -1.72 NSNPM 16.14 12.95 -19.78 0.23 -1.69 NSROCE 31.69 18.58 -41.37 0.11 -2.76 NSRONW 20.45 13.04 -36.25 0.02 -7.66 **

STRIDES OPM 22.53 14.80 -34.31 0.12 -2.59 NSNPM 10.28 9.22 -10.34 0.82 -0.26 NSROCE 14.07 6.18 -56.10 0.02 -6.80 **RONW 12.72 6.10 -52.03 0.07 -3.57 **OPM 19.94 -6.08 -130.51 0.05 -4.52**NPM 12.49 215.50 1624.89 0.45 0.93 NS

Piramal Enterprises Ltd ROCE 26.08 1.45 -94.43 0.02 -6.82 **RONW 23.64 36.41 53.98 0.78 0.32 NS

Lupin Ltd OPM 15.67 21.18 35.19 0.03 5.60 **NPM 11.02 58.79 433.48 0.38 1.11 NSROCE 22.83 27.34 19.76 0.43 0.98 NSRONW 26.41 27.21 3.05 0.91 0.12 NS

Suven Life Sciences Ltd OPM 19.20 11.36 -40.82 0.10 -3.00*NPM 10.62 5.84 -44.98 0.11 -2.70 NSROCE 8.67 6.36 -26.62 0.33 -1.27 NSRONW 7.36 6.88 -6.48 0.71 -0.42 NS

Bliss GVS Pharma Ltd OPM 21.00 33.51 59.58 0.30 1.37 NSNPM 13.08 28.53 118.09 0.13 2.53 NSROCE 23.22 40.47 74.30 0.29 1.42 NSRONW 14.79 41.41 179.92 0.13 2.44 NS

Ranbaxy Laboratories Ltd OPM 12.25 13.79 12.51 0.83 0.24 NSNPM 9.55 3.15 -67.06 0.71 -0.43 NSROCE 13.08 8.99 -31.31 0.66 -0.51NSRONW 12.38 2.45 -80.22 0.59 -0.63 NS

Sun Pharmaceutical OPM 11.11 2.67 -75.96 0.61 -0.60 NSIndustries Ltd NPM 26.35 29.71 12.75 0.36 1.18 NS

ROCE 11.98 21.87 82.50 0.57 0.68 NSRONW 29.63 0.67 -97.75 0.07 -3.53 **


Ratio Pre Post


by7.55%, 29.89% and 39.43% respectively. This shows that the acquiring companies are able to generate more assets.

The test of Return on Total Assets (ROTA) eight companies have shown increase in the post mean ratio. Abbott Laboratories, Cipla Ltd, Novartis India Ltd. Strides Arcolab Ltd, Piramal Enterprises Ltd. Lupin Ltd, Ranbaxy Laboratories Ltd and Sun Pharmaceutical Industries Ltd by 69.33%,99.12%,208.20%,115.91,31.73%,17.89% and 837.67% respectively, but Cipla ltd, Novartis India and Piramal Enterprises Ltd is highly significant at 1% . Other companies Piramal Enterprises and Suveen life science has shown decline in their post mean performance indicating underutilization of their assets.

5.3 Liquidity and Solvency Ratios

Liquidity and solvency ratios for pre and post acquisition periods for the selected companies are reported in Table 5.

It can be observed from the Table 5 that the Current Ratio of four companies Abbott Laboratories, Suven Life Sciences Ltd, Bliss GvsPharma Ltd and Sun Pharmaceutical Industries Ltd have shown post acquisition increase in mean. They have shown increase of 31.35%, 0.96%, 64.24%, 22.21% respectively. The result was positive but was not statistically significant. Quick ratio of six companies has improved which are Abbott Laboratories, Strides Arcolab Ltd, PIRAMAL, Bliss GVS Pharma Ltd, Ranbaxy Laboratories Ltd, and Sun Pharmaceutical Industries Ltd, by 107.22%, 5.42%, 227.08%, 96.32%,

4.11%, 18.60% respectively. Abbott Laboratories was significant level 10%.

Debt to equity Ratio - Test revealed that four companies reduced their debt in the post acquisition period namely, Cipla, Piramal Enterprises, Lupin Ltd and Sun Pharmaceuticals by 53.85%, 68.79% and 75.92 % respectively. This indicates that the funds brought in from the acquired companies were able to meet debt claims. On the other hand, debt to equity ratio had increased for the companies like, Strides Arcolab Ltd, Suven Life Sciences Ltd, Bliss GVS Pharma Ltd and Ranbaxy Laboratories Ltd by 73.49%, 76.71%, 55.56% and 48.63% respectively as these companies added long term debt to their balance sheet. It indicates that the acquisitions were financed by the debt and the acquisition company already had debt in their balance sheets.

6. Impact of Acquisition on Shareholders Wealth of Select Indian Pharmaceutical Companies.

The impact of acquisition announcement has been studied using Event study methodology. Event study is a statistical method to gauge the impact of a various corporate event and announcements. It has become a standard method of measuring security price reaction to such announcements. The event study methodology assesses whether the specific events create abnormal returns for shareholders of a firm. The stock return on the days around the announcement that are surely due to the occurrence of the mergers and acquisition announcement are called Cumulative Abnormal returns (CAR).

Applying well established methodology of event study, we divide the total period of analysis in respect of each acquirer into two major time periods viz. estimation window and event window as depicted in the figure below:

The event window covers period surrounding the

announcement of merger. The date of announcement of merger is termed as 't'day. Period before 't-'day is called as pre-announcement period while period after 't+'day is called as post-announcement period.

Three event windows are selected for pre-announcement period viz t-5(5 days before announcement date), t-15 (15 days before announcement date) & t-30 (30 days before announcement date) similarly three event windows are selected in post-announcement period t+5 (15 days after announcement date ), t+15 (15 days after announcement date) & t+30 (30 days after the announcement date).

Once event windows are identified, the abnormal returns are computed in respect of each acquirer firm during these event windows. Abnormal return is the difference between expected return and the actual return on acquirer firm's stock during an event an event window. Thus

AR it =Rit - E (Rit) ………………………….(1)

Where, AR it is the abnormal returns on acquirer i's stock at time t in the event window, Rit is the actual returns on acquirer I 'stock and E(Rit) is the expected returns. For the purpose of computing expected returns E (Rit) the market model depicting a linear relationship between acquirer's stock return and the market returns is used. Thus,

E (Rit) = αi+ βi Rmt

Where Rmt is the return on market index (Nifty index in this study) during the estimation window period and αi and βi are the firm specific coefficients. The alpha (αi) and beta (βi) components in the above model are computed by regressing market returns on stock returns during estimation window. Estimation window comprises of time period of 180days prior to t-30. The estimation window period is thus a 'clean period' so selected to avoid including stock returns in regression model that are included with merger news. The abnormal returns so computed in Eq.(1) above are then used to compute Cumulative Abnormal Returns (CARs)as under:-

CARs = , t …………(2)

The event window determines the number of days over which we measure the possible abnormal return caused by

Estimation window Event Window

t- 30 t t+30

Table 5: Liquidity and solvency ratios of select Indian pharmaceutical companies

Name of the Company MeanRatio Pre Post


Abbott Laboratories CR 2.24 2.95 31.35 0.21 1.83 NSQR 0.92 1.91 107.22 0.10 2.91*DE 0.00 0.00 0.00 0.00 0.00

Cipla Ltd/India CR 2.36 2.33 -1.41 0.77 -0.33 NSQR 1.85 1.73 -6.83 0.54 -0.73 NSDE 0.13 0.06 -53.85 0.37 -1.15 NS

NOVARTIS CR 4.21 3.83 -9.10 0.72 -0.41NSQR 3.76 3.46 -8.07 0.73 -0.40 NSDE 0.00 0.00 0.00 0.00 0.00

Strides Arcolab Ltd CR 1.35 0.99 -26.49 0.51 -0.79 NSQR 2.40 2.53 5.42 0.93 0.11NSDE 1.12 1.95 73.59 0.46 0.92 NS

PIRAMAL CR 1.76 1.34 -23.91 0.62 -0.58 NSQR 1.72 5.64 227.08 0.16 2.19 NSDE 0.58 0.18 -68.79 7.06 -119.00 NS

Lupin Ltd CR 1.03 0.96 -7.10 0.48 -0.87 NSQR 13.84 1.48 -89.28 0.18 -2.02 NSDE 1.09 0.45 -59.02 0.12 -2.56 NS

Suven Life Sciences Ltd CR 1.04 1.05 0.96 0.93 0.09 NSQR 0.94 0.81 -13.83 0.08 -3.22 **DE 0.24 0.43 76.71 0.02 6.84 **

Bliss GVS Pharma Ltd CR 2.01 3.31 64.24 0.34 1.24 NSQR 1.72 3.38 96.32 0.30 1.40 NSDE 0.06 0.09 55.56 0.66 0.52 NS

Ranbaxy Laboratories Ltd CR 1.66 1.63 -2.00 0.87 -0.19 NSQR 0.97 1.01 4.11 0.90 0.15DE 0.61 0.91 48.63 0.57 0.67 NS

Sun Pharmaceutical CR 2.90 3.54 22.21 0.71 0.43 NSIndustries Ltd QR 2.72 3.23 18.60 0.81 0.28NS

DE 0.64 0.15 -75.92 0.51 -0.79 NS


53"Pragyaan: Journal of Management" Volume 13, Issue 2, December 2015


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by7.55%, 29.89% and 39.43% respectively. This shows that the acquiring companies are able to generate more assets.

The test of Return on Total Assets (ROTA) eight companies have shown increase in the post mean ratio. Abbott Laboratories, Cipla Ltd, Novartis India Ltd. Strides Arcolab Ltd, Piramal Enterprises Ltd. Lupin Ltd, Ranbaxy Laboratories Ltd and Sun Pharmaceutical Industries Ltd by 69.33%,99.12%,208.20%,115.91,31.73%,17.89% and 837.67% respectively, but Cipla ltd, Novartis India and Piramal Enterprises Ltd is highly significant at 1% . Other companies Piramal Enterprises and Suveen life science has shown decline in their post mean performance indicating underutilization of their assets.

5.3 Liquidity and Solvency Ratios

Liquidity and solvency ratios for pre and post acquisition periods for the selected companies are reported in Table 5.

It can be observed from the Table 5 that the Current Ratio of four companies Abbott Laboratories, Suven Life Sciences Ltd, Bliss GvsPharma Ltd and Sun Pharmaceutical Industries Ltd have shown post acquisition increase in mean. They have shown increase of 31.35%, 0.96%, 64.24%, 22.21% respectively. The result was positive but was not statistically significant. Quick ratio of six companies has improved which are Abbott Laboratories, Strides Arcolab Ltd, PIRAMAL, Bliss GVS Pharma Ltd, Ranbaxy Laboratories Ltd, and Sun Pharmaceutical Industries Ltd, by 107.22%, 5.42%, 227.08%, 96.32%,

4.11%, 18.60% respectively. Abbott Laboratories was significant level 10%.

Debt to equity Ratio - Test revealed that four companies reduced their debt in the post acquisition period namely, Cipla, Piramal Enterprises, Lupin Ltd and Sun Pharmaceuticals by 53.85%, 68.79% and 75.92 % respectively. This indicates that the funds brought in from the acquired companies were able to meet debt claims. On the other hand, debt to equity ratio had increased for the companies like, Strides Arcolab Ltd, Suven Life Sciences Ltd, Bliss GVS Pharma Ltd and Ranbaxy Laboratories Ltd by 73.49%, 76.71%, 55.56% and 48.63% respectively as these companies added long term debt to their balance sheet. It indicates that the acquisitions were financed by the debt and the acquisition company already had debt in their balance sheets.

6. Impact of Acquisition on Shareholders Wealth of Select Indian Pharmaceutical Companies.

The impact of acquisition announcement has been studied using Event study methodology. Event study is a statistical method to gauge the impact of a various corporate event and announcements. It has become a standard method of measuring security price reaction to such announcements. The event study methodology assesses whether the specific events create abnormal returns for shareholders of a firm. The stock return on the days around the announcement that are surely due to the occurrence of the mergers and acquisition announcement are called Cumulative Abnormal returns (CAR).

Applying well established methodology of event study, we divide the total period of analysis in respect of each acquirer into two major time periods viz. estimation window and event window as depicted in the figure below:

The event window covers period surrounding the

announcement of merger. The date of announcement of merger is termed as 't'day. Period before 't-'day is called as pre-announcement period while period after 't+'day is called as post-announcement period.

Three event windows are selected for pre-announcement period viz t-5(5 days before announcement date), t-15 (15 days before announcement date) & t-30 (30 days before announcement date) similarly three event windows are selected in post-announcement period t+5 (15 days after announcement date ), t+15 (15 days after announcement date) & t+30 (30 days after the announcement date).

Once event windows are identified, the abnormal returns are computed in respect of each acquirer firm during these event windows. Abnormal return is the difference between expected return and the actual return on acquirer firm's stock during an event an event window. Thus

AR it =Rit - E (Rit) ………………………….(1)

Where, AR it is the abnormal returns on acquirer i's stock at time t in the event window, Rit is the actual returns on acquirer I 'stock and E(Rit) is the expected returns. For the purpose of computing expected returns E (Rit) the market model depicting a linear relationship between acquirer's stock return and the market returns is used. Thus,

E (Rit) = αi+ βi Rmt

Where Rmt is the return on market index (Nifty index in this study) during the estimation window period and αi and βi are the firm specific coefficients. The alpha (αi) and beta (βi) components in the above model are computed by regressing market returns on stock returns during estimation window. Estimation window comprises of time period of 180days prior to t-30. The estimation window period is thus a 'clean period' so selected to avoid including stock returns in regression model that are included with merger news. The abnormal returns so computed in Eq.(1) above are then used to compute Cumulative Abnormal Returns (CARs)as under:-

CARs = , t …………(2)

The event window determines the number of days over which we measure the possible abnormal return caused by

Estimation window Event Window

t- 30 t t+30

Table 5: Liquidity and solvency ratios of select Indian pharmaceutical companies

Name of the Company MeanRatio Pre Post


Abbott Laboratories CR 2.24 2.95 31.35 0.21 1.83 NSQR 0.92 1.91 107.22 0.10 2.91*DE 0.00 0.00 0.00 0.00 0.00

Cipla Ltd/India CR 2.36 2.33 -1.41 0.77 -0.33 NSQR 1.85 1.73 -6.83 0.54 -0.73 NSDE 0.13 0.06 -53.85 0.37 -1.15 NS

NOVARTIS CR 4.21 3.83 -9.10 0.72 -0.41NSQR 3.76 3.46 -8.07 0.73 -0.40 NSDE 0.00 0.00 0.00 0.00 0.00

Strides Arcolab Ltd CR 1.35 0.99 -26.49 0.51 -0.79 NSQR 2.40 2.53 5.42 0.93 0.11NSDE 1.12 1.95 73.59 0.46 0.92 NS

PIRAMAL CR 1.76 1.34 -23.91 0.62 -0.58 NSQR 1.72 5.64 227.08 0.16 2.19 NSDE 0.58 0.18 -68.79 7.06 -119.00 NS

Lupin Ltd CR 1.03 0.96 -7.10 0.48 -0.87 NSQR 13.84 1.48 -89.28 0.18 -2.02 NSDE 1.09 0.45 -59.02 0.12 -2.56 NS

Suven Life Sciences Ltd CR 1.04 1.05 0.96 0.93 0.09 NSQR 0.94 0.81 -13.83 0.08 -3.22 **DE 0.24 0.43 76.71 0.02 6.84 **

Bliss GVS Pharma Ltd CR 2.01 3.31 64.24 0.34 1.24 NSQR 1.72 3.38 96.32 0.30 1.40 NSDE 0.06 0.09 55.56 0.66 0.52 NS

Ranbaxy Laboratories Ltd CR 1.66 1.63 -2.00 0.87 -0.19 NSQR 0.97 1.01 4.11 0.90 0.15DE 0.61 0.91 48.63 0.57 0.67 NS

Sun Pharmaceutical CR 2.90 3.54 22.21 0.71 0.43 NSIndustries Ltd QR 2.72 3.23 18.60 0.81 0.28NS

DE 0.64 0.15 -75.92 0.51 -0.79 NS


53"Pragyaan: Journal of Management" Volume 13, Issue 2, December 2015


å=

L

Kt

AR

the event. Any shift in the stock price caused by the event will happen immediately due to rational behavior which talks in favour of short event window since a long window could risk diluting the possibility if finding any significant evidence, however if the event window is too short the effect of the event if the information comes out only after closing of the market and therefore, does not reach the public and in some cases the information is leaked day before announcement date and therefore, causes effect before the actual date. Therefore, the period needs to be long enough to measure the returns

The pre and post acquisition period of CARs are analyzed in order to examine the impact of acquisition on the shareholders wealth of selected Pharmaceutical companies in India. The results show that Piramal Enterprises Ltd did not have any negative impact on CAR values for all post announcement window periods signifying that the company was successful in adding value to their shareholders wealth. In case of Sun Pharmaceuticals which had given negative returns in all the pre window period has resulted in positive in the positive returns in the post period. But in case of Ranbaxy Laboratories Ltd which had given positive returns in the pre period resulted in negative retuns in the post period.

As can be observed from the Table 6 for the window period t-5, four companies have negative CAR values in the pre announcement period and five companies have negative CAR in the post announcement period. The CAR value in case of Novartis India which was negative (-0.42) in the pre announcement period have shown positive results in the post-announcement period (0.21%). Suven life science

which had positive return (0.07%) has shown negative returns in the post announcement period (-0.6%).

Strides Arcolab Ltd and Bliss GvsPharma Ltd which had given positive returns has resulted in the negative returns in the post announcement period. When it comes to piramal it has given positive returns.

The 30 days window period is the longest window period of the study. It shows the long term impact on the shareholders return to the announcement of acquisition. In this period the companies like Abbott Laboratories, Bliss GVS Pharma Ltd, Ranbaxy Laboratories Ltd has shown the negative returns. On the other hand, the companies like Sun Pharmaceutical which had given the negative returns of -0.13% has resulted in positive returns of 0.16%. Piramal which had given the returns of 0.20% in the pre announcement period has resulted to incredible returns of 0.84% in the post-announcement period.

7. Impact of Acquisition on Long Term Share Price Performance.

The long term effect of acquisition on share prices of acquirers is studied using Buy and Hold Abnormal Returns (BHAR) methodology. To study the long term wealth creation effect of acquisition BHAR methodology has been used. The BHAR essentially indicates the excess returns over the industry average that an investor buying the shares of acquiring firm will be enjoying if he makes the purchase of those shares after acquisition.

Three different event windows have been constructed for the purpose of examining long term wealth creation effect

of mergers with length of 1 year, 2 year and 3 year holding period during post merger period. The BHAR over the relevant event window is then computed by following the standard model given below:-

………………(3)

Where, BHARi is abnormal returns due to buy and hold of shares of sample acquirer firm, Ri,t is the raw weekly return on share prices of acquirer firm (i) for period t, Rbenchmark , t is the weekly return on benchmark index for period t. It essentially implies that the cumulative returns on share of acquiring company are computed by compounding the weekly returns on the acquiring company's returns during the selected event window or holding period. The Benchmark index selected for the purpose of calculation of BHAR are the nifty relevant to a given acquirer in the sample. The selection of index is more appropriate as the long term abnormal returns are computed in comparison to industry average returns. Finally, the average buy and hold returns across the portfolio of acquirer companies in

a given sector during a holding period T is computed as:

………………(4)

Where N is the total number of acquirer companies in the sample.

The (BHAR) Buy and Hold Abnormal Return is used to explain the long term effect of acquisition . The BHAR explain that the investor buying the share of the acquiring firm will be enjoying if the acquiring company improves profit after merger and acquisition.

Three different event window have been defined for the purpose of examining long term wealth creation effect of merger with length of 1 year, 2 year and 3 year holding period during post merger period.

For the first year after the event, Abbott, Cipla, Novartis India, Piramal, Lupin and Suven life sciences ltd have shown positive returns of 0.06%, 0.003%, 0.10%, 0.01%, 0.18%, 0.06% respectively. With varying amount of standard deviation indicating that holding the share of

Table 6. Calculation of CAR (%) of the Pharmaceutical Companies during Pre and Post Announcement Window Period

Name of the Company Pre Announcement Post Announcement

t-30 t-15 t-5 T+5 T+15 T+30

Abbott Laboratories 0.28 0.58 2.11 -1.00 0.16 -0.19

Cipla Ltd/India -0.29 -0.29 0.60 -0.81 -0.41 -0.10

NOVARTIS -0.29 -0.47 -0.42 0.21 0.06 -0.09

Strides Arcolab Ltd -0.09 0.26 0.24 0.22 -0.24 -0.42

PIRAMAL 0.20 -0.02 -0.52 0.39 0.72 0.84

Lupin Ltd -0.60 -1.01 -1.22 -0.15 -0.32 -0.15

Suven Life Sciences Ltd -0.05 -0.79 0.07 -0.60 -0.90 -0.58

Bliss GVS Pharma Ltd 0.76 1.60 2.16 0.08 -0.89 -0.96

Ranbaxy Laboratories Ltd 0.23 -0.16 0.81 -1.31 -0.56 -0.41

Sun Pharmaceutical Industries Ltd -0.13 -0.36 -0.04 -0.56 0.10 0.16

Table 7: BHAR of Pharmaceutical Companies After Post-Acquisition Period

Name of the Company Holding Period after Merger and Acquisition

Holding BHAR Standard Standard t-statistics Period (Years) Deviation Error

Abbott Laboratories 1 0.060 2.07 0.13 -0.07

2 0.050 1.86 0.08 -0.03

3 0.002 1.65 0.06 -0.06

Cipla Ltd/India 1 0.003 1.39 0.09 -0.08

2 0.030 1.46 0.07 -0.03

3 0.030 1.46 0.05 -0.02

Novartis AG 1 0.100 1.80 0.11 -0.01

2 0.005 1.70 0.08 -0.07

3 -0.070 1.72 0.06 -0.13

Strides Arcolab Ltd 1 -0.370 3.44 0.22 -0.59

2 -0.280 3.67 0.17 -0.44

3 -0.060 3.46 0.13 -0.19

Piramal Enterprises Ltd 1 0.010 2.15 0.14 -0.12

2 0.010 1.99 0.09 -0.08

3 0.020 1.92 0.07 -0.05



the event. Any shift in the stock price caused by the event will happen immediately due to rational behavior which talks in favour of short event window since a long window could risk diluting the possibility if finding any significant evidence, however if the event window is too short the effect of the event if the information comes out only after closing of the market and therefore, does not reach the public and in some cases the information is leaked day before announcement date and therefore, causes effect before the actual date. Therefore, the period needs to be long enough to measure the returns

The pre and post acquisition period of CARs are analyzed in order to examine the impact of acquisition on the shareholders wealth of selected Pharmaceutical companies in India. The results show that Piramal Enterprises Ltd did not have any negative impact on CAR values for all post announcement window periods signifying that the company was successful in adding value to their shareholders wealth. In case of Sun Pharmaceuticals which had given negative returns in all the pre window period has resulted in positive in the positive returns in the post period. But in case of Ranbaxy Laboratories Ltd which had given positive returns in the pre period resulted in negative retuns in the post period.

As can be observed from the Table 6 for the window period t-5, four companies have negative CAR values in the pre announcement period and five companies have negative CAR in the post announcement period. The CAR value in case of Novartis India which was negative (-0.42) in the pre announcement period have shown positive results in the post-announcement period (0.21%). Suven life science

which had positive return (0.07%) has shown negative returns in the post announcement period (-0.6%).

Strides Arcolab Ltd and Bliss GvsPharma Ltd which had given positive returns has resulted in the negative returns in the post announcement period. When it comes to piramal it has given positive returns.

The 30 days window period is the longest window period of the study. It shows the long term impact on the shareholders return to the announcement of acquisition. In this period the companies like Abbott Laboratories, Bliss GVS Pharma Ltd, Ranbaxy Laboratories Ltd has shown the negative returns. On the other hand, the companies like Sun Pharmaceutical which had given the negative returns of -0.13% has resulted in positive returns of 0.16%. Piramal which had given the returns of 0.20% in the pre announcement period has resulted to incredible returns of 0.84% in the post-announcement period.

7. Impact of Acquisition on Long Term Share Price Performance.

The long term effect of acquisition on share prices of acquirers is studied using Buy and Hold Abnormal Returns (BHAR) methodology. To study the long term wealth creation effect of acquisition BHAR methodology has been used. The BHAR essentially indicates the excess returns over the industry average that an investor buying the shares of acquiring firm will be enjoying if he makes the purchase of those shares after acquisition.

Three different event windows have been constructed for the purpose of examining long term wealth creation effect

of mergers with length of 1 year, 2 year and 3 year holding period during post merger period. The BHAR over the relevant event window is then computed by following the standard model given below:-

………………(3)

Where, BHARi is abnormal returns due to buy and hold of shares of sample acquirer firm, Ri,t is the raw weekly return on share prices of acquirer firm (i) for period t, Rbenchmark , t is the weekly return on benchmark index for period t. It essentially implies that the cumulative returns on share of acquiring company are computed by compounding the weekly returns on the acquiring company's returns during the selected event window or holding period. The Benchmark index selected for the purpose of calculation of BHAR are the nifty relevant to a given acquirer in the sample. The selection of index is more appropriate as the long term abnormal returns are computed in comparison to industry average returns. Finally, the average buy and hold returns across the portfolio of acquirer companies in

a given sector during a holding period T is computed as:

………………(4)

Where N is the total number of acquirer companies in the sample.

The (BHAR) Buy and Hold Abnormal Return is used to explain the long term effect of acquisition . The BHAR explain that the investor buying the share of the acquiring firm will be enjoying if the acquiring company improves profit after merger and acquisition.

Three different event window have been defined for the purpose of examining long term wealth creation effect of merger with length of 1 year, 2 year and 3 year holding period during post merger period.

For the first year after the event, Abbott, Cipla, Novartis India, Piramal, Lupin and Suven life sciences ltd have shown positive returns of 0.06%, 0.003%, 0.10%, 0.01%, 0.18%, 0.06% respectively. With varying amount of standard deviation indicating that holding the share of

Table 6. Calculation of CAR (%) of the Pharmaceutical Companies during Pre and Post Announcement Window Period

Name of the Company Pre Announcement Post Announcement

t-30 t-15 t-5 T+5 T+15 T+30

Abbott Laboratories 0.28 0.58 2.11 -1.00 0.16 -0.19

Cipla Ltd/India -0.29 -0.29 0.60 -0.81 -0.41 -0.10

NOVARTIS -0.29 -0.47 -0.42 0.21 0.06 -0.09

Strides Arcolab Ltd -0.09 0.26 0.24 0.22 -0.24 -0.42

PIRAMAL 0.20 -0.02 -0.52 0.39 0.72 0.84

Lupin Ltd -0.60 -1.01 -1.22 -0.15 -0.32 -0.15

Suven Life Sciences Ltd -0.05 -0.79 0.07 -0.60 -0.90 -0.58

Bliss GVS Pharma Ltd 0.76 1.60 2.16 0.08 -0.89 -0.96

Ranbaxy Laboratories Ltd 0.23 -0.16 0.81 -1.31 -0.56 -0.41

Sun Pharmaceutical Industries Ltd -0.13 -0.36 -0.04 -0.56 0.10 0.16

Table 7: BHAR of Pharmaceutical Companies After Post-Acquisition Period

Name of the Company Holding Period after Merger and Acquisition

Holding BHAR Standard Standard t-statistics Period (Years) Deviation Error

Abbott Laboratories 1 0.060 2.07 0.13 -0.07

2 0.050 1.86 0.08 -0.03

3 0.002 1.65 0.06 -0.06

Cipla Ltd/India 1 0.003 1.39 0.09 -0.08

2 0.030 1.46 0.07 -0.03

3 0.030 1.46 0.05 -0.02

Novartis AG 1 0.100 1.80 0.11 -0.01

2 0.005 1.70 0.08 -0.07

3 -0.070 1.72 0.06 -0.13

Strides Arcolab Ltd 1 -0.370 3.44 0.22 -0.59

2 -0.280 3.67 0.17 -0.44

3 -0.060 3.46 0.13 -0.19

Piramal Enterprises Ltd 1 0.010 2.15 0.14 -0.12

2 0.010 1.99 0.09 -0.08

3 0.020 1.92 0.07 -0.05



these companies was profitable. Rest of the companies have shown negative results the lowest was -0.03% of Bliss GVS Pharma Ltd followed by -0.10% of Ranbaxy Laboratories Ltd.

For the second year some of the companies which had recorded positive return during the first year have shown positive return also for the next year like Cipla. However, some companies have shown decline in the returns as compared to the previous year like Abbott Laboratories (from 0.06% to 0.05%), Novartis India, lupin Ltd.( from 0.18% to 0.13%), Suven Life Sciences (from 0.6% to -.0.03%) in the second year. On the other side, Bliss GVS Pharma Ltd which had negative return of -0.03% has given 0.31% return in the second year.

For the third year Abbott Laboratories, Cipla, Piramal Enterprises Ltd, Lupin Ltd continued to give positive returns. Novartis India returns decrease from 0.005% to -0.07%. Strides Arcolab Ltd further gave negative returns as compare to first two year. Returns from Lupin India increase as compare to the first two years. Bliss GVS Pharma Ltd showed decline in returns to 0.10% which was less compare to previous two years, Ranbaxy Laboratories Ltd also resulted in further negative returns as compare to first and second years.

8. Conclusion

The study aimed to understand the impact of the acquisition of the selected pharmaceutical companies by examining the financial performance by comparing the pre and post-acquisition performance. The study reveals that the some companies have already started gaining the benefit of the acquisition. But some of the companies have shown negative result which indicated that these companies have not actually benefited which might further impact the performance of the companies or these companies might get the benefit from the deal in the future time period.

The CAR (cumulative abnormal returns) which helps to understand the impact of the acquisition on the share price has shown positive result for Piramal Enterprises Ltd. On the other hand, it has shown negative results for rest of the three companies post acquisition window period. The other strategy that is used is the buy and hold abnormal return which evaluates whether holding the existing share in the post-acquisition period results in positive returns. The study reveals that most of the companies did not show the improved financial health during the post-acquisition period as compare to pre acquisition period. Also the study indicates that most of the sample companies were not able to generate value for the shareholders

It has been seen that the performance ratios of few companies have shown an increase in returns in post-acquisition period, rest have resulted in the decline. It appears that it requires longer period, exceeding three years, for realisation of actual benefits of acquisition. The decline might be because of the management differences and other factors which affect the working of the companies in the effective manner.

References

Chadamiya and Mital Menapara (2012). Financial performance of Indian BankingSectors during pre and post mergers and acquisitions, Journal of Applied Management and Investments,1(2)146-150

Hogarthy Thomas F (1970), The Profitability of Corporate Mergers, Journal of Busines, 43(3), 317-327

Jarrell Gregg A , James A Brickley and Jeffry M Netter ( 1988). The Market for Corporate Control: The Empiricaal Evidence Since 1980, Journal of Economic Perspectives, 2(1), 49-68

Jensen Michael C and Richard S Ruback (1983). The Market for Corporate Control: The Scientific Evidence, Journal of Financial Economics, 11(1-4), 5-50.

Lev Baruch and Gershon Mandelker (1972), The Macroeconomic Consequences of Corporate Mergers, Journal of Business, 45(1), 85-104

Mital Menapara and Vijay Pithadia A study on financial performance ofselected companies during pre-post merger and acquisition, ABHINAV,1(11), 192-198

Neena Sinha, Kaushik and Chaudhary .(2013). Measuring Post Merger and Acquisition Performance: An Investigation of Select Financial Sector Organizations in India” International Journal of Economics and Finance, 2(4)190-200

Neha Verma and Rahul Sharma (2014). Impact of Mergers & Acquisitions on Firms'Long Term Performance: A Pre & Post Analysis of the Indian Telecom Industry, International Journal of Research in Management & Technology ,4(1)11-19

McGowan and Zunaidha, A Note On The Effect Of M&A Announcements On Stock Price Behavior And Financial Performance Changes: The Case Of Arab Malaysian Bank Berhad And Hong Leong Bank Berhad, International Business & Economics Research Journal, 7(9), 21-26

Mahesh R. and Daddikar Prasad(2012). Post merger and Acquisition financial performance analysis : A case study of selected Indian Airline companies, International Journal of Engineering and Management,3(3),362-368

Ravenscraft David J and Scherer F.M, ( 1989), The Profitability of Mergers, International Journal of Industrial Organisation, 7(1), 101-116

Smith Abbie J (1990), Corporate Ownership Structure and Performance; The Case of Management Buyouts, Journal of Financial Economics, 27(1), 143-164

Websites:

http://www.ibef.org/

http://indiainbusiness.nic.in/newdesign/index.php?param=industryservices_landing/347/1

http://www.business.rediff.com

http://www.moneycontrol.com

http://www.way2wealth.com

Lupin Ltd 1 0.180 2.52 0.16 0.02

2 0.130 2.77 0.13 0.01

3 0.140 2.52 0.09 0.04

Suven Life Sciences Ltd 1 0.060 3.11 0.20 -0.13

2 -0.030 3.23 0.14 -0.18

3 -0.120 3.39 0.12 -0.25

Bliss GvsPharma Ltd 1 -0.030 3.69 0.23 -0.26

2 0.310 3.90 0.17 0.14

3 0.100 4.25 0.16 -0.06

Ranbaxy Laboratories Ltd 1 -0.100 3.07 0.19 -0.30

2 -0.050 3.50 0.16 -0.21

3 -0.010 3.00 0.11 -0.12

Sun Pharmaceutical Industries Ltd 1 -0.960 1.71 0.11 -1.07

2 -0.970 1.64 0.07 -1.04

3 -0.970 1.94 0.07 -1.04



these companies was profitable. Rest of the companies have shown negative results the lowest was -0.03% of Bliss GVS Pharma Ltd followed by -0.10% of Ranbaxy Laboratories Ltd.

For the second year some of the companies which had recorded positive return during the first year have shown positive return also for the next year like Cipla. However, some companies have shown decline in the returns as compared to the previous year like Abbott Laboratories (from 0.06% to 0.05%), Novartis India, lupin Ltd.( from 0.18% to 0.13%), Suven Life Sciences (from 0.6% to -.0.03%) in the second year. On the other side, Bliss GVS Pharma Ltd which had negative return of -0.03% has given 0.31% return in the second year.

For the third year Abbott Laboratories, Cipla, Piramal Enterprises Ltd, Lupin Ltd continued to give positive returns. Novartis India returns decrease from 0.005% to -0.07%. Strides Arcolab Ltd further gave negative returns as compare to first two year. Returns from Lupin India increase as compare to the first two years. Bliss GVS Pharma Ltd showed decline in returns to 0.10% which was less compare to previous two years, Ranbaxy Laboratories Ltd also resulted in further negative returns as compare to first and second years.

8. Conclusion

The study aimed to understand the impact of the acquisition of the selected pharmaceutical companies by examining the financial performance by comparing the pre and post-acquisition performance. The study reveals that the some companies have already started gaining the benefit of the acquisition. But some of the companies have shown negative result which indicated that these companies have not actually benefited which might further impact the performance of the companies or these companies might get the benefit from the deal in the future time period.

The CAR (cumulative abnormal returns) which helps to understand the impact of the acquisition on the share price has shown positive result for Piramal Enterprises Ltd. On the other hand, it has shown negative results for rest of the three companies post acquisition window period. The other strategy that is used is the buy and hold abnormal return which evaluates whether holding the existing share in the post-acquisition period results in positive returns. The study reveals that most of the companies did not show the improved financial health during the post-acquisition period as compare to pre acquisition period. Also the study indicates that most of the sample companies were not able to generate value for the shareholders

It has been seen that the performance ratios of few companies have shown an increase in returns in post-acquisition period, rest have resulted in the decline. It appears that it requires longer period, exceeding three years, for realisation of actual benefits of acquisition. The decline might be because of the management differences and other factors which affect the working of the companies in the effective manner.

References

Chadamiya and Mital Menapara (2012). Financial performance of Indian BankingSectors during pre and post mergers and acquisitions, Journal of Applied Management and Investments,1(2)146-150

Hogarthy Thomas F (1970), The Profitability of Corporate Mergers, Journal of Busines, 43(3), 317-327

Jarrell Gregg A , James A Brickley and Jeffry M Netter ( 1988). The Market for Corporate Control: The Empiricaal Evidence Since 1980, Journal of Economic Perspectives, 2(1), 49-68

Jensen Michael C and Richard S Ruback (1983). The Market for Corporate Control: The Scientific Evidence, Journal of Financial Economics, 11(1-4), 5-50.

Lev Baruch and Gershon Mandelker (1972), The Macroeconomic Consequences of Corporate Mergers, Journal of Business, 45(1), 85-104

Mital Menapara and Vijay Pithadia A study on financial performance ofselected companies during pre-post merger and acquisition, ABHINAV,1(11), 192-198

Neena Sinha, Kaushik and Chaudhary .(2013). Measuring Post Merger and Acquisition Performance: An Investigation of Select Financial Sector Organizations in India” International Journal of Economics and Finance, 2(4)190-200

Neha Verma and Rahul Sharma (2014). Impact of Mergers & Acquisitions on Firms'Long Term Performance: A Pre & Post Analysis of the Indian Telecom Industry, International Journal of Research in Management & Technology ,4(1)11-19

McGowan and Zunaidha, A Note On The Effect Of M&A Announcements On Stock Price Behavior And Financial Performance Changes: The Case Of Arab Malaysian Bank Berhad And Hong Leong Bank Berhad, International Business & Economics Research Journal, 7(9), 21-26

Mahesh R. and Daddikar Prasad(2012). Post merger and Acquisition financial performance analysis : A case study of selected Indian Airline companies, International Journal of Engineering and Management,3(3),362-368

Ravenscraft David J and Scherer F.M, ( 1989), The Profitability of Mergers, International Journal of Industrial Organisation, 7(1), 101-116

Smith Abbie J (1990), Corporate Ownership Structure and Performance; The Case of Management Buyouts, Journal of Financial Economics, 27(1), 143-164

Websites:

http://www.ibef.org/

http://indiainbusiness.nic.in/newdesign/index.php?param=industryservices_landing/347/1

http://www.business.rediff.com

http://www.moneycontrol.com

http://www.way2wealth.com

Lupin Ltd 1 0.180 2.52 0.16 0.02

2 0.130 2.77 0.13 0.01

3 0.140 2.52 0.09 0.04

Suven Life Sciences Ltd 1 0.060 3.11 0.20 -0.13

2 -0.030 3.23 0.14 -0.18

3 -0.120 3.39 0.12 -0.25

Bliss GvsPharma Ltd 1 -0.030 3.69 0.23 -0.26

2 0.310 3.90 0.17 0.14

3 0.100 4.25 0.16 -0.06

Ranbaxy Laboratories Ltd 1 -0.100 3.07 0.19 -0.30

2 -0.050 3.50 0.16 -0.21

3 -0.010 3.00 0.11 -0.12

Sun Pharmaceutical Industries Ltd 1 -0.960 1.71 0.11 -1.07

2 -0.970 1.64 0.07 -1.04

3 -0.970 1.94 0.07 -1.04



Our Contributors

Dr. Indranil Bose

Dean Business Studies, Western International College-Off shore campus of University of Bolton (UAE)

Sredharran Sampath

Associate Dean, Westford School of Management (UAE)

Dr. Tripti Barthwal, Professor, LBS Institute of Management & Development Studies, Lucknow

Dr. Akansha SrivastavaAssociate Professor, LBS Institute of Management & Development Studies, Lucknow

M. I. M. Loya, Research Scholar, Mechanical Engineering Department, NIT Raipur

A. M. RawaniProfessor, Mechanical Engineering Department, NIT Raipur

Raghav UpadhyaiAssistant Professor, IMS Unison University, Dehradun

Dr. H.S. Grewal Professor, Omkarananda Institute of Management and Technology, Rishikesh

Trilok Pratap Singh, Research Scholar, Department of Management, Jiwaji University, Gwalior

Dr. Somesh Dhamija, Professor, Institute of Business Management, GLA University, Mathura

Krishanveer SinghAssistant Professor, Institute of Business Management, GLA University, Mathura

Harsandaldeep Kaur, Assistant Professor, Department of Commerce, Guru Nanak Dev University, Amristsar

Nidhi SabharwalAssistant Professor, PG Department of Commerce and Business Administration, Khalsa College, Amritsar

Dr. Tarak Nath Shaw

Reddy Y V

Mayuresh Natekar

Associate Professor, IMS Unison University, Dehradun

Professor and Dean, Faculty of Commerce, Goa University, Goa

Mayuresh Natekar, PG Student, Department of Commerce, Goa University, Goa

Call for Papers for Pragyaan: Journal of Management

Pragyaan: Journal of Management (ISSN: 0974-5505) is a double blind refereed journal of IMS Unison

University (formerly Institute of Management Studies), Dehradun. The journal is dedicated to develop,

promote and coordinate theory, research, and practice in the areas of Management, in Indian as well as

global context. It aims at bringing together the academicians as well as practicing managers.

The University publishes conceptually sound articles and papers through this Journal, which have the potential

to enrich the existing management education, theory and practice. The papers could deal with research on

contemporary issues covering the fields of general management, corporate strategy, policy and governance,

finance, public policy, marketing, organisational behavior, production and operations management, retail

management, international business and other related areas of economics and social sciences including

macro as well as micro perspectives.

Our journal provides food for thought to the managers in public as well as the private sector, consultants,

academicians and students.

We invite research papers, case studies and book reviews on management related issues for our subsequent

issues. Empirical studies as well as sound conceptual and application oriented studies in the area of

Management are welcome.

The papers should be prepared as per the guidelines and submitted to the Editor, Pragyaan: Journal of

Management at [email protected].

Warm regards

Editor


IMS Unison University

Makkawala Greens, Mussoorie Diversion Road Dehradun,248009 Uttarakhand (India).

Phones: 91-135-3000873/874/600 Fax: 91-135-3000700

E-mail: [email protected]

Our Contributors

Dr. Indranil Bose

Dean Business Studies, Western International College-Off shore campus of University of Bolton (UAE)

Sredharran Sampath

Associate Dean, Westford School of Management (UAE)

Dr. Tripti Barthwal, Professor, LBS Institute of Management & Development Studies, Lucknow

Dr. Akansha SrivastavaAssociate Professor, LBS Institute of Management & Development Studies, Lucknow

M. I. M. Loya, Research Scholar, Mechanical Engineering Department, NIT Raipur

A. M. RawaniProfessor, Mechanical Engineering Department, NIT Raipur

Raghav UpadhyaiAssistant Professor, IMS Unison University, Dehradun

Dr. H.S. Grewal Professor, Omkarananda Institute of Management and Technology, Rishikesh

Trilok Pratap Singh, Research Scholar, Department of Management, Jiwaji University, Gwalior

Dr. Somesh Dhamija, Professor, Institute of Business Management, GLA University, Mathura

Krishanveer SinghAssistant Professor, Institute of Business Management, GLA University, Mathura

Harsandaldeep Kaur, Assistant Professor, Department of Commerce, Guru Nanak Dev University, Amristsar

Nidhi SabharwalAssistant Professor, PG Department of Commerce and Business Administration, Khalsa College, Amritsar

Dr. Tarak Nath Shaw

Reddy Y V

Mayuresh Natekar

Associate Professor, IMS Unison University, Dehradun

Professor and Dean, Faculty of Commerce, Goa University, Goa

Mayuresh Natekar, PG Student, Department of Commerce, Goa University, Goa

Call for Papers for Pragyaan: Journal of Management

Pragyaan: Journal of Management (ISSN: 0974-5505) is a double blind refereed journal of IMS Unison

University (formerly Institute of Management Studies), Dehradun. The journal is dedicated to develop,

promote and coordinate theory, research, and practice in the areas of Management, in Indian as well as

global context. It aims at bringing together the academicians as well as practicing managers.

The University publishes conceptually sound articles and papers through this Journal, which have the potential

to enrich the existing management education, theory and practice. The papers could deal with research on

contemporary issues covering the fields of general management, corporate strategy, policy and governance,

finance, public policy, marketing, organisational behavior, production and operations management, retail

management, international business and other related areas of economics and social sciences including

macro as well as micro perspectives.

Our journal provides food for thought to the managers in public as well as the private sector, consultants,

academicians and students.

We invite research papers, case studies and book reviews on management related issues for our subsequent

issues. Empirical studies as well as sound conceptual and application oriented studies in the area of

Management are welcome.

The papers should be prepared as per the guidelines and submitted to the Editor, Pragyaan: Journal of

Management at [email protected].

Warm regards

Editor



Makkawala Greens, Mussoorie Diversion Road Dehradun,248009 Uttarakhand (India).

Phones: 91-135-3000873/874/600 Fax: 91-135-3000700


Guidelines for Contributors

1. Manuscripts for publication should be typed in double space with a margin of 1.5 inches on both sides

to facilitate editing, only on one side of the paper and sent in duplicate to the Editor along with a soft

copy in the format of 12 point text single font- Times Roman and package preferably MS Word for

Editorial convenience. All articles should include an abstract of about 150 words, and a few key

words.

2. Each manuscript should be accompanied by a declaration of the author that the paper has neither

been published nor submitted for publication elsewhere.

3. Articles which are published should not be reproduced or reprinted in any form either in full or in part

without the prior permission of the editor.

4. Wherever copyrighted material is used, the authors should be accurate in reproduction and obtain

permission from the copyright holders, if necessary.

5. Papers submitted or presented in a seminar must clearly indicate this fact at the bottom of the first

page.

6. Notes and references should be consecutively numbered and presented at the end of the article on

separate sheets of paper, and not at the foot of each page.

7. The articles can fall into any one of the following types: research based articles on management (with

executive summaries), case studies, book reviews, letters to the editors, or interviews with

academicians/gurus/CEOs.

8. Footnotes, typed in single-space, should be numbered serially and placed at the end of the text.

Reference to literature cited should be carried within the text in brackets. The references, to be placed

after footnotes, should be listed alphabetically by author and chronologically for each author, and

should follow APA style of referencing as shown below.

Khainh, N. T. & Hau, L. N. (2009). Mobile Advertising; The Influence of Emotional Attachment to

Mobile Devices on Consumer Receptiveness. Journal of Marketing Communications, Vol.15, No. 4,

pp. 267-280..

9. Contributors are advised to be brief in introducing the subject and devote most of the paper to the

principal theme. The Journal prefers papers based on original data and fresh theoretical insights.

References to previous works should be made economically. The Journal does not publish survey of

literature comprising lengthy bibliographical references.

10. Present each figure and table on a separate sheet of paper. All tables must be consecutively numbered

using Arabic numerals with appropriate titles.

11. Write numbers in figures (rather than words) for exact measurement and series of quantities, including

percentages. Use thousands and millions rather than lakhs and crores.

12. Book review must contain the name of the author and the book reviewed, place of publication and

publisher, date of publication, number of pages and price.

13. A brief resume of the author/s should accompany the research articles.

14. Manuscripts are accepted for publication on the understanding that they are subject to editorial

revisions. Proofs will not be sent to the authors.

15. Authors will receive a complimentary copy of the journal.

16. All manuscripts should be addressed to:

The Editor



Makkawala Greens, Mussoorie Diversion Road

Dehradun,248009 Uttarakhand (India).

Phones: 91-135-3000873/874/600 Fax: 91-135-3000700


The Editor



Makkawala Greens,

Mussoorie – Diversion Road, Dehradun

Pin-248009, Uttarakhand

Ph: (M) (Editor) - 91-135-3000873/600

Fax: +91-135-3000700

Sir,

Sub: Assignment of Copyright

I/We,_____________________________________________________________________, author(s) of the article

entitled______________________________________________________________________________

do hereby authorize you to publish the above said article in Pragyaan: Journal of Management.

I/We further state that:

1) The Article is my/our original contribution. It does not infringe on the rights of others and does not contain any libelous

or unlawful statements.

2) Wherever required I/We have taken permission and acknowledged the source.

3 The work has been submitted only to this journal Pragyaan: Journal of Management and that it has not been

previously published or submitted elsewhere for publication.

I/We hereby authorize, you to edit, alter, modify and make changes in the Article in the process of preparing the

manuscript to make it suitable for publication.

I/We hereby assign all the copyrights relating to the said Article to the IMS Unison University, Dehradun.

I/We have not assigned any kind of rights of the above said Article to any other person/Publications.

I/We agree to indemnify the IMS Unison University, Dehradun against any claim or action alleging facts which, if true,

constitute a breach of the foregoing warranties.

First author Second author Third author

Name: Name: Name:

Signature: Signature: Signature:

Guidelines for Contributors

1. Manuscripts for publication should be typed in double space with a margin of 1.5 inches on both sides

to facilitate editing, only on one side of the paper and sent in duplicate to the Editor along with a soft

copy in the format of 12 point text single font- Times Roman and package preferably MS Word for

Editorial convenience. All articles should include an abstract of about 150 words, and a few key

words.

2. Each manuscript should be accompanied by a declaration of the author that the paper has neither

been published nor submitted for publication elsewhere.

3. Articles which are published should not be reproduced or reprinted in any form either in full or in part

without the prior permission of the editor.

4. Wherever copyrighted material is used, the authors should be accurate in reproduction and obtain

permission from the copyright holders, if necessary.

5. Papers submitted or presented in a seminar must clearly indicate this fact at the bottom of the first

page.

6. Notes and references should be consecutively numbered and presented at the end of the article on

separate sheets of paper, and not at the foot of each page.

7. The articles can fall into any one of the following types: research based articles on management (with

executive summaries), case studies, book reviews, letters to the editors, or interviews with

academicians/gurus/CEOs.

8. Footnotes, typed in single-space, should be numbered serially and placed at the end of the text.

Reference to literature cited should be carried within the text in brackets. The references, to be placed

after footnotes, should be listed alphabetically by author and chronologically for each author, and

should follow APA style of referencing as shown below.

Khainh, N. T. & Hau, L. N. (2009). Mobile Advertising; The Influence of Emotional Attachment to

Mobile Devices on Consumer Receptiveness. Journal of Marketing Communications, Vol.15, No. 4,

pp. 267-280..

9. Contributors are advised to be brief in introducing the subject and devote most of the paper to the

principal theme. The Journal prefers papers based on original data and fresh theoretical insights.

References to previous works should be made economically. The Journal does not publish survey of

literature comprising lengthy bibliographical references.

10. Present each figure and table on a separate sheet of paper. All tables must be consecutively numbered

using Arabic numerals with appropriate titles.

11. Write numbers in figures (rather than words) for exact measurement and series of quantities, including

percentages. Use thousands and millions rather than lakhs and crores.

12. Book review must contain the name of the author and the book reviewed, place of publication and

publisher, date of publication, number of pages and price.

13. A brief resume of the author/s should accompany the research articles.

14. Manuscripts are accepted for publication on the understanding that they are subject to editorial

revisions. Proofs will not be sent to the authors.

15. Authors will receive a complimentary copy of the journal.

16. All manuscripts should be addressed to:

The Editor



Makkawala Greens, Mussoorie Diversion Road

Dehradun,248009 Uttarakhand (India).

Phones: 91-135-3000873/874/600 Fax: 91-135-3000700


The Editor



Makkawala Greens,

Mussoorie – Diversion Road, Dehradun

Pin-248009, Uttarakhand

Ph: (M) (Editor) - 91-135-3000873/600

Fax: +91-135-3000700

Sir,

Sub: Assignment of Copyright

I/We,_____________________________________________________________________, author(s) of the article

entitled______________________________________________________________________________

do hereby authorize you to publish the above said article in Pragyaan: Journal of Management.

I/We further state that:

1) The Article is my/our original contribution. It does not infringe on the rights of others and does not contain any libelous

or unlawful statements.

2) Wherever required I/We have taken permission and acknowledged the source.

3 The work has been submitted only to this journal Pragyaan: Journal of Management and that it has not been

previously published or submitted elsewhere for publication.

I/We hereby authorize, you to edit, alter, modify and make changes in the Article in the process of preparing the

manuscript to make it suitable for publication.

I/We hereby assign all the copyrights relating to the said Article to the IMS Unison University, Dehradun.

I/We have not assigned any kind of rights of the above said Article to any other person/Publications.

I/We agree to indemnify the IMS Unison University, Dehradun against any claim or action alleging facts which, if true,

constitute a breach of the foregoing warranties.

First author Second author Third author

Name: Name: Name:

Signature: Signature: Signature:

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Documents

Volume 13, Issue 2, December 2015 - IMS Unison …pragyaanmanagement.iuu.ac/upload_dynamic_content/2015...Professor T. J. Kamlanabhan DMS IIT, Madras Dr. S. P. Kala Professor (Retd.),