Structuring Latent Nature of Planning Competencies of Business Operators and Its Impact on Business Performance: Evidence from Sri Lanka

Kengatharan. N / IJAR-BAE, 02, 02 (2013) 01–13

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International Journal of Applied Research in

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ISSN: 1839-8456 Perth, Australia


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CChhiieeff,, EEddiittoorriiaall BBooaarrdd Md. Abdul Hannan Mia, PhD

EEddiittoorriiaall BBooaarrdd MMeemmbbeerrss Shaokun Coral Yu, PhD Northern Illinois University, USA Dr. Iqbal Hossain, Post-Doc in Econometrics, Imperial College, UK M Kabir Hassan, PhD University of New Orleans, USA Md. Abdul Hannan Mia, PhD University of Dhaka, Bangladesh & University of Toronto, Canada. Md. Shariat Ullah University of Dhaka, Bangladesh & Ritsumaiken University, Japan. Saalem Sadeque University of Western Australia, Australia. Rami M. Ayoubi, PhD Damascus University, Syria Ondrej Zizlavsky PhD Brono University of Technology, Czech Republic Rarshid Mehrdoust, PhD University of Guilan, Iran Md. Moazzam Hossain Curtin University, Australia Jai Ganesh PhD Infosys Labs, Bangalore, India Md. Mohan Uddin, PhD University Utara Malaysia, Malaysia Mahfuja Malik University of Boston, USA Md. Anisur Rahman University of Dhaka, Bangladesh. Md. Mamun Habib, PhD, AIUB, Bangladesh Kazi Sohag, UKM, Malaysia Fazeela Jameel Ahsan, PhD University of Colombo, Sri Lanka Rajeshkumar U. Sambhe, PhD Jawaharalal Darda Institute of E&T, India.

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Kengatharan. N1* 1

Lecturer in Business Administration, University of Jaffna, Sri Lanka. * Corresponding author’s e-mail:

[email protected]

Article History ABSTRACT

Received: 23-02-2013 Accepted: 29-03-2013 Available online: 22-04-2013

Keywords: Planning Competencies, Business Performance, Small-scale Enterprise.

JEL Classification: M130, M160

Planning crafts of business operators into their business is identified as predominant latent variable which effectuate in flourishing business performance. All successful planning competencies found to be effect in some countries would not be effective in another country due to the environment milieu in which business operates. The purpose of this paper is to twofold: structuring planning competencies of business operators and investigating its impact on performance of small-scale enterprises operating in Sri Lanka. Self reported deliver collection questionnaire have been employed to collect the required data for this study. Subjects consisted of 156 business operators from 11 different small business sectors where convenient sampling techniques was adopted within the cross sectional research design. Exploratory factor analysis produced three factors solution: Goal setting, information seeking, systematic planning and monitoring. Results revealed that 51.8 % of the total variance in business performance was explained by all three factors of planning competencies. This study would support for micro finance institutions, training institution, and other funding organizations in screening and selecting business operators and to fine grain their potential.

Citation: Kengatharan. N (2013). Structuring Latent Nature of Planning Competencies of Business Operators and Its Impact on Business Performance: Evidence from Sri Lanka, IJAR-BAE 2(2): 01 – 13.

Copyright: @2013 Kengatharan. N. This is an open access article distributed according to the terms of the Creative Common Attribution (CCC) 3.0 License under PKP (Public Knowledge Project) of Simon Fraser University, Canada.

1.0 Introduction Small and medium sized enterprises (SMEs) have been identified to play a crucial role in the economic development process by developed as well as developing countries. It is said to be the backbone of the economies in developing as well as developed nations (Gamage, 2000). It is even more important to developing countries as the poverty and unemployment are burning problems in those economies. Research has shown that in Sri Lanka 68% of the small business fail within the first 2-5 years of operation (Mendis, Seneviratne & Nanayakkara, 1999). In the United States of America the rate of failure is as high as 80% (Mendis et al, 1999). In the European Economic Community Countries out of every 1000 small businesses only 4 will service for more than 10 years from the start (Mendis et al, 1999). Why do such a large number of small firms fail each year? Therefore, it is important to identify the causes of failures as well as the success of small enterprises. Success of enterprises can be measured by performance of an organization.

IJAR-BAE Vol. 02. Issue 02. Article No. 01

Full-length Original Open Access Research Paper


International Journal of Applied Research in Business Administration and Economics 02, 02 (2013) 01–13



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The success of the organizational performance and development are in the hands of the business operator of the particular business venture. Since the business operators should have a reasonable knowledge, skills and capacity to achieve with the pre determined targets through the workers in his or her business venture while they have full characteristics as suited for an entrepreneur and utilized his/her knowledge, skills and abilities in the business. Researcher interest is on entrepreneurial competencies as a source of business success. This research was created by the basic question of how significantly influence the planning competencies of business operators’ on their business performance and what factors of planning competencies are mostly influence on business performance. The objective of this study is twofold: structuring planning competencies of business operators and investigating its impact on performance of small-scale enterprises operating in Sri Lanka. 2.0 Literature review and hypothesis development

2.01 Concept of entrepreneurship Generally, "entrepreneurship" means the ability to work harder and more effectively than competitors, or the ability to create, maintain and develop a profit-making organization (Eagly, 2005)."Entrepreneur", on the other hand is broadly defined as an organizer of an economic enterprise; a person who has the spirit of creativity, owns and manages an enterprise, and bears the risks associated with it (Mavin, Bryans, & Waring, 2004).

2.02 Entrepreneurial competencies Competencies are seen as behavioral and observable characteristic of an entrepreneur. Consequently, competencies are changeable and learnable, allowing multi method empirical studies including quantitative approaches to measurement (Bird, 1989). Skills and competencies have taken much concern of researchers at past and present in view of success of entrepreneurs. According to Kuznetsov, McDonald and Kuznetsova (2000) entrepreneurial competencies and their interaction with strategy and industry structure have become increasingly looked upon as principal factors determining the success of new ventures. Monk (2000) examined the causes of small business failures in Canada, failure rate of small businesses; Business skills needed by small-business owners to succeed and suggests that there are several important business skills that small to medium-sized enterprises (SMEs) must have to succeed. These include business planning, financial planning, operational management and control, financial management planning and control, human resource management, awareness of knowledge management, and an interest in e-commerce. A factor analytic study of the perceived causes of small business failure done by Gaskill Auken and Manning (1993) identifies managerial and planning functions as one of four main areas often contributed to business failures. Man and Lau (2000) detailed seven competency areas and several clusters with examples of component behaviors through their qualitative analysis of entrepreneurial competencies of SME owner/managers in the Hong Kong services sector. The identified competency areas are Opportunity competencies (identify, assess and seek), Relationship competencies (build and keep network and relationships, use networks and relationships, build and keep trust and confidence, use trust and confidence, expose to the media, communicate, negotiate, manage conflicts, build consensus), Conceptual competencies (think intuitively, view from different angle, innovate, assess risks), Organizing competencies (plan, organize, lead, motivate, delegate, control), Strategic competencies (vision, set and evaluate goals, use scope and capabilities, make strategic change, set and evaluate position, move ahead to set goals, use tactics, Budget for strategy, Control strategic outcomes), Commitment competencies (sustain effort, commit to long-term goals, devote to work, commit to staff, commit to beliefs and values, commit for personal goals, Re-start after failure) and supporting competencies (learn, adapt, manage time, evaluate oneself, balance life, manage worries and hold on to integrity).

2.03 Organizational performance Firm performance is a complex and multidimensional construct (Chandler & Hanks, 1993). Therefore, the use of multiple indicators to gauge new venture performance has been recommended by several researchers (Zahra, Newbaum,& El-Hagrassey 2002). Sales growth rate was measured in the same



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manner as in several previous studies (Amason, Shrader, & Tompson, 2006; Covin, Green & Slevin, 2006). Growth rate in profit, a second measure, has been widely used in past research (Chandler & Hanks, 1993; Wiklund & Shepherd, 2005). A third measure, employment growth rate, has been also used in previous research as an indicator of new venture performance (Wiklund & Shepherd, 2005). The most common non-financial measures adopted by the SMEs are number of employees (Orser, Hogarth-Scott & Riding, 2000; Robinson & Sexton, 1994), growth in revenue across time, market share and revenue per employee (Johannisson, 1993).

2.04 Relationship between entrepreneurial competencies and business performance Competency is one of most crucial factors to ensure the success of business ventures (Grove, 1996). The entrepreneurs faced even greater challenge when they have successfully bring their organizations to growth and as the company moves into this stage, it experienced what observers refer to as strategic reflection point (Grove, 1996). Entrepreneurs who have the necessary competencies especially in the area of operations, finance, marketing and human resources, and management skills required for the business are more likely to be successful at start-up (Swiercz & Spencer, 1992). Areas of competency have been greatly researched in most developed countries, and most literature revealed that they are positively related to companies at venture growth. Entrepreneurial competencies to serve as a bridge between individual level characteristics and firm performance (Bautista,Barlis & Nazario, 2007). Based on the past researches, this study is going to examine the impact of planning competencies on business performance. Therefore based on the literature survey following hypothesis is formulated H1: Planning competencies as a composite as well as its dimensions have positive significant relations with business performance. Moreover, the above hypothesis associated with the following two hypotheses: H1.1: Planning competencies as a composite has positive significant relations with business performance. H1.2: Dimensions of planning competencies have positive significant relations with business performance.

3.0 Research methodology 3.01 Sample Stratified random sample of 68 business operators was selected from the 11 different types of small scale enterprises in Vavuniya district. Out of 68 sample entrepreneurs, 56 participants were responded to the study, 5 participants did not responded and 7 enterprises had been dropped out from business activities during the last two years period.

3.02 Data sources Primary and secondary data were used for the study. Primary data were collected through the questionnaire survey following direct personal interviewing technique and direct observation and the secondary data was collected through the books, magazine, records, journals, selected enterprises’ records and etc.

3.03 Instrumentation The structured questionnaire was used to collect the data. The questionnaire was divided into Part I, Part II and Part III. Part I of the questionnaire consisting 15 facts related to planning competencies was used to measure the planning competencies. Part II questionnaire consisted of 20 questions to get information related to performance indicators. Using a modified instrument developed by the Gupta and Govintharajan, Dess and Robinson (1984). Subjective measures were used to measure the organizational performance in this study. Subjective measures which are perceptions collected from and stakeholders (Campbell, 1977). For the Part I and II of the questionnaire a 5-point Likert scale was used. Part III of the questionnaire was used to get general idea and background of their business.



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3.04 Reliability of the scales To establish reliability of the questionnaire, pilot test was conducted with a 30 convenience sample of business operators of small scale industries in Vavuniya district. The Cronbach’s alpha was used to measure of reliability random errors. The reliability coefficient of all items of planning competencies was 0.778 and indicators of business performance were 0.843 which indicated the high reliability (Gliner & Morgan, 2000). Therefore, questionnaire was taken as an acceptable instrument to be administered.

4.0 Results and discussions

4.1 Identifying the factors A principal components analysis for identify the items of planning competencies and indicators of business performance was performed. However, before using the factor analysis, a number of initial tests were conducted to determine the suitability of our data for such an analysis. Here Bartlett’s test of sphericity and the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy (George & Mallery, 2003) were used. Both of these tests can be used to determine the factorability of the matrix as a whole. If Bartlett’s test of sphericity is large and significant, and if the KMO measure is greater than 0.5, then factorability is assumed. For the factors of planning competencies, as presented in Table 2 a measure of sampling adequacy value of 0.733 and a large value of Bartlett’s test of sphericity (361.432 and df = 105) at a high level of significance (p < .000) indicated that a principal component analysis would be useful. As Table 3 the three factor solution suggested by the eigen values greater than one criterion explained 58% of the variance in the data to confirm that the factor analysis is valid (Kasier, 1958).

Table 02: KMO and Bartlett’s test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.

0.733

Bartlett's Test of Sphericity Approx. Chi-Square 361.432

df 105.000

Sig. 0.000 Source: Survey

Enterprises

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Manufacture of Bakery Products 33 14 11 02 01 32 42.40 Rice and Grinding Mill 44 20 15 02 02 42 45.45 Manufacture of Agricultural Machinery Products, Lathe and Welding Work

07 05 04 - 01 06 71.42

Manufacture of Food Products and Confectionery Items

11 07 07 - - 11 63.64

Manufacture of Soft Drinks Products 03 03 03 - - 03 100 Production of Iron & Wooden Furniture/ Carpentry Works

07 04 04 - - 07 57.14

Manufacture of Stone Quarrying, Clay and Sand Pits

01 01 01 - - 01 100

Manufacture of Jewelers Related Articles 11 06 03 - 03 08 33.33 Tailoring Works and Beauty Centers 06 04 04 - - 06 54.54 Printing Works and Communication 02 02 02 - - 02 100 Garage, Repairing works & Service Station

02 02 02 - - 02 100

Total 127 68 56 05 07 120 53.54 Table 01 : Population and sample profile



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Factor loadings were greater than 0.50 were considered significant (Tharmaseelan, 2005) and thus the larger the absolute size of the factor loading, the more important the loading in interpreting the factor matrix. When the original 15 items were analyzed by the principal component factor analysis with varimax rotation a three factor emerged. The factor loadings have ranged from 0.842 to 0.515 with communalities of ranged from 0.799 to 0.462.

The internal consistency of the items used to measure each factor was calculated using Cronbach’s alpha, Factor 1: This factor was represented by five items, was named goal setting accounted for the amount of variance 33.41%. Factor loadings of this variable ranged from 0.842 to 0.515. Factor 2: This factor was represented by five items, was named information seeking accounted for the amount of variance 14.36%. They carried factor loadings ranged from 0.835 to 0.535. Factor 3: This factor was represented by five items, was named systematic planning and monitoring accounted for the amount of variance 10.45%. Factor loadings of this variable ranged from 0.781 to 0.558. The internal consistency of the items used to measure each factor was calculated using Cronbach’s alpha, which is the procedure of choice for investigating the internal consistency of items using Likert-type scale (Walsh & Betz, 1995 cited in Tharmaseelan, 2005). Cronbach’s alpha for each factor: factor 1, factor 2, and factor 3 were 0.732, 0.811, and 0.757, respectively which results of reliability analysis confirmed that consistency is at an acceptable level for each factor. For the factors indicating business performance, as

Table 03: Principal components analysis - Varimax rotation factors indicating to the planning competencies

Factor 1

Factor 2

Factor 3

I would like to think about the future

0.785

It's a waste of time to think about those which have to be done in the life

0.535 The more specific I can be about what I want out of life, the more chance I have to succeed

0.660

I have a very clear plan for my life

0.567

In achieving my yearly objectives I pay attention in my weekly objectives

0.835 When I venture into a new task or a new project, I collect relevant information in a great deal. 0.666

I seek the advice of people who know a lot about the tasks I'm working on 0.801

I take action without wasting much time in gathering information 0.515

When I am engaged in others tasks, in order to confirm that I have understand their wishes, I ask many questions. 0.746

I seek several different sources to get information to support the tasks and projects 0.842

I plan a large project by breaking it down into smaller tasks

0.622 I think about the advantages and disadvantages or different ways of accomplishing the tasks

0.781

I try to think of all the problems I may encounter and plan what to do if each problem occurs.

0.676

I deal with problems as they arise rather than spend time to anticipate them

0.558 In dealing with a particular problem when an approach is not successful. I think about another approach.

0.770

Eigen Value 5.012 2.153 1.567

Proportion of Variance Explained 33.41 14.36 10.450

Cumulative Variance Explained 33.41 47.77 58.220

Alpha 0.732 0.811 0.757

Source: Survey data Factor 1: This factor was represented by five items, was named goal setting accounted for the amount of variance 33.41%. Factor loadings of this variable ranged from 0.842 to 0.515. Factor 2: This factor was represented by five items, was named information seeking accounted for the amount of variance 14.36%. They carried factor loadings ranged from 0.835 to 0.535. Factor 3: This factor was represented by five items, was named systematic planning and monitoring accounted for the amount of variance 10.45%. Factor loadings of this variable ranged from 0.781 to 0.558.



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presented in Table 4 a measure of sampling adequacy value of .637 and a large value of Bartlett’s test of sphericity (642.708 and df = 190) at a high level of significance (p < .000) indicated that a principal component analysis would be useful. After being varimax rotated to obtain a simple structure the five-factor solution gave a clear factor structure. Table-5 shows the results of the principal components analysis

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.637

Bartlett's Test of Sphericity Approx. Chi-Square 642.708

df 190.000

Sig. 0.000 Table 04: KMO and Bartlett’s test

Source: Survey data

Table 05: Principal components factor analysis - Varimax rotation factors indicating to the performance of small

scale industries (Source: Survey Data)

Factor 1

Factor 2

Factor 3

Factor 4 Factor 5

Satisfaction in Business Growth including Achievement of Business Goal

0.670

Improvement in Life Standard after the business

0.833 Growth in Personal Income from the beginning of business

0.599

Improvement in Income Level when comparing before and after the business

0.511

Improvement in saving capacity and accumulation of resources from the business

0.437

Growth on net profit earnings from the business over the past five years

0.554

Improvement in Return on Investment (ROI) from the business over the past five years

0.864

Improvement in Return on Assets (ROA) from the business over the past five years

0.898

Growth in turnover/sales from the business over the past five years

0.754

Growth in turnover compared to the competitors over the past five years

0.613

Increasing in no. of employees from the beginning of business

0.816

Ability of industries to keep the organization's best and most talented people

0.745

Level of customer satisfaction related to business activities 0.791 Conducting survey to measure satisfaction of the customers

and carry out the necessary changes 0.767 The market coverage of business enterprises 0.549 Increasing the no. of customers from the beginning of

business 0.700 Overcoming the actions of the competitors over the past 5

years 0.457 Achievement at business growth by facing the

environmental challenge & strong competition 0.690 Organization enhance organizational performance by being

attentive to external changes & leading internal changes in structure, strategy and operational methods 0.736

Delivering new products and services based on market change 0.752 Eigen Value 6.084 3.127 1.935 1.398 1.216 Proportion of Variance Explained 21.60% 12.51% 12.36% 12.33% 10.00% Cumulative Variance Explained 21.60% 34.11% 46.47% 58.80% 68.80% Alpha 0.87 0.832 0.714 0.762 0.817



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Factor loadings were greater than 0.50 were considered significant (Hair et al., 1995 cited in Tharmaseelan, 2005). When the original 20 items were analyzed by the principal component factor analysis with varimax rotation a five factor emerged. Here, two items were dropped from the analysis because of their low loadings without significant and difficulty of interpretation which loadings were .457 in factor 1 and .437 in factor 5. All items loaded highly with the ranged from 0.898 to 0.511, with communalities of .484 or higher. As table 5 the five factor solution suggested by the eigenvalues greater than one (Kasier, 1958) criterion explained 68.80% of the variance in the data to again confirm that the factor analysis is valid. Factor 1: This factor was represented by seven items, was named customer satisfaction with managing change accounted for the amount of variance 21.60%. Factor loadings of this variable ranged from 0.791 to 0.549. Factor 2: This factor was represented by three items, was labeled growth in profitability accounted for the amount of variance 12.51%. Factor loadings of this variable ranged from 0.898 to 0.554. Factor 3. This factor was represented by four items, was named growth in business and income level accounted for the amount of variance 12.36%. Factor loadings of this variable were 0.833 and 0.511.Factor 4: This factor was represented by two items, was named growth in no. of employees and retaining key employees accounted for the amount of variance 12.33%. Factor loadings of this variable were 0.816 and 0.745. Factor 5: This factor was represented by two items, was named growth in turnover/ sales accounted for the amount of variance 10%. Factor loadings of this variable were 0.754 and 0.613. Cronbach’s alpha for each factor: factor 1, factor 2, factor 3, and factor 4 and factor 5 were 0.870, 0.832, 0.714, 0.762 and 0.817 respectively which results of reliability analysis confirmed that consistency is at an acceptable level for each factor

4.02 Correlations analysis: Relationship between planning competencies and business performance

Planning competencies are composited within the combinations of goal setting, information seeking and systematic planning and monitoring. Result indicates in table 6, that planning competencies significantly, positively related to business performance (r = 0.717, p< 0.01).

Table 06: Correlation matrix for planning competencies and business performance PC1 PC2 PC3 PC10 BP PC1: Goal setting 1 PC2: Information seeking

.319* (0.016)

1

PC3: Systematic planning and monitoring

.286* (0.032)

.460** (0.000)

1

PC: Planning competencies

.681** (0.000)

.813** (0.000)

.769** (0.000)

1

BP: Business Performance

.501** (0.000)

.548** (0.000)

.580** (0.000)

.717** (0.000)

1

Source: Survey Data ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). Therefore a hypothesis (H1.1) planning competency as a composite has positive significant relations with business performance is accepted.

It means there is a positive significant relationship between planning competencies as a composite and business performance. The impact of dimensions of planning competencies on business performance of the business operators are illustrated in table 7. Three sub dimensions of planning competencies are considered to explain and predict the effects of dimensions of planning competencies on business performance.



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Table 07: Results of multiple Regression analysis with business performance as dependent variable and

dimensions of planning competencies as predictor variables.

Model independent Variables Unstandardized

Coefficients Standardized Coefficients T Sig.

B Std. Error Beta 1 (Constant) 8.067 8.13 0.992 0.326

Goal setting 1.022 0.34 0.307 2.98 0.004 Information seeking 0.783 0.31 0.284 2.555 0.014 Systematic planning and monitoring 1.128 0.34 0.361 3.284 0.002

R2 0 .518 F = 18.664 P = 0.000 Source: Survey Data

The finding of the analysis demonstrates that all dimensions of planning competencies have positive significant impact on business performance. Goal setting, information seeking and systematic planning and monitoring emerged as significant predictors of business performance explains together (R2= .518) 51.8% percent of the total variance in business performance. As the model reveals the remaining 48.2% of variability is not explained. An Analysis of Variance (ANOVA) indicates that F= 18.664, p < 0.01, the model is significant. Goal setting, information seeking and systematic planning and monitoring produce positive significant result with beta(β) weights of 0.307, 0.284 and 0.361 respectively. Significant positive relationship of all dimensions of planning competencies with business performance is found (p < 0.01). This means that there is positive impact of dimensions of planning competencies on business performance. Therefore hypothesis (H1.2) dimensions of planning competencies have positive a significant relation with business performance is accepted. Hypothesis (H1) states that planning competencies as a composite as well as its dimensions have positive significant relationship with business performance. Based on the acceptance of sub hypotheses the results illustrate that planning competencies as a composite as well its dimensions have positive significant relationship with business performance and as a result main hypothesis is accepted. Among the three dimensions of planning characteristics, systematic planning and monitoring is most significant dimension that influenced towards the business performance of business operators with high beta weight of 0.361. Further, result indicates that the second (β= 0.307) and third (β= 0.284) important dimensions are goal setting and information seeking that influence on business performance. 5.0 Conclusion The objective of the study related to identifying the factors influencing on the planning competencies and its impact on business performance. According to the analysis carried out in the above, planning competencies have positive significant impact on business performance. In this study, identified factors of the planning competencies are goal setting, information seeking, systematic planning and monitoring and measurements of business performance are growth in profitability, growth in turnover, growth in business and income level, growth in number of employees and customer satisfaction with managing change. Findings of the study revealed that planning competencies have significant positive influence on business performance, which indicated that 51.8 % of the total variance in business performance explained by all three dimensions of planning competencies. Out of the three dimensions of planning competencies, systematic planning and monitoring was most important factor to influence the business performance. The results of this study would elicit useful insight to the investors, managers and also academicians to comprehend the importance of business performance well on the way to create successful firm performance and sustain it in developing countries

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Structuring Latent Nature of Planning Competencies of Business Operators and Its Impact on Business Performance: Evidence from Sri Lanka