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STUDY OF MANAGEMENT DEVELOPMENT EFFECTIVENESS OF BANKING ORGANIZATIONS IN
PAKISTAN
By Ghulam Dastgeer
MBA, Federal Urdu University, Islamabad, 2006
A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
In Human Resource Development
To
FACULTY OF MANAGEMENT SCIENCES
(Human Resource Development)
NATIONAL UNIVERSITY OF MODERN LANGUAGES, ISLAMABAD
September, 2012
© Ghulam Dastgeer, 2012
ii
NATIONAL UNIVERSITY OF MODERN LANGUAGES FACULTY OF MANAGEMENT SCIENCES
THESIS/DISSERTATION AND DEFENSE APPROVAL FORM
The undersigned certify that they have read the following thesis, examined the defense, are satisfied with the overall exam performance, and recommend the thesis to the Faculty of Management Sciences (FMS) for acceptance: Thesis / Dissertation Title: Study of Management Development Effectiveness of Banking
Organizations in Pakistan
Submitted by: Ghulam Dastgeer Registration No. 286-MPhil/HRD/2007 (Jan.) Doctor of Philosophy . Degree Name in Full Human Resource Development Name of Discipline Dr. Atiq Ur Rehman _____________________ Name of Research Supervisor Signature of Research Supervisor Prof. Dr. Rashid A. Khan _____________________ Name of Dean (FMS) Signature of Dean (FMS) Maj. Gen. ® Masood Hasan _____________________ Name of Rector Signature of Rector September, 2012 Date
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CANDIDATE DECLARATION FORM I Ghulam Dastgeer Son of Abdul Aziz Registration No. 286-MPhil/HRD/2007 Discipline: Human Resource Development Candidate of Doctor of Philosophy at the National University of Modern Languages does hereby declare that the dissertation: Study of Management Development Effectiveness of Banking Organizations in Pakistan. Submitted by me in partial fulfillment of PhD degree in discipline Human Resource Development is my original work, and has not been submitted or published earlier. I also solemnly declare that it shall not, in future, be submitted by me for obtaining any other degree from this or any other university or institution. I also understand that if evidence of plagiarism is found in my dissertation at any stage, even after the award of degree, the work may be cancelled and the degree revoked. 25 September, 2012 _________________
Signature of Candidate
Ghulam Dastgeer ________________
Name of Candidate
iv
ABSTRACT
Thesis Title: Study of Management Development Effectiveness of Banking Organizations in
Pakistan
The objectives of the present study are to assess the effectiveness of management
development (MD) programs in Pakistani banking sector, identify factors affecting the success of MD and investigate relationships among those factors that affect MD effectiveness. The research employed a blend of qualitative and quantitative methodologies. Based on extensive literature review a model of MD effectiveness was developed and tested with structural equation modeling techniques. The achieved sample for the current study consisted of managers from 33 banking organizations operating in Rawalpindi/Islamabad using “self-reported rating” survey questionnaire and interviews which resulted in 168 completed responses and 25 in-depth interviews. Although participants of the study were very hopeful regarding bright future of MD in Pakistan yet the current level of MD effectiveness is not high. Both lack of trainees’ seriousness in self-development and less top management support for MD were found serious threats to effectiveness. Observed model of MD effectiveness had a good fit with the predicted model and all paths were significant. Individual initiatives for self-development, MD program design and opportunity for skill utilization were the three variables most closely associated with MD effectiveness. Top management should assign higher priority to MD. Pakistani organizations should create strong link between their MD efforts and their corporate strategies, focus more on creating positive training attitude of their employees, provide training program which are flexible enough, contents of MD programs must be relevant to company’s real problems and issues and provide maximum opportunities to utilize knowledge and skills gained through development program in the work place. Risk taking and new ideas should be encouraged. The reward system needs revising and a continuous learning environment ought to be established for effective MD in Pakistan. This study, for the first time, assessed the current state of MD effectiveness in Pakistan and contributes to the present stock of knowledge and understanding of the subject by contextualizing the concept of “MD effectiveness” in Pakistani banking sector. Keywords – Management development, Effectiveness, Top management, Corporate strategy, Banking sector organizations, Pakistan
v
TABLE OF CONTENTS
Chapter Page
THESIS/DISSERTATION AND DEFENCE APPROVAL FORM………... ii
CANDIDATE DECLARATION FORM……………………………………. iii
ABSTRACT…………………………………………………………………. iv
TABLE OF CONTENTS………………………………………………….... v
LIST OF TABLES…………………………………………………………... x i
LIST OF FIGURES………………………………………………………….. xiii
LIST OF APPENDICES…………………………………………………….. xiv
LIST OF ABBREVIATION………………………………………………… xv
DEDICATION……………………………………………………………… xvii
ACKNOWLEDGEMENT…………………………………………………... xviii
1 INTRODUCTION ------------------------------------------------------------------- 1
Background of the Study ------------------------------------------------------------- 1
Objectives of the Research Study --------------------------------------------------- 7
Research Questions ------------------------------------------------------------------- 7
Significance of Research ------------------------------------------------------------- 8
Overview of Research Design and Research Methodology --------------------- 9
Organization of the Thesis ----------------------------------------------------------- 9
2 LITERATURE REVIEW---------------------------------------------------------- 12
Definition of Terms and Concepts -------------------------------------------------- 12
Management Development ---------------------------------------------------------- 17
Components of MD ------------------------------------------------------------------- 18
vi
Management Education ---------------------------------------------------------- 18
Management Training ------------------------------------------------------------ 18
On-the-job Experience ----------------------------------------------------------- 19
The MD Cycle ------------------------------------------------------------------------- 20
Need Assessment Phase ---------------------------------------------------------- 21
MD Program Design and Implementation Phase ----------------------------- 22
Evaluation Phase ------------------------------------------------------------------ 22
MD in Relation to Corporate Strategy --------------------------------------------- 24
MD as a Strategic Activity ------------------------------------------------------- 24
MD Interventions in the World ----------------------------------------------------- 27
Strategic Perspective of MD ----------------------------------------------------- 27
The Volume of MD Activities -------------------------------------------------- 28
Common MD Methods ----------------------------------------------------------- 28
Outcomes of MD ------------------------------------------------------------------ 29
Banking Sector of Pakistan ---------------------------------------------------------- 30
MD in Banking Sector of Pakistan ------------------------------------------------- 31
NIBAF ------------------------------------------------------------------------------ 31
IBP ---------------------------------------------------------------------------------- 32
Measurement of MD Effectiveness ------------------------------------------------- 34
Evolution Models --------------------------------------------------------------------- 35
Burgoyne (1998) ------------------------------------------------------------------ 35
Mumford and Gold (1993) ------------------------------------------------------- 36
Mumford (1994) ------------------------------------------------------------------- 37
Burack et al. (1997) --------------------------------------------------------------- 38
Luoma (2004) ---------------------------------------------------------------------- 38
Strength and Weaknesses of Existing Models -------------------------------- 40
D’Netto Model of MD Effectiveness ---------------------------------------------- 42
Strength and Weaknesses of D’Netto Model ---------------------------------- 44
Conceptual Framework -------------------------------------------------------------- 46
Dependent Variable --------------------------------------------------------------- 50
Independent Variables ------------------------------------------------------------ 52
vii
Antecedent Components ----------------------------------------------------- 52
Program Design and Implementation Components ----------------------- 58
Post-Program Components --------------------------------------------------- 61
3 RESEARCH METHODOLOGY ------------------------------------------------ 65
Introduction ---------------------------------------------------------------------------- 65
Research Approaches ----------------------------------------------------------------- 65
Quantitative Approach ----------------------------------------------------------- 66
Qualitative Approach ------------------------------------------------------------- 66
Unit of Analysis ----------------------------------------------------------------------- 66
Target Population --------------------------------------------------------------------- 67
Sampling Strategy -------------------------------------------------------------------- 68
Data Collection Tools ---------------------------------------------------------------- 70
Semi-Structured Interviews ------------------------------------------------------ 70
Research Questionnaire ---------------------------------------------------------- 70
Measure of Dependent and Independent variables-------------------------------- 71
The Pilot Testing and Results ------------------------------------------------------- 74
Validity of Quantitative Research Instrument ---------------------------- 75
Reliability of Quantitative Research Instrument -------------------------- 77
Data Collection ------------------------------------------------------------------------ 80
Response Rate ------------------------------------------------------------------------- 80
Statistical Techniques ---------------------------------------------------------------- 81
Descriptive Statistic --------------------------------------------------------------- 81
SEM --------------------------------------------------------------------------------- 82
Statistical Softwares ------------------------------------------------------------------ 84
Researcher’s Interference ------------------------------------------------------------ 84
Research Ethics ----------------------------------------------------------------------- 85
viii
4 DESCRIPTION OF SAMPLE CHARATERISTICS ------------------------ 87
Introduction ---------------------------------------------------------------------------- 87
Description of the Sample by Means of Frequency Tables --------------------- 88
Gender ------------------------------------------------------------------------------ 88
Age ---------------------------------------------------------------------------------- 89
Sector ------------------------------------------------------------------------------- 90
Region ------------------------------------------------------------------------------ 91
Organizations ---------------------------------------------------------------------- 92
Educational Qualification -------------------------------------------------------- 92
Occupational Level --------------------------------------------------------------- 93
Work Experience ------------------------------------------------------------------ 94
MD Program Attended ----------------------------------------------------------- 95
Summary ------------------------------------------------------------------------------- 96
5 QUANTITATIVE DATA ANALYSIS AND DISCUSSION ---------------- 97
Introduction ---------------------------------------------------------------------------- 97
Descriptive Statistics ----------------------------------------------------------------- 97
Descriptive Analysis of all Items ----------------------------------------------- 97
Descriptive Analysis of Constructs --------------------------------------------- 102
Group Statistics of MD Effectiveness ------------------------------------------ 104
Group Statistics of Individual Initiative ---------------------------------------- 106
Group Statistics of Top Management Support -------------------------------- 108
Model Estimation with Structural Equation Modeling -------------------------- 110
Item Parceling --------------------------------------------------------------------- 111
The Measurement Model --------------------------------------------------------- 123
Evaluating Goodness-of-fit Criteria ---------------------------------------- 124
Offending Estimates ------------------------------------------------------- 124
Correlation among Latent Constructs ----------------------------------- 124
Standardized Regression Weights --------------------------------------- 126
ix
Overall Model Fit (Goodness of Fit Indices) --------------------------- 129
Measurement Model Fit ------------------------------------------------------ 130
Reliability ------------------------------------------------------------------- 130
Variance- Extracted ------------------------------------------------------- 131
The Structural Model ------------------------------------------------------------- 133
Overall Model Fit (Evaluating Goodness-of-fit Indices) ---------------- 133
Absolute Fit Measures ---------------------------------------------------- 134
Incremental Fit Measures ------------------------------------------------- 135
Noncentrality Based Measures ------------------------------------------- 136
Parsimonious Fit Measures ----------------------------------------------- 136
Structural Model Fit (Standardized Parameter Estimates) --------------- 141
Competing Models ---------------------------------------------------------------- 147
Discussion ----------------------------------------------------------------------------- 151
6 QUALITATIVE DATA ANALYSIS AND DISCUSSION ------------------ 155
Introduction ---------------------------------------------------------------------------- 155
Coding and Identifications of Themes --------------------------------------------- 157
Theme 1: Individual Perspective ---------------------------------------------------- 158
Individual behavior and Motivation -------------------------------------------- 159
Theme 2: Management Perspective ------------------------------------------------ 165
Senior Management Support ---------------------------------------------------- 166
Rewards ---------------------------------------------------------------------------- 170
Feedback --------------------------------------------------------------------------- 172
Minimizing Blockages to Effective Transfer of Learning ------------------- 173
Theme 3: Program Design Perspective -------------------------------------------- 176
Linking MD to Corporate Strategy --------------------------------------------- 177
Delivery Methods ----------------------------------------------------------------- 179
Content Validity ------------------------------------------------------------------- 181
Continuation of Process ---------------------------------------------------------- 183
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7 SUMMARY AND CONCLUSION ---------------------------------------------- 185
Introduction --------------------------------------------------------------------------- 185
Summary of the Research Findings ------------------------------------------------ 186
Theoretical Significance of the Current Study ----------------------------------- 190
Suggestions for Future Research --------------------------------------------------- 192
Limitations of the Present Study --------------------------------------------------- 193
Final Conclusion ---------------------------------------------------------------------- 194
BIBLOGRAPHY --------------------------------------------------------------------
196
APPENDICES -----------------------------------------------------------------------
209
xi
LIST OF TABLES
Table No. Page
1 Comparison of a traditional model for MD with Berry model ------------ 26
2 Number of banks operating in Pakistan -------------------------------------- 30
3 Summary of key variables ----------------------------------------------------- 47
4 Dimensions of MD effectiveness --------------------------------------------- 51
5 Number of branches of banks operating in Rawalpindi and Islamabad- 68
6 Sector wise details and distribution of sample ------------------------------ 69
7 Correlation matrix of pilot study ---------------------------------------------- 76
8 Internal reliability of scales ---------------------------------------------------- 79
9 Effective response rate --------------------------------------------------------- 81
10 Frequency distribution: Gender ----------------------------------------------- 88
11 Frequency distribution: Respondents’ ages into age group ---------------- 89
12 Frequency distribution: Sector ------------------------------------------------ 90
13 Frequency distribution: Region ----------------------------------------------- 91
14 Frequency distribution: Educational qualification -------------------------- 92
15 Frequency distribution: Occupational level ---------------------------------- 93
16 Frequency distribution: Work experience ------------------------------------ 94
17 Frequency distribution: Number of MD program attended ---------------- 95
xii
18 Descriptive analysis of all items ---------------------------------------------- 98
19 Means and Standard Deviations (SD) ---------------------------------------- 102
20 Group statistics of MD effectiveness ----------------------------------------- 105
21 Independent sample test for MD effectiveness ------------------------------ 105
22 Group statistics of Individual Initiative -------------------------------------- 107
23 Independent sample test for Individual Initiative --------------------------- 107
24 Group statistics of top management support -------------------------------- 109
25 Independent sample test for top management support --------------------- 109
26 Eigenvalues of measures ------------------------------------------------------- 114
27 Revised eigenvalues of measures --------------------------------------------- 119
28 Cronbach’s values for constructs --------------------------------------------- 120
29 Simple random parceling ------------------------------------------------------ 121
30 Correlation among latent construct ------------------------------------------- 125
31 Measurement model results (standardized regression weights) ---------- 127
32 Goodness-of-fit indices for the measurement model ----------------------- 129
33 Reliability estimates for all constructs ------- -------------------------------- 131
34 Variance-extracted estimates for the structural model---------------------- 132
35 Comparison of goodness-of-fit measures for the structural model ------ 138
36 Acceptance or rejection of hypotheses --------------------------------------- 141
37 Structural equation coefficients and “t” values for the structural model 144
38 Structural equation coefficient for COMPMOD1 -------------------------- 148
39 Structural equation coefficient for COMPMOD2 -------------------------- 148
40 Summary of interviews conducted ------------------------------------------- 155
xiii
LIST OF FIGURES
Figure No. Page
1 MD process model ---------------------------------------------------------- 20
2 The effectiveness triangle in MD ------------------------------------------ 37
3 Luoma’s model of SMD ------------------------------------------------------ 40
4 D’Netto model of MD effectiveness ---------------------------------------- 43
5 Conceptual framework of present study ------------------------------------ 49
6 Standardized regression coefficients for the hypothesized structural
model -----------------------------------------------------------------------
146
7 Competing model 1 ---------------------------------------------------------- 149
8 Competing model 2 -------------------------------------------------------- 150
9 Summary of emerging themes and sub-themes -------------------------- 157
10 Theme 1: individual perspective ------------------------------------------ 158
11 Summary of theme1 -------------------------------------------------------- 164
12 Theme 2: management perspective ------------------------------------------ 165
13 Theme 3: Program design perspective -------------------------------------- 176
xiv
LIST OF APPENDICES
Appendix Page
A Research Questionnaire ---------------------------------------------------- 209
B Banks Operating in Rawalpindi/Islamabad ----------------------------- 224
C Frequency Distribution: Age ---------------------------------------------- 227
D Frequency Distribution: Organization ----------------------------------- 229
E Complete LISREL Results of Measurement Model ------------------- 232
F Complete LISREL Results of Structural Model ------------------------ 248
xv
LIST OF ABBREVIATIONS
CFA Confirmatory Factor Analysis
CFI Comparative Fit Index
GFI Goodness of Fit Index
HR Human Resource
HRD Human Resource Development
IBP Institute of Bankers Pakistan
IFI Incremental Fit Index
LISREL Linear Structural Relation
MBA Master’s in Business Administration
MD Management Development
MLE Maximum Likelihood Estimation
NFI Normed Fit Index
NIBAF National Institute of Banking and Finance
NNFI Non-Normed Fit Index
PIM Pakistan Institute of Management
RMSEA Root mean Square Error of Approximation
xvi
ROI Return on Investment
SBP State Bank of Pakistan
SD Standard Deviation
SEM Structural Equation Modeling
SMD Strategic Management Development
SRS Stratified Random Sampling
T&D Training and Development
TLI Tucker-Lewis Index
TNA Training Need Assessment
xvii
DEDICATION
To my sons,
Muhammad Ibraheem & Muhammad Ali
with love
xviii
ACKNOWLEDGEMENT
“All praise belongs to Allah, the lord of all the worlds the All-Merciful, the very
Merciful”
(al - Qur’ān: 1)
After Allah I wish to extend my sincere gratitude and appreciation to the following people for the
contributions to this research script.
My research supervisor Dr. Atiq Ur Rehman, who provided assistance in all phases of
this research work. This thesis would not have been what it is without him.
Professor Dr. Rashid A. Khan, who taught me the basics of research.
Dr. Brian D’Netto (Australia) and Dr. Gerhard Mels (USA) for their valuable cooperation
and kind help.
My parents for all their support and encouragement over the past years.
My wife, for her support, patience and encouragement, but above all, her love and
understanding.
My brothers for their support, sacrifices and patience.
The respondents, without their contribution, this study would not have been possible.
Ghulam Dastgeer
STUDY OF MANAGEMENT DEVELOPMENT EFFECTIVENESS OF BANKING
ORGANIZATIONS IN PAKISTAN
By Ghulam Dastgeer
NATIONAL UNIVERSITY OF MODERN LANGUAGES ISLAMABAD
September 2012
1
CHAPTER 1
INTRODUCTION 1.1 Background to the Research Study
Many organizations in the world are restructuring, reorganizing, and realigning
their competitive strategies in an effort to compete or just to survive in today’s global
competitive environment. In this competitive business environment organizations are also
struggling to retain experienced, capable and skilled managers (McClelland, 1994).
Desimone, Harris and Werner (2002) believe that an organization must have high quliaty
and flexible management teams to survire and successd (p. 512). In a more recent study,
D’Netto, Bakas & Bordia (2008) have found human capital differentiation as an
instrument for gaining sustainable competitive advantage.
Development of managers who can face the challenges of this competitive
environment is a priority area for all progressing organizations. The development of
managers is placed under the field of Management Development (MD). Voleberghs
(1998) argues “all MD activities are concentrated on improving the quality of
management and hence, the quality of organizations” (p. 649).
Desimone et al. (2002) define MD as “an organizations’ conscious effort to
provide its managers (and potential managers) with opportunities to learn, grow and
change, in hopes of producing over the long term cadre of managers with the skills
necessary to function effectively in that organization” (p. 513). According to Dikken and
Hoeksema, (2001) “the main goals of MD are developing and having the disposal of
2
enough qualified managers, realizing organizational change and making use of young
talent to realize organizational goals” (p. 169).
The importance of MD has been acknowledged in several management training
and education reviews and MD has been linked with the attainment of competitive
advantage. Discussing the historical context of MD, Vloeberghs (1998) stated that in the
past, role of MD was only confined to training and education of the employees and MD
was used as a tool of extension to succession planning. The role of training was just to
train a manager or employee for a higher level position. But now the situation is different
and MD is viewed as a strategic partner in progressing organizations. Brown (2005)
argues “for more than 15 years, it has been contended that MD has a strategic role to play
in organizations, MD should be an integral part of strategic plans and strategic change”
(p. 209). The successful organizations of the world have made MD a central means of
running business (Fulmer, Gibbs, & Goldsmith, 2000). These organizations have not only
linked their MD interventions with their overall corporate strategies but also successful in
retaining this link over time.
There are several benefits of MD. Effective MD results in enhanced
organizational performance (Meldrum & Atkinson, 1998), higher productivity, lower
absenteeism, better customer services (D’Netto et al., 2008), increased sales, more
satisfied customer (Noe, 2000), improved communication, improved quality of service
delivery, improved morale among employees, improved decision making (Newton &
Wilkinson, 1998) and effective managerial behavior (Mumford, 1994).
MD is equally necessary for banking industry. Banks have vital part in the
economic growth of a country. The banking sector of Pakistan consists of a number of
3
institutions like central bank, local, foreign, Islamic, and microfinance banks. In 1947
Pakistani banking sector had no worth but in first two decades there was a remarkable
evolution and development. Till 1970, Pakistan had attained a prosperous and developed
banking sector (Khan, 2004). According to SBP (2010), today 61 banks of different
categories are operating in Pakistan.
In banking industry of Pakistan, public and private sectors are operating their
business and MD programs are integral part of overall development plans of all banks of
both sectors. National Institute of Banking and Finance (NIBAF) is a dedicated institute,
which runs MD programs for banks in general and SBP in particular (SBP Annual
Report, 2008-2009). The Institute of Bankers Pakistan (IBP) is another institution serving
the same purpose for the banking industry. It was incorporated in 1951 with the technical
support of the Institute of Bankers (UK). This Institute is also committed to give training
and development services for the banking sector of Pakistan. For providing effective
training to employees, a number of banks in Pakistan have their own training and
development center.
To promote MD in Pakistan, in 1954 Government of Pakistan established
“Pakistan Institute of Management” (PIM). PIM provide MD services to managers from
different sectors and industries of Pakistan and this institute is considered as a pioneer of
executive development in the country. Institutes like “Suleman Dawood School of
Business” at Lahore University of Management Sciences (LUMS), Pakistani Society of
Training and Development, Management Development Institute (MDI), Institute of
Business Administration (IBA) Karachi and many others are also providing MD facilities
to public and private sector organizations.
4
According to Berry (1990) Organizations spend millions of dollars on MD
programs every year to make their executives and managers more capable, but few of
them affect the organization’s ability to compete (p. 20). Sugrue stated that the normal
expenditure of organizations on education and training and development in US is more
than 2.2 per cent of payroll (as cited in Kirwan & Birchall, 2006, p. 253). Kirwan and
Birchall (2006) argue that organizations are not receiving the encouraging value from
their spending on T&D (p. 253).
A few theoretical models of MD have been put forward in the literature. For
example, Luoma (2004), Burack Hochwarter and Mathys (1997), Mumford (1994),
Mumford and Gold (1993), Berry (1990) and Burgoyne (1988). These models clarify the
anatomy of the strategic linkage of MD goals with corporate goals. One major
shortcoming of these models is that these models are not comprehensive and their focus
is not on specifically measuring the MD effectiveness. D’Netto et al. (2008) state “MD
interventions can yield desired result only when MD is effective. Yet researchers have
not specifically measured MD effectiveness” (p. 03).
Stone (2005), and Noe (2000) proposed a three-stage approach to MD: 1)
assessment of development need; a process of identifying and articulating the HRD need
of an organization 2) conducting the development program; a process of developing
training curricula and materials to meet training and development needs and 3) evaluating
the program; a process by which results of MD program are collected to determine if MD
is successful. D’Netto et al. (2008) adopted the approach proposed by Desimone et al.
(2002) and Neo et al. (2000) and built their model of MD effectiveness. D’Netto et al.
(2008) attempted to address the deficiencies of the earlier MD models. They analyzed the
5
key factors associated with MD effectiveness. D’Netto model of MD effectiveness
includes variables of the first and last stages of the MD process. Variables included in the
model are “organizational learning culture, individual initiative, top management support,
link to corporate strategy, post-program evaluation, line manager support and opportunity
for skill utilization”. D’Netto et al. (2008) specifically measured MD effectiveness and
emphasize that to be effective, MD must be systematic and should be linked to corporate
objectives, goals and strategy and organizations should provide facilities to managers to
apply newly learned skills on the work place. However a critical weakness of D’Netto
model is that this model includes variables associated with the first and last stage of MD
process only and ignores the variables associated with the second stage of MD process.
Despite the fact that MD interventions are common in Pakistani organizations,
however, traditional Pakistani organizations have been criticized for their passivity,
bureaucratic and hierarchical cultures, in these organizations turnover is high and
organizational commitment is low (Khilji, 2002). Khilji (2002) in her study has also
concluded that managers are ready to depart from traditional organizational cultures and
practices, despite the fact that not all organizations are.
One possible reason of the poor performance of Pakistani organizations may be
the ineffectiveness of MD. A broad review of literature reveals that no comprehensive
research or study has been conducted in the field of MD to identify the nature and level
of MD effectiveness in Pakistan.
Iqbal (2007) studied Training Needs Assessment (TNA) in Pakistani
pharmaceutical organizations. His study particularly identified current TNA practices in
Pakistan and impact of TNA on improvement of human productivity. Iqbal (2007)
6
concluded that TNA and human productivity are correlated directly. TNA was found
essential for goal settings, arousing learning motivation for trainees. Further TNA was
found instrumental to help reduce training cost etc. Shad (2008) studied influence of
organizational work environment on transfer of training in banking sector of Pakistan. He
concluded that organizational work environment has a positive and significant influence
on transfer of training.
Rehman (2007) studied training and development practices and investigated the
dynamics of human behavior in public sector projects in Pakistan. Results of Rehman
(2007) indicated that there is high degree of training inadequacy and training and
development practices are ineffective in public sector projects organizations in Pakistan.
Rehman (2007) also identified several reasons for inadequacy of training, which include
workload does not permit, training is not a priority of top management, lack of
appropriate training opportunities etc.
However the above referred studies did not answer the questions like what are key
variables associated with effectiveness of MD and how MD can be made more effective.
To fill the gap in literature of MD effectiveness available from Pakistan, a need arises to
study and measure the current state of MD effectiveness in Pakistani banking sector, to
conduct a broad analysis of key factors associated with the MD effectiveness and to
identify ways in which MD can be made more effective in achieving desired goals.
In the present study, researcher has conducted analysis of key variables of MD in
Pakistani banking sector. This study also identified ways to make MD more effective.
D’Netto’s Model of “MD effectiveness” provided basic framework for measuring MD
effectiveness. In the current, study researcher considered all three stages of MD process.
7
Based on extensive literature review research added the variables associated with second
stage of MD process in the existing model and empirically justified the strength of
relationships of all variables. This research work is also an endeavor to fill the gap in
literature of MD available from Pakistan.
1.2 Objectives of the Research Study
The objectives of this research study are,
1. To assess the current state of effectiveness of MD in Pakistani banking sector.
2. To identify factors effecting the success/effectiveness of MD.
3. To investigate relationships among those various factors which affect the
success of MD.
1.3 Research Questions
The research questions which guided the conduct of this study are:
1. What is the current state of MD effectiveness in Pakistani banking sector?
2. What are the factors that affect the effectiveness of MD?
3. What are the relationships among factors affecting the MD effectiveness?
8
1.4 Significance of Research
It is theoretically claimed that MD is used as a competitive weapon by
organizations. But empirical research work on MD is still insufficient (D’Netto et al.,
2008). In developing countries like Pakistan, there is dearth of such studies. The present
study is a contribution towards advancement in the knowledge on MD effectiveness.
A major theoretical contribution of the current study is that it has attempted to
address the weakness of D’Netto model of MD effectiveness. For example, D’Netto
model did not focus on all stages of MD process, model presented in this research
includes the variables associated with all three stages of MD process and researcher
empirically justifies that how all three stages of MD process are equally important for the
effectiveness of MD. This study assessed the current state of MD in Pakistani banking
sector and contributes to the present stock of knowledge and understanding of the subject
by contextualizing the concept of “MD effectiveness” in Pakistani banking sector. The
research findings also have significant academic values for all those institutions which
are teaching or carrying out research in this field.
The findings of current study are particularly significant for banking organizations
in Pakistan which invest precious resources on MD programs but a small proportion of
that investment actually translates into improved organizational and individual
performance. These findings are expected to help them to identify and understand the
process of MD programs implementation, its bottlenecks and critical success factors of
MD effectiveness in the context of Pakistani environment.
9
1.5 Overview of Research Design and Research Methodology
The research employed a blend of qualitative and quantitative methodologies.
Based on extensive literature review a model of MD effectiveness was developed and
tested with structural equation modeling techniques. A random sample of 350 managers
employed in banks operating in Rawalpindi and Islamabad was taken for the execution of
the research. The achieved sample for the current study consisted of managers from 33
banking organizations operating in Rawalpindi/Islamabad using “self-reported rating”
survey questionnaire and interviews which resulted in 168 completed responses and 25
in-depth interviews. To confirm the viability of the data collection methods and to
measure the reliability and validity of the quantitative questionnaire, pilot study on a
sample of 80 managers was conducted by the researcher.
1.6 Organization of the Thesis
The present thesis consists of seven chapters to achieve the objectives of the
current study. The chapters are structured as explained below.
Chapter 1 – Introduction
This chapter serves as an introduction to the study. The chapter includes
background to the research study, objectives of the research study, research questions,
significances of study and brief introduction of the research design and methodology.
10
Chapter 2 – Literature Review
This chapter provides a comprehensive literature related to the research issue.
This chapter covers definitions of key concepts related to the study, MD and its strategic
perspective, MD in the world and in banking sector of Pakistan. Relevant theories and
models specifically related to MD effectiveness are discussed. This chapter also discusses
the theoretical framework of the study and includes relevant literature on variables of
interest.
Chapter 3- Research Methodology
In this chapter detailed discussion on research design and methodology selected is
given. This chapter includes a detailed explanation on research approaches, sampling
strategy, research instrumentation, validity and reliability of the instrument and data
analysis procedures.
Chapter 4 – Description of Sample Characteristics
In this chapter biographical characteristics of the sample of 168 respondents are
presented. Frequency tables are presented to provide a description and summary of the
dispersion of the respondents across the demographical variables. Demographic variables
that are presented in this chapter are, gender, age, sector, region, organization,
occupational level, educational qualifications, work experience and number of MD
program attended.
11
Chapter 5 – Quantitative Data Analysis and Discussion
In this chapter analysis of qualitative data is presented. Using structural equation
modeling techniques, empirical validation of the MD effectiveness model is given. This
chapter further constitutes a discussion on the findings derived from the quantitative data
analysis.
Chapter 6 – Qualitative Data Analysis and Discussion
This chapter deals with the presentation and interpretation of the qualitative data.
Qualitative research results are presented by means of the presentation and discussion of
the emerging themes.
Chapter 7 – Summary and Conclusion
Chapter 7 is a concluding chapter. In this chapter summary of the major findings
is provided. Further theoretical significance of the study and suggestions for the future
research are also discussed. This chapter ends with some concluding remarks.
12
CHAPTER 2
LITERATURE REVIEW
2.1 Definitions of Terms and Concepts
Management
“Management is a process of designing and maintaining an environment in which
individuals, working together in groups, efficiently accomplish selected aims” (Weihrich,
1999).
Human Resource Development (HRD)
According to Desimone et al, (2002) “HRD is a set of systematic and planned
activities designed by an organization to provide its members with the opportunities to
learn necessary skills to meet current and future job demands” (p. 03).
Management Development
1. “Management development is a dynamic and complex process by which
individuals learn to perform effectively in managerial roles” (Longenecker &
Fink, 2001).
2. According to Jansen (2001), MD means “A system of personnel practices by
which an organization tries to guarantee the timely availability of qualified
and motivated employees for its key positions” (p. 106).
13
3. According to Desimone et al, (2002), MD is “an organizations’ conscious
effort to provide its managers (and potential managers) with opportunities to
learn, grow and change, in hopes of producing over the long term cadre of
managers with the skills necessary to function effectively in that organization”
(p. 513).
Above definitions make several key points. Firstly, these definitions suggest that
MD is a common activity of HRD. Secondly, MD is a difficult process because learning
process of individuals is different. Individuals learn in different ways, consciously or
unconsciously. Thirdly, MD control and manage the learning process of managers; MD
consists of providing employees with opportunities to modify their management styles,
change their attitudes, and update their technical/professional skills. The objective of MD
is, to have the right type of managers at the right moment. Fourthly, organizations should
take MD efforts consciously because organizations will not get the desired change if
development is left on chance.
MD Effectiveness
According to D’Netto et al, (2008), “MD effectiveness refers to the extent to
which MD programs have yielded desired outcomes” (p. 04).
Strategic MD (Link to corporate strategy)
According to Brown (2005), “MD interventions, which are intended to enhance
the strategic capability and corporate performance of the organization” (p. 210).
14
Organizational Culture
According to Kopelman et al., “organizational culture refers to the shared
meanings and manifestations of organizational behavior” (as cited in Bates &
Khasawneh, 2005, p. 98).
Organizational Learning Culture
“Organizations that have a learning culture have a set of attitudes, values and
practices that support and encourage a continuous process of learning” (Bates &
Khasawneh, 2005).
Top Management Support
Top management support refers to “degree to which top management provides
weight, authority and status to MD activities” (Sadler, 1998).
Line Manager Support
According to Noe (2000), line manager support refers to “degree to which
trainees’ managers emphasize the importance of attending development programs and
stress the application of training content to the job” (p. 118).
Post Program Evaluation
Post program evaluation in this context “refers to the process of collecting the
outcomes needed to determine if MD program is effective”.
15
Effective Monitoring
“Monitoring consists of those processes performed to observe training and
development program implementation and execution in order to identify the potential
problems in a timely manner and corrective action can be taken, when necessary, to
control the execution of the development program”.
Program Design
MD program design in this context refers to “its contents, which is training
courses, and the methods by with training is offered to employees”.
Opportunity for Skills Utilization
According to Noe (2000), opportunity to skill utilization refers to “the extent to
which the trainee is provided with or actively seeks experience with newly learned
knowledge, skill, and behaviors from the training program” (p. 122).
Effective Transfer of Knowledge
Effective transfer of knowledge refers to “the capacity of trainees to apply the
knowledge, skills and abilities gained from the training to their work practice” (Baldwin
& Ford, 1988).
Transfer Climate
“Workplace situations and consequences facilitating and supporting the transfer
of specific training to the work situation, such as the influence and the provision of
16
feedback from management, the attitudes of colleges toward training, and the support of
organizational policies and practices on training” (Burke & Baldwin, 1999).
Individual Initiative
According to D’Netto et al. (2008), individual initiative refers to “the active role
managers must play in their own development” (p. 05).
17
2.2 Management Development
Today business markets have become more unpredictable and competition in the
business markets is growing stronger. In this competitive business environment
organizations are also struggling to retain experienced, capable and skilled managers
(McClelland, 1994). One-way for an organization to increase the chance that its managers
will be effective is through MD. MD is realized as an important tool for attracting and
retaining skilled and competent employees. MD is a common activity of human resource
development (Desimone et al., 2002)
Desimone et al. (2002) defined MD as “an organization’s conscious effort to
provide its managers (and potential managers) with opportunities to learn, grow and
change, in hopes of producing over the long term cadre of managers with the skills
necessary to function effectively in that organization”( p. 513).
According to Jansen (2001), “MD is the system of personnel practices by which
an organization tries to guarantee the timely availability of qualified and motivated
employees for its key positions” (p. 106). In the given definition, the objective of MD is
to have the right type of employees, managers and specialist at the right time.
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2.3 Components of MD
MD has been described as having three main components, 1) management
educations, 2) management training, and 3) on-the-job experience (Desimone et al.,
2002). These components are explained as following,
2.3.1 Management Education
Management education can be defined as “the acquisition of a broad range of
conceptual knowledge and skills in formal classroom situations in degree-granting
institutions”. Programs dealing with basic management disciplines such as economics
and psychology tend to be lumped together under the heading of management education
(Sadler, 1998). These programs are usually longer rather than shorter in duration.
Management education continues to be an extremely popular activity (Desimone et al.,
2002). Management educations can be grouped into two categories:
1. Bachelor’s or master’s programs in business administration (B.B.A. or M.B.A)
offered at colleges and universities.
2. Executive education, which can range from condensed M.B.A programs to short
courses delivered by universities, private institutes, consulting firms, and
professional and industrial associations (Desimone et al., 2002).
2.3.2 Management Training
Management training emphases on providing particular knowledge or skills that
can be instantly applied by the managers (Desimone et al., 2002). Noe (2000) state “the
goal of training is for employees to master the knowledge, skill and behaviors
19
emphasized in training program and to apply them to their day to day activities (p. 04)”.
According to Desimone et al. (2002) “almost 90 per cent of organizations provide
training and on the job experiences as part of their efforts to develop managers. The
majority of organizations use a combination of externally provided and internally
developed courses and programs to achieve this goal” (p. 537).
Sadler (1998) stated that objectives of formal management training programs vary
considerably and they include:
1. Acquisition of knowledge
2. Learning of techniques
3. Developing interpersonal skills and related behavior patterns
4. Developing latent qualities within the individual
5. Changing attitudes
2.3.3 On-the-job Experiences
On-the-job experiences have a significant part in the learning and development of
employees (Desimone et al., 2002). Sadler (1998) stated that the frequently expressed
view “experience is the best teacher” is strongly supported by major research projects.
And many organizations use job assignments and experiences as part of their MD efforts.
Desimone et al. (2002) define on-the-job experiences as “planned or unplanned
opportunities for manager to gain self-knowledge, enhance existing skills and abilities, or
obtain new skills or information within the context of day-to-day activities” (p. 514) e.g.
mentoring, coaching, assignment to a task force or challenging jobs, action learning,
experience of other people (Sadler, 1998), job rotation, transfer, and promotion (Noe,
20
2000). Pointing out the major assumption of using on-the-job experience for employee
development, Sadler (1998) stated “development is most likely to occur when there is a
mismatch between the employee’s skills and past experience and the skills required for
the job”.
2.4 The MD Cycle
MD activities should always be results-oriented. To ensure that MD activities are
result oriented and achieving the desired goals, care must be taken when designing and
delivering MD programs. Stone (2005), Desimone et al. (2002) and Noe (2000): all these
authors propose that MD interventions involve a process, which includes a three- step
sequence: need assessment, MD program design and implementation, and evaluating the
program (see Figure 1). A detailed discussion of these steps is beyond the scope of this
study. However, these steps have been summarized as following:
Figure 1: MD process model
Source: adopted from Stone (2005) and Noe (2000)
MD Need Assessment
Designing & Implementing MD Program
Evaluating MD Program
21
2.4.1 Need Assessment Phase
The first step in managing MD is to determine MD needs and set objectives for
these needs. Desimone et al. (2002) define need assessment is “a process by which an
organization’s HRD needs are identified and articulated” (p. 128). Identifying the
purpose of need assessment, Prokopenko (1998) states that by effective need assessment
organizations can find out what T&D should be given to mangers, and what conditions
ought to be created in order to make sure that this training and development will have a
positive impact on organizational performance. Needs can exist at any of at least three
levels
Organizational analysis: “Organizational analysis is a process used to better
understand the characteristics of the organization to determine where training and
HRD efforts are needed and the conditions within which they will be conducted”
(Desimone et al., 2002, p. 131).
Task analysis: “Task analysis includes identifying the important tasks and
knowledge, skills, and behaviors that need to be emphasized in training for
employees to complete their tasks” (Noe, 2000, p. 51).
Person analysis: person analysis involves “1) determining whether performance
deficiencies result from lack of knowledge, skill, abilities or from motivational or
work-design problem, 2) identifying who needs training and, 3) determining
employees’ readiness for a development program” (Noe, 2000, p. 51).
In essence, any gap between expected and actual results suggests a need for training
and development.
22
2.4.2 MD Program Design and Implementation Phase
The second phase of the MD process involves designing and implementing MD
program. Program design is a process of developing training curricula and materials to
meet training and development needs (Butler, 1998). This step involves activities like
selecting the specific objectives of the program, developing lesson plan, developing
materials, selecting trainers and most appropriate methods and scheduling the program
(Desimone et al., 2002). The goal of the successful assessment and design phases is to
implement effective MD program, using most appropriate means or methods (Desimone
et al., 2002). After successful design and implementation of the MD program, the next
step is monitoring the program (Butler, 1998). Monitoring consists of those processes
performed to observe training and development program implementation and execution.
Effective monitoring identifies potential problems in the effective implementation and
smooth running of training and development program, so that corrective action can be
taken, when necessary, for the smooth running of the development program
2.4.3 Evaluation phase
Noe (2000) defined program evaluation as “the process of collecting the outcomes
needed to determine if training and development program is effective” (p. 130). Careful
evaluation of the MD program provides information on participants’ reaction to the
program, I.e. extent of their learning from the program, utilization of newly learned skills
by trainees back on the job, and whether the program improved the organization’s
effectiveness (Desimone et al., 2002). Noe (2000) states that a training and development
program should be evaluated:
23
To identify strengths and weaknesses. This confirms whether the T&D programs
are meeting the learning objectives or not.
To assess whether the content organization, and administration of the program
including the schedule, accommodations, trainers, and materials contribute to
learning and the use of training contents on the job.
To identify which trainees benefited from T&D program least or most.
To compare the cost and benefits of training verses non training investments.
To collect data to help in marketing future programs.
To compare the costs and benefits of different training programs to choose the
best program
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2.5 MD in Relation to Corporate Strategy
Organizations do not remain static. They grow, they diversify, they expend
overseas. Increased competition among organizations and changing conditions in the
global marketplace have forced many organizations to restructure, reorganize and rethink
their competitive strategies in an effort to compete or even just to survive. McClelland
(1994) stated “competitive strategy formulation is a mean by which an organization
develops a course of action so as to attain specific objectives which are considered
mandatory if the organization is to successfully compete in the marketplace” (p. 05).
McClelland (1994) stated “throughout the past decade, MD professionals have
been advocating the position that MD should has a more strategic role and be
incorporated as an integral part of the competitive strategy formulation process. Evidence
that this position has been gaining considerable acceptance by many senior executives is
clear (p. 05).”
2.5.1 MD as a Strategic Activity
In the initial years of the MD, basic objective of MD was extension to succession
planning. The successor or a candidate had to be trained for the higher level, the criteria
for which often emphasized formal qualifications such as professional experience and
education (Voleberghs, 1998). But now this view has given way. Top management now
often demands not only that HR and MD be fully aligned with company goals but that
they also generate demonstrable added value.
For more than 15 years, it has been contended that MD has a strategic role to play
in organizations. MD should be an integral part of strategic plans and strategic change
25
(Brown, 2005). MD has assumed new levels of importance as increasing numbers of
firms seek to integrate business strategy and HR practices (Burack, Hochwarter, &
Mathys, 1997). In several management training and education reviews, the excellent
performance of winning companies has been explained by their ability to make MD
central mean of running business (Fulmer et al., 2000). This means that these companies
have not only linked their MD interventions with their overall corporate strategies but
also successful in retaining is link over time. Newton and Wilkinsin (1995) stated “MD
has become a critical success factor on which strategic change is fundamentally
dependent for its success and for achieving organizational excellence” (p. 17). Brown,
2005 has defined strategic management development (SMD) as:
“MD interventions which are intended to enhance the strategic capabilities and
corporate performance of the organization” (p. 210).
Brown (2005) has demonstrated that SMD can act as a catalyst for change at a
strategic level, contributing to the generation and adoption of new strategic management
processes and strategies.
Berry (1990) presented a SMD model (see Table 1) based on the belief that “we
need managers who can deal with the critical issues confronting organization today” (p.
22). Berry (1990) stated “a distinction between this model and traditional ones has to do
with focus. Traditional MD focuses on individual effectiveness. After determining
managers’ weaknesses, organizations develop or find program to run them into strengths.
The alternative model focuses on organizational effectiveness. Organizations analyze the
organization’s ability to implement strategy and deal with business challenges, and then
design or select programs that address organizational weaknesses in those areas” (p. 22).
26
Table 1: Comparison of a traditional model for MD with Berry model
Traditional Model Berry Model
1. Educational: need for well-educated,
broad based managers
1. Consulting: need for managers who can
deal with strategic or tactical issues
2. Primary focus: individual effectiveness 2. Primary focus: organization and unit
effectiveness
3. Analysis of positions: competencies
required
3. Analysis of current business issues:
competencies required
4. Attended by individuals 4. Attended by management team
Source: Berry (1990)
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2.6 MD Interventions in the World
2.6.1 Strategic Perspective of MD
The commitment and willingness of organizations to invest in the training and
development of their employees is greater than ever. Today MD plays its role as a key
organizational process that helps the whole organization meet its future competitive
environment (Luoma, 2004). Jensen et al. (2001) found that many organizations are
unsuccessful in creating a strong link between MD interventions and organizational
strategies and policies. Fulmer et al. (2000) argued that the reason of effective
performance of successful companies in the world is making MD a central means of
running business. For example in the paper of Unilever, Reitsma (2001) has presented a
comprehensive discussion on MD in Unilever and stated “Unilever uses MD as a
strategic tool to help the organization meet its short and long term goals” (p. 131). The
companies like 3M have integrated their strategy of global competition into their MD
program (Seibert et al., 1995; cited in Desimone et at., 2002). Berry (1990) reported that
Coca-Cola has successfully linked MD programs to strategies, challenges, or problem of
the organizations. Melum claims “in the United States, 90 per cent of the top 100
companies include development within the corporate strategy, mission, goals and values
strategies” (as cited in D’Netto et al., 2008).
28
2.6.2 The Volume of MD Activities
Heraty and Michael (2001) stated “the level of MD, as measured by the number
of days per annum, has increased in recent years” (p. 60). Heraty and Michael (2001)
assessed the level of MD interventions in Ireland and reported that the mean number of
management training days per annum in Ireland now stands at 4.5 days and the results
were in consistent with evidence from other European countries. In a large scale survey
of MD in UK, Mabey and Thomson (2000) stated “there are signs that attitudes towards
the importance of management training and development in the UK are changing for the
better (p. 272), and picture emerging can be summarized as reasonably progressive in
terms of overall MD activities, when compared with that a decade ago” (p. 283). They
found that average number of days per annum training reported per manager in the UK
organizations were 5.5 days.
2.6.3 Common MD Methods
During the 20 years, many innovative methods of MD have been developed,
tested and adopted. During late 1990s, MD facilitatirs could count somewhere between
70 to 100 methods and techniques of MD described in books and training manuals
(Prokopenko, 1998). The number of techniques is on rise.
In a large scale survey of MD in UK, Mabey and Thomson (2000) found “a wide
range and usage of both internal and external formal method of MD reported by mangers:
Of the three main formal methods reported by HRD managers, time off to go on external
courses ranks highest, followed by seminars, then formal qualifications” (p. 278). They
also found that in UK, “the most frequently cited method of informal MD was learning
29
on-the-job. Coaching was the next most mentioned method; round half of the sample also
referred to use of mentors, job observation and in-company job rotation for developing
managers” (p. 279). Mabey and Thomson (2000) stated that there is a noticeable shift in
the style of MD interventions in UK organizations as compere to past. Today mostly
organizations use tailored, action learning, on-the-job methods to development their
managers.
2.6.4 Outcomes of MD
In order to assess the outcomes of MD in UK organizations, Mabey and Thomson
(2000) asked from the respondents “how successful do you believe the organization’s
current MD practices are in achieving their objectives and how would you rate the impact
of MD on the organization”? They found that 41 per cent of HRD managers were
modestly satisfied with the success of MD (mean score of 5.9 on a 10 point scale) and
nearly half rated the impact of MD on the organization as high (mean score 6.2 on a 10
point scale) (p. 281). On overall basis, picture of MD depicts that the outcomes of MD
are mediocre.
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2.7 Banking Sector of Pakistan
Demand for wide range of financial products in Pakistan is rapidly increasing due
to growth in urbanization, increase in standard of living, increased consumption and
favorable economic climate. Khan (2004) states that “Pakistan’s banking and financial
sector is much stronger today as compared to the recent past and also in comparison to
other countries in the Asian Region”. In a short period of time (CY2000-05), Pakistani
banking sector has been converted from a slow and government-dominated sector to an
active, profitable and competitive industry. The banking sector of Pakistan contains
different institutions like central bank, commercial banks, Islamic banks, micro finance
banks to fulfill the requirements of different sectors. According to SBP (2010), total
number of banks operating in Pakistan are 61 which are categorized in Table 2.
Table 2: Number of banks operating in Pakistan
Category of Banks Number of Banks
Central Bank 1
Nationalized Scheduled Banks 3
Specialized Banks 4
Private Scheduled Banks 24
Investment Banks 14
Micro Finance Banks 9
Islamic Banks 6
Source: SBP (2010)
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2.8 MD in Banking Sector of Pakistan
Today networked banking facilities are available in most of the Pakistani cities.
Number of opportunities in banking sector has also increased. Due to the rapid expansion
of the banking sector, the need of MD in this sector has also increased. History of MD in
Pakistan is about 60 years old. In banking industry of Pakistan public and private sectors
are operating their business and MD programs are integral part of overall development
plans of all banks of both sectors. Two prominent MD institutes in banking sector of
Pakistan are National Institute of Banking and Finance (NIBAF) and Institute of Bankers
Pakistan (IBP).
2.8.1 NIBAF
The SBP since its foundation has played a founding role in the sphere of banking
training, both for its own members and for the banking industry of Pakistan. NIBAF was
established as a Private Limited Company on 8th March 1993 and was sponsored by the
erstwhile “Pakistan Banking Council” (PBC). In 1997 SBP took over NIBAF. The main
purpose of NIBAF is to provide training and develop services to human resources of SBP
and its subsidiaries. NIBAF also offer its services to assist other financial institutions,
international and national banking organizations, and governments in their T&D
interventions. NIBAF also offers international trainings annually.
32
NIBAF Core Functions
Following are the core functions of NIBA:
Designing and developing training and development modules/programs.
Preparation and publications of training material.
Delivering international and domestic training programs.
Evaluation of programs.
Providing support for seminars and workshops and training programs.
NIBAF also provide support and cooperation by facilitating a number of institutions
in their T&D interventions. A number of training and development programs were held in
FY2009 at NIBAF Islamabad and Karachi campuses. During FY 2009 NIBAF hosted
105 training weeks for different financial institutions and more than 5900 managers
participated in those training and development programs. During FY 2009 the
stakeholders who availed NIBAF training and development services included Meezan
bank, Habib Bank Ltd., Askari bank, Union Bank Ltd., Khushali Bank, National Bank
Pakisan, NTS, M/S FINCON Inc., Bank Al Habib, IBP, COMSATS, LMDA, Finance
Division Government of Pakistan, Asia Foundation, M/S Event Management, M/S Sidat
Hyder Morshed Associates etc.
2.8.2 IBP
In 1951 with the partnership of the Institute of Bankers (UK) IBP was
incorporated. This is also a renowned institution devoted to provide technical T&D
services for the banking sector/industry in Pakistan. The mission of IBP is “to train and
33
develop a sound human resource base for the financial sector and to work for continuous
learning and professional development of bankers”.
IBP aims to provide a strong technical training platform for on-going personal
growth and a reliable yardstick for assessing the quality and depth of knowledge and
skills acquired. The breadth of training, education and professional development
programs at the institute cover all key banking disciplines including: operations, branch
banking, consumer, credit, risk, compliance, SME, governance, Islamic Banking,
microfinance etc.
IBP offers a wide range of training programs that cater to the financial services industry.
1. Effective branch management
2. Certified bank tellers
3. Branch fraud risk management program
4. Branch fraud investigation and reporting
5. Branch operations specialist
6. Bank risk management
7. Effective time management
8. Audit report writing
9. General banking etc.
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2.9 Measurement of MD effectiveness
Organizations spend millions of dollars on MD programs every year to make their
executives and managers more capable, but few of them affect the organization’s ability
to compete (Berry, 1990). Sugrue (2003; cited in Kirwan & Birchall, 2006) reports that
the expending of US organizations on education and T&D of employees is more than 2.2
per cent of payroll. Bunch stated “in the USA annual training and MD budget has been
estimated to be from $55.8 billion to as much as $200 billion and is likely to increase” (as
cited in Martin, 2009, p.520). Kirwan and Birchall (2006) argue “the value that
organizations derive from what they spend on training and development interventions is
not encouraging”.
The concept of organizational effectiveness is encountered repeatedly in the
literature. Steers argued “a meaningful way to understand the abstract idea of
effectiveness is to consider how researchers have operationalized and measured the
construct in their work” (as cited in D’Netto et al., 2008, p. 04). By "construct" he means
an abstract idea which is based on the hypothesis that several variables will consistently
fit together to form a unified whole. D’Netto et al. (2008) defined MD effectiveness as
“extent to which MD programs have yielded desired outcomes”. Effective MD enhances
organizational performance, achieving its goals and it will lead to beneficial outcomes for
the organization (Meldrum & Atkinson, 1998). “Organization also benefits from higher
productivity, lower absenteeism and better customer services” (D’Netto et al., 2008). MD
programs help organization grow and adjust to changing environmental and business
circumstances (Meldrum & Atkinson, 1998). Effective MD also results in lower turnover,
increased job satisfaction, less stress, preparing employees and managers for greater
35
responsibilities, more awareness and helping them to manage their own and others’
careers.
2.10 Evolution models
A few theoretical models of MD have been put forward in the literature. These
models delve deeper into the formation of the strong link between MD and strategic
management. A detailed discussion of these models or studies is beyond the scope of this
study. However, the main contributions are summarized as following.
Burgoyne (1988), Mumford and Gold (1993), Burack et al. (1997) and Luoma
(2004) presented their models to clarify the anatomy of the strategic linkage between MD
and strategic management.
2.10.1 Burgoyne (1988)
Model presented by Burgoyne (1988) defines an evolutionary logic. This model
demonstrates that how an organization can gradually built a strong integration between
MD and strategic management. Burgoyne model suggests six levels of maturity that
organizations need to follow if they want to enhance MD’s role as a strategic activity.
Level 1: no systematic MD: No deliberate MD efforts in structural or
developmental sense, MD totally relays on natural and uncontrived processes.
Level 2: isolated tactical MD: MD activities are isolated, of either structural or
developmental kinds.
36
Level 3: integrated and co-ordinated structural and developmental tactics: The
specific MD tactics of career structure management and of learning, education
and training that impinge directly on the individual manager.
Level 4: an MD strategy input to corporate policy: A MD strategy plays its part in
implementing corporate policies through managerial HR planning.
Level 5: MD strategy input to corporate policy formation: MD processes feed
information into corporate policy decision-making processes.
Level 6: strategic development of the management of corporate policy: MD
processes enhance the nature and quality of corporate policy-forming processes.
2.10.2 Mumford and Gold (1993)
Mumford and Gold (1993) identified three basic approaches that organizations
utilize when managing MD in relation to their strategic purposes.
Type 1, “informal managerial”, includes “accidental learning processes, which occur
naturally in connection with (other) key managerial activities”. In this type MD has no
clear development objectives and MD is understructure in development terms
Type 2, “integrated managerial”, refers to “opportunistic processes where natural
managerial activities are structured in such a way as to make use of the already available
learning opportunities”. MD activities are planned beforehand and/or consequently
reviewed as learning experiences.
Type 3, “formalized development”, means “planned learning processes, which take place
away from normal managerial activities”. In this type MD has clear development
objectives and which are based on clear intention.
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2.10.3 Mumford (1994)
Mumford (1994) presented “the effectiveness triangle in MD (see Figure 2). This
describes what effective MD is based on, firstly, on awareness of effective managerial
behavior. Secondly, awareness of effective learning process must be a prime constituent.
Thirdly, development is most likely to arise from real work rather from abstract
knowledge or even simulation of real work. The triangle is equilateral: this means that all
three aspects are equally important. The point, literally, of this effectiveness triangle is
that the purpose of MD is not to have a particular kind of development, or even to
provide an effective learning process, but that these two both focus on and are pointed
towards effective managerial behavior. As Mumford (1994) argues that the triangle gives
emphasis to the desired end conclusive- effective managerial behavior.
Figure 2: The effectiveness triangle in MD (Mumford, 1994)
38
2.10.4 Burack et al. (1997)
Burack et al. (1997) also tried to elaborate the concept of strategic MD and identified
seven themes that they believe are common to strategic MD.
1. A linkage between MD and the business plans and strategies.
2. Seamless programs, which cut across hierarchical and functional boundaries.
3. A global orientation and a cross-cultural approach.
4. Individual learning focused within organizational learning.
5. A recognition of the organizational culture and ensuring that the MD design fits
within and creates or supports the desired culture.
6. A career development focus.
7. An approach built on empirically determined core competencies.
2.10.5 Luoma (2004)
Models of Burgoyne (1988) and Mumford and Gold (1993) highlight different
aspects of SMD. Burgoyne’s model emphasizes the depth of integration and the
progression in the management of the activity, whereas Mumford’s model emphasizes a
variety of forms integration may have and the nature of learning that results. Luoma
(2004) presented his model by merging together the above mentioned aspects of
Burgoyne and Mumford’s models. According to Luoma (2004) “three-stage model
distinguishes between concrete stages of development and organizes them so that they
reflect the progress towards higher-level integration between strategic management and
MD” (p. 647). The stages and their basic contents are as following.
39
Sporadic MD (levels 1 and 2, type 1).in sporadic MD, “MD is uncoordinated and the
target setting is vague. Line organization ownership of MD initiatives is weak. The
content of MD is only loosely coupled with specific development needs or future
aspirations of the organization. Learning benefits individuals rather than the
organization”.
Reactive MD (levels 2 and 3, type 3). In reactive MD, “MD is used as a response to
identified problems or anticipated failures in performance. MD follows technological,
financial or product/market related considerations of strategy. There is some consistency
in various MD initiatives, which represent mainly formal learning. MD is designed to
benefit the organization rather than individuals”.
Integrative MD (levels 4, 5 and 6, type 2). In integrated MD, “Various MD initiatives,
formal and non-formal, form an integrated whole. MD focuses on the key elements of
current strategy and/or addresses previously unidentified solutions or problems, which
might lead to novel strategies. MD’s input to business strategy is sought intentionally.
MD benefits both individuals and the organization”.
Luoma’s model of SMD is depicted in Figure 3.
40
Figure 3: Luoma's Model of SMD.
2.10.6 Strengths and Weaknesses of Existing Models
Despite the abundance of quality research in MD, theoretical MD models are
comparatively inadequate. Model presented by Burgoyne (1988) defines an evolutionary
logic and demonstrates that how an organization can gradually built a strong integration
between MD and strategic management. Model presented by Mumford and Gold (1993)
defines three basic approaches that organizations adopt to link MD to corporate strategy.
Work of Luoma (2005) reflects the progress towards higher-level integration between
strategic management and MD. The effectiveness triangle of MD presented by Mumford
(1994) gives emphasis to the desired effective managerial behavior. All these models and
work done by McClelland (1994), Brown (2005) and Berry (1990) focus on linking the
MD to strategic management. However, these models possess shortcomings in term of
their comprehensiveness because these studies do not focus on variables or factors
41
associated with MD effectiveness. A wide variety of factors affect MD effectiveness and
no comprehensive model had been put forward in the literature which can identify
variables associated with the MD effectiveness (D’Netto et al., 2008).
One other model that focuses on variables associated with MD effectiveness, is
that of D’Netto et al. (2008).
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2.11 D’Netto Model of MD Effectiveness
To fill this gap in literature D’Netto et al. (2008) presented their model of MD
effectiveness by examining relationships of constructs from previous empirical research,
shown in Figure 4.
As discussed earlier Cascio (2003), Prokopenko (1998), Desimone et al. (2002)
and Noe (2000) proposed a three-stage approach to MD that involves “assessment of
development needs, conducting the development program and evaluating the program”.
Based on this staged approach D’Netto et al. (2008) build their model, focused on
variables of first and third stages of the MD process. D’Netto model of MD effectiveness
specifically focuses on what happens before and after learning occurs. D’Netto model
postulates that “two group of variables, i.e. antecedent components, which deal with
issues in the pre-program phase, and post program components, which deals with follow-
up activities, are associated with the dependent variable, management development
effectiveness” (p. 04). Variables included in the antecedent components are
“organizational learning culture, individual initiative, top management support, link to
corporate strategy”. Variables in post-program components are “post-program evaluation,
line manager support and opportunity for skill utilization” (see Figure 4).
D’Netto et al. (2008) hypothesized 14 paths to have positive coefficients. Results
of their study supported the past research on T&D i.e. Chiaburu and Marinova (2005),
Tharenou (2001) and Tracey et al. (2001). Results of D’Netto et al. (2008) indicated that
all the hypothesized paths had positive path coefficients. D’Netto et al. (2008) found
“organizational learning culture plays a vital and basic role in the MD process, and is
positively associated with top management support, line manager support and post
43
program evaluation” (p. 13). They also found that individuals at all levels give
importance to MD programs if strong top and line management support is available.
Results of D’Netto et al. (2008) also emphasize that to be effective, MD must be linked to
corporate strategy, it must be systematic, and organizations should provide maximum
facilities to managers to apply newly learned skills which mean they found a direct
significant relationship between corporate strategy, opportunity for skill utilization, and
MD effectiveness.
Figure 4: D’Netto model of MD effectiveness [Source: D’Netto et al. (2008)]
44
2.11.1 Strengths and Weaknesses of D’Netto Model
The strength of D’Netto model is its comprehensiveness and its usability in MD
contexts. This model analyzes the key factors associated with MD effectiveness and the
strength of relationships of all those variables. However, as discussed earlier Cascio
(2003), Noe et al. (2000), Prokopenko (1998), Desimone et al. (2002) and Noe (2000)
proposed a three-stage approach to MD, based on this staged approach D’Netto et al.
(2008) build their model, their model focused on variables of first and third stages of the
MD process. As D’Netto et al. (2008) argue “many MD programs are conducted outside
the organization by MD providers; the organization does not have complete control over
the content of such programs” (p. 04).
Major shortcoming of D’Netto Model of MD effectiveness is that it does not
focus on second stage of MD process “conducting the development program”. All three
stages of MD process are equally important for a MD program to be effective or
successful, but D’Netto model ignored the second stage. Butler (1998), Desimone et al.
(2002), Noe (2000) and Chen and Sok (2006) all these authors argue that MD program
design, its proper implementationa and monitoring are key steps of second stage for a
MD program to be successful.
As Desimone et al. (2002) pointed that second step involves activities like
selecting the specific objectives of the program, developing lesson plan, developing
materials, selecting trainers and most appropriate methods and scheduling the program.
After proper implementation of the program, the next step is effective monitoring of the
MD program. D’Netto model of MD effectiveness did not focus on all these activities
and ignored the effects of these activities on the success or failure of the MD program.
45
D’Netto model correlates the variables of first and third stage of MD process but this
model does not represent that how the first and last stage of MD process is correlated
with the second stage and how does second stage affect the overall results of MD
effectiveness?
46
2.12 Conceptual Framework
D’Netto Model of “MD effectiveness” provided framework for measuring MD
effectiveness. As discussed above that the D’Netto Model of MD effectiveness does not
focus on second stage of MD process “conducting the development program”. All three
stages of MD process are equally important for a MD program to be effective or
successful. So based on extensive literature review, two more variables related to second
stage of MD program are added in existing model of D’Netto et al. (2008). This model
proposes that three groups of variables, i.e. antecedent components, which deal with
issues in the “pre-program phase”, program design and implementation components,
which deal with issues in the “program running phase”, and post-program components,
which deal with “follow-up activities”, are associated with the dependent variable, MD
effectiveness (see Figure 5). Antecedent components include “organizational learning
culture, individual initiative, top management support, link to corporate strategy”.
Program design and implementation components include “MD program design and
effective monitoring”. Post-program components include “post-program evaluation, line
manager support and opportunity for skill utilization”. To support the hypothesized
relationships of variables of MD effectiveness model, researcher has incorporated
pertinent literature on MD. A summary of literature references regarding variables
included in the model is given in Table 3.
47
Table 3: Summery of key variables
Name of Variable Literature References
1. Management Development Effectiveness D’Netto et al. (2008); Meldrum &
Atkinson (1998)
2. Organizational Learning Culture McCracken and Winterton (2006); Bates
and Khasawneh (2005); Nelson (2002);
Bovin (1998);
3. Top Management Support Mondy (2008); Sadler (1998); Goravan,
Costine and Heraty (1997)
4. Line Manager Support D’Netto et al. (2008); Luoma (2005);
Gumuseli and Ergin (2002); Reitsma
(2001); Noe (2000)
5. Individual Initiative D’Netto et al. (2008); Paauwe and
Williams (2001); Boydell (1998)
6. Opportunity for Skill Utilization Desimone et al.(2002); Kirwan & Birchall
(2000); Neo (2000); Hall (1995 cited in
D’Netto et al. 2008);
7. Link to Corporate Strategy Brown (2005); Luoma (2004); Paauwe and
Williams (2001); Jensen et al. (2001);
Burack et al. (1997); McClelland (1994);
Mumford and Goal (1993); Berry (1990);
Burgoyne (1988).
8. MD Program Design Chen and Sok (2006); Berry (1990);
48
9. Monitoring and Evaluation Phillips and Phillips (2001); Noe (2000);
Campagna (1998); Easterby-Smith (1998);
Goravan et al. (1997); Phillips (1995);
Kirkpatrick (1983)
49
Figure 5: Conceptual framework of present study
Note: Fifteen paths are hypothesized to have positive path coefficients
50
2.12.1 Dependent Variable
MD Effectiveness
D’Netto, et al. (2008) defined MD effectiveness as “extent to which MD
programs have yielded desired outcomes” (p. 04). Effective MD enhances organizational
performance, helps in achieving its goals and it will lead to beneficial outcomes for the
organization (Meldrum & Atkinson, 1998). Effective MD results in lower absenteeism,
higher productivity, and better customer services (D’Netto et al., 2008), increased sales
and more satisfied customer (Noe, 2000). Newton and Wilkinson (1995) state that
successful MD programs result in improved communication, improved quality of service
delivery, improved morale and improved decision making. Prime purpose of MD is
effective managerial behavior (Mumford, 1994).
Mighty and Ashton (2003) found that MD programs help employees to solve
problems, manage change, resolve conflicts, increased ability to deal with future
management challenges, communicate and think critically. MD programs also help
organizations to grow and adjust to changing environmental and business circumstances
(Meldrum & Atkinson, 1998). Further effective MD results in “higher job satisfaction,
lower turnover, less stress resulting from skill inadequacies” (D’Netto, 2008), preparing
employees and managers for greater responsibilities, better planning and time
management, improved customer relation, better focus on customer needs, reduced
queues, revenue growth, increased competitiveness, improvements in productivity and
decreased unit cost (Winterton & Winterton, 1997). Dimensions of MD effectiveness
used to measure MD effectiveness in Pakistani banking sector are given in table 4.
51
Table 4: Dimensions of MD effectiveness
S/N MD effectiveness dimensions Literature references
1 Increased employee motivation D’Netto et al. (2008)
Winterton & Winterton (1997)
2 Increased job satisfaction D’Netto et al. (2008)
3 Increased morale among employees Newton and Wilkinson (1995)
4 Reduced stress level among employees D’Netto et al. (2008)
5 Reduced employees’ turnover D’Netto et al. (2008)
Winterton & Winterton (1997)
6 Higher productivity and financial gain D’Netto et al. (2008)
Meldrum & Atkinson (1998)
7 Increased capacity to adopt new technology Winterton & Winterton, (1997)
8 Less employees’ grievances D’Netto et al. (2008)
9 Better customer services D’Netto et al., (2008)
Winterton & Winterton (1997)
52
2.12.2 Independent Variables
2.12.2.1 Antecedent Components
Antecedent components refer to pre-program variables that are under the control
of the organization. As D’Netto et al. (2008) argue “organizational learning culture,
individual initiative, top management support and link to corporate strategy are likely to
enhance MD effectiveness” (p. 04).
Organizational Learning Culture
D’Netto et al., (2008) built their model on the premise that organizational learning
culture plays a vital role in the MD process. Schein (1990) defines the organization
culture as “the values and norms shared by members of a social unit”. It is argued that
every organization is to some degree a learning organization but the degree or level of
learning of different organizations may be different i.e. faster, slow or completely.
According to Pedler et al., “An organization, which facilitates the learning of all of its
members and continuously transforms itself is a learning organization” (as cited in Bovin,
1998, p. 363). Bates and Khasawneh stated “an organizational learning culture becomes
important in the consideration of innovation because it enables an organization to
anticipate and adapt to the dynamics of a changing environment. In fact, an
organizational learning culture has been characterized as one in which all organizational
members value learning and strive for high performance through the application of
learning to progressive, innovative work” (p. 98).
53
Leadership and MD must be interlinked into the organizational culture and
become part of the everyday language (Nelson, 2002). D’Netto et al. (2008) argue “this
will help to create a continuous learning organization, resulting in intellectual and
emotional growth. Strong leadership is required from senior management to help the
organization grow into a learning organization” (p. 05). When organizations have strong
learning culture, management appears to give priority to MD efforts (McCracken &
Winterton, 2006). Researcher, therefore, predicts that in a learning culture top (H1) and
line managers (H2) support the MD activities, have a positive attitude towards MD and
perceive it as a priority.
Bates and Khasawneh (2005) stated “learning-oriented culture can substantially
influence organizational effectiveness. Organizational learning culture emphasizes the
open exchange of information and ideas in ways that facilitate learning and its creative
application” (p. 98). Bates & Khasawneh (2005) asserted that attitudes, practices and
values of learning organizations support a constant process of learning in those
organizations (Bates & Khasawneh, 2005). A learning organizational culture will
facilitate a move toward double-loop learning as opposed to single-loop learning. Single-
loop learning takes place when the organization responds to information by correcting
practices, but double loop learning occurs when errors are corrected by changing the
governing values and then the actions which mean where if organization is able to search
for underlying causes, such as by questioning existing norms (Argyris, 2002). D’netto et
al. (2008) stated “organizational learning takes place as a result of the constant evaluation
of activities, practices and procedures in the organization. As evaluation and knowledge
management are key components of organizational learning” (p. 05), researcher,
54
therefore, predicts a positive association between organizational learning culture and
program monitoring & evaluation (H3).
H1: Organizational learning culture is significantly associated with top management
support.
H2: Organizational learning culture is significantly associated with line manager support.
H3: Organizational learning culture is significantly associated with program monitoring
and evaluation.
Individual Initiative
D’Netto et al. (2008) define individual initiative as “the active role managers must
play in their own development” (p. 05). Goleman (1999, cited in D’Netto et al., 2008)
found that 80% of the senior managers attending development program feel themselves
captives of the HR department. Further he suggests the managers should assess their own
level of readiness to learn. As defined by Paauwe and Williams (2001), a “pull strategy of
learning” where development is not organized by the organization or by the MD
providers but is provided on request of the managers related to a strong felt need.
Managers learn most when they are ready to learn which means when managers
themselves feel that their previous knowledge and skills are no longer useful in current
situation, only then they should be sent on training.
To remain more competitive in job market, individuals have to take more
responsibility for their own development. Success in MD programs cannot be achieved
without strong elements of self-development. Any formal T&D program can produce
55
anticipated outcomes when a person is adequately motivated and organized to his/her
own development (Boydell, 1998). Hence, researcher predicts a significant association
between individual initiative and MD effectiveness (H13).
H13: Individual initiative is significantly associated with MD effectiveness.
Top management support
Support and commitment of top management to MD is essential for effective MD
(Mondy, 2008; Sadler, 1998). Executives responsible for MD are among the most able
executives in business with great potential for promotion. Top management provides
weight, authority and status to MD activities (Sadler, 1998). Goravan, Costine and Heraty
(1997) argue that it is the primary responsibility of top management to create and sustain
a positive attitude to T&D in all its manifestation, determine training and development
objectives and policies, in consultation with the training specialists, be personally
associated with and involved in formal training and developments events, periodically
review the effectiveness of training and development process.
Top management should provide resources needed to enable the training and
development function to operate effectively, i.e. budget allocation, people, facilities, time
etc. And the temptation to cut this allocation back in leaner time should be strongly
resisted (Sadler, 1998). Reitsma (2001) stated that to have depth and breadth of talent
within the business, organizations need to develop their employees. Support from top
management for MD effectiveness enhances both individual initiative for self-
development (H7) and line manager support (H4) for such programs.
56
Research works by Vicere (1998) and Flumer et al. (2000) have reported a trend
towards increased investment in MD. The reasons for this development are more
demanding markets for products and services, growing technological capabilities,
structural changes and decentralization, changing nature of employer- employee relations
etc. (Luoma, 2004). D’Netto et al. (2008) stated “this positive trend indicates that top
management is recognizing the importance of MD; it is likely that such programs will be
linked more closely to corporate strategy (H5). As organizations increase their
expenditure on MD, they are also likely to provide greater opportunities for trainees to
utilize the newly acquired knowledge and skills in the workplace (H6)” (p. 06).
H4: Top management is significantly associated with line manager support.
H5: Top management is significantly associated with link to corporate strategy.
H6: Top management is significantly associated with opportunity for skill utilization.
H7: Top management is significantly associated with individual initiative.
Link to Corporate Strategy
McClelland (1994) argues “many organizations do not consider MD and related
issues to be part of their competitive strategy formulation processes. However, those that
do have found it to be of value in their efforts to gain, as well as maintain a competitive
advantage” (p. 11).
Organizations can enhance effectiveness of their MD intervention if MD
programs goals are linked to corporate strategy and HR objectives (Brown, 2005). Jensen
(2001) found that many organizations are unsuccessful in building a strong link between
57
MD policy, organizational strategy, and management activities. Berry (1990) stated that
MD programs do not any value to corporate strategy, if the programs are not linked to the
corporate strategies, vision, mission or challenges or programs focus on individuals.
Tregoe and Zimmerman (1984) stressed the involvement of HR departments during the
strategic-planning process. The HR department should base any new programs on the
needs identified by the senior executives themselves (Paauwe & Williams, 2001). Melum
stated “In the United States, 90 per cent of the top 100 companies include development
within the corporate strategy, mission, goals and values strategies” (as cited in D’Netto et
al., 2008, p. 07).
According to McClelland (1994) “organizations which move to develop and
integrate SMD into their competitive strategy formulation process, will find that they
have a greater degree of flexibility in the allocation and efficient usage of their
managerial talents while becoming effectively proactive to constantly changing market
conditions” (p. 12). The objective of MD is to help individuals and organizations to
compete more successfully, now and in the future (D’Netto et al., 2008).
Organizations which develop link between MD and corporate strategy, design or
select program that address organizational weaknesses, help participants confront reality,
contents of MD courses relate specifically to the organization’s operating strategies, its
vision, and its short-term objectives, the program design recognizes the participants that
what they are learning is different from their existing knowledge and skills and
participants attend the program out of personal or organizational interest (Berry, 1990).
Hence, researcher predicts that link to corporate strategy will be positively linked with
MD program design (H12).
58
H12: Link to corporate strategy is significantly associated with program design.
2.12.2.2 Program Design and Implementation Components
Program design and implementation components refer to variables associated
with actual running of the MD program. Researcher believes that MD program design
and effective monitoring and evaluation are likely to enhance MD effectiveness.
MD Program Design
MD program design, in this context refers to “its contents, which is training
courses, and the methods by with training is offered to employees”. For an effective T&D
program the course content of such program must be related to job requests and should
use methods of teaching that can help participant to involve in program practically. Chen
and Sok (2006) stated “good training permits participants to share real-world experiences
and apply just-learned skills rather than just to learn theory. A properly planned training
and development program ensure success and return on investment for training dollars”
(p. 846). Learning is the core of the MD interventions. Individuals have different learning
styles and also have a different learning needs; training and development program has to
be flexible enough to fit with the different learning styles of each employee (Chen & Sok,
2006).
Berry (1990) pointed out “why does MD program fail to add value to corporate
strategy? Rarely is there a connection to the company’s real business issues. Programs
fail to help participants confront reality. Very little learning takes place if people do not
recognize that what are they leaning is different from their current practices, and that the
59
knowledge and skills being offered are different from those they have” (p. 21).
Chen and Sok (2006) argue that a positive relationship exists between the
effectiveness of the training and development with its program’s design. In other words,
“a high level of course relevance to job requirements hints at a high level of training and
development effectiveness, and vice versa” (p. 851). Hence, researcher predicts a positive
association between appropriate program design and MD effectiveness (H15).
H15: Program design is significantly associated with MD effectiveness.
Effective Monitoring and Evaluation
Monitoring consists of those processes performed to “observe training and
development program implementation and execution so that potential problems can be
identified in a timely manner and corrective action can be taken, when necessary, to
control the execution of the development program”. Campagna (1998) argues that all
activities of training and development should be monitored to avoid any disturbance in
smooth running of program and these all are of crucial importance to the effective MD
process. The obvious benefit of monitoring is that variances in MD program can be
identified by constantly observing and measuring the performance of such programs.
Goravan, et al. (1997) state that top management should periodically review the
effectiveness of the training and development process in relation to the objectives set, and
update policies and objectives in line with changing organizational circumstances (in
consultation with training specialist).
60
Post program evaluation refers to “the process of collecting the outcomes needed
to determine if training and development program is effective”. Noe (2000) argued that
organizations with high-leverage T&D interventions invest huge amount of money into
T&D programs and also evaluate those programs. Top executives and managers funding
the development programs demand that such programs show a return on the organization
investment in programs (Phillips & Phillips, 2001). Easterby-Smith (1998) argues that
evaluation of training and development programs determine that a certain program has or
has not, had an effect on trainee’s behavior.
Phillips & Phillips (2001) stated that number of factors have emphasised
organizations to conduct broad evaluation of T&D processes, i.e. exectives or top
management of companites demand for T&D programs evaluation data, rapidly
increasing competition for scarce resources within companies, growth in T&D budget,
failing of T&D programs to deliver the desired outcomes and demand by top
management that training shows a return on the organization investment in programs.
Post program evaluation is necessary to determine the extent to which trainees have
changed and have acquired knowledge, skills, attitude, behavior (Noe, 2000).
“The current focus on evaluation is apparent but few organizations understand the
importance and procedure of conducting evaluation” (Phillips & Phillips, 2001).
Desimone et al. (2002) argued that the most effective and popular T&D evaluation
framework is that of “Kirkpatrick evaluation framework”. His framework describes four
stages of evaluation, 1) Participant reaction: this stage identifies that did trainees like the
program and feel it was useful and effective? 2) Learning: this stage measures how much
knowledge and skills trainees acquired. 3) Behavior: this stages measures improvement
61
of trainees’ behavior and attitudes on the work place, 4) Results: measures business
results achieved by trainees such as the profitability and effectiveness of the organization
(Kirkpatrick, 1983). Phillips (1995) added the fifth level ROI in Kirkpatrick framework.
ROI compares the monetary value of the business impact with the cost for the program.
D’Netto et al. (2008) stated “Organizations that have a systematic follow-up evaluation
of MD are likely to benefit from this process” (p. 08). Desimone et al. (2002) state that
actions should be taken to evaluate the MD programs regularly and modify and update
the program as needs change. Hence, researcher predicts a positive relationship between
program monitoring & evaluation and program design. (H11).
H11: “Program monitoring and evaluation is positively associated with MD program
design”.
2.12.2.3 Post-Program Components
According to D’Netto et al. (2008) post program components refer to “activities
that organization must use in order to ensure that the new knowledge and skills acquired
in MD program are actually transferred to work place” (p. 07). Variables in this stage
include post-program evaluation (discussed in second stage), line manager support and
opportunity to utilize newly learned skills.
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Line Manager Support
Noe (2000) defines line manager support as “degree to which trainees’ managers
emphasize the importance of attending development programs and stress the application
of training content to the job” (p. 118). Support from the managers is a key work-
environment variable which has an impact on MD effectiveness (D’Netto et al., 2008).
Noe (2000) argues that line manager can support training and development activities and
there will be more transfer of training or learning if line manager provide greater support.
Luoma (2004) found that in order to ensure effective MD, line manager should actively
involve in all stages of MD processes, such as design, conduct, and evaluation.
Association of line manager with different stages of MD processes emphasizes that line
managers can play vital role in linking MD to corporate strategy. Hence, researcher
predicts that line manager support is significantly associated with link to corporate
strategy (H8).
Line managers can provide support to trainees by encouraging them to attend
training programs, goal setting, reinforcing use of learned capabilities, discussing
progress with trainees and providing opportunities to practice (Noe, 2000). If individuals
in the organization have more support from their managers they are likely to play more
active role for their self-development (Gumuseli & Ergin, 2002). Hence, researcher
predicts that line manager support is significantly associated with individual initiative
(H9).
In the paper of Unilever, Reitsma (2001) states that both HR department and line
managers are responsible for the development of their people. Line manager can enhance
the transfer of learning and ensure the training and development success by providing
63
opportunities to practice the newly learned skills (Noe, 2000). Therefore, researcher
predicts a significant link between line manager support and opportunity for skill
utilization (H10).
H8: Line manager support is significantly associated with link to corporate strategy.
H9: Line manager support is significantly associated with individual initiative.
H10: Line manager support is significantly associated with opportunity for skill
utilizations.
Opportunity for Skill Utilization
Opportunity to perform what has been learned back on the job is an important
element of the work environment (Desimone et al., 2002). And ensure the success of MD
(Kirwan & Birchall, 2000). D’Netto et al. (2008) stated “companies must reinforce the
behavioral changes by including employees in task and projects that help to stretch their
knowledge base. Noe (2000) define opportunity to skill utilization as “the extent to which
the trainee is provided with or actively seeks experience with newly learned knowledge,
skill, and behaviors from the training program” (p.122). Neo (2000) believed that trainees
who are given maximum opportunities to utilize newly learned skills on the work place
are more likely to retain learned skills than trainees given less opportunities.
If the opportunities to utilize the learned skills are not available in the
organization, the development programs could be wasteful expenditures. HRD strategy
should ensure that trainees have provided with opportunities to utilize their new skills and
knowledge if any real organizational benefit is to be expected (Desimone et al., 2002) and
likelihood of learning being transferred to the job increase if the MD is linked to the
64
organization strategy and MD becomes more beneficial (Hall, 1995 cited in D’Netto et al.
2008). Hence researcher predicts a significant link between opportunity to use new skills
and knowledge and MD effectiveness. (H14).
H14: Opportunity for skill utilizations is significantly associated with MD effectiveness.
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CHAPTER 3
RESEARCH METHODOLOGY
3.1 Introduction
The purpose of this chapter is to present the plan or blueprint of how the
researcher conducted the study to achieve its stated objectives. Aspects of the research
methodology that were addressed include the research design, brief description of the
population followed by a discussion of the sample and the determination of a proper
sample size, instrumentation, reliability and validity of the instrument, the process of data
collection needed to empirically test the conceptual framework, methods of statistical
analysis and finally limitations of the study.
3.2 Research Approaches
Based on the nature of the study and to explore the issue in depth two types of
research approaches were employed i.e. quantitative approach and qualitative approach.
The quantitative and qualitative measures included in the study were applied sequentially
which helped researcher to elaborate on and broaden the findings of one method with
another. As Cooper and Schindler (2003) state that a quantitative study can precede a
qualitative study and many researchers believe/recognize that qualitative research
compensates for the weakness of quantitative research and vice versa.
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3.2.1 Quantitative Approach
Quantitative research attempts to measure something precisely and answers
questions related to how much, how often, how many, when and who (Cooper &
Schindler, 2003). Quantitative methods are used to determine relationships of variables,
which can be proven through testing of hypotheses. The present study commenced with a
quantitative phase through which relationship between MD effectiveness and its
predictors was measured.
3.2.2 Qualitative Approach
Along with quantitative approach, qualitative analysis was also conducted by the
researcher to explore the qualitative aspects of the issue. Qualitative research approach
aims to in-depth understanding of a situation. The strength of qualitative research is its
ability to provide complex textual descriptions of how people experience a given research
issue. To collect the data regarding qualitative aspects of the issue, detailed semi-
structured interviews were conducted by the researcher.
3.3 Unit of Analysis
Current study is explanatory in nature and the survey of real setting is more
appropriate approach. Banking sector was selected for the main study. According to
Sekaran (2006) “unit of analysis refers to the level of aggregation of the data collected
during the subsequent data analysis stage” (p. 132). In any specific research, unit of
analysis could be individuals, groups, organizations, industry or countries. In this study,
the unit of analysis is managers working in banks. To explore the factors of effective
67
MD, only those managers were included in the research who had attended any MD
program.
3.4 Target Population
According to Sekaran, population refers to “the entire group of people, events, or
things of interest that the researcher wishes to investigate” (p. 265).The population of the
study included all managerial positions of all banks (public and private) working in
Pakistan. The planned population for the current study was all managers working in all
banks operating in the area of Rawalpindi/Islamabad. According to official website of
State Bank of Pakistan (SBP, 2010), 38 banks are operating in Rawalpindi/Islamabad.
From the official websites of these 38 banks, researcher found that a total number of 498
branches of these banks operating in the area of Rawalpindi/Islamabad out of which 69
branches belong to public sector and 429 belong to private sector banks (retrieved 1 May,
2010). Table 5 depicts the banks and their number of branches operating in Rawalpindi
and Islamabad (for more details see Appendix-B).
68
Table 5: Number of branches of banks operating in Rawalpindi and Islamabad.
s/n Name of Bank Branches in
Islamabad
Branches in
Rawalpindi
Total
Branches
1 Public Sector Banks 32 29 61
2 Specialized Banks 4 3 7
3 Private Banks 189 187 376
4 Islamic Banks 23 14 37
5 Foreign Banks 7 7 14
6 Micro Finance Banks 1 2 3
Total 256 242 498
3.5 Sampling Strategy
The population of the current study was divided into two subgroups i.e. public
sector and private sector. Stratified Random Sampling (SRS) technique was used to
include banking organizations in sample. Burns & Bush (2001) explained “SRS separates
the population into different subgroups and then samples all of these subgroups”.
According to Sekaran (2003) “in multivariate research (including multiple
regression analysis), the sample size should be several times (preferably 10 times or
more) as large as the number of variables in the study” (p. 296). Reisinger and Mavondo
(2007) argue “although there is no correct sample size for multivariate data analysis
technique such as structural equation modeling, recommendation is a minimum ratio of at
least five respondents for each estimated parameter, with a ratio of 10 respondents per
69
parameter considered most appropriate” (p. 52). Following the recommendations of
Reisinger and Mavondo (2007) and Sekaran (2003) it was decided to take a sample of
350 managers selected randomly. Proportional allocation was done to determine the
sample size in both categories of population i.e. public sector banks and private sector
banks.
Each sector has different number of branches in Rawalpindi/Islamabad, so
weighted average method was used in this study that is 100 percent weight given to
number of branches of banks in each category operating in Rawalpindi/Islamabad. Sector
wise details and distribution of sample size for each sector is given in Table 6.
Table 6: Sector wise details and distribution of sample
Sector Number of Branches Sample Size
Public Sector 69 48
Private sector 429 302
Total 498 350
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3.6 Data Collection Tools
Data was collected with the help of semi-structured interviews and research
questionnaire.
3.6.1 Semi-Structured Interviews
To explore the qualitative aspects of variables of interest semi-structured
interviews were conducted by the researcher. One face to face and nine telephonic semi-
structured interviews with human resource development (HRD) managers were
conducted to know the MD providers views regarding the variables of interest. Further
researcher conducted 15 in-depth interviews with trainees i.e. branch manager to know
the trainees’ views regarding the effectiveness of MD programs. Each interview lasted
appropriately 30 to 45 minutes.
3.6.2 Research Questionnaire
As discussed in chapter 2 “literature review” D’Netto’s Model of “MD
effectiveness” provided framework for measuring MD effectiveness. Based on extensive
literature review two more variables related to second stage of MD “program design and
implementation phase” were added in existing model of D’Netto et al. (2008) to develop
framework for the current study. The instrument used to measure the 8 variables of
D’Netto model was development by D’Netto et al. (2008). Few minor changes were
made in the existing questionnaire (for details see section 3.7). Based on extensive
literature review questionnaire was developed to measure two variables related to second
71
stage of MD program. All of scales were derived from the literature and were developed
to assess factors affecting MD effectiveness.
There were three main sections of the questionnaire. In the first section
demographic information of the respondents were collected. In second section,
respondents rated each of the question on a 7-point Likert scale (1= strongly disagree
through 7= strongly agree). Last section was consisting of an open-ended question in
which the respondents were asked their opinion regarding the issues related with
effectiveness of MD. All respondents were asked to take their current organization into
consideration while completing the questionnaire. Copy of questionnaire is provided in
Appendix A.
3.7 Measures of Dependent and Independent Variables
3.7.1 MD effectiveness
MD effectiveness was measured using a nine-item scale. Some new items added
in existing scale of D’Netto et al. (2008) were “MD has increased morale among
employees”, “MD has increased efficiencies in process, resulting in higher productivity
and financial gain” and “MD has increased capacity to adopt new technology and
methods”.
3.7.2 Organizational learning culture
Organizational learning culture was measure using a seven-item scale. Some new
items added in existing scale of D’Netto et al. (2008) were “my organization facilitate the
72
learning and personal development of all employees”, “continuous process of
organizational transformation is prevalent in my organization” and “individual members
are encouraged to learn and to develop their full potential”
3.7.3 Individual initiative
Individual initiative was measured using a seven-item scale. Some new items
added in existing scale of D’Netto et al. (2008) were “I am motivated to learn in my
every management development program” and “I am always ready to learn whenever I
recognize that my past experience is no longer useful”.
3.7.4 Top management support
Top management support was measured using a seven-item scale. Some new
items added in existing scale of D’Netto et al. (2008) were “senior managers are
personally involved in formal in-house management development programs”, “top
management provides adequate resources needed to enable management development
function to operate effectively” and “top management determine management
development objectives, polices in consultation with training specialists”.
3.7.5 Link to corporate strategy
Link to corporate strategy was measured using a seven-item scale. Some new
items added in existing scale of D’Netto et al. (2008) were “development needs are tied
to the business strategy” and “organization’s business issues are discussed with HR
department”.
73
3.7.6 Post-program evaluation
Post-program evaluation was measured using a seven-item scale. Some new
items added in existing scale of D’Netto et al. (2008) were “In my organization after
completing management development program, evaluations are carried out” and
“evaluation was carried to measure extent to what I have changed and acquired new
knowledge, skills and behavior”.
3.7.7 Line manager support
Line manager support was measured using a seven-item scale. Some new items
added in existing scale of D’Netto et al. (2008) were “In my organization managers
encourage trainees to play an active role in self-development” and “managers assist
trainees in goal setting and planning their management development”.
3.7.8 Opportunity for skill utilization
Opportunity for skill utilization was measured using a seven-item scale. An
example item was “My organization provides me with opportunities to use my new
knowledge and skills”.
3.7.9 Program design
Program design was measured using a nine item scale. An example item was
“selected methods of management development have direct connection to the company’s
real problem and issues”.
74
3.7.10 Effective monitoring
Effective monitoring was measure using a seven-item scale. An example item was
“during training secession my performance was monitored periodically by my
organization”.
3.8 The Pilot Testing and Results
Characteristic of a good measurement instrument is that the instrument must be
perfect indicator of what a researcher is interested in assessing or measuring. It is
necessary for any empirical research work to examine the reliability and validity of
measurement instrument. Measurement instrument having maximum validity will show
more accurate results that reveal true characteristics of the population. Reliability is the
requirement that the application of the valid measurement to the different individuals and
groups under different sets of conditions may result in the same conclusion. To confirm
reliability and validity of the quantitative research instrument pilot study was conducted
by the researcher. A sample of 90 managers working in different banks of
Rawalpindi/Islamabad was chosen randomly by the researcher. The respondents selected
for the pilot study were chosen from the target respondents of the main study. Researcher
approached the respondents at their work place and requested to fill out the questionnaire.
A total number of 80 managers filled the questionnaire; a response rate of 89 percent.
75
3.8.1 Validity of the Quantitative Research Instrument
The pilot study assisted in analyzing the validity of the research instrument.
3.8.1.1 Construct Validity
Construct validity is measured in term of how well the items selected for the
construct actually measures the construct (Coldwell & Herbest, 2004). According to
Cooper and Schindler (2006) and Sekaran (2006), researchers can demonstrate construct
validity using correlation coefficients, factor analysis or simply by judgment. Firstly, this
study utilized an extensive literature review in the relevant domain which gives strong
construct validity to the constructs that are being empirically measured. Secondly,
correlation analysis was conducted to further confirm the construct validity. Sekaran
(2006) sates that a correlation matrix indicates nature, direction, strength, and
significance of the relationships of all the variables in the study.
Table 7 presents the correlation among all latent constructs. Examination of the
intercorrelation matrix shows that each construct is significantly correlated with the other
constructs and none of the correlations are above 0.73. Therefore, multicollinearity
problem is fairly low, as Hair, Anderson, Tatham, and Black (2006) state that results can
be affected by multicollinearity and correlations exceeding 0.80 can be indicative of
problems but value exceeding 0.90 should always be examined.
76
9 1.00
8 1.00
0.65
**
7 1.00
0.62
**
0.49
**
6 1.00
0.63
**
0.64
**
0.66
**
5 1.00
0.39
*
0.46
**
0.69
**
0.44
**
**. C
orre
latio
n is
sig
nific
ant a
t the
0.0
1 le
vel (
2-ta
iled)
. *.
Cor
rela
tion
is s
igni
fican
t at t
he 0
.05
leve
l (2-
taile
d).
4 1.00
0.56
**
0.25
*
0.29
*
0.58
**
0.45
**
3 1.00
0.49
**
0.73
**
0.57
**
0.58
**
0.67
**
0.37
*
2 1.00
0.64
**
0.26
*
0.26
0.65
**
0.40
*
0.41
*
0.31
*
Tabl
e 4:
Cor
rela
tion
mat
rix o
f pilo
t stu
dy
1 1.
00
0.46
**
0.36
*
0.52
**
0.29
*
0.56
**
0.47
**
0.29
*
0.45
**
Var
iabl
es
1.
Line
Man
ager
Sup
port
2.
Mon
itorin
g an
d Ev
alua
tion
3.
MD
Pro
gram
Des
ign
4.
Opp
ortu
nity
for S
kills
Util
izat
ion
5.
MD
Eff
ectiv
enes
s
6.
Link
to C
orpo
rate
Stra
tegy
7.
Indi
vidu
al In
itiat
ive
8.
Org
aniz
atio
nal L
earn
ing
Cul
ture
9.
Top
Man
agem
ent S
uppo
rt
77
3.8.1.2 Content Validity
According to Cooper and Schindler (2006) “content validity of a measuring
instrument is the extent to which it provides adequate coverage of the investigative
questions guiding the study” (p. 318). Content validity can be judged by panel evaluation
or simply by judgment (Cooper & Schindler, 2006 and Sekaran, 2006). Procedurally,
research instrument was presented for review to three HRD experts. In preparation of the
final version of the questionnaire, feedback received from three HRD experts was taken
into consideration.
3.8.1.3 Face Validity
Burns and Bush (2001) stated that face validation is concerned with the “degree
to which a measurement looks like it measures which it is designed to measure” (p. 333).
The face validity of the quantitative research instrument was judged through written and
oral comments of the participants of pilot study regarding the clarity of questions and
instrument, and steps regarding rewording and re-sequencing questions were taken. The
research instrument was also presented for review to three HRD experts. In preparation of
the final version of the questionnaire, feedback received from three HRD experts was
taken into consideration.
3.8.2 Reliability of the Quantitative Research Instrument
Sekaran (2006) stated “reliability of a measure is an indication of the stability and
consistency”. According to Sekaran (2006) researcher can measure reliability of the
research instrument through internal consistency method by computing the Cronbach’s
alpha. Internal consistency reliability confirms the consistency of respondents’ answer to
78
all the items in a measure and items are independent measures of the same concept
(Sekaran, 2006). The Cronbach’s alpha coefficient value of the entire research instrument
was 0.92. In Table 8 it is depicted that the Cronbach’s alpha coefficient values for
constructs ranged from 0.68 to 0.93. Burns and Bush (2001) and Sekaran (2006) state
“the closer the reliability coefficient gets to 1.0, the better” (p. 307). In general, value of
0.60 deemed the lower limit of acceptability (Hair at al., 2006). In brief, the higher the
Cronbach’s a value of a construct, the higher the reliability is of measuring the same
construct. Cronbach’s alpha values of this pilot study confirmed that the scales used in
the quantitative research instrument are appropriate for the actual study.
79
Table 8: Internal Reliability of Scales
Constructs/Scales Cronbach’s
Alpha
Number of
Items
Management Development
Effectiveness
0.88 9
Organizational Learning
Culture
0.90 7
Individual Initiative 0.68 7
Top Management Support 0.93 7
Link to Corporate Strategy 0.91 7
Line Manager Support 0.91 7
Opportunity for Skill
Utilization
0.92 7
MD Program Design 0.92 9
Program Monitoring &
Evaluation
0.85 14
80
3.9 Data Collection
After finalization of the research questionnaire and ensuring the validity and
reliability of the instrument data collection from sampled population started in May 2010
and completed in October 2010. Data collected through survey was cross-sectional in
nature. The participants were approached in their job settings and were briefed about the
nature and purpose of the research. After the willingness of participants, the MD
effectiveness questionnaire was handed over to them. In order to further enrich the data
10 follow-up interviews with HRD managers and 15 interviews with trainees (bank
managers) were carried out in the same period of time.
3.10 Response Rate
The data for this study include responses from 33 banking organizations in
Pakistan. In total 370 questionnaire were distributed out of which 320 questionnaires
were distributed in private sector banks and 50 were distributed in public sector banks. A
total of 177 filled questionnaires were received. The response rate was 50.57 percent.
However, two respondents partially responded and seven were treated as outlier because
those were substantially different from the other observations (as suggested by Hair et al.,
2006) so those total nine questionnaires were dropped out. Thus effective responses from
public sector were 17 yielding 34 percent and from private sector were 151 yielding 47
percent. In total effective responses were 168 yielding 45 percent. Detail of effective
response rate is given in Table 9.
81
Table 9: Effective response rate.
Sector Questionnaires Distributed
By Hand By Email Total
Targeted
Sample
Achieved
Sample
Response
Rate
Public 25 25 50 48 17 34
Private 260 60 320 302 151* 47
Total 370 350 168 45
*System missing questionnaires are added in private sectors banks
A total of 168 questionnaires were chosen for analysis. Hair et al. (2006) argue
that although there is no correct sample size for structural equation modeling technique,
recommendations are for a size ranging between 100 to 200 (p. 605), with increases
occurring if misspecification is suspected, the model is overly large or complex. Hence
the sample size of 168 is under the critical range suggested by Hair et al. (2006).
3.11 Statistical Techniques
Various statistical techniques were employed to examine the data such as
descriptive statistics and Structural Equation Modeling (SEM).
3.11.1 Descriptive Statistic
Descriptive statistics techniques such as frequency distribution, arithmetic mean,
standard deviation were employed to reveal the general pattern of responses. These
techniques are used early in the analysis process and become bases for later analysis
(Burns & Bush, 2001).
82
3.11.2 SEM
To test the proposed complex model of MD effectiveness in the current study
SEM technique had been used. According to Hair et al. (2006) “SEM encompasses an
entire family of models known by many names, among them covariance structure
analysis, latent variable analysis, confirmatory factor analysis and simple LISREL
analysis are common” (p. 584). Reisinger and Mavondo (2007) describes SEM as “an
important multivariate technique which simultaneously estimates and tests a series of
hypothesized inter-related dependency relationships between a set of latent constructs,
each measured by one or more manifest variables” (p. 42). It has been widely used in a
number of disciplines, including psychology, sociology, economics, cross-cultural
research, environmental studies, marketing, tourism studies and management (Reisinger
& Mavondo, 2007). Researchers like Bulut and Culha (2010), D’Netto et al. (2008);
Garcia-Morales, Llorens-Montes and Verdu-Jover (2008); Chaiburu and Marinova
(2006); Cheng (2001) and Tracey et al. (2001) used SEM in the field of MD and reported
the benefits and effectiveness of SEM for MD research.
Cheng, 2001 states “SME functions have been found to be better than other
multivariate techniques including multiple regression, path analysis and factor analysis”
(p. 650). These multivariate techniques allow only single relationship between dependent
and independent variables (Hair et al., 2006) but human and behavioral issues in
management are more complicated and one dependent variable may be an independent
variable in other dependence relationship hence SEM is preferred technique. As Cheng
(2001) argued “SEM examines a series of dependence relationships simultaneously and
helps to address complicated managerial and behavioral issues”.
83
SEM has acquired hegemony among multivariate techniques, becomes the
preeminent multivariate method of data analysis and out of all the multivariate
techniques, SEM has been, and continues to be, the technique that is undergoing the most
refinement and extension (Hershberger, 2003). Schumacker and Lomax stated “SEM can
be used to examine the nature and magnitude of postulated dependence relationships and
at the same time assess the direct and indirect relations” (as cited in Reisinger &
Mavondo, 2007, p. 42).
The primary purpose of SEM is to test and analyze interrelationships among latent
constructs and their measured variables. SEM allows to model and test complex patterns
of relationships, including a multitude of hypotheses simultaneously as a whole. It allows
testing complex models for their compatibility with the data in their entirety, and allows
testing specific assumptions about parameters for their compatibility with the data
(Reisinger & Mavondo, 2007). The empirical relationships between all observed
variables are compared to the relationships implied by the structure of the theoretical
model which allows to assess whether the model fits the data well or not so well, the
model is or is not able to correctly reproduce relationships between particular variables
and provide suggestions for potential model improvements and these suggestions can
then be evaluated for interpretability and compatibility with an underlying theory.
84
3.12 Statistical Softwares
Computer software “Statistical Package for Social Sciences” (SPSS) 17th edition
was used for descriptive and statistics’ techniques. Statistical techniques like principal
component factor analysis, arithmetic mean, standard deviation and frequency
distribution were conducted in SPSS.
“Computer programs are important tools for the conduct of SEM. About 30 years
ago, Linear Structural Relations (LISREL) was essentially the only widely available SEM
program. The situation is now very different; however, as there are many other choices of
SEM computer programs including AMOS, CALIS, EQS, Mplus, Mx Graph, RAMONA,
and SEPATH, are openly available” (Kline, 2005). To test the predicted model of MD
effectiveness, SEM analysis was conducted using the LISREL program. LISREL is the
most widely used program for structural equation modeling. LISREL has found
applications across all fields of study and has become almost synonymous with SEM
(Hair et al., 2006). SEM techniques like confirmatory factor analysis, structural model
analysis, goodness-of-fit measures reliability and variance extracted were conducted with
the help of LISREL.
3.13 Researcher’s Interference
“An explanatory or correlational study is conducted in the natural environment of
the organization with minimum interference by the researcher with the normal flow of
work” (Sekaran, 2009). Extent of researcher’s interference has been minimal as
researcher developed the theoretical framework, collected the relevant data by
85
administering a questionnaire and conducting interviews of managers without interfering
with the normal activities in the banks, analyzed the data and came up with the findings.
3.14 Research Ethics
According to Sekaran (2009) “ethics in business research refers to a code of
conduct or expected societal norm of behavior while conducting research” (p. 17). Ethical
behavior pervades each step of the research process, while collecting data several ethical
issues be addressed, which include treating the data given by the respondent as strictly
confidential and guarding respondent’s privacy, personal or seemingly intrusive
information should not be solicited, self-respect of the participant in all aspects and
avoidance of enforcing the participant in case he or she takes time to respond, the honesty
and truthfulness of the researcher is the most important aspect needs to be considered
ethically (Sekaran, 2009). Cooper and Schindler (2006) state “the goal of ethics in
research is to ensure that no one is harmed or suffers adverse consequences from research
activities” (p. 116). Explaining study objective and benefits, explaining participant rights
and protections and obtaining informed consent are guidelines to safeguard against any
harm during research.
In this study it was ensured to give due considerations in the designing of
questionnaire and data collection. Therefore, a covering letter with the questionnaire was
also sent informing purpose of the study and explaining the basic terms and concepts that
were used in the main questionnaire. Managers were assured of confidentiality of data by
mentioning in the set of survey documents. Efforts were made not to put any question
that could reveal sensitive information. Before beginning of each qualitative interview,
86
purpose of the study was explained to the respondents. Respondents were also assured
through recommendation letter from university about confidentiality and cooperation.
87
CHAPTER 4
DESCRIPTION OF SAMPLE CHARACTERISTICS
4.1 Introduction
In order to get the clear picture of the sample biographical characteristics of the
sample of 168 respondents are presented in this chapter. Frequency tables are presented
to provide a description and summary of the dispersion of the respondents across the
demographic variables. Demographic variables that were measured from the respondents
were as follow,
Gender Age
Sector Region
Organization Occupational level
Educational Qualification Work Experience
Number of MD program attended
88
4.2 Description of the Sample By Means of Frequency Tables
Frequencies tables are part of the descriptive statistics. The frequency tables
presented for the biographical variables are as follow.
4.2.1 Gender
In Table 10, the distribution of male and female respondents is depicted. This
table of frequency shows that the majority of respondents in the study were male (n =
130), representing a total of 83 per cent, while 17 per cent represents female (n = 26)
respondents.
Table 10: Frequency distribution: Gender
Frequency Percent Valid Percent
Cumulative
Percent
Valid Male 130 77.4 83.3 83.3
female 26 15.5 16.7 100.0
Total 156 92.9 100.0
Missing System 12 7.1
Total 168 100.0
89
4.2.2 Age
Participants’ age varies between a minimum of 23 years and a maximum of 62
years. The mean age of the respondents is 34 years with a standard deviation (S.D) of 7.5
years suggesting that the respondents are relatively young (see Appendix-C).
In Table 11, participants are classified into five age groups. The majority of
respondents were in the age group of 25 to 34 years old represented by 48.9 per cent of
the total respondents’ population. Only a small fraction of the sample (2.8%) is above 55
years of age.
Table 11: Frequency distribution: respondents’ ages into age group
Frequency Percent Valid Percent
Cumulative
Percent
Valid 20 - 24 7 4.1 5.0 5.0
25 - 34 69 40.8 48.9 53.9
35 - 44 55 32.5 39.0 92.9
45 - 54 6 3.6 4.3 97.2
55 - 64 4 2.4 2.8 100.0
Total 141 83.4 100.0
Missing System 27 16.6
Total 168 100.0
90
4.2.3 Sector
Table 12 shows the sector of the respondents’ banking organizations. This table
depicts that majority of the respondents (n = 141) were from private sector banks (89 per
cent). Only 17 respondents belong to public sector banks, representing a total of 11 per
cent.
Table 12: Frequency distribution: Sector
Frequency Percent Valid Percent
Cumulative
Percent
Valid Public Sector 17 10.1 10.8 10.8
Private Sector 141 83.9 89.2 100.0
Total 158 94.0 100.0
Missing System 10 6.0
Total 168 100.0
91
4.2.4 Region
Table 13 shows the region of the respondents’ banking organizations. This table
depicts that a total of 83 respondents belong to Islamabad region, representing a total of
52.5 per cent of the respondents’ population and 75 respondents belong to Rawalpindi
region, representing a total of 47.5 per cent of respondents’ population.
Table 13: Frequency distribution: Region
Frequency Percent Valid Percent
Cumulative
Percent
Valid Islamabad 83 49.4 52.5 52.5
Rawalpindi 75 44.6 47.5 100.0
Total 158 94.0 100.0
Missing System 10 6.0
Total 168 100.0
92
4.2.5 Organizations
Managers from 32 banking organizations participated in the study. In Appendix-D
name of the banking organizations and the number of respondents from the relative
organizations are presented.
4.2.6 Educational Qualification
Table 14 shows the distribution of the respondents’ level of education. It is
apparent from the Table 14 that the majority of the respondents (n =118) have Master’s
degree, representing a total of 83 per cent. Remaining 17 per cent of respondents have
Bachelor degree.
Table 14: Frequency distribution: Educational qualification
Frequency Percent Valid Percent
Cumulative
Percent
Valid Master’s Degree or
equivalent
118 70.2 83.1 83.1
Bachelor’s Degree
or equivalent
24 14.3 16.9 100.0
Total 142 84.5 100.0
Missing System 26 15.5
Total 168 100.0
93
4.2.7 Occupational Level
Respondents were requested to indicate their current position in the organization.
Five possible positions were given. These were front line manager, middle manager,
senior manager, senior vice president and Chief Executive Officer (CEO). Table 15
shows the distribution of the current occupied positions of respondents. It is apparent that
the majority of the respondents (n =58, 35.4 percent) were from middle management and
lowest from upper management (n =3, 1.8 percent).
Table 15: Frequency distribution: Occupational level
Frequency Percent Valid Percent
Cumulative
Percent
Valid Senior Vice
President
3 1.8 2.0 2.0
Senior Manager 33 19.6 21.9 23.8
Middle Manager 58 34.5 38.4 62.3
Front Line Manager 57 33.9 37.7 100.0
Total 151 89.9 100.0
Missing System 17 10.1
Total 168 100.0
94
4.2.8 Work Experience
The mean work experience of the respondents is 10 years with S.D of 7 years. In
Table 15, participants are classified into seven work experience groups. Table 16 shows
that the majority of the respondents (n =52, 31 per cent of respondents) fall in the work
experience group of 6 to 10 years.
Table 16: Frequency distribution: Work experience
Frequency Percent Valid Percent
Cumulative
Percent
Valid 0-2 12 7.1 8.5 8.5
3-5 32 19.0 22.5 31.0
6-10 52 31.0 36.6 67.6
11-15 28 16.7 19.7 87.3
16-20 9 5.4 6.3 93.7
21-30 4 2.4 2.8 96.5
More than 30 5 3.0 3.5 100.0
Total 142 84.5 100.0
Missing System 26 15.5
Total 168 100.0
95
4.2.9 MD Program Attended:
Respondents were asked to indicate how many number of MD programs they
have attended during previous two years. Four possible groups were given in the
questionnaire. Total number of MD programs attended by the participants is depicted in
Table 17.
Table 17: Frequency distribution: Number of MD programs attended
Frequency Percent Valid Percent
Cumulative
Percent
Valid 1 47 28.0 30.9 30.9
2-4 69 41.1 45.4 76.3
5 11 6.5 7.2 83.6
more than 5 25 14.9 16.4 100.0
Total 152 90.5 100.0
Missing System 16 9.5
Total 168 100.0
96
4.3 Summary
In this chapter a description of the sample of 168 respondents was presented, it is
evident from the analysis of frequency distributions that the most subjects are male
(83%). The majority of the subjects are young while the average age is 34 years. Subjects
predominantly have master’s degree (83%). While the average work experience of the
respondents is 10 years with SD of 7. Most subjects belong to private sector banks (89%).
97
CHAPTER 5
QUANTITATIVE DATA ANALYSIS AND DISCUSSION
5.1 Introduction
The results of statistical analysis of quantitative data are presented in this chapter.
The aim of the empirical part of the current study was to provide data that could answer
the research questions as stated in chapter 1 of this study. The main aim of this study was
to conduct a comprehensive analysis of the key aspects of MD in Pakistani banking
sector and to investigate the causal relationships among various factors that affect MD
practices. To accomplish these research aims or objectives, a model of MD effectiveness
was developed and analyzed with the help of SEM.
5.2 Descriptive Statistics
5.2.1 Descriptive Analysis of all Items
Details of descriptive analysis of all items of questionnaire are given in the Table
18. Questionnaire was based on 7-points liker scale (1 strongly disagree, 7 strongly
agree). Mean values of all indicators show that none of the item had very high or very
low mean score. Items in each construct had mean score just above the midpoint of the
scale. This provided support that all data were normally distributed.
98
Table 18: Descriptive analysis of all items Construct Items Minimum Maximum Mean SD
MD Effectiveness VarB1 2.00 7.00 5.6548 1.32226
VarB2 1.00 7.00 5.2917 1.36840
VarB3 1.00 7.00 5.1310 1.23599
VarB4 1.00 7.00 4.9464 1.41531
VarB5 1.00 7.00 4.3810 1.49574
VarB6 1.00 7.00 5.3988 1.30011
VarB7 1.00 7.00 5.3512 1.30011
VarB8 1.00 7.00 4.6845 1.39777
VarB9 1.00 7.00 5.5714 1.23604
Organizational Learning VarC1 1.00 7.00 5.2381 1.47733
Culture VarC2 1.00 7.00 5.0298 1.31971
VarC3 1.00 7.00 4.1964 1.65337
VarC4 1.00 7.00 5.1429 1.44473
VarC5 1.00 7.00 4.9464 1.53310
VarC6 1.00 7.00 4.9226 1.78146
VarC7 1.00 7.00 5.0238 1.45574
Individual Initiative VarD1 1.00 7.00 5.3869 1.20342
99
VarD2 1.00 7.00 5.4107 1.21039
VarD3 1.00 7.00 5.6429 1.22492
VarD4 1.00 7.00 3.4524 1.77410
VarD5 1.00 7.00 4.3750 1.66574
VarD6 2.00 7.00 5.1548 1.36240
VarD7 1.00 7.00 5.4405 1.47921
Top Management Support VarE1 1.00 7.00 4.8750 1.53282
VarE2 1.00 7.00 4.7202 1.61922
VarE3 1.00 7.00 4.5179 1.60080
VarE4 1.00 7.00 4.6369 1.54542
VarE5 1.00 7.00 4.5952 1.51732
VarE6 1.00 7.00 4.2917 1.60222
VarE7 1.00 7.00 4.6845 1.42745
Link to Corporate Strategy VarF1 1.00 7.00 4.5714 1.46648
VarF2 1.00 7.00 4.5714 1.41240
VarF3 1.00 7.00 4.6607 1.42194
VarF4 1.00 7.00 4.7143 1.46063
VarF5 1.00 7.00 4.9583 1.30570
VarF6 1.00 7.00 4.8036 1.38105
100
VarF7 1.00 7.00 4.2738 1.60725
Post-program Evaluation VarG1 1.00 7.00 4.5536 1.49954
VarG2 1.00 7.00 4.4167 1.40749
VarG3 1.00 7.00 4.3393 1.72973
VarG4 1.00 7.00 4.5298 1.55122
VarG5 1.00 7.00 5.0714 1.47462
VarG6 1.00 7.00 4.4345 1.40844
VarG7 1.00 7.00 4.6667 1.50714
Line Manager Support VarH1 1.00 7.00 5.1190 1.48771
VarH2 1.00 7.00 4.9821 1.36453
VarH3 1.00 7.00 4.3988 1.61631
VarH4 1.00 7.00 4.7321 1.47016
VarH5 1.00 7.00 4.9524 1.44690
VarH6 1.00 7.00 4.6905 1.47617
VarH7 1.00 7.00 4.5714 1.47868
Opportunity for Skill VarI1 1.00 7.00 5.0952 1.46512
Utilization VarI2 1.00 7.00 4.7917 1.36621
VarI3 1.00 7.00 4.8333 1.42125
101
VarI4 1.00 7.00 5.2321 1.28545
VarI5 1.00 7.00 4.6548 1.53205
VarI6 1.00 7.00 5.0357 1.48805
VarI7 1.00 7.00 5.1071 1.46019
MD Program Design VarJ1 1.00 7.00 5.1369 1.28056
VarJ2 1.00 7.00 4.9226 1.36683
VarJ3 1.00 7.00 4.7381 1.42366
VarJ4 1.00 7.00 4.9702 1.21579
VarJ5 1.00 7.00 4.8393 1.27308
VarJ6 1.00 7.00 5.0536 1.24419
VarJ7 2.00 7.00 5.0417 1.13915
VarJ8 1.00 7.00 4.9464 1.29142
VarJ9 1.00 7.00 4.9583 1.31027
Effective Monitoring VarK1 1.00 7.00 4.3214 1.58330
VarK2 1.00 7.00 4.1786 1.53725
VarK3 1.00 7.00 4.1250 1.62388
VarK4 1.00 7.00 3.8095 1.65226
VarK5 1.00 7.00 3.8452 1.52027
VarK6 1.00 7.00 4.1310 1.64357
102
VarK7 2.00 7.00 5.6369 1.38610
Note: Descriptions of items are given in Appendix-A
5.2.2 Descriptive Analysis of Constructs
Table 19 shows the mean and standard deviation of the constructs. The data in
this table shows that none of the variable (construct) had very high mean scores. The
dependent variable MD effectiveness had a mean score of 5.15 with SD of 0.99 on a 7-
point Likert scale. This indicates that the quality of MD effectiveness in Pakistan is just
on satisfactory level. All other variables had mean scores slightly above the midpoint of
the scale.
Table 19: Means and Standard Deviations (SD) of all constructs
Variables Mean
(7-point scale)
SD
1.MD Effectiveness 5.15 0.99
2.Individual Initiative 4.97 0.82
3.Top Management Support 4.63 1.24
4.Link to Corporate Strategy 4.63 1.09
5. Monitoring & Evaluation 4.31 1.05
6.Line Manager Support 4.77 1.17
7.Opportunity for Skill utilization 4.97 1.12
8.Program Design 4.95 0.97
9.Organizational Learning Culture 4.92 1.17
103
Table 19 depicts that there is lack of seriousness on the part of top management as
evident from low score of top management support. The mean score for top management
support was 4.64 with highest SD of 1.24. The low mean score of the link to corporate
strategy (4.63, SD 1.09) indicates that MD is not perceived as priority by the senior
management and there is lack of serious efforts by upper management to link MD goals
with organizational goals. Mean score of monitoring and evaluation (4.31., SD 1.05) also
indicate that management does not give much importance to monitor the smooth running
of MD programs and to evaluate the program properly once it is completed. These low
mean scores adversely affects the MD effectiveness.
Individual initiative and opportunity for skill utilization had second highest mean
score of 4.97 indicating the increasing role that managers have to play in their own
development and importance of providing the best opportunities by the management to
utilize the newly learned skills on real job settings. The mean for organizational learning
culture was 4.92, for program design mean score was 4.95 and line manager support had
mean score of 4.77.
104
5.2.3 Group Statistic of MD Effectiveness
In order to see the mean differences between MD effectiveness of public sector
banks and private sector banks, researcher run independent-sample T test. Results of T
test are depicted in Table 20 and Table 21. Table 20 shows that the mean value of MD
effectiveness of public sector banks is 5.21 (SD 1.15) and mean value of MD
effectiveness of private sector banks is 5.11 (SD .99). Table 21 shows independent
sample T test results which indicate that T test is non-significant with p = 0.62, so,
homogeneity of variance can be assumed. Two tailed significance of 0.717 indicating
non-significant difference between public and private sector groups.
In sum, it is found that there is no mean difference between MD effectiveness of
public sector and private sector banks.
105
Table 20: Group statistic of MD Effectiveness
Sector N Mean
Std.
Deviation
Std. Error
Mean
Public Sector 17 5.2092 1.15061 .27906
Private Sector 141 5.1151 .99225 .08356
Table 21: Independent samples test for MD effectiveness
Levene's Test for Equality of
Variances t-test for Equality of Means
95% Confidence Interval of the
Difference
F Sig. T df Sig. (2-tailed)
Mean Difference
Std. Error Difference Lower Upper
Equal variances
assumed
.247 .620 .363 156 .717 .09410 .25921 -.41792 .60612
Equal variances not
assumed
.323 18.98 .750 .09410 .29131 -.51565 .70385
106
5.2.4 Group Statistic of Individual Initiative
In order to see the mean differences between individual initiative of male and
female managers, researcher run independent-sample T test. Results of T test are depicted
in Table 22 and Table 23. Table 22 shows that the mean value of individual initiative of
male managers is 5.00 (SD 0.83) and mean value of individual initiative of female
managers is 4.94 (SD 0.83). Table 23 shows independent sample T test results which
indicate that T test is non-significant with p = 0.786, so, homogeneity of variance can be
assumed. Two tailed significance of 0.745 indicating non-significant difference between
male and female groups.
These results indicate that there is no mean difference between individual
initiative of male and female managers.
107
Table 22: Group statistic of Individual initiative
Gender N Mean Std.
Deviation Std.
Error Mean Individual
Initiative
Male 130 5.0047 .82799 .07262
female 26 4.9466 .83392 .16355
Table 23: Independent samples test for Individual Initiative
Levene's Test for Equality of Variances t-test for Equality of Means
95% Confidence Interval of the
Difference
F Sig. t df
Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference Lower Upper
Equal variances
assumed
.074 .786 .326 154 .745 .05812 .17809 -.29369 .40993
Equal variances
not assumed
.325 35.562 .747 .05812 .17894 -.30495 .42119
108
5.2.5 Group Statistic of Top Management Support
In order to see the mean differences between top management support of public
sector banks and private sector banks, researcher run independent-sample T test. Results
of T test are depicted in Table 24 and Table 25. Table 24 shows that the mean value of
top management for MD of public sector banks is 4.80 (SD 0.95) and mean value of top
management support for MD of private sector banks is 4.67 (SD 1.28). Table 25 shows
independent sample T test results which indicate that T test is non-significant with p =
0.27, so, homogeneity of variance can be assumed. Two tailed significance of 0.683
indicating non-significant difference between public and private sector groups.
In sum, it is found that there is no mean difference between top management
support for MD of public sector and private sector banks.
109
Table 24: Group statistic of top management support
Sector N Mean Std. Deviation Std. Error Mean
Top Management Support
Public Sector 17 4.8039 .95604 .23187
Private Sector 141 4.6722 1.28484 .10820
Table 25: Independent samples test for top management support
Levene's Test for Equality of
Variances t-test for Equality of Means
95% Confidence Interval of the
Difference
F Sig. t df Sig. (2-tailed)
Mean Difference
Std. Error Difference Lower Upper
Equal variances assumed
1.192 .277 .409 156 .683 .13174 .32223 -.50476 .76824
Equal variances not assumed
.515 23.599 .611 .13174 .25588 -.39684 .66032
110
5.3 Model Estimation with Structural Equation Modeling
To accomplish research objectives of the present study, a model of MD
effectiveness was developed and analyzed with the help of SEM. Model for this study
had 9 constructs and 74 indicators. Having sample of 168, it was not possible to get
reliable results of complex and large model of MD effectiveness.
Hair et al. (2006) recommend that in SEM, a large sample is required if the model
is overly large or complex. Hair et al. (2006) suggest “minimum ratio of at least five
respondents for each estimated parameter should be there” (p. 604). Reisinger &
Mavondo (2007) state that sample size has a significant influence on the complexity of a
model, simple model is preffered if sample size is small and complexed models can be
examined if large sample is avaialble (p. 52).
Hall, Snell and Singer (1999) state that increasing the number of indicators
directly affects the sample requirments and further they recommended that with a small
sample size, the number of indicators per construct should be limited e.g., to three or four
(p. 235). There were two possible ways to tackle this problem either to increase the
sample size or to use the item parceling technique in order to reduce the number of
parameters estimated (Bagozzi & Edwards, 1994). Due to limitations of time and
resources it was not possible to increase the sample size so it was decided to apply item
parceling technique to reduce the number of estimated parameters.
111
5.3.1 Item Parceling
Item parcels are commonly formed in order to reduce the number of indicators of
lengthy scales (Bandalos & Finney, 2001). According to Little, Cunningham and Shahar
(2002), “Parceling is a measurement practice that is used in multivariate data analysis
approaches, particularly for use with latent variable analysis techniques such as SEM and
Confirmatory Factor Analysis (CFA)” (p. 152). Bandalos and Finney (2001) define item
parceling as “a process by which raw item responses are combined into sub-scales prior
to analysis”. This process is done by combining or averaging item responses into parcel
score, these parcels are used as the observed variables most commonly in CFA or SEM
(Bandalos, 2002).
Bandalos (2002) argues that use of item parceling has become common in SEM
(p. 78). In review of SEM applications in seven prominent journals, Bandolas and Finney
(2001) found that from 1989 to 1994, of 317 applied SEM or CFA studies, 62 or 19.6 per
cent employed some type of parceling procedure. The techniques of item parceling have
been adopted by researchers in areas such as education, psychology, marketing and
organizational research (Bandalos, 2002).
Meade and Kroustalis (2005) stated that because of advantageous properties,
parcels have been advocated by many authors. These include greater reliability than
individual items, a more optimal indicator to sample size ratio, a greater likelihood of
achieving a proper model solution and better model fit (p. 02). Bandalos and Finney
(2001) reported that researchers have cited three common reasons for using item
parceling, first, it increases the stability of the parameter estimated, second, it improves
the variable to sample size ratio and third, it is a remedy to small sample size.
112
Bagozzi and Edwards (1998) argue that item parceling can reduce the number of
parameters estimated, resulting in more stable parameter estimates and proper solution of
model fit. Coffman and MacCallum (2005) state “in SEM or CFA as the number of
indicators increases so does the number of parameter estimated and the order of
correlation matrix. The larger the order of a correlation matrix the less likely the model is
to fit well” (p. 238). From this perspective using parcels rather than items as indicators of
latent variables involves the reduction in the number of measured variables and likely to
fit model batter than model with items as indicators (Coffman & MacCallum, 2005).
The use of item parceling is not without controversy. Perhaps most important is
determining the dimensionality of the items to be parceled (Bandalos, 2002). Because the
dimensional nature of a measured construct can have a serious impact on the accuracy
and validity of various parceling techniques (Little et al., 2002). Bandalos and Finney
(2001) recommended that researcher should use item parceling only when parceled items
are strictly unidimentional. Hair et al. (2006) argue that unidimentionality is similar to the
concept of reliability and define unidimentionality as “a characteristic of a set of
indicators that has only one underlying trait or concept in common” (p. 584). Item parcels
work effective when constructed on unidimensional structures (Little et al., 2002). “It has
also been found that the use of parceling can result in biased estimates of model
parameters” (Hall et al., 1999). In sum, the amount of argumentation for the advantages
side far outweighs the disadvantage side of item parceling (Little et al., 2002) and
researchers will continue to view item parceling as an attractive option (Hall et al., 1999).
113
5.3.1.1 Unidimentionality of measurement instrument
The measurement instrument used in the current study was based on extensive
literature review. To test the unidimentionality of measurement instrument, at first,
rationale review of item contents was done by researcher to determine like items (Hall et
al., 1999). Secondly, principal component factor analysis was used to test for
unidimentionality as suggested by Droge and Daugherty (as cited in Hoe, 2008, p. 80).
Further Realibility values for all constructs were computed.
5.3.1.1.1 Principal Component Factor Analysis
Principal component factor analysis was run to determine the eigenvalues.
According to Hoe (2008), “As a rule, eigenvalues that are greater than 1 provide support
for the unidimensionality of these scales” (p. 80). All constructs in the current study were
separately subject to principal component analysis and the eigenvalues presented in Table
26.
114
Table 26: Eigenvalues of measures
Construct Component Total Initial Eigenvalues
% of Variance Cumulative%
Management
Development Effective
1
2
3
4
5
6
7
8
9
5.030
0.967
0.752
0.562
0.429
0.390
0.344
0.273
0.252
55.890
10.747
8.356
6.245
4.767
4.335
3.825
3.029
2.805
55.890
66.638
74.994
81.239
86.006
90.341
94.167
97.165
100.00
Organizational
Learning Culture
1
2
3
4
5
6
7
4.226
0.772
0.553
0.488
0.397
0.338
0.225
60.375
11.028
7.904
6.976
5.673
4.826
3.217
60.375
71.403
79.308
86.284
91.957
96.783
100.00
Top Management
Support
1
2
4.517
0.807
64.531
11.524
64.531
76.055
115
3
4
5
6
7
0.534
0.378
0.318
0.271
0.175
7.631
5.393
4.546
3.871
2.504
83.686
89.079
93.625
97.469
100.00
Link to Corporate
Strategy
1
2
3
4
5
6
7
3.955
0.919
0.551
0.513
0.454
0.323
0.285
56.500
13.130
7.865
7.331
6.482
4.615
4.078
56.500
69.630
77.495
84.825
91.307
95.922
100.00
Line Manager Support 1
2
3
4
5
6
7
4.475
0.829
0.571
0.374
0.343
0.237
0.170
63.933
11.844
8.159
5.347
4.905
3.379
2.433
69.933
75.777
83.936
89.283
94.188
97.567
100.00
Opportunity for Skill 1 4.328 61.825 61.825
116
Utilization 2
3
4
5
6
7
0.597
0.547
0.503
0.407
0.353
0.266
8.529
7.816
7.185
5.808
5.044
3.793
70.353
78.170
85.355
91.163
96.207
100.00
MD program Design 1
2
3
4
5
6
7
8
9
5.231
0.796
0.599
0.571
0.477
0.449
0.328
0.302
0.247
58.123
8.844
6.656
6.347
5.304
4.990
3.644
3.352
2.741
58.123
66.966
73.622
76.696
85.273
90.263
93.907
97.259
100.00
Individual Initiative 1
2
3
4
5
6
2.765
1.053
0.919
0.751
0.604
0.452
39.493
46.474
13.131
10.734
8.632
6.460
39.493
55.968
69.099
79.833
88.465
94.925
117
7 0.355 5.075 100.00
Post Program
Evaluation
1
2
3
4
5
6
7
3.560
1.135
0.689
0.534
0.420
0.348
0.315
50.857
16.211
9.836
7.635
5.993
4.966
4.502
50.857
67.068
76.903
84.538
90.532
95.498
100.00
Effective Monitoring 1
2
3
4
5
6
7
4.265
1.106
0.733
0.367
0.244
0.213
0.173
60.928
14.371
10.467
5.245
3.480
3.039
2.470
60.982
75.299
85.766
91.011
94.491
97.530
100.00
Table 26 depicts that except individual initiative, post program evaluation and
effective monitoring all other constructs had only the first eigenvalue greater than 1. This
provided support for the unidimensionality of these scales. For individual initiative, two
eigenvalues were greater than 1 but the second eigenvalue was only 1.05. Since second
eigenvalue is close to 1 and this is a measure that has been used in D’Netto et al. (2008)
research, it is reasonable to accept the unidimensioanlity of this scale. For post program
118
evaluation and effective monitoring, two eigenvalues were greater than 1. To enhance the
unidimensionality of these two constructs, once again a rationale review of items was
done by researcher, assessed the Croncach’s alpha of item deleted and incremental
modification was carried out to find out the threats.
It was found that item K7 (I believe monitoring is an effective tool for a
successful training and development program) of effective monitoring and item G5 (I
believe post program evaluation is benificial) of post program evaluation are serious
threats to the unidimensionality of their constructs. These two items were deleted from
the data sheet and principal components analysis was rerun on these two construct to
determine the eigenvalues. Table 27 shows that only first eigenvalue was greater than 1
for both constructs. This provided support for the unidimensionality of these scales.
119
Table 27: Revised eigenvalues of measure
Construct Component Total Initial Eigenvalues
% of Variance Cumulative%
Effective Monitoring 1
2
3
4
5
6
4.242
0.739
0.381
0.247
0.215
0.175
70.703
12.323
6.347
4.120
3.588
2.919
70.703
83.026
89.373
93.494
97.081
100.00
Post Program
Evaluation
1
2
3
4
5
6
3.283
0.939
0.631
0.452
0.380
0.316
54.710
15.648
10.511
7.531
6.337
5.264
54.710
70.357
80.868
88.400
94.736
100.00
5.3.1.1.2 Reliability
To assess the unidimensionality further, Cronbach’s alpha statistics was used. The
acceptable threshold of Cronbach’s alpha is 0.70 (Nunnally & Bernstein, 1994). Table 28
shows that the Cronbach’s values for all constructs except individual initiative ranged
from 0.83 to 0.92. Only the construct “individual initiative” had value of 0.68 falling
somewhat short of the recommended level. Henceforth, the Cronbach’s values for all
120
constructs imply that they are unidimentional. That means all items of each constructs are
measuring the same content universe (i.e. construct).
Table 28: Cronbach’s values for constructs
Constructs/Scales Cronbach’s
Alpha
Number of
Items
Organizational Learning
Culture
0.89 7
Individual Initiative 0.68 7
Top Management Support 0.91 7
Link to Corporate Strategy 0.87 7
Line Manager Support 0.91 7
Opportunity for Skill
Utilization
0.92 7
MD Program Design 0.91 9
Effective Monitoring 0.92 6
Effective Evaluation 0.83 6
Management Development
Effectiveness
0.89 9
121
5.3.1.2 Simple Random Parceling
After determining the nature of dimentionality of set of items, one or other
technique for parceling items can be applied. Based on the unidimentioanl nature of the
measures, “simple random assignment” technique was used. In simple method for
constructing parcels, according to Little et al. (2002) “all items are assigned randomly
and without replacement to one of the parcels grouping and depending on the number of
items to be assigned, two, three or, possibly four parcels could be created” (p. 165). As
discussed before keeping in view the recommendations of Hair et al. (2006), Little et al.
(2002) and Hall et al. (1999), it was decided to create 3 parcels per latent construct. Table
29 depicts the simple random parceling process and name of parcels along with their
aggregated items.
Table 29: Simple random parceling
Name of Constructs Name of Parcels Aggregated Items
Organizational Learning
Culture
Culture1
Culture2
Culture3
C1+C2
C3+C4
C5+C6+C7
Individual Initiative Individual1
Individual2
Individual3
D1+D2
D3+D4
D5+D6+D7
Top Management Support Top1
Top2
Top3
E1+E2
E3+E4
E5+E6+E7
122
Link to Corporate Strategy Strategy1
Strategy2
Strategy3
F1+F2
F3+F4
F5+F6+F7
Line Manager Support Line1
Line2
Line3
H1+H2
H3+H4
H5+H6+H7
Opportunity for Skill
Utilization
Skill1
Skill2
Skill3
I1+I2
I3+I4
I5+I6+I7
Effective Monitoring &
Evaluation
Evaluation1
Evaluation2
Monitoring1
Monitoring2
G1+G2+G3
G4+G6+G7
K1+K2+K3
K4+K5+K6
MD Program Design Design1
Design2
Design3
J1+J2+J3
J4+J5+J6
J7+J8+J9
Management Development
Effectiveness
MD1
MD2
MD3
B1+B2+B3
B4+B5+B6
B7+B8+B9
LISREL software was used to estimate the model and constructs’ correlations.
For parameter estimation number of estimation methods are available including
maximum likelihood, weighted least squares, instrumental variables, generalized least
123
squares, two-stage least squares, unweighted-least squares, ordinary least squares, and
diagonally weighted least squares depending on the data and nature of model (Reisinger
& Mavondo, 2007). For the current study, researcher used Maximum Likelihood
Estimation (MLE) procedure for the model estimation which is most commonly used and
accepted for estimation (Reisinger & Mavondo, 2007). Hair et al. (2006) argue, MLE
provides valid results even if sample size is small (p. 605). Following the two-step
approach suggested by Andreson and Gerbing (1988) and by Cheng (2001) researcher
examined a measurement model before estimating structural model relationships.
5.4 The Measurement Model
According to Hair et al. (2006), “A measurement model specifies the indicators
for each construct and assesses the reliability of each construct for estimating the causal
relationships” (p. 581). In SEM, a measurement model is tested to validate the
measurement instrument (Cheng, 2001). According to Cheng (2001) “two different ways
are used to evaluate a measurement model’s validity: a) a test of the measure of each
construct separately; and b) a test of all measures together at one time” (p. 653). Cheng
(2001) suggests that second method of evaluation of measurement model is better than
the first one. For the present study, researcher adopted the second method of
measurement model’s validity as per Cheng’s recommendation. Procedurally, researcher
performed a “Confirmatory Factor Analysis” (CFA) of the combined measurement model
to validate the measures of the latent constructs. In CFA, overall model fit portrays the
degree to which the specified indicators represent the hypothesized constructs. All the
indicators of latent constructs were loaded on their specific constructs and all constructs
124
were inter-correlated. To ensure reliability of the indicators by CFA, it was confirmed
that the factor loads are higher than 0.4 and significant (t ≥1.96; p≤0.05), composite
reliability of each whole scale by applying the Cronbach alpha, composite reliability
(≥0.7) and average variance extracted (≥0.5) (Hair et al., 2006). Table 31 contains the
LISREL estimates for the measurement model.
5.4.1 Evaluating Goodness-of-fit Criteria for Measurement Model
5.4.1.1 Offending Estimates
Results were examined for nonsensical or theoretically inconsistent estimates.
According to Hair et al. (2006) “three most common offending estimates are negative
error variance, standardized coefficient exceeding or very close to 1.0, or very large
standard error” (p. 633). Table 29 and Table 30 reveal no instances of any of these
problems.
5.4.1.2 Correlation among Latent Constructs
Table 30 presents the correlation among all latent constructs. Examination of the
intercorrelation matrix shows that each construct is significantly correlated with the other
constructs and none of the correlations are above 0.77. Therefore, multicollinearity
problem is fairly low, as Hair et al. (2006) state that results of SEM can be affected by
multicollinearity and correlations exceeding 0.80 can be indicative of problems but value
exceeding 0.90 should always be examined.
125
9 1.00
Not
e: In
Com
plet
ely
Stan
dard
ized
Sol
utio
n LI
SREL
doe
s not
gen
erat
e “P
” va
lue.
Res
ults
of c
orre
latio
n am
ong
late
nt
cons
truct
s by
Stan
dard
ized
Sol
utio
n w
ith “
P” v
alue
s are
giv
en in
App
endi
x-E
8 1.00
0.65
7 1.00
0.70
0.
55
6 1.00
0.77
0.55
0.
65
5 1.00
0.76
0.
65
0.45
0.
55
4 1.00
0.75
0.
60
0.64
0.
55
0.48
3 1.00
0.60
0.
69
0.67
0.
57
0.45
0.
62
2 1.00
0.65
0.
64
0.67
0.
57
0.51
0.
70
0.73
1 1.00
0.69
0.
66
0.45
0.
54
0.43
0.
39
0.56
0.
59
Tabl
e 30
: Cor
rela
tion
amon
g la
tent
con
stru
cts
Var
iabl
es
1.
MD
Eff
ectiv
enes
s
2.
Org
aniz
atio
nal L
earn
ing
Cul
ture
3.
Indi
vidu
al In
itiat
ive
4.
Top
Man
agem
ent S
uppo
rt
5.
Link
to C
orpo
rate
Stra
tegy
6.
Mon
itorin
g an
d Ev
alua
tion
7.
Line
Man
ager
Sup
port
8.
Opp
ortu
nity
for S
kills
Util
izat
ion
9.
MD
pro
gram
Des
ign
126
5.4.1.3 Standardized Regression Weights of Measurement Model
Table 31 shows the indicator loadings that all the indicators were statistically
significant for the proposed constructs and no indicators had loading so low that they
should be deleted. The “t” values associated with each of the loadings exceed the critical
values for the .05 significance level (critical value = 1.96) as suggested by Hair et al.
(2006). All variables are significantly related to their specified constructs, verifying the
posited relationships among indicators and constructs. In summary, the various measures
of overall model goodness-of-fit and standardized regression weights lend sufficient
support to deeming the results an acceptable representation of the hypothesized
constructs.
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Table 31: Measurement model results (Standardized regression weights or construct loadings)
Constructs (Variables) Indicators Standardized Structural Coefficient
t values
Management Development
Effectiveness
MD1
MD2
MD3
0.728***
0.785***
0.718***
09.99
11.02
09.81
Organizational Learning Culture
Culture1
Culture2
Culture3
0.785***
0.798***
0.822***
11.60
11.89
12.42
Individual Initiative Individual1
Individual2
Individual3
0.780***
0.500***
0.627***
10.11
05.41
08.33
Top Management Support
Top1
Top2
Top3
0.715***
0.840***
0.876***
10.21
12.83
13.65
Link to Corporate Strategy
Strategy1
Strategy2
Strategy3
0.836***
0.829***
0.732***
12.81
12.65
10.58
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Program Monitoring & Evaluation
Monitoring1
Monitoring2
Evaluation1
Evaluation2
0.733***
0.687***
0.635***
0.686***
10.40
09.55
08.64
09.54
Line Manager Support
Line1
Line2
Line3
0.696***
0.809***
0.875***
09.86
12.16
13.65
Opportunity for Skill utilization Opportunity1
Opportunity2
Opportunity3
0.893***
0.886***
0.806***
14.41
14.24
12.30
Program Design
Design1
Design2
Design3
0.861***
0.884***
0.805***
13.48
14.05
12.18
Notes: ***p ˂ 0.001 (two-tailed).
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5.4.2 Overall Model Fit (goodness-of-fit indices)
Table 32 represents the goodness-of-fit indices for the measurement model. The
table indicates that the χ²/d.f ratio was 1.82, which was much smaller than the threshold
value of 3.00 as suggested by Hair et al. (2006). All other indices supported a good fit to
the data (GFI = 0.81, NFI = 0.95, IFI = 0.98, RFI = 0.94, CFI = 0.98, NNFI = 0.97 and
RMSEA =0.06) as compared to the recommended values suggested by Hair et al. (2006).
Complete LISREL results of measurement model are given in Appendix-E (Detailed
discussion on goodness of fit indices and recommended values are given in Table 35.).
Table 32: Goodness-of-fit indices for the measurement model
Goodness-of fit Indices Calculation of Measure*
χ² 572
d.f 314
χ²/d.f 1.82
GFI 0.81
NFI 0.95
IFI 0.98
RFI 0.94
CFI 0.98
RMSEA 0.06
NNFI 0.97
* For recommended values see Table 34; d.f, degree of freedom; GFI, Goodness of Fit Index; IFI, Incremental Fit Index; RFI, Relative Fit Index; CFI, Comparative Fit Index; RMSEA, Root Mean Square Error of Approximation; NNFI, Non-Normed Fit Index.
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5.4.3 Measurement Model Fit
According to Hair et al. (2006), after assessing the overall measurement model
goodness of fit and examination of the construct loadings, “the reliability and variance
extracted measures for each construct need to be computed to assess whether the
specified indicators are sufficient in their representation of the constructs” (p. 612). Table
33 and Table 34 present the computations for the reliability and the variance extracted
measures.
5.4.3.1 Reliability
Hair et al. (2006) stated “reliability is a measure of the internal consistency of the
constructs’ indicators, depicting the degree to which they indicate the common latent
constructs” (p. 612). Table 33 shows that all constructs displayed satisfactory levels of
reliability ranging from 0.79 to 0.90 and exceed the level of 0.70 suggested by Hair et al.
(2006) except individual initiative. Construct individual initiative has a value of 0.68,
falling somewhat short of the recommended level.
The reliability of the constructs was measured with the help of following formula
as proposed by Hair et al. (2006).
(Sum of standardized leading)2 Construct reliability = (Sum of standardized leading)2 + Sum of indicator measurement error *
* Indicator measurement error was calculated as 1- (Sum of standardized leading)2. Or it can be found as diagonal of the measurement error correlation matrix (theta-delta matrix) in the LISREL output. For details see Appendix –E.
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Table 33: Reliability for all constructs
Constructs Reliability
MD Effectiveness 0.79
Organizational Learning Culture 0.85
Individual Initiative 0.68
Top Management Support 0.85
Link to Corporate Strategy 0.84
Monitoring & Evaluation 0.79
Line Manager Support 0.88
Opportunity for Skill utilization 0.90
Program Design 0.89
5.4.3.2 Variance Extracted
Hair et al. (2006) stated “variance extracted measure reflects the overall amount
of variance in the indicators accounted for by the latent constructs” (p. 612). Higher
variance extracted values occur when the indicators are truly representative of the latent
construct. For the variance extracted measures, Table 34 shows all constructs exceeded
the recommended level 0.50 or 50 per cent (Hair et al., 2006) substantially ranging from
0.56 to 0.74 except individual initiative. Construct “individual initiative” has a value of
0.47, falling somewhat short of the recommended level. Thus for all the constructs, the
indicators are sufficient in term of how the measurement model is now specified.
Variance Extracted of the constructs was measured with the help of following
formula as proposed by Hair et al. (2006).
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Sum of squared standardized leadings Variance Extracted = Sum of squared standardized leading + Sum of indicator measurement error
Table 34: Variance-Extracted for all constructs
Constructs Variance Extracted
MD Effectiveness 0.56
Organizational Learning Culture 0.64
Individual Initiative 0.47
Top Management Support 0.66
Link to Corporate Strategy 0.64
Monitoring & Evaluation 0.65
Line Manager Support 0.65
Opportunity for Skill utilization 0.74
Program Design 0.72
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5.5 The Structural Model
Cheng (2001) and Andreson & Gerbing (1988) argue that after assessing the
measurement model that has achieved the reasonable goodness-of-fit the second step of
analysis is evaluating relationships among constructs and examining the expected
coefficients. The whole process is called assessment of structural model (Hair et al.,
2006). Following the suggestion of Cheng (2001) researcher followed two steps approach
to assess the structural model. In the first step researcher evaluated the goodness-of-fit
indices for the structural model and in the following step researcher estimated
standardized parameter for the structural model to justify the hypothesized causal
relationships among constructs. This process is also known as structural model fit.
Results of assessment of structural model with the help of LISREL program are
given in Table 35 and Table 37.
5.5.1 Overall Structural Model Fit
Overall structural model fit is also known as evaluation of goodness-of-fit
measures of structural model. Goodness-of-fit measures determine whether the researcher
should reject or accept the structural model being tested. There are four main types of
goodness-of-fit measures to assess the structural model. For example
1. Incremental Fit Measures
2. Parsimonious Fit Measures
3. Absolute Fit Measures
4. Noncentrality-based Measures
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LISREL results of all four types of goodness-of-fit measures are given in Table
35. Several researchers including Hair et al. (2006) and Reisinger & Mavondo (2007)
argue that researchers should not report all tyes of goodness-of-measures but different
indices from each type of goodness-of-fit meausre should be reported to assess the
structural model. In the current study different indices from all four types goodness-of-fit
meaures are given and research has also vindicated the choice of all those measures.
Table 34 contains the results of different indices from all four types of goodness
measures. These results indicate that the proposed model has a best fit to the data as all
measures achieved the acceptable level and model should be accpted. Details on all four
types of goodness-of-fit measures are given in the following sections.
5.5.1.1 Absolute Fit Measures
Reisinger and Mavondo, (2007) stated that, “Absolute fit measures determine the
degree to which the overall model (structural and measurement models) provides an
acceptable fit to the data with no adjustment for overfitting” (p. 56). Hair et al. (2006)
argued that “In absolute fit measure no distinction is made as to whether the model fit is
better or worse in the structural or measurement models”. Chi-square (χ²) and the
Goodness of Fit Index (GFI) are two main measures in Absolute Fit Measures. Hair et al.
(2006) argue that “chi-square (χ²) is the only statistically based measure of goodness-of-
fit available in SEM”. The results of chi-square are
χ² = 795, p ˃.05 (N=168).
However, several researcher including Reisinger and Mavondo (2007) and Cheng
(2001) have criticised the use of chi-square. As Cheng (2001) argue that it is hard to
135
attain a non-significant chi-square (p. 653). Reisinger and Mavondo (2007) criticised the
use of chi-squere by arguing that use of this measure is not effective in many
applications. Bentler and Bonnet (as cited in Reisinger and Mavondo, 2007) argued that
“the chi-square tests the hypothesis, not the model fit”
To attain a good acceptability level of structural model fit, researched examined a
number of other goodness-of fit indices as suggested by (Reisinger and Mavondo, 2007).
Hair et al., (2006) stated that GFI is a non-statistical goodness-of-fit measure and
signifies overall degree of fit of the structural model. The achieved value of GFI for the
current structural model is 0.80 that is marginally acceptable (Hair et al., 2006). The
results of the absolute fit measures conclude that the structural model is acceptable.
5.5.1.2 Incremental Fit Measures
“The second class of measures compares the proposed model to some baseline
model (also called null or independence model)” (Reisinger and Mavondo, 2007). Hoe
(2008) stated that Non-Normed Fit Index (NNFI) or Tucker-Lewis Index (TLI)
“compares a proposed model’s fit to a nested baseline or null model” and this measure of
goodness-of-fit is strongly suggested. Hair et al. (2006) stated that two indices of
incremental fir measures like Incremental Fit Index (IFI) and Normed Fit Index (NFI) are
used to compare estimated structural model with a null model. Hair et al. (2006) proposed
the acceptable value of 0.90 for IFI, NNFI/TLI and NFI. Results of the current model
indicate that incremental fir measures values are IFI 0.96, NFI 0.93 and TLI 0.96. All
these values of incremental fit measures are above the acceptable level and indicate that
model is acceptable.
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5.5.1.3 Noncentrality Based Measures
“Noncentrality-based indices test the degree of rejection of an incorrect model”.
Researchers including Burnette & Williams (2005) and Hoe (2008) argued that to test the
goodness-of-fit measure, values of Root Mean Square Error of Approximation (RMSEA)
and Comparative Fit Index (CFI) should be calculated. It is argued that the value of
RMSEA is not affected by small sample size and this measure is highly recommended if
the sample size is small. Hu and Bentler proposed RMSEA on the ground that “this index
yields appropriate conclusions about model quality and provides precise fit” (as cited in
Reisinger & Mavondo, 2007, p. 56). Suggested or acceptable value of RMSEA by Hair et
al. (2006) is 0.08 or less. Results of the current study indicate that the achieved value of
RMSEA is 0.07. Hoe (2008) stated that CFI is also an appropriate measure if there is a
problem of small sample size. Suggested or acceptable value CFI by Hair et al. (2006) is
0.90 or greater. Achieved value of CFI for the current model is 0.96, which is more than
minimum acceptable value. Results of non-centrality based fit indices conclude that the
current structural model is accepted.
5.5.1.4 Parsimonious Fit Measures
“Parsimonious fit measures relate the goodness-of-fit of the model to the number
of estimated coefficients required to achieve this level of fit” (Hair et al., 2006). In
parsimonious measures assessing the values of Normed Chi-square and relative Fit Index
are more appropriate. Suggested or acceptable value Normed Chi-square by Hair et al.
(2006) is 3 or less. Value of Normed Chi-square can be computed by dividing value of
chi-square by degree of freedom. Results of the current study indicate that the achieved
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value of Normed Chi-square is 2.28. Suggested or acceptable value of RFI by Hair et al.
(2006) is .90 or more. Achieved value of RFI for the current structural model is 0.92.
In conclusion it is stated that all four types of goodness-of-fit measures indicate
that data supports the structural model and model should be accepted. Cheng (2001),
Reisinger & Mavondo (2007) and Hair et al. (2006) argue that final approach in
achieving a best fitting model is comparison of proposed model with some competing
models. This final approach of competing models is accessed in the coming section of
this chapter.
138
Table 35: Comparison of goodness-of-fit measures for structural model
Structural Model Data:
28 indicators/parcels for 9 constructs (1 exogenous, 8 endogenous)
Total degree of freedom = 335
Sample Size = 168
Proposed Model: chi-square = 765 df =335 p = .000
Null or Independent Model: chi-square = 10123 df = 378 p = .000
Goodness-of-Fit
Measure Accepted Value* Calculation Adequacy*
1.Absolute Fit
Measures
Likelihood ratio chi-
square statistic(χ²)
χ²= 765
Significance
level:000
Goodness of Fit
index (GFI)
Higher values indicates better
fit, no established thresholds
GFI = 0.78
Marginal
2.Incremental Fit
Measures
Tucker-Lewis Index
(TLI)
Acceptable value: ≥0.90 TLI or NNFI =
0.96
Good
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Normed Fit Index
(NFI)
Acceptable value: ≥0.90 NFI = 0.93 Good
Incremental Fit
Index (IFI)
Acceptable value: ≥0.90
IFI = 0.96
Good
3.Noncentrality-
based Measures
Root mean square
error of
approximation
(RMSEA)
Acceptable values under 0.08 RMSEA = 0.07 Good
Comparative Fit
Index (CFI)
Acceptable value: ≥0.90
CFI = 0.96
Good
4.Parsimonious Fit
Measures
Normed chi-square
Acceptable value: Lower
value: 1.0
Upper value: 3.0 or 5.0
Normed χ² =
χ²/d.f = 2.28
Good
140
Parsimonious
Normed Fit Index
(PNFI)
greater value shows well fit,
PNFI = 0.83 Marginal
Relative Fit Index
(RFI)
Acceptable value: ≥0.90 RFI = 0.92 Good
* Source Hair et al. (2006)
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5.5.2 Structural Model Fit (Standardized Parameter Estimates)
Following the two step approach to assess the structural model, the next step is
justifying the causal relationships among all latent constructs and calculating the path
coefficients for all hypothesized path in the structural model. Reisinger & Mavondo
(2007) argued “a good model fit does not indicate the strong relationshops among
variables and suggest that researcher should report not only model fit indices but also the
strength of the paths in the model”. Table 36 depicts the results of 15 hypotheses.
Table 36: Acceptance or rejection of hypotheses
Name of
Hypothesis
Hypothesis Statement Accepted/Rejected
H1 Organizational learning culture will be positively
associated with top management support.
Accepted
H2 Organizational learning culture will be positively
associated with line manager support.
Accepted
H3 Organizational learning culture will be positively
associated with program monitoring and evaluation.
Accepted
H4 Top management will be positively associated with
line manager support.
Accepted
H5 Top management will be positively associated with
link to corporate strategy.
Accepted
H6 Top management will be positively associated with
opportunity for skill utilization.
Accepted
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H7 Top management will be positively associated with
individual initiative.
Accepted
H8 Line manager support will be positively associated
with link to corporate strategy.
Accepted
H9 Line manager support will be positively associated
with individual initiative.
Accepted
H10 Line manager support will be positively associated
with opportunity for skill utilizations.
Accepted
H11 Program monitoring and evaluation is positively
associated with Program design.
Accepted
H12 Link to corporate strategy will be positively
associated with program design.
Accepted
H13 Individual initiative will be positively associated
with MD effectiveness.
Accepted
H14 Opportunity for skill utilization will be positively
associated with MD effectiveness.
Accepted
H15 Program design will be positively associated with
MD effectiveness.
Accepted
143
The strength of relationship among constructs was represented by standardized
path coefficients. Table 37 reveals that all the structural equations contain statistically
significant coefficients having acceptable “t” values. Minimum acceptable value of “t” is
1.96 and a value less than 1.96 at 5 per cent significant level and can be deleted
(Reisinger & Mavondo, 2007). The examination of parameter estimates (path
coefficients) conclude that organizational learning culture strongly affects top
management support (0.74, p˂0.001), line manager support (0.35, p˂0.01) and program
monitoring and evaluation (0.68, p˂0.001), these positive links support hypotheses 1, 2
and 3. Top management support was found significantly related to line manager support
(0.40, p˂0.01), link to corporate strategy (0.67, p˂0.001), opportunity for skill utilization
(0.20, p˂0.05) and individual initiative (0.52 p˂0.001) and all these positive path
coefficients support hypotheses 4, 5, 6 and 7. Line manager support had positive direct
effects on link to corporate strategy (0.23, p˂0.01), individual initiative (0.22, p˂0.05)
and opportunity for skill utilization (0.58, p˂0.001). These positive links support
hypotheses 8, 9 and 10. Program monitoring and evaluation was found to be significantly
related to program design (0.59, p˂0.001) and supports the hypothesis 11. It was also
found that link to corporate strategy affects MD program design (0.22 p˂0.05) and
supports the hypothesis 12. Finally, it was found that dependent variable (MD
effectiveness) was directly positively affected by the individual initiative (0.43, p˂0.001),
opportunity for skill utilization (0.24, p˂0.01) and program design (0.23, p˂0.01) and
support the Hypothesizes 13, 14 and 15.
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Table 37: Structural equation coefficients and “t” values for the structural model
Effect From To Total Effect(coefficient)
“t” Value
Organizational Learning
culture
Top Management
Support
0.736*** 7.88
Organizational Learning
culture
Line Manager
Support
0.349** 2.73
Organizational Learning
culture
Monitoring and
Evaluation
0.678*** 5.64
Top Management Support Line Manager
Support
0.395** 3.02
Top Management Support Link to Corporate
Strategy
0.671*** 6.14
Top Management Support Individual Initiative 0.520*** 4.17
Top Management Support Opportunity for Skill
Utilization
0.198* 1.99
Line Manager Support Link to Corporate
Strategy
0.231** 2.45
Line Manager Support Opportunity for Skill
Utilization
0.579*** 5.24
Line Manager Support Individual Initiative 0.225* 1.88
Link to Corporate Strategy Program Design 0.216* 2.65
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Monitoring and Evaluation Program Design 0.590*** 5.10
Program Design MD Effectiveness 0.228** 2.64
Opportunity for Skill
Utilization
MD Effectiveness 0.241** 2.55
Individual Initiative MD Effectiveness 0.426*** 3.68
Notes: *p<0.05, **p<0.01, ***p<0.001
Standardized regression coefficients for the hypothesized structural model of MD
effectiveness are also depicted the Figure 6. Once again this figure shows that all the
structural equations contain statistically significant coefficients and all paths were in
expected directions, confirming the acceptance of all hypotheses. Complete LISREL
results of structural model are given in Appendix-F.
146
Figure 6: Standardized regression coefficients for the hypothesized structural model of MD effectiveness
147
5.6 Competing Models
Kelloway (1995) and Hair et al. (2006) suggest that final approach in achieving a
best fitting model is comparison of proposed model with some competing models. The
selection of one of the competing models must be done on both theoretical and empirical
basis (Hair et al., 2006). In this way, researcher can determine whether the proposed
model is acceptable if no other competing model can reach a greater level of fit.
Two alternative models were proposed with the same number of constructs and
indicators. In the first model (COMPMOD1), researcher added paths, from top
management support to MD effectiveness, from organizational learning culture to MD
effectiveness, from line manager support to MD effectiveness and from program
monitoring and evaluation to MD effectiveness. In the second model (COMPMOD2),
researcher added paths from link to corporate strategy to opportunity for skill utilization
and from opportunity for skills utilization to individual initiative and rerun the SEM
models (for results of new paths, see Table 38 and Table 39).
Hair et al. (2006) state that if researchers increase path links in the model it will
improve the absolute fit measures. The results across all three types of measures showed
mixed results, but most of these newly added paths were less or non-significant. Figure7
and Figure 8 depict complete results of COMPMOD1 and COMPMOD2 respectively.
Thus researcher accepts the proposed model as the final model with reservations until
additional constructs can be added, measures refined, or causal relationships re-specified.
148
Table 38: Structural equation coefficients for COMPMOD1
Effect From To Total
Effect(coefficient)
Top Management Support MD Effectiveness 0.08
Line Manager Support MD Effectiveness -0.31
Monitoring & Evaluation MD Effectiveness -0.09
Table 39: Structural equation coefficients for COMPMOD2
Effect From To Total
Effect(coefficient)
Link to Corporate Strategy Opportunity for Skill
Utilization
-0.36
Opportunity for Skill Utilization Individual Initiative -0.09
149
Figure 7: Competing model 1 (COMPMOD1)
150
Figure 8: Competing model 2 (COMPMOD2)
151
5.7 Discussion
As discussed that D’Netto et al., (2008) built their model on the ground that a
learning culture of an organization plays a dynamic role in the MD process. Researcher
found that organizational learning culture was significantly associates with line manager
support, top management support and program monitoring & evaluation. The result of
positive association between organizational learning culture and top management support
was in consonance with Sadler (1998) that in organizations where learning culture is
prevalent, top management appears to support MD efforts and provides weight, authority
and status to MD activities. It was also found that in a culture of learning, line managers
provide support to all development programs and activities from emphasizing the
significance of attending MD program to emphasizing the application of program
contents on the work/job. Researcher also found that the organizations having learning
culture properly monitor their training and development program and take any corrective
action, when necessary. These organizations also conduct effective post-program
evaluation.
As predicted, researcher found that strong top management support is positively
associated with line manager support and individual initiative. This result is inconsonance
with Reitsma (2001) that if top management supports the MD activities, all employees in
the organization show their seriousness towards MD programs. Positive correlation
among top management support and individual initiative and line manager support
indicate the importance of top management support for the success of MD programs.
Researcher also found that individual initiative for self-development can be enhanced if
top management provides motivations, rewards, financial and emotional support to
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individuals at all levels. Researcher found that annual per capita spending on T&D in
Pakistani banking sector was only US$270. Researcher computed per capita spending on
T&D by dividing the total spending on T&D in organizations by total managers in those
organizations. This indicates that training and development budget in Pakistan is quite
low as compared to budget of advance countries. D’Netto et al. (2008) found that in
Australia annual median per capita spending was $833. In US, per capita spending on
employee T&D is $1,068 (ASTD State of the Industry Report, 2009).
Low budget of training and development emphasizes the need for more top
management support for MD programs. As D’Netto et al. (2008) argue that a low budget
on T&D can harmfully affect the value of employees. Researcher also found that in
organizations having learning culture, top management provides more opportunities for
trainees to apply the newly learned skills in the job. It was found that for effectiveness of
MD programs, top management should play vital role in strategy formulation and should
link such programs more closely to corporate strategy.
It is found that MD efforts and corporate strategy is positively associates with
program design. Linking the MD goals and objectives to corporate strategy is necessary
to successfully design and implement MD program. Providing general nature of training
which is not fully linked to corporate objectives makes MD less effective. These results
support the past research on T&D that linking MD to corporate strategy helps to design
or select MD program that address organizational weaknesses, helps the participants to
confront reality, contents of MD programs relates to the organization’s vision, objectives
and strategies (Berry, 1990).
153
Researcher found that line manager support is directly linked with individual
initiative, opportunity for skill utilization and link to corporate strategy which indicates
that the role of line manager in enhancing the MD effectiveness is multidimensional. Line
manger’s support for MD programs enhances the individual manager initiative for his/her
self-development. Strong line manager support increases the employees’ participation in
the MD program and also stresses the application of training content to the job.
Researcher also found that line managers’ support for the MD programs enhances
relationship between MD programs and corporate strategy. That means line manager play
vital role in linking MD goals with corporate goals. For the effectiveness of the MD
programs line managers also provide better opportunities to the employees for the
utilizations of newly learned skills.
In the current study researcher found that effective monitoring and evaluation is
positively associated with the MD program design. These findings indicate that
monitoring is an effective tool to avoid any disturbance in smooth running and
implementation of training and development program and program evaluation helps in
controlling the T&D program and helps to program provider to take any necessary action
if training program is not meeting its objectives.
Results of the current study indicate that individual initiative is positively
associated with MD effectiveness. It is found that support from top management and
immediate supervisor helps to make a trainee more serious for a development program.
And employee who is motivated and shows positive attitude towards MD program,
perceives the development program as an opportunity to learn and plays active role for
his/her self-development and assesses his/her level of readiness for a developmental
154
change and takes initiatives for self-development. These results indicate that MD
programs can produce desired result when a manager-trainee is sufficiently motivated
and organized to his/her own development.
It was also found that MD program design is directly positively associated with
MD effectiveness. As Chen & Sok (2006) argued that ROI for T&D can be ensured by
properly planning T&D program. Researcher also found that the high level of course
relevance to job requirements, proper delivery methods can produce the desired results
and enhance the MD effectiveness.
Results indicate that opportunity for skills utilization is directly positively
associated with MD effectiveness. These findings are inconsonance with past research
which indicates that by providing maximum facilities to trainees in real workplace,
organizations can maximize the transfer of learning (Kirwan & Birchall, 2000). It is
found that providing enough opportunities to use newly learned skills help managers to
maintain the skills over a long period of time and it would be only wastage of resources if
organization does not provide opportunities to trainees to utilize the newly learned skills.
Male supremacy of management jobs continues in Pakistani banking sector. Only 17
percent of the respondents were female managers (see Table 10). As D’Netto et al. (2008)
argue that provision of less MD facilities to female employees may be cause of this
inequality.
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CHAPETER 6
QUALITATIVE DATA ANALYSIS AND DISCUSSION
6.1 Introduction
This chapter is concerned with the presentation and interpretation of the
qualitative data in order to investigate the qualitative aspects of the main purpose of this
research study, i.e. to conduct a comprehensive analysis of the key aspects of MD
effectiveness in Pakistani banking sector.
In total 25 semi-structured interviews in banking sector were conducted by the
researcher. In Table 40, summery of the number of interviews, the management level of
participants and the duration of the interviews is presented.
Table 40: Summery of interviews conducted
Number of
interviews
Type of
interviews
Middle
management
level
Senior
management
level
Duration per
interview
HRD
Department
10 1= face to face
9= telephonic
4 6 15 minutes
Individual
Managers
(Trainees)
15 15 = face to
face
8 7 30 to 45
minutes
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The qualitative data analysis phase commenced with a process of open coding
where the focus was laid on general concepts, similar quotes labeled together. At next
step, axial coding was done. Axial coding is the identification of core themes where the
initial list of concepts and categories were refined. Finally, themes and relationships
identified during coding were integrated into the conceptual framework developed in
chapter 3.
To explore the qualitative aspects of the issue, several qualitative research questions
were asked from the participants. These qualitative research questions was aim to have
in-depth understanding of the situation and to achieve research objectives. I.e. to achieve
the objectives of this research study following three important questions were asked from
the interviewees.
To what extent your MD programs are successful in achieving goals?
What major issues are related with effectiveness of management development
(success factors)?
How can MD programs be made more effective?
As it was decided by the researcher that results of the current qualitative research
would be presented by means of the presentation and discussion of the emerging themes
so it was not possible to answer above qualitative research questions in isolation in the
current chapter. In attempting to interpret qualitative research data in context, it became
clear that the above research questions largely formed part of an integrated whole.
157
6.2 Coding and Identification of Themes
Research results are presented by means of the presentation and discussion of the
emerging themes identified during the coding process of the qualitative data. The results
are presented in boxes mostly containing the quoted responses from various respondents;
these quotes are presented in italic type. Responses have been interpreted in respect to
three main identified themes. Figure 9 illustrates the summery of main themes and sub-
themes.
Figure 9: Summery of emerging themes and sub-themes.
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6.3 Theme 1: Individual Perspective
The first theme elicited from the interview transcriptions is “individual
perspective” which refers to the role of individual managers which they have to play for
the sake of their own development. It is depicted in Figure 10 that from the interviews
data one major issue (sub-theme) has been identified in respect to individual perspective
which can influence the effectiveness of MD. The present study finds that responsibilities
for MD have moved from the organization to the individual and individuals should play
an energetic role for their self-development. These trends are in consistence with findings
of D’Netto et al. (2008) and Paauwe and Williams (2001).
Figure 10: Theme1: Individual perspective.
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6.3.1 Individual Behavior and Motivation Responses and Findings
Respondent 6 (HRD) stated that “trainee’s attitude play a vital role for effectiveness of
any development program. A motivated trainee will be serious towards the training
program and would perceive the development program as an opportunity rather than a
burden only then the program will lead to valued outcomes”.
Respondent 1 (HRD) made an argument that for an effective development program,
organizations should motivate the trainees to participate in the development program
because motivated trainees believe that the participating in the training and development
program would enhance their knowledge, skills and abilities.
Respondent 13 (trainee) asserted that only motivated employees perceive that
participating in the development program will lead to valued outcomes.
Respondent 15 (trainee) elaborated the fact that “senior management or supervisors
play a significant role in subordinates’ training motivation, goal setting, and reinforce
the transfer of their learning”.
Respondent 2 (HRD) commented that “if a trainee is serious and motivated towards
training and perceives the development program as an opportunity, he/she will give
attention to the contents of the training program and apply the newly learned skill on the
real job settings”. Further, Respondent asserted that a motivated employee consider that
every development opportunity would lead to desired outcomes and for every new
development program, he will be serious and participate enthusiastically.
Respondent 3 (HRD) was of the opinion that “most of Pakistani employees don’t
perceive the development program as an opportunity to enhance their knowledge and
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skills but they are concerned or hope for financial benefits by participating in the
training program. This sort of behavior caused the program ineffective”.
Respondent 8 (HRD) supports the above response that “trainees expect the immediate
financial benefits from the development program for example cash rewards or increment
in pay scale rather than increased knowledge and skills. This sort of attitude makes the
MD programs less affective”.
Respondent 16 (trainee) commented that “ most of the times trainee’s attitude causes
the failure of all efforts…. for example…. sometimes when employees get bore or
exhausted from the routine jobs they want some change and then they feel attending a
training program as an opportunity to get relaxed. Even some times, boss feels that his
subordinate is feeling exhausted and he sends him on training for relaxation. If trainee
doesn’t perceive the training program as an opportunity and doesn’t give it priority, I
think, all efforts are wasted”.
Respondent 7 (HRD) considered it a problem that “attitude of managers in most of the
Pakistani organizations towards training and development is non-serious. Employees
don’t have the mind set to learn more through T&D”. He further commented that MD is
the responsibility of both organization and individual, the main hurdle in the way of MD
effectiveness is employees’ attitude. If people show seriousness and consider the
developmental opportunities on propriety basis, organizations can achieve their MD
objectives.
Respondent 17 (trainee) pointed out that “many times MD is not perceived positively
just because managers believe that after returning from the program our work load will
be increased and in return our organization would not offer any reward”.
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Respondent 15 (trainee) was of the view that “many times we have to attend a training
program just because of the boss’ order. What we people need is totally ignored”. She
further commented that this particular situation makes us reluctant to attend a
development program and after returning from the program, we people are not able to
apply more than 10 percent of learned skills.
In term of individual behavior and motivation, three important interrelated aspects
are found from the above responses. Trainee’s motivation, trainee’s behavior
(seriousness) and trainee’s self-development.
From the research and responses, it is clear that a training and development
program can produce desired outcomes when a manager-trainee is sufficiently motivated
and organized to his/her own development. Researchers like Chiaburu and Takleab
(2005), Methieu et al. (1992) and Neo and Schmitt (1986) opine that trainees, who are
motivated to attend a T&D program and to pay proper attention to the contents of the
T&D program, can learn maximum for such programs. Respondent 15 discussed a fact
that management and supervisors should motivate employees to attend and complete a
development program. Respondent 13 was vocal in stating that only motivated employees
would perceive that participating in the development program will lead to valuable
outcomes. Motivation from management perspective is further discussed in theme 2.
From the responses, it is clear that trainees’ attitude or seriousness towards
development programs strongly influence the effectiveness of such programs.
Respondents from HRD departments commented on attitude of managers/trainees that in
most of the Pakistani banking organizations trainees usually lacks their seriousness
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towards training and development. Most of employees do not have interest in learning
more through T&D. Development programs are perceived as burden and trainees feel
themselves as captives at training program. Respondent 7 elaborated the issue of trainee’s
behavior that non serious attitude of managers causes the failure of all efforts.
Respondent 3 commented employees do not perceive the development program as an
opportunity to enhance their knowledge and skills but their perceived outcomes from
such programs are financial rewards and increased pay scale. These views are also
supported by individual managers (trainees) such as Respondent 16 asserted that training
programs are perceived as opportunity to get relaxed from hectic routine jobs. Further
according to Respondent 17 trainees believe that after returning from training program
their workload will increase, as they will be given more responsibilities. These findings
or issues are also common in public sector projector organizations in Pakistan (Rehman,
2007).
It is also found that a motivated trainee mostly has a positive attitude towards
training. Motivation from top management and immediate supervisor helps to make a
trainee more serious for a development program. Respondent 1 and 13 explained that a
motivated trainee believes that participating in the development program would lead to
valued outcomes and would enhance his knowledge skills and abilities. These views were
supported by respondent 2 as well that employee who is motivated and shows seriousness
perceives the development program as an opportunity to learn and a serious employee
gives due attention to the contents of the training program and after returning from the
program, he/she applies newly learned skills on the real job settings.
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This is also found that employee who shows seriousness towards development
programs, plays an active role for his/her self-development. Respondent 2 elaborated the
fact that motivated employee gives due attention to contents of training program and
employee believes that every development opportunity would lead to desired outcomes
and he/she will eagerly participate in the next program. Respondent 7 pointed out that
MD is not only the responsibility of organization or management but both individuals and
organization are responsible for the success or failure of the MD programs. For a
development program to be effective individuals need to play active role in their own
development and should believe that participating in MD programs will results in desired
outcomes. A motivated and serious employee assesses his level of readiness for a
developmental change and takes initiatives for self-development. As Paauwe and
Willians (2001) presented a learning strategy named as “pull strategy of learning” where
development programs are provided to managers only when managers demand for a
development program. And further, they suggested that individual managers and HR
department must identify the learning need of managers. Possible reasons found behind
the lack of self-development initiative in Pakistani managers, are lack of seriousness and
lack of motivation from top management and immediate supervisors.
In conclusion of this theme, it can be stated that along with other factors
individual-trainee is directly related with the success or failure of MD programs. This
finding of qualitative analysis is also supported by quantitative analysis in chapter 6 that
support from top and line management make individual trainees more serious towards
training and self-development and these motivated and serious trainees directly influence
the effectiveness of MD. Top and line management should motivate employees to attend
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the training program because only motivated employees will show seriousness towards
the program. And serious employees show readiness to learn from the program. For a
MD program to be successful and more effective, managers should be sent on training
and development program when they are highly motivated, serious, and show their
readiness to learn. Figure 11 depicts the conclusion of above discussion.
Figure 11: Summery of theme 1.
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6.4 Theme 2: Management Perspective
The second theme elicited from the interviews data is the “management
perspective”. Management perspective in this context refers to the support and role of top
and line management which they play for creating a MD program more effective. It is
depicted in Figure 12 that from the interviews data, four major issues (sub-themes) have
been identified in respect to management perspective that can influence the effectiveness
of MD. Chiaburu and Marinova (2005) and Lim and Johnson (2002) stated that
management or organizational support is necessary to guarantee that investment in MD
has realized preferred outcomes. Interviewees expressed very specific expectations with
regard to management support that support the above mentioned studies.
Figure 12: Theme2: Management perspective.
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6.4.1 Senior Management Support Responses and Findings Respondent 7 (HRD) stated that “executive support is a critical factor for the success or
failure of MD programs. Higher management should involve in all phases of a
development program I.e. developing curriculum, selecting trainees, and monitoring the
program”. He further stated that linking the MD goals to the corporate goals is the
responsibility of the top management.
Respondent 8 (HRD) suggested that “ top management should take the MD on priority
basis and substantial efforts should be taken to make MD more effective”
Respondent 15 (trainee) elaborated on the fact that “senior management or supervisors
play a significant role in subordinates’ training motivation, goal setting, and reinforce
the transfer of their learning”.
Respondent 1 (HRD) commented that “top management and immediate supervisors paly
vital role in success of a MD program. They motivate trainees, allocate resources,
conduct need analysis, monitor program and emphasize the applicability of newly
learned skill”. He further proclaimed that in his organization management support for
management development programs is mediocre.
Respondent 11 (trainee) asserted that being trainees “if we don’t find the supportive
behavior of our top management, will not likely to apply training contents to our jobs”.
Talking about line manager or immediate supervisor support, he further commented that
being trainee, we need supervisor support on every step. And in Pakistani banking
organizations, there is lack of such support which makes MD less effective.
Respondent 22 (trainee) stated that “the per capita training and development
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expenditure in Pakistan is much lower as compared to the advance countries, further
during crisis top management reduces the development budget”. He was also of the
opinion that top management should provide enough financial resources for the smooth
and continuous running of the development programs.
Respondent 21 (trainee) commented that “after returning from a program we need
coaching, mentoring or challenging assignments from senior management. Development
program won’t be as successful as it otherwise could be if our seniors do not provide us
coaching or give us challenging jobs”.
Respondent 16 (trainee) asserted that “after working in many organizations I have seen
that top management does not give priority to the development of employees. For
example top management does not give any importance to new ideas and risk taking is
always discouraged”. He further commented that such behavior of management makes
me reluctant to self-development.
From the above comments, it is found that without the support and involvement
from management, MD programs will not be successful. Top management should give
priority to MD programs and must involve in all phases of a MD program. For the
effectiveness of MD Respondent 8 stated that it is the basic responsibility of top
management that it should take substantial efforts and should give priority to MD
interventions. These comments were also supported by Respondent 7 that executive
support is a critical factor for the success or failure of MD programs. It is also found that
for the success of MD interventions, top management should involve in all phases of MD
i.e. starting from motivating employees to attend program, developing curriculum of MD
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program, allocating resources, conducting need analysis, implementing program,
monitoring and evaluating program and finally emphasizing the applicability of newly
learned skills. Respondent 1 commented that top management should play role from need
analysis till providing opportunities to apply new skills. Respondent 15 also supported
these findings that senior management plays significant role in all steps of MD program.
From the comments above it is also found that management or supervisor support
is important factor in enhancing employees training motivation. Management support
positively influences trainees’ motivation. Chen (1990) found that a motivated trainee
attends training program with stronger belief in the program’s usefulness and
management or supervisor support is important factor in enhancing trainee’s motivation.
As discussed in Theme1, it is also found that Pakistani managers being trainees need
more supportive management. Respondent 15 and 1 asserted that management should
provide support to motivate trainees. It is also found that supervisor support helps
employees to participate in and complete training program enthusiastically and apply
training contents to their jobs. Respondent 11 elaborated this fact that without supportive
behavior of management or immediate supervisor it is not possible to fully apply training
contents to our jobs.
Further, respondents also expressed their need for coaching and mentoring from
management for successfully applying newly learned skills. As respondent 21 asserted
that development programs would not be as successful as it otherwise could be if senior
management does not provide us coaching, mentoring and give us challenging jobs after
returning from a development program. Further, respondents commented that
management should provide enough financial resources for the smooth running of MD
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programs and any temptation to cut these financial resources back in any circumstances
should strongly be resisted.
From respondents, it is also found that current state of management support for
MD in Pakistani banking organizations is mediocre. Management does not give priority
to MD interventions; there is also lack of supportive behavior and financial resources
from management. These findings are inconsonance with past research on HRD in public
sector projector organizations in Pakistan (Rehman, 2007). For the effectiveness of MD,
management should give priority to MD interventions, motivate trainees, provide
financial resources, involve in all phases of MD program, link MD objectives to
corporate objective, be mentor and coach and give challenging assignments to trainees.
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6.4.2 Rewards
Responses and Findings
Respondent 4 (HRD) stated that “in Pakistan, mostly trainees expect financial benefits
from a development program, these benefits may be cash rewards or increased pay
scales”. He further suggested that to motivate such employees, top management should
give rewards to high performing employees during or after a development program.
Respondent 3 (HRD) identified that “the obvious beneficial consequences of the
development programs may include learning new knowledge, skills and increased
opportunities to pursue jobs in the company. But the mind set of Pakistani employees
differs on the point of financial rewards”. She further commented that rewards always
increase the motivation of employees to attend the development program and to transfer
the learned skills. Organizations must have proper rewarding system for exceptional
performance.
Respondent 1 (HRD) asserted that “proper rewarding is a facilitator of transfer of
effective learning and ultimately making a development program more effective”.
Respondent 16 (trainee) stated that “we people being trainees expect many thing from a
development program other than acquiring new knowledge and skill”. Researcher what
are other expectations? Respondent 16 “for me that is cash rewards and increased pay
scale and if my organization does not give me such rewards I would feel reluctant to
attend next training program”. He further argued that “what i have seen is that in my
organization many times incentive system is neither fair nor consistent. Many times, I
have observed gender discrimination in incentive system. Rewards should be given fairly
based on exceptional behavior. Fair and immediate rewards make trainees serious and
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motivated for self-development”.
The interviewees regarded fair reward system as important factor in enhancing the
employee’s training motivation. A consistent and fair reward system for exceptional
behavior motivates the employees to learn more. Noe (2000) stated that if employees do
not believe that the rewards for performance are adequate, they will be unlikely to meet
performance standards.
From comments above it is found that proper rewarding system is important
factor in enhancing employees’ training motivation. Respondent 4 suggested that there
should be a proper rewarding system in organization to motivate employees. Respondent
3 also commented that rewards motivate employees to attend development program and
transfer the learned skills. These views were also supported by Respondent 1 that proper
rewarding is a facilitator of effective transfer of learning which makes a MD program
more effective.
It is also found that Pakistani managers expect financial consequences from MD
programs along with other obvious beneficial consequences like learning of new
knowledge and skills. Respondent 2 suggested that to motivate such employees,
management should give financial benefits to trainees showing exceptional performance.
Respondent 16 also elaborated this fact that Pakistani managers expect financial benefits
like cash rewards or increased pay scale from MD programs. In the absence of proper and
fair reward system trainees would feel reluctant to attend MD programs.
Further respondents added that rewards should be given immediately after the
MD program or good performance/behavior. To make MD more effective, senior
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management should give incentives to trainees. Proper rewarding system or adequate
incentives for performance likely to enhance the motivational level of employees to learn
more and attend every development program, meet performance standards, transfer
learning and maintain the learning over a long period of time.
6.4.3 Feedback
Responses and Findings
Respondent 4 (HRD) asserted that “ proper and frequent feedback to trainees regarding
their performance plays very important role in enhancing the training-motivation of
trainees”
Respondent 19 (trainee) was of the opinion that “in Pakistani organizations, one of the
major problems in achieving the maximum learning is absence of the feedback. If
management doesn’t provide us the feedback regarding the extent to what we are meeting
performance standards, our learning may be adversely affected”.
Respondent 15 (trainee) stated that “for effective MD top management should provide
proper feedback to trainees. Being trainee, I need detailed feedback of effective and
ineffective performance”. She further commented that in Pakistani organizations I feel
the absence of proper and frequent feedback. “I think, the feedback should be provided
frequently”.
The above findings indicate that there is absence of proper feedback to the
managers (trainees) regarding their performance in Pakistani banking organizations
which makes the development programs less effective. Respondent 19 and 15 expressed
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their desperate need of receiving proper and frequent feedback. Managers need to know
extent to what they have met performance standards. Trainees need proper and frequent
feedback from the management regarding their effective or ineffective performance. It is
found that learning process of trainees can be enhanced by providing them frequent
feedback regarding their performance which ultimately enhances the effectiveness of
MD.
6.4.4 Minimizing Blockages to Effective Transfer of Learning
Responses and Findings
Respondent 5 (HRD) stated that “for maintaining the learned skills and knowledge over
a period of time management should remove blocks to effective transfer of learning”.
Respondent 6 (HRD) suggested that “for effectiveness of MD process, management
should provide enough opportunities to practice the new skills on the job and should
minimize the blockages in the way of effective transfer of learning”.
Respondent 13 (trainee) was of the view that returning from a training program, trainee
who is motivated to apply his new knowledge/skills to his day to day job may face many
hurdles. And main hurdle is no proper utilization of the new skills.
Respondent 19 (trainee) pointed out that “effective transfer of knowledge is much
important for an effective MD program. Supervisor’s support, opportunity to apply
whatever I learned from MD program, motivation to risk taking receiving feedback etc.
all these are facilitators to the effective transfer of knowledge”.
Respondent 23 (trainee) was of the view that “senior management should offer
opportunities to practice trained skills and barriers to transfer such as heavy work load,
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lack of resources and opportunities to implement new skill and ideas, lack of supervisor
support, lack of feedback, and lack of co-operation should be minimized for effective MD
programs”.
Interviewees expressed a need to have more opportunities to apply newly learned
skills on job and removing of barriers to transfer of learning by the top management.
After returning from a development program to day to day jobs, trainees may face
number of barriers which block their way to convert new knowledge and the skills into
action (Poulet, 1997). Belling, James and Ladkin (2004) identified several barriers to
effective transfer of learning. Further they suggested that these perceived barriers should
be minimized for an effective MD program.
Interviewees perceived a strong barrier to effective MD is lack of opportunities to
apply what they have learned. It is found that providing enough opportunities to use
newly learned skills is an important factor in ensuring the success of MD. Respondent 13
and 16 elaborated the fact that for effectiveness of MD, management should minimize or
remove the hurdles in the way of effective transfer of knowledge and further management
should provide opportunities to practice the newly learned skills. It is also found that
providing maximum opportunities to apply new skills help managers to maintain the
skills over a long period of time. Interviews results also support the work done by
Cheeseman (1994) that it would be only wastage of resources if organization doesn’t
provide opportunities to trainees to utilize the new knowledge and skills.
In conclusion of this theme, it can be stated that in Pakistani banking
organizations, HRD and individual managers expect more management support for MD
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programs to make such programs more effective. Top and line management both play
their role from start to the end of a MD intervention. Motivating employees for their self-
development, making proper need analysis, designing and monitoring a development
program, linking MD program goals to corporate goals, providing opportunities to utilize
new knowledge and the skills, removing barriers to effective learning transfer, rewarding
exceptional performance/behavior, providing feedback, mentoring etc. all these roles
management has to play for the effectiveness of the MD programs.
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6.5 Theme 3: Program Design Perspective
The third theme elicited from the interviews data is the “program design
perspective”. Program design perspective in this context refers to the contents of training
courses, and the methods by with training is offered to employees. It is depicted in Figure
13 that from the interviews data, four major issues (sub-themes) have been identified in
respect to program design perspective that can influence the effectiveness of MD. For
effectiveness of MD, contents of such programs must be relevant to current job
requirements and learning or teaching methods should help participants to actively
involve in the program.
Figure 13: Theme 3: Program design perspective
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6.5.1 Linking MD to Corporate Strategy
Responses and Findings
Respondent 5 (HRD) stated that “for effectiveness of MD, MD programs should be
linked to strategies and challenges of the organization. I believe that in my organization,
MD programs are linked to corporate strategies. That’s why my organization provides
more specific training programs where the current job problems are addressed”.
Respondent 7 (HRD) pointed out that “HRD goal should be linked to corporate
strategies. Providing general nature of training makes the development programs less
effective”.
Respondent 17 (trainee) suggested that “for effectiveness of MD, MD programs should
have clear development objectives and these objectives should be linked to corporate
objective”.
Respondent 16 (trainee) pointed out “in my organization MD programs reinforce the
corporate strategy... I don’t think so… so far, I believe our programs are not fully
focused”.
Respondent 22 (trainee) stated that “in my organization link between MD and corporate
strategy is weak”. Researcher what could be the possible reason? Respondent “reason
might be the small size of my organization. But I have seen some big organizations in
Pakistan where strategic management development is properly implemented”.
Respondent 3 (HRD) asserted that “few years back in Pakistan it was rear to find an
organization where strategic management development was applied. But now
management realizes the importance of SMD and organizations are paying more
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concentration on linking MD to the corporate strategy”.
McClelland (1994) argued “MD should have a more strategic role and be
incorporated as an integral part of competitive strategy formulation process”. From the
comments above, it is found that effectiveness of MD can be enhanced by linking MD
goals to corporate objectives and strategy. MD interventions can assist organizations to
meet their objectives if there is a strong link between MD procedures and established
corporate objectives. Respondent 5 and 17 asserted that a clear link between MD
objectives and organization objectives makes MD programs more effective. It is also
found that if there is no strategic link between MD objectives and corporate objectives
then MD programs do not address challenges or problems of the organizations and these
programs fail to add value to corporate strategy. Providing general nature of training
which is not fully linked to corporate objectives makes MD less effective.
Is link between MD objectives and corporate objectives in Pakistani banking
organizations established? Respondent 16 and 22 pointed out the absence of strong link
between MD objectives and corporate objectives in Pakistani banking organizations. It is
also found that management in Pakistani banking organizations is now realizing the
importance of SMD and paying more concentration to properly implement SMD in
organizations. Respondent 3, 22 and 5 indicated the increasing interest and seriousness of
management in implementing SMD in organizations. Management demands MD be fully
associated with corporate objectives and goals and should create value. As discussed in
chapter 6 “quantitative data analysis” it is also found in qualitative analysis that a clear
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MD strategy makes MD programs more specific and helps organizations to make or
choose T&D programs where the current job problems are addressed. In conclusion, it is
stated that banking organizations in Pakistan committed to enhance the effectiveness of
MD interventions, will need to have a clear MD strategy which defines destination and
direction of all these development efforts and this strategy should be incorporated with
the corporate strategy.
6.5.2 Delivery Method
Responses and Findings
Respondent 19 (trainee) was of the view that “the selected methods of training and
development have direct connection with effectiveness of such programs. Management
should offer variety of development methods and a trainee should be allowed to select
any method.
Respondent 15 (trainee) argued that “now Pakistani managers want to get rid of
traditional class room training methods”. She further commented that we want to learn
by doing instead of reading books and listening lecture.
Respondent 5 (HRD) stated that “an effective MD program method must provide people
with opportunity to experiment. Management should realize that in class room training
after reading books or listening lectures, it is not possible to implement concepts on job
without any opportunities for experimentations”.
Respondent 16 (trainee) commented that “organizations conduct development
programs for the learning. And I believe learning occurs only after practice. In Pakistani
organizations management give more stress or importance to traditional training
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methods such as class room training methods”. He further commented that trainees are
fully fed up now with these methods. For effective MD, only those methods should be
selected which emphasize the practice more.
Respondent 23 (trainee) pointed out that if management wants to make MD more
effective then action learning should be part of the process. In method of action learning
trainees are able to practice new skills.
Respondent 9 (HRD) was of the view that “mostly class room trainings are boring and
trainees have no interest. For effectiveness of MD, training and development methods
should be interesting and should emphasize applicability”.
The above findings emphasize the importance of appropriate delivery methods for
the effectiveness of MD. Interviewees expressed definite need in term of selection of
training delivery methods that create more interest for participants and emphasize the
trainees’ involvement and applicability. Respondents 9, 16 and 5 indicated that traditional
training methods such as class room training makes development process slow or less
effective. Above findings suggest that existing methods (like class room) being followed
in MD fail to generate interest of participants in training. Hence, effectiveness of the
programs diminishes. Traditional methods hardly enable the participants of training to
integrate learning into practice. Rehman (2007) also found same result in his study on
HRD practices in public sector projector organizations in Pakistan.
So there is a need for assigning more weight to careful selection of training
methods. Training methods should be selected in such a way that encourage the
participants to easily relate new learning to the workplace requirements. Above responses
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also illustrate that for effectiveness of MD programs, management should select those
training methods that provide trainees more opportunities for practice. The participants of
training should be encouraged to make experiments to foster learning. Action learning
methods could be more effective in such cases.
Pakistani managers want to learn by doing and need variety of training methods
that can fulfill their learning need. These findings are in line with the findings reported in
the literature, as Chan and Sok (2006) stated that all individuals have different learning
needs and learn from different styles; organizations should understand these needs and
should select training and development program that can fulfill the learning needs of all
employee.
6.5.3 Content Validity
Responses and Findings
Respondent 13 (trainee) stated that “for effective MD program, the learning contents
should be related to the current problems or job”.
Respondent 17 (trainee) asserted that “for me, mostly training programs are not
interesting I feel bore during the program, just because the contents are not relevant to
me. Most of the time my organization gives me training regarding those skills and
knowledge which I already have”.
Respondent 16 (trainee) suggested that for high level of learning and for the maximum
satisfaction of the trainees, the program should be well architected and perfectly
implemented.
Respondent 8 (HRD) argued that “MD programs would not be as successful as it should
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be if it is not audience specific. The program contents should focus on the job levels and
the real problem of the audience (trainees)”.
Respondent 16 (trainee) stated that “I have attended some development programs where
skills being offered were not different from what I already had. Obviously I wouldn’t
learn anything from such programs”. He further suggested that a program should help
the participants confront reality rather than the repetition of the knowledge.
For the effective MD interventions, contents of programs must be related to
current requirements. Berry (1990) argued that if a MD program does not help trainees to
confront reality and fails to establish a linking to organization’s current issue that
program would not add value to corporate strategy. Respondents 16 and 17 expressed a
concern that mostly program contents are not valid or relevant to the current job. Further
respondents pointed out that repetition of knowledge makes trainees reluctant to attend
the program and managers feel boring during session. Respondents expressed their need
that contents of MD programs must be audience-specific and relevant to company’s real
problems and issues. From the comments above, it is found that relevant program
contents result in high level of learner satisfaction and ultimately make the development
process more effective. As Chen and Sok (2006) stated “high level of course relevance to
job requirements hints at a high level of training effectiveness and vice versa”.
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6.5.4 Continuation of the Process
Responses and Findings
Respondent 15 (trainee) stated that in today’s rapidly changing organizations, learning
programs should be on continuous basis, because learning occurs by repetition.
Respondent 8 (HRD) was of the opinion that learning is the core of any development
program. Formally training programs have their definite first day and the last day. These
programs provide opportunities for the learning. But learning should proceeds
continuously.
Respondent 21 (trainee) argued that “for effective MD learning process should not stop.
It should continue over time”. He further stated that organizational culture should support
such continuous process of learning.
Respondent 13 (trainee) stated that any formal training program is perceived episodic
process. But learning doesn’t mean having episodic nature. We can learn from training
program, from the job or from any event. In any organization learning should be treated
as a continuous process. An organization should strive for the learning culture where
organization facilitates the learning and development of all of its employees.
Sadler (1998) stated that people see formal course of education and training
largely as episodic process. But learning however does not begin when the course begins,
nor stops when the course finishes. Learning proceeds continuously over time changing
from the informal to more formal modes and back again. He further gives stress on
reduction of the episodic nature of MD and gives it a continuity extending beyond the
boundaries of formal education process. Kuber and Prokopenko (cited in Sadler, 1998)
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also proposed MD cycle which demonstrates the continuity of the MD process both for
an individual manager and for an organization.
Interviewees made several remarks that support the work of Sadler (1998).
Further they added that organizational culture should support the continuous learning. For
effectiveness of MD, learning process should not stop it should continue over time.
In conclusion of this theme, it can be stated that HRD and individual managers
expect more help from senior management to establish a strong link between MD and
corporate strategy. It is evident that Pakistani executives realize the importance of SMD.
Though SMD is not fully mature in Pakistan yet substantial efforts are being made to
implement the SMD in organizations. It is the prime responsibility of the management to
make the strategy for MD which addresses the objectives and directions of MD
interventions. Organizations which have clear MD strategy that is incorporated with the
corporate strategy always design the MD programs that address organizational current
problems and weakness and these programs help participants to confront reality. By
developing a strong link between MD and corporate strategy organizations choose the
contents of MD courses that relate particularly to the organization’s objectives and
vision. A strong MD strategy helps to select the MD methods which are more interesting
for participants and emphasize the participants’ involvement. For effectiveness of MD,
MD strategies should also emphasize the continuation of MD processes as respondents
stated that learning occurs by repetition.
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CHAPETER 7
SUMMARY AND CONCLUSION
7.1 Introduction
The objective of the present research study was to assess effectiveness of MD
programs in Pakistani banking organizations, identify the factors of MD effectiveness and
to investigate what relationships exist among those factors. To achieve the research
objectives, researcher employed a blend of qualitative and quantitative methodologies in
the current study. D’Netto model of MD effectiveness provided basic framework for the
study. Based on extensive literature review two variables of second stage of MD process
were included in the existing model of D’Netto and researcher also specified the
relationships among variables. Target population in this study was all banking
organizations operating in Islamabad and Rawalpindi. To measure the predicted model of
MD effectiveness, a “self-reported rating” survey questionnaire was used. The
quantitative data for current research included responses from 168 managers from 32
banking organizations operating in Rawalpindi/Islamabad (Pakistan). In order to explore
the qualitative aspects of the issue, researcher also conducted 25 semi structured
interviews in banking sector.
In total, 15 hypotheses were developed which were analyzed through SEM using
LISREL program and found that the observed model of MD effectiveness had a good fit
with the predicted model of MD effectiveness. All hypothesized links had positive path
coefficients and were in the predicted directions. The results of this study support the past
186
research on T&D (D’Netto et al., 2008; Chaiburu & Marinova, 2005; Tracey et al., 2001).
Summary of the major findings and contribution of this study towards advancement in
theory is discussed as following.
7.2 Summary of the Research Findings
Empirical findings show that current state of MD effectiveness in Pakistani
banking organizations is just over satisfactory level. On a 7-point Likert scale, MD
effectiveness had mean score of 5.15 (SD 0.99). Low mean scores of top (4.63) and line
management support (4.77) for MD effectiveness indicate that management does not
provide adequate support for the MD programs and management does not give priority to
MD interventions; there is also lack of supportive behavior, proper feedback, mentoring,
coaching, rewards and financial resources from top management. The annual per capita
spending of US$ 270 on T&D in Pakistani banking sector is quite low. A low mean score
of link to corporate strategy (4.63) indicates that management is not making substantial
efforts to link MD goals with corporate goals. Management is also not interested in
properly monitoring and evaluating MD programs and individual efforts for their self-
development are also not satisfactory.
When organizations have a strong culture of learning, top management appears to
support MD efforts and provides weight, authority and status to MD activities. It was also
found that in a culture of learning, line managers provide support to all development
programs and activities from emphasizing the importance of attending training and
development program to stressing the application of training contents to the job.
Organizations having strong learning culture properly monitor their training and
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development program and take corrective action, when necessary and also conduct
effective post-program evaluation. Post-program evaluation helps in assessing success of
the existing program and in improving design of future programs.
The results are in consonance with Reitsma (2001) that if top management
supports the MD activities, managers from different levels in the organization give due
consideration to MD activities. Without the support and involvement from top
management, MD programs will not be successful. For the success of MD interventions,
top management should involve in all phases of MD i.e. starting from motivating
employees to attend program, developing curriculum of MD program, allocating
resources, conducting need analysis, implementing program, monitoring and evaluating
program and finally emphasizing the applicability of newly learned skills.
Individual initiative for self-development can be enhanced if top management
provides motivation, financial and emotional support to individuals at all levels. Top
management in a learning organization provides maximum opportunities for trainees to
properly utilize the newly learned skills and knowledge in the real job and removes
barriers to effective transfer of learning. For effectiveness of MD programs, top
management should play vital role in strategy formulation and should link such programs
more closely to corporate strategy. The current state of management support for MD in
Pakistani banking organizations is mediocre. There was no mean difference between top
management support for MD of public sector and private sector banks. Management does
not give priority to MD interventions; there is also lack of supportive behavior and
financial resources from management. Lack of top management support for MD is a
serious threat to the MD effectiveness.
188
This research supports the findings of (Brown, 2005; Cascio, 20003; McClelland,
1994). Linking the MD goals to established corporate strategy is essential to successfully
design and implement the MD program. Creating link between MD objectives and
corporate strategy helps to design or select program that addresses organizational
weaknesses, helps the participants to confront reality, contents of MD courses relate
explicitly to the organization’s vision, strategy, and objectives. If there is no strategic link
between MD objectives and corporate objectives, then MD programs do not address
challenges or problems of the organizations and these programs do not add any value to
organization strategy. There is lack of strong link between MD objectives and corporate
objectives in Pakistani banking organizations. Providing general nature of training which
is not fully linked to corporate objectives makes MD less effective.
The role of line manager in enhancing the MD effectiveness is multidimensional.
Line manger’s support for MD programs motivates the trainees, makes trainee more
serious towards a development program and enhances the individual initiative for his/her
self-development. Strong line manager support increases the employees’ participation in
the MD program, helps employees to complete training program enthusiastically and also
stresses the application of training content to the job. Line managers’ support for the MD
programs enhances relationship between MD programs and corporate strategy. For the
effectiveness of the MD programs, the line managers also provide better opportunities to
the employees for the utilizations of newly learned skills. Qualitative analysis also
indicates that Pakistani managers being trainees need more supportive management and
believe that development programs would not be as successful as it otherwise could be if
189
line managers or supervisors do not provide coaching, mentoring, job rotation or job
enrichment to trainees after returning from MD program.
Monitoring of MD program is also an effective tool to avoid any disturbance in
smooth running and implementation of T&D program. Program evaluation helps the
organization to control the T&D program because if the training is not effective, then it
can be dealt with accordingly. Trainee’s motivation, trainee’s behavior (seriousness) and
trainee’s efforts for self-development directly influence the effectiveness of MD
programs. Motivation from top management and immediate supervisor helps to make a
trainee more serious for a development program. And employee who is motivated and
shows positive attitude towards MD program, perceives the development program as an
opportunity to learn and believes that participating in the development program would
lead to valued outcomes.
This research supports the findings of Tharenou (2001). A motivated and serious
employee gives proper attention to the contents of the training program and after
returning from the program, he/she applies newly learned skills on the real job settings.
Employee who shows seriousness towards development programs plays active role for
his/her self-development and assesses his level of readiness for a developmental change
and takes initiatives for self-development. Such employee believes that every
development opportunity would lead to desired outcomes and he/she eagerly participates
in every development program. Pakistani banking organizations are facing the problem of
less training-motivation and non-serious attitude of trainees towards training and
development. The lack of trainees’ seriousness in self-development is also found as a
serious threat to the MD effectiveness.
190
Findings of the qualitative analysis are in support of the above results. In
qualitative component of research, interviewees expressed definite need in term of
selection of training delivery methods that create more interest for participants and
emphasize on the trainees’ involvement and applicability, so, there is need for assigning
more weight to careful selection of training and development methods. The course
contents relevant to job requirements result in high level of learner satisfaction and
ultimately make the development process more effective. In qualitative study,
respondents expressed their need that contents of MD programs must be audience-
specific and relevant to company’s real problems and issues.
Opportunities for skills utilization is directly positively associated with MD
effectiveness. In qualitative survey, the respondents emphasized upon the need to have
more opportunities to apply newly learned skills on job and removing of barriers to
transfer of learning by the top management. Study reveals that in Pakistani banking
sector, strong barrier to effective MD is lack of opportunities to apply what trainees have
learned in a development program. It is found that providing enough opportunities to use
newly learned skills help managers to maintain the skills over a long period of time.
7.3 Theoretical Significance of the Current Study
Despite the abundance of quality research in MD, limited research has been done
on effectiveness of MD. Most MD literature still only focuses on linkage between
strategic management and MD and does not on effectiveness of MD. While some
researchers like D’Netto et al. (2008) have explored the predictors of effective MD.
However, the work of D’Netto et al. (2008) is having some critical gaps. For example,
predictors of MD and their strength of association had not been fully explored.
191
The present study has attempted to fill above-discussed gaps in the literature. A
major theoretical contribution of the current study is that it has attempted to develop a
new and more holistic model of MD effectiveness. In this model researcher has tried to
address the weakness of D’Netto model of MD effectiveness, for example model
presented in this research includes the variables associated with all three stages of MD
process and empirically justified that how all three stages of MD process are equally
important for the effectiveness of MD. This study supports the overall model of effective
MD and attempted to highlight key weaknesses and failing in current attitudes towards
MD. This study also introduced new path links in the model. All those paths were
theoretically justified, significant and in the expected directions making model more
reliable in measuring MD effectiveness.
Another contribution of the current study is that in an attempt to deepen the
understanding of how extensive and effective MD is in Pakistani banking organizations,
qualitative research was also conducted by the researcher. The qualitative part of the
present study helped to highlight those issues which were not addressed by quantitative
analysis. For example, achievement of MD goals, problems in enhancing MD
effectiveness in banking organizations was accessed. In qualitative analysis, rather than
relying on the corporate perception of MD provision, the views of participant managers
(trainees) were compared to those of HRD managers.
D’Netto et al., (2008) used path analysis to test the predicted model of MD
effectiveness. In the present study, researcher used SEM techniques for quantitative data
analysis and model testing. “SME functions have been found to be superior to other
multivariate techniques including multiple regression, path analysis and factor analysis”
192
(Cheng, 2001). CFA of the “combined measurement model” was performed by
researcher to validate the measures of the latent constructs. All indicators were loaded on
their original constructs and inter-correlation was drawn among all constructs. Further,
researcher assessed the structural model by evaluating the relationships between the
latent constructs and by examining the estimated coefficients. The SEM results of the
current study are more reliable than path analysis results.
The literature review failed to provide any worthwhile data about the nature and
level of MD effectiveness in Pakistani banking organizations. This study tried to assess
the current state of MD effectiveness in Pakistani banking sector and contributed to the
present stock of knowledge and understanding of the subject by contextualizing the
concept of “MD effectiveness” in Pakistani banking sector. The research findings also
have significant academic values for all those institutions which are teaching or carrying
out research in this field.
7.4 Suggestions for Future Research
There are number of suggestions for the future research on this topic. Researchers
can use longitudinal data with more industries and increased sample size to test the model
or to enhance the generalizability of the findings of this research. Researchers can use
cross cultural data to test whether there is any impact of culture on the strength of the
relationships between the factors and MD or not. The proposed studies can investigate
effect of trainees’ motivation, their attitude towards MD program, alignment of MD with
personal development of trainee managers, methods of MD programs delivery. Similarly,
the proposed studies may also investigate mediation effect of trainees’ interest in training
193
between MD program effectiveness and factors like perceived value of development
programs, interest and support from top management, integration of training with overall
strategic plan of the organization, accountability, power distance, and development
practices like feedback mechanism, mentoring, coaching, and compensation system. It is
also suggested that antecedents for the perception about MD programs as burden also
need to be explored in the given social and cultural context.
7.5 Limitations of the Present Study
Owing to limitation of both time and cost this research has limitations which
should be taken into consideration if any generalization or conclusions are to be drawn
from the research findings:
1. Generalization of the study is limited, as this study was conducted within one
industry setting. The model of MD effectiveness needs to be further tested in
other industries of country like, telecommunication companies, software houses,
government institutions, oil and gas etc.
2. The population of this study was confined to banks operating in Rawalpindi and
Islamabad only.
3. The study was conducted in twin cities (Rawalpindi/Islamabad) of Pakistan that
might have the element of cultural specificity. Therefore, the instrument can be
applied in other cultures or cities to test the validity.
4. Researcher used cross-sectional data to test the model. Ideally, study should have
been spread over a time for drawing more meaningful results.
194
7.6 Final Conclusion
Although participants of the study were very hopeful regarding bright future of
MD in Pakistan yet the current quality of MD effectiveness is not very high. To conclude,
Pakistani banking organizations need to explore answers of following critical questions in
an effort to enhance the quality of MD.
Do we have a proper learning culture where learning proceeds
continuously over time, changing from the informal to more formal
modes?
Do we have proper written documents which state our policy of MD?
Does MD is fully systematic and goals of MD linked to corporate strategy
and goals?
Are our HR departments fully involved during strategic planning process?
Does our senior management give high priority to MD interventions and
provide sufficient training and development budget and properly reward
the trainees?
Does our top and middle management provide enough motivation to
managers to participate in and give due attention to the contents of MD
program?
Do top and middle management ensure that MD programs are strategically
designed and these programs meet the actual needs of our managers and
contents of MD programs are audience-specific and relevant to company’s
real problems and issues?
195
Do our trainees fully motivated and show their positive attitude towards
MD program?
Do our employees assess their level of readiness for a developmental
change and take initiatives for their self-development?
Do we provide proper opportunities to our trainees to utilize knowledge
and skills gained through MD program in the workplace?
Does our management provide enough coaching and mentoring to
managers once they come back from and development program?
To gain higher competitiveness in the global economic race, Pakistani banking
organizations should focus on effectiveness of MD because only effective MD programs
would justify a significant investment in MD. If MD is to contribute to the attainment of
competitive objectives, and is to be used as a competitive weapon, MD needs must be
assessed against corporate requirements. For an effective MD program, Pakistani banking
organizations should focus more on creating positive training attitude of their employees,
provide training programs which are flexible enough, contents of MD programs must be
relevant to company’s real problems and issues and provide maximum opportunities to
utilize knowledge and skills gained through development program in the work place.
196
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Appendix-A QUESTIONNAIRE
A study on “Predictors of Management Development Effectiveness in Pakistani
Banking Organizations” Dear Sir/Madam,
It is to appraise that I am a PhD scholar at National University of Modern Languages (NUML), Islamabad. We all know that management development programmes (MDPs) are integral part of overall development plans of all of the progressing banking organizations. However, studies indicate that not all MDPs succeed in achieving the desired goals. In this way, organizational efforts and resources are wasted. Why does it happen? This is most critical question for the organizations that are investing precious resources on the people.
Unfortunately, no such studies have been undertaken in Pakistan to assist banking organizations in Pakistan to cope with such problem. Cognizant of this fact, I am conducting a study here in Pakistan to explore the predictors of the success of such programmes. As a pilot case, I have chosen the banking industry in Pakistan for detailed study. The sampling exercise has picked your organization to be included in the sample.
I have constructed a questionnaire which is presented in the following pages. The study is expected to bring out some revealing findings. I am sanguine, the findings will be useful for all banking related organizations which are running or are intending to launch MDPs.
You are requested to please fill this questionnaire and return it back on the address given below within one week. I assure you that your identity will not be disclosed and your valuable views will be used for academic purpose only. The data collected with the help of this survey would be analyzed and only the aggregate results would be disclosed by the researcher. I shall feel obliged for your kind cooperation. With thanks and best regards, Ghulam Dastgeer C.A 167 Noble boys hostel Room #13, Saidpur Road, Pindora Stop, Opp:Gulzar hotel. Rawalpindi Mob: 0333-5111469
210
Questionnaire Management development effectiveness
This questionnaire has three sections. The first section is for collecting the demographic
information. In the second section, 7-points Likert scales (1=strongly disagree through
7=strongly agree) are used to collect information on variables of interest in this study.
The final section of the questionnaire consists of open-ended questions in which the
respondents are asked to provide any additional information they believe is relevant to
the study. Please take your current organization into consideration while completing
the questionnaire.
A. Respondent Information 1. Name 2.
Organization
3. Age 4. Gender 5. Highest education 6. E-mail
7. Your experience in years
7. Experience in current firm
8. Your designation in the present organization? a. Front line manager b. Middle manager c. Senior manager d. Senior vice president e. CEO
9. How many management development programs you have attended during previous two years
a. None b. One c. Two to four d. Five e. More than five
10. Total number of managers in your organization 11. Total number of employees in your organization 12. Total annual budget of training and development
211
Definitions of Terms and Concepts
Management Development
1. Management development is a dynamic and complex process by which individuals
learn to perform effectively in managerial roles (Longenecker & Fink 2001).
2. A system of personnel practices by which an organization tries to guarantee the timely
availability of qualified and motivated employees for its key positions (Jansen 2001).
3. An organizations’ conscious effort to provide its managers (and potential managers)
with opportunities to learn, grow and change, in hopes of producing over the long term
cadre of managers with the skills necessary to function effectively in that organization
(Desimone et al. 2002).
Management Development Effectiveness
Management development effectiveness refers to the extent to which management
development programs have yielded desired outcomes. Common ways of measuring
organizational results include employee or management suggestions, manufacturing
indices, attitude survey results, frequency of union grievances, absenteeism rates,
customer complaints and other organizational results (Rothwell & Kazanas 2003).
212
Management Development Methods
Clarifying roles, goals and performance expectations
Ongoing performance measurements and coaching
Being mentored by senior managers
Formal career planning discussions
Challenging/ difficult job assignments
Purposeful cross-training experiences
Visiting other facilities/departments
Increased contact with external/internal customers
Special assignments to task forces, problem-solving teams
360° feedback systems
Mentoring junior managers/supervisors
Computer technology and networks
Involvement with professional associations
Outside seminars and workshops
Pursuing additional college education
In-house seminars and workshops
Serving as an internal trainer/facilitator
Outside reading assignments, video and audio tapes, etc.
213
B. Management development effectiveness 13. In your own experience please indicate the extent to which you agree with the
following statements (Circle your answer)
Statement Strongly
Disagree Strongly
Agree
1. I perceive that management development
has increased employee’s motivation.
1 2 3 4 5 6 7
2. I perceive that management development
has increased job satisfaction.
1 2 3 4 5 6 7
3. Management development has increased
morale among employees.
1 2 3 4 5 6 7
4. Management development has reduced
stress level among employees in my
organization.
1 2 3 4 5 6 7
5. Management development programs have
reduced employees’ turnover in my
organization.
1 2 3 4 5 6 7
6. Management development has increased
efficiencies in process, resulting in higher
productivity and financial gain.
1 2 3 4 5 6 7
7. Management development has increased
capacity to adopt new technology and
methods.
1 2 3 4 5 6 7
8. Employees’ grievances have reduced. 1 2 3 4 5 6 7
9. Management development has enhanced my
ability to deal with customers more
effectively.
1 2 3 4 5 6 7
214
C. Organizational learning culture
14. Please indicate the extent to which you agree with the following statements (Circle
your answer)
Statement Strongly
Disagree Strongly
Agree
1. My organization facilitate the learning and
personal development of all employees.
1 2 3 4 5 6 7
2. Continuous process of organizational
transformation is prevalent in my
organization.
1 2 3 4 5 6 7
3. Taking initiatives and risk is encouraged. 1 2 3 4 5 6 7
4. Individual members are encouraged to
learn and to develop their full potential.
1 2 3 4 5 6 7
5. Regulations, policies and procedures of my
organization support management
development.
1 2 3 4 5 6 7
6. High performance employees are
rewarded.
1 2 3 4 5 6 7
7. Management development is perceived in a
positive way.
1 2 3 4 5 6 7
215
D. Individual initiative 15. Please indicate the extent to which you agree with the following statements (Circle your
answer)
Statement Strongly
Disagree Strongly
Agree
1. I take more responsibility and play an active
role in planning my own management
development.
1 2 3 4 5 6 7
2. I am motivated to learn in my every
management development program.
1 2 3 4 5 6 7
3. I am always ready to learn whenever I
recognize that my past experience is no longer
useful.
1 2 3 4 5 6 7
4. I left the management development program
believing I mastered new knowledge and skills.
1 2 3 4 5 6 7
5. My workload does not inhibit my ability to
attend management development programs.
1 2 3 4 5 6 7
6. I am encouraged to participate in management
development activities that will assist with my
personal growth.
1 2 3 4 5 6 7
7. I would attend a management development
program if the program fulfills my learning need.
1 2 3 4 5 6 7
216
E. Top management support 16. Please indicate the extent to which you agree with the following statements (Circle your
answer)
Statement Strongly
Disagree Strongly
Agree
1. Top management supports management
development.
1 2 3 4 5 6 7
2. Top management has a positive attitude to
management development and perceives it as a
priority.
1 2 3 4 5 6 7
3. Senior managers are personally involved in
formal in-house management development
programs.
1 2 3 4 5 6 7
4. Top management provides adequate resources
needed to enable management development
function to operate effectively.
1 2 3 4 5 6 7
5. Top management determine management
development objectives, polices in consultation
with training specialists.
1 2 3 4 5 6 7
6. Senior management always chooses the right
people for management development programs.
1 2 3 4 5 6 7
7. Top management provides weight, authority
and status to management development activities.
1 2 3 4 5 6 7
217
F. Link to corporate strategy
17. Thinking about the Human Resources function in your organization please indicate the extent to which
you agree with the following statements (Circle your answer)
Statement Strongly
Disagree Strongly
Agree
1. Management development programs goals
are linked to corporate strategy.
1 2 3 4 5 6 7
2. The organization has a succession plan
which is linked to the organization structure
and strategy.
1 2 3 4 5 6 7
3. HR department is involved during
strategic planning process.
1 2 3 4 5 6 7
4. Management development programs meet
future business needs.
1 2 3 4 5 6 7
5. Management development programs have
developed me to think strategically.
1 2 3 4 5 6 7
6. Development needs are tied to the business
strategy.
1 2 3 4 5 6 7
7. Organization’s business issues are
discussed with HR department.
1 2 3 4 5 6 7
218
G. Post-Program evaluation
18. Please indicate the extent to which you agree with the following statements (Circle your
answer)
Statement Strongly
Disagree Strongly
Agree
1. In my organization after completing
management development program,
evaluations are carried out.
1 2 3 4 5 6 7
2. Evaluation was carried to measure extent to
what I have changed and acquired new
knowledge, skills and behavior.
1 2 3 4 5 6 7
3. I was asked to take a test or complete an
assignment to assess the extent of learning in my
last program.
1 2 3 4 5 6 7
4. I believe that management development has
contributed significantly to changing my behavior.
1 2 3 4 5 6 7
5. I believe that post-program evaluation is
beneficial.
1 2 3 4 5 6 7
6. Management development is assessed to
measure the return on organization investment in
program.
1 2 3 4 5 6 7
7. Management development is assessed to
determine the improvement to organizational
performance and outcomes.
1 2 3 4 5 6 7
219
H. Line manager support 19. Please indicate the extent to which you agree with the following statements (Circle your
answer)
Statement Strongly
Disagree Strongly
Agree
1. In my organization trainees can communicate
easily with their managers regarding their
management development.
1 2 3 4 5 6 7
2. Managers emphasize the importance of
attending a management development program.
1 2 3 4 5 6 7
3. Managers provide coaching to trainees after
they return from management development
program.
1 2 3 4 5 6 7
4. After the program, my manager supports the
use of my newly acquired knowledge and skills.
1 2 3 4 5 6 7
5. My manager's feedback is always constructive. 1 2 3 4 5 6 7
6. In my organization managers encourage
trainees to play an active role in self-
development.
1 2 3 4 5 6 7
7. Managers assist trainees in goal setting and
planning their management development.
1 2 3 4 5 6 7
220
I. Opportunity for skill utilization 20. Please indicate the extent to which you agree with the following statements (Circle your
answer)
Statement Strongly
Disagree Strongly
Agree
1. My organization provides me with
opportunities to use my new knowledge and
skills.
1 2 3 4 5 6 7
2. What I learnt in the management
development program is easily transferable to
my work environment.
1 2 3 4 5 6 7
3. Follow-up activities after the management
development program occur back at the
workplace.
1 2 3 4 5 6 7
4. I am motivated to apply my new knowledge
and skills in my job.
1 2 3 4 5 6 7
5. I have sufficient time in my workplace to use
my new knowledge and skills.
1 2 3 4 5 6 7
6. There is no resistance to using new skills in
the workplace.
1 2 3 4 5 6 7
7. The equipment and facilities at my workplace
are adequate for applying my new knowledge
and skills.
1 2 3 4 5 6 7
221
J. Management development program design 21. In your own experience please indicate the extent to which you agree with the
Statement Strongly
Disagree Strongly
Agree
1. Training and development course contents were
relevant to job requirements.
1 2 3 4 5 6 7
2. Selected methods of management development
have direct connection to the company’s real
problem and issues.
1 2 3 4 5 6 7
3. Management development programs realize me
that what I am learning is different from my current
practice.
1 2 3 4 5 6 7
4. Management development programs are flexible
enough that allow me to think for myself and learn
from my mistakes.
1 2 3 4 5 6 7
5. Knowledge and skills being offered during MD
program are different from those I have.
1 2 3 4 5 6 7
6. Management development programs fulfill need
of the both organization and individual.
1 2 3 4 5 6 7
7. Selected methods of MD were interesting,
emphasize applicability.
1 2 3 4 5 6 7
8. There was a variety of training methods to fit
with my learning style.
1 2 3 4 5 6 7
9. Training facilities were sufficient during
secession to promote my learning.
1 2 3 4 5 6 7
following
222
K. Effective Monitoring 22. In your own experience please indicate the extent to which you agree with the following
statements (Circle your answer)
Statement Strongly
Disagree Strongly
Agree
1. During training secession my performance
was monitored periodically by my
organization.
1 2 3 4 5 6 7
2. My seniors interacted with me during the
training to know about training effectiveness.
1 2 3 4 5 6 7
3. My learning gain was monitored by top
management along with program director.
1 2 3 4 5 6 7
4. HR department of my organization
interacted with me during the training to know
about training effectiveness.
1 2 3 4 5 6 7
5. During secession program design was
changed/corrective actions were taken on my
feedback.
1 2 3 4 5 6 7
6. Top and line managers met trainers for
smooth running of the program.
1 2 3 4 5 6 7
7. I believe monitoring is an effective tool for a
successful training and development program.
1 2 3 4 5 6 7
223
L. Open-ended Questions (Please use additional sheet if necessary) 23. What major issues are related with effectiveness of management development? And what do you suggest for improvements in the effectiveness of management development?
Thank you for completing this questionnaire! Please return it to researcher on given address
Ghulam Dastgeer C.A 167 Noble boys hostel Room #13, Saidpur Road, Pindora Stop,
Opp:Gulzar hotel. Rawalpindi
If you have any questions or comments regarding this questionnaire, please contact
224
Appendix-B
Banks Operating in Rawalpindi/Islamabad
s/n Name of Bank Branched in
Islamabad
Branches in
Rawalpindi
Total
Branches
PUBLIC SECTOR BANKS
1 First Women Bank Limited 3 2 5
2 National Bank of Pakistan 24 14 38
3 The Bank of Khyber 1 2 3
4 The Bank of Punjab 4 11 15
SPECIALIZED BANKS
5 Industrial Development Bank of
Pakistan
1 1 2
6 SME Bank Limited1 1 1 2
7 Zarai Taraqiati Bank Limited 2 1 3
PRIVATE BANKS
8 Allied Bank Limited 30 34 64
9 Arif Habib/Summit Bank Limited 1 2 3
10 Askari Bank Limited 18 17 35
11 Atlas Bank Limited 3 1 4
12 Bank Alfalah Limited 11+3(Islamic) 13+3(Islamic) 30
13 Bank Al Habib Limited 5 6 11
225
14 Faysal Bank Limited 9 6 15
15 Habib Bank Limited 25 30 55
16 Habib Metropolitan Bank Limited 2 2 4
17 JS Bank Limited 5 4 9
18 KASB Bank Limited 5 5 10
19 MCB Bank Limited 19 23 42
20 Mybank Limited 2 3 5
21 NIB Bank Limited 12 8 20
22 SAMBA Bank Limited 3 1 4
23 Soneri Bank Limited 5 6 11
24 Standard Chartered Bank (Pakistan)
Limited
14 8 22
25 The Royal Bank of Scotland Limited 3 3 6
26 United Bank Limited 14 12 26
ISLAMIC BANKS
27 BankIslami Pakistan Limited 5 3 8
28 Dawood Islamic Bank Limited 4 1 5
29 Dubai Islamic Bank Pakistan Limited 2 2 4
30 Emirates Global Islamic Bank
Limited
2 1 3
31 Meezan Bank Limited 10 7 17
FOREIGN BANKS
32 Albaraka Islamic Bank B.S.C. (E.C.) 2 3 5
226
33 Barclays Bank PLC 1 2 3
34 Citibank N.A. - Pakistan Operations 1 1 2
35 Deutsche Bank AG 1 0 1
36 HSBC Bank Middle East Limited 2 1 3
MICRO FINANCE BANKS
37 Khushhali Bank Limited 0 1 1
38 Pak Oman Microfinance Bank
Limited
1 1 2
Total 256 242 498
227
Appendix-C
Frequency distribution: Age
Frequency Percent Valid Percent
Cumulative
Percent
Valid 23.00 2 1.2 1.4 1.4
24.00 5 3.0 3.5 5.0
25.00 6 3.6 4.3 9.2
26.00 11 6.5 7.8 17.0
27.00 9 5.3 6.4 23.4
28.00 8 4.7 5.7 29.1
29.00 7 4.1 5.0 34.0
30.00 4 2.4 2.8 36.9
31.00 10 5.9 7.1 44.0
32.00 11 6.5 7.8 51.8
33.00 2 1.2 1.4 53.2
34.00 2 1.2 1.4 54.6
35.00 19 11.2 13.5 68.1
36.00 7 4.1 5.0 73.0
37.00 4 2.4 2.8 75.9
228
38.00 6 3.6 4.3 80.1
39.00 5 3.0 3.5 83.7
40.00 6 3.6 4.3 87.9
42.00 5 3.0 3.5 91.5
43.00 2 1.2 1.4 92.9
48.00 2 1.2 1.4 94.3
49.00 1 .6 .7 95.0
51.00 1 .6 .7 95.7
53.00 1 .6 .7 96.5
54.00 1 .6 .7 97.2
55.00 2 1.2 1.4 98.6
56.00 1 .6 .7 99.3
62.00 1 .6 .7 100.0
Total 141 83.4 100.0
Missing System 27 16.6
Total 168 100.0
229
Appendix- D
Frequency distribution: Organizations
Frequency Percent Valid Percent
Cumulative
Percent
Valid Citi Bank 2 1.2 1.3 1.3
Bank of Khayber 3 1.8 1.9 3.2
HSBC Bank 3 1.8 1.9 5.1
SME Bank 5 3.0 3.2 8.3
Allied Bank 8 4.8 5.1 13.5
Bank Alflah 11 6.5 7.1 20.5
Bank Al-Habib 9 5.4 5.8 26.3
Dubai Islamic Bank 9 5.4 5.8 32.1
Samba Bank 5 3.0 3.2 35.3
KASB Bank 5 3.0 3.2 38.5
Faysal bank 7 4.2 4.5 42.9
Albaraka bank 6 3.6 3.8 46.8
Muslim Commercial
Bank
6 3.6 3.8 50.6
JS Bank 5 3.0 3.2 53.8
230
Bank Islami 3 1.8 1.9 55.8
Meeazan Bank 11 6.5 7.1 62.8
Soneri Bank 3 1.8 1.9 64.7
Bank of Punjab 5 3.0 3.2 67.9
United Bank 3 1.8 1.9 69.9
Askari Islamic Bank 3 1.8 1.9 71.8
Habib Bank 4 2.4 2.6 74.4
Askari Bank Ltd. 4 2.4 2.6 76.9
NIB Bank 8 4.8 5.1 82.1
Standard Chartered
Bank
6 3.6 3.8 85.9
National Bank Pakistan 2 1.2 1.3 87.2
Dawood Islamic Bank 1 .6 .6 87.8
Barclays Bank 4 2.4 2.6 90.4
Emirates Global Islamic
Bank Limited
3 1.8 1.9 92.3
First Woman Bank 2 1.2 1.3 93.6
Atlas Bank 3 1.8 1.9 95.5
Deutsche Bank 1 .6 .6 96.2
Royal Bank of Scotland 6 3.6 3.8 100.0
Total 156 92.9 100.0
231
Missing System 12 7.1
Total 168 100.0
232
Appendix-E
COMPLETE LISREL RESULTS OF MEASUREMTN MODEL
Covariance Matrix of All Indicators
MD1 MD2 MD3 CUL1 CUL2 CUL3
-------- -------- ------- -------- -------- --------
MD1 1.548
MD2 0.784 1.243
MD3 0.706 0.766 1.338
CUL1 0.674 0.678 0.694 1.546
CUL2 0.718 0.673 0.629 1.106 1.889
CUL3 0.685 0.498 0.703 1.066 1.300 1.979
INDI1 0.619 0.518 0.455 0.605 0.570 0.606
INDI2 0.321 0.228 0.088 0.303 0.257 0.318
INDI3 0.375 0.295 0.336 0.389 0.441 0.593
TOP1 0.737 0.472 0.654 0.751 0.656 1.108
TOP2 0.496 0.296 0.470 0.588 0.611 0.938
TOP3 0.517 0.329 0.567 0.751 0.740 1.040
COR1 0.625 0.380 0.412 0.517 0.649 0.920
COR2 0.546 0.376 0.501 0.607 0.676 0.952
COR3 0.634 0.509 0.450 0.622 0.767 0.913
LINE1 0.382 0.387 0.296 0.597 0.727 0.728
LINE2 0.592 0.378 0.326 0.559 0.564 0.515
LINE3 0.485 0.248 0.365 0.593 0.629 0.608
OPPO1 0.630 0.458 0.500 0.865 0.894 0.870
OPPO2 0.625 0.561 0.501 0.789 0.758 0.742
OPPO3 0.491 0.425 0.481 0.803 0.758 0.805
DES1 0.558 0.508 0.432 0.686 0.766 0.781
233
DES2 0.596 0.560 0.453 0.676 0.785 0.760
DES3 0.442 0.365 0.273 0.593 0.762 0.764
EVA1 0.328 0.067 0.256 0.351 0.400 0.516
EVA2 0.537 0.411 0.447 0.441 0.503 0.615
MON1 0.511 0.333 0.310 0.503 0.685 0.590
MON2 0.486 0.393 0.124 0.703 0.909 0.660
Covariance Matrix
INDI1 INDI2 INDI3 TOP1 TOP2 TOP3
-------- -------- -------- -------- -------- --------
INDI1 1.193
INDI2 0.315 1.279
INDI3 0.570 0.330 1.148
TOP1 0.737 0.334 0.592 2.230
TOP2 0.581 0.326 0.480 1.357 2.090
TOP3 0.571 0.245 0.441 1.164 1.433 1.769
COR1 0.690 0.297 0.626 1.021 1.002 0.981
COR2 0.555 0.201 0.412 0.885 0.993 0.989
COR3 0.619 0.246 0.290 0.749 0.747 0.757
LINE1 0.626 0.191 0.451 0.824 0.702 0.786
LINE2 0.456 0.356 0.232 0.604 0.875 0.827
LINE3 0.577 0.202 0.472 0.843 0.814 0.916
OPPO1 0.430 0.320 0.354 0.699 0.760 0.789
OPPO2 0.429 0.224 0.285 0.542 0.512 0.696
OPPO3 0.341 0.232 0.247 0.603 0.646 0.733
DES1 0.536 0.289 0.436 0.571 0.556 0.656
DES2 0.487 0.323 0.379 0.561 0.421 0.493
DES3 0.379 0.212 0.363 0.560 0.398 0.505
234
EVA1 0.391 0.271 0.370 0.482 0.670 0.706
EVA2 0.611 0.248 0.467 0.815 0.733 0.624
MON1 0.506 0.209 0.567 0.645 0.597 0.640
MON2 0.441 0.398 0.523 0.692 0.525 0.683
Covariance Matrix
COR1 COR2 COR3 LINE1 LINE2 LINE3
-------- -------- -------- -------- -------- --------
COR1 1.633
COR2 1.142 1.628
COR3 0.852 1.003 1.449
LINE1 0.807 0.820 0.627 1.807
LINE2 0.675 0.673 0.738 1.052 1.927
LINE3 0.741 0.789 0.739 1.098 1.297 1.761
OPPO1 0.460 0.536 0.525 0.676 0.954 0.958
OPPO2 0.428 0.514 0.574 0.573 0.825 0.856
OPPO3 0.427 0.512 0.490 0.610 0.739 0.777
DES1 0.555 0.588 0.578 0.653 0.642 0.707
DES2 0.472 0.444 0.539 0.515 0.531 0.542
DES3 0.521 0.519 0.553 0.559 0.443 0.503
EVA1 0.795 0.723 0.648 0.775 1.025 0.834
EVA2 1.039 0.846 0.734 0.577 0.855 0.784
MON1 0.791 0.739 0.698 0.834 0.841 0.872
MON2 0.771 0.757 0.646 0.803 0.828 0.909
235
Covariance Matrix
OPPO1 OPPO2 OPPO3 DES1 DES2 DES3
-------- -------- -------- -------- -------- --------
OPPO1 1.572
OPPO2 1.149 1.367
OPPO3 1.147 1.090 1.625
DES1 0.697 0.742 0.637 1.303
DES2 0.681 0.677 0.614 0.939 1.150
DES3 0.537 0.586 0.497 0.812 0.782 1.066
EVA1 0.516 0.411 0.454 0.334 0.245 0.383
EVA2 0.598 0.514 0.394 0.450 0.424 0.414
MON1 0.610 0.537 0.558 0.721 0.630 0.743
MON2 0.682 0.588 0.529 0.802 0.798 0.815
Covariance Matrix
EVA1 EVA2 MONI1 MON2
-------- -------- -------- --------
EVA1 1.828
EVA2 0.818 1.462
MON1 0.873 0.737 1.977
MON2 0.777 0.542 1.448 2.156
236
Standardized Solution
LISREL Estimates (Maximum Likelihood)
NOTE: MD = Management Development Effectiveness;
Culture = Organizational Learning Culture;
Indi = Individual Initiative;
Top = Top Management Support;
Corp = Link to Corporate Strategy;
Moni = Monitoring and Evaluation;
Line = Line Manager Support;
Skill = Opportunities for Skill Utilizations;
Design = MD Program Design
PHI MD Culture Indi Top Corp Moni -------- -------- -------- -------- -------- -------- MD 1.000 Culture 0.696 1.000 (0.059) 11.777 Indi 0.665 0.652 1.000 (0.075) (0.072) 8.898 9.050 Top 0.455 0.642 0.609 1.000 (0.078) (0.059) (0.074) 5.846 10.818 8.244 Corp 0.536 0.671 0.700 0.752 1.000 (0.073) (0.058) (0.068) (0.044) 7.341 11.628 10.334 15.579
237
Moni 0.435 0.571 0.673 0.598 0.762 1.000 (0.084) (0.071) (0.075) (0.067) (0.046) 5.163 8.047 9.031 8.923 15.872 Line 0.388 0.505 0.566 0.643 0.654 0.770 (0.083) (0.072) (0.078) (0.058) (0.059) (0.047) 4.695 7.047 7.253 11.000 11.167 16.290 Skill 0.564 0.706 0.455 0.550 0.454 0.546 (0.068) (0.051) (0.083) (0.064) (0.073) (0.070) 8.333 13.859 5.491 8.577 6.249 7.843 Design 0.595 0.731 0.619 0.481 0.549 0.650 (0.066) (0.049) (0.072) (0.070) (0.066) (0.061) 9.046 14.946 8.612 6.844 8.324 10.652 PHI Line Skill Design -------- -------- -------- Line 1.000 Skill 0.698 1.000 (0.051) 13.692 Design 0.554 0.653 1.000 (0.065) (0.054) 8.495 12.176
238
LISREL Estimates (Maximum Likelihood) LAMBDA-X MD Learning Indi Top Corp Moni -------- -------- -------- -------- -------- -------- MD1 0.906 - - - - - - - - - - (0.091) 9.997 MD2 0.875 - - - - - - - - - - (0.079) 11.023 MD3 0.830 - - - - - - - - - - (0.085) 9.813 CUL1 - - 0.976 - - - - - - - - (0.084) 11.607 CUL2 - - 1.096 - - - - - - - - (0.092) 11.882 CUL3 - - 1.157 - - - - - - - - (0.093) 12.426 INDI1 - - - - 0.853 - - - - - - (0.084) 10.116 INDI2 - - - - 0.398 - - - - - - (0.095) 4.204 INDI3 - - - - 0.672 - - - - - -
239
(0.084) 8.033 TOP1 - - - - - - 1.068 - - - - (0.105) 10.217 TOP2 - - - - - - 1.214 - - - - (0.095) 12.836 TOP3 - - - - - - 1.164 - - - - (0.085) 13.657 CORPO - - - - - - - - 1.068 - - (0.083) 12.812 CORPO2 - - - - - - - - 1.057 - - (0.084) 12.652 CORPO3 - - - - - - - - 0.881 - - (0.083) 10.584 LINE1 - - - - - - - - - - - - LINE2 - - - - - - - - - - - - LINE3 - - - - - - - - - - - - OPPO1 - - - - - - - - - - - - OPPO2 - - - - - - - - - - - - OPPO3 - - - - - - - - - - - -
240
DESIGN1 - - - - - - - - - - - - DESIGN2 - - - - - - - - - - - - DESIGN3 - - - - - - - - - - - - EVA1 - - - - - - - - - - 0.859 (0.099) 8.644 EVA2 - - - - - - - - - - 0.830 (0.087) 9.539 MONI1 - - - - - - - - - - 1.030 (0.099) 10.407 MONI2 - - - - - - - - - - 1.009 (0.106) 9.558 LAMBDA-X Line Skill Pro -------- -------- -------- MD1 - - - - - - MD2 - - - - - - MD3 - - - - - - CUL1 - - - - - - CUL2 - - - - - - CUL3 - - - - - -
241
INDI1 - - - - - - INDI2 - - - - - - INDI3 - - - - - - TOP1 - - - - - - TOP2 - - - - - - TOP3 - - - - - - CORPO - - - - - - CORPO2 - - - - - - CORPO3 - - - - - - LINE1 0.936 - - - - (0.095) 9.861 LINE2 1.123 - - - - (0.092) 12.169 LINE3 1.161 - - - - (0.085) 13.652 OPPO1 - - 1.120 - - (0.078) 14.417 OPPO2 - - 1.036 - - (0.073) 14.241 OPPO3 - - 1.028 - -
242
(0.084) 12.303 DESIGN1 - - - - 0.983 (0.073) 13.479 DESIGN2 - - - - 0.948 (0.067) 14.059 DESIGN3 - - - - 0.831 (0.068) 12.181
THETA-DELTA
MD1 MD2 MD3 CUL1 CUL2 CUL3
-------- -------- -------- -------- -------- --------
0.727 0.477 0.649 0.594 0.687 0.641
(0.105) (0.079) (0.091) (0.082) (0.097) (0.097)
6.957 6.015 7.090 7.241 7.061 6.637
THETA-DELTA
INDI1 INDI2 INDI3 TOP1 TOP2 TOP3
-------- -------- -------- -------- -------- --------
0.467 1.120 0.696 1.089 0.615 0.413
(0.094) (0.127) (0.092) (0.137) (0.098) (0.078)
4.971 8.810 7.565 7.959 6.298 5.312
THETA-DELTA
243
COR1 COR2 COR3 LINE1 LINE2 LINE3
-------- -------- -------- -------- -------- --------
0.492 0.510 0.672 0.931 0.665 0.414
(0.075) (0.076) (0.085) (0.115) (0.096) (0.077)
6.601 6.745 7.916 8.093 6.957 5.379
THETA-DELTA
OPPO1 OPPO2 OPPO3 DESIGN1 DESIGN2 DESIGN3
-------- -------- -------- -------- -------- --------
0.318 0.293 0.568 0.338 0.251 0.376
(0.056) (0.049) (0.075) (0.054) (0.045) (0.051)
5.731 5.960 7.579 6.265 5.568 7.338
THETA-DELTA
EVA1 EVA2 MONI1 MONI2
-------- -------- -------- --------
1.090 0.773 0.915 1.138
(0.133) (0.098) (0.122) (0.144)
8.218 7.909 7.499 7.901
244
Squared Multiple Correlations for X - Variables
MD1 MD2 MDE3 CUL1 CUL2 CUL3
-------- -------- -------- -------- -------- --------
0.530 0.617 0.515 0.616 0.636 0.676
Squared Multiple Correlations for X - Variables
INDI1 INDI2 INDI3 TOP1 TOP2 TOP3
-------- -------- -------- -------- -------- --------
0.609 0.124 0.393 0.512 0.706 0.767
Squared Multiple Correlations for X - Variables
COR1 COR2 COR3 LINE1 LINE2 LINE3
-------- -------- -------- -------- -------- --------
0.698 0.687 0.536 0.485 0.655 0.765
Squared Multiple Correlations for X - Variables
OPPO1 OPPO2 OPPO3 DESIGN1 DESIGN2 DESIGN3
-------- -------- -------- -------- -------- --------
0.798 0.785 0.650 0.741 0.782 0.648
Squared Multiple Correlations for X - Variables
EVA EVA2 MONI1 MONI2
-------- -------- -------- --------
0.404 0.471 0.537 0.472
245
Goodness of Fit Statistics
Degrees of Freedom = 314
Minimum Fit Function Chi-Square = 572.502 (P = 0.0)
Normal Theory Weighted Least Squares Chi-Square = 542.743 (P = 0.00)
Estimated Non-centrality Parameter (NCP) = 228.743
90 Percent Confidence Interval for NCP = (168.031 ; 297.321)
Minimum Fit Function Value = 3.428
Population Discrepancy Function Value (F0) = 1.370
90 Percent Confidence Interval for F0 = (1.006 ; 1.780)
Root Mean Square Error of Approximation (RMSEA) = 0.0650
90 Percent Confidence Interval for RMSEA = (0.0566 ; 0.0753)
P-Value for Test of Close Fit (RMSEA < 0.05) = 0.00324
Expected Cross-Validation Index (ECVI) = 4.352
90 Percent Confidence Interval for ECVI = (3.988 ; 4.762)
ECVI for Saturated Model = 4.862
ECVI for Independence Model = 60.953
Chi-Square for Independence Model with 378 Degrees of Freedom = 10123.080
Independence AIC = 10179.080
Model AIC = 726.743
Saturated AIC = 812.000
Independence CAIC = 10294.551
Model CAIC = 1106.148
Saturated CAIC = 2486.329
Normed Fit Index (NFI) = 0.946
Non-Normed Fit Index (NNFI) = 0.972
246
Parsimony Normed Fit Index (PNFI) = 0.786
Comparative Fit Index (CFI) = 0.977
Incremental Fit Index (IFI) = 0.977
Relative Fit Index (RFI) = 0.935
Critical N (CN) = 116.455
Root Mean Square Residual (RMR) = 0.0958
Standardized RMR = 0.0587
Goodness of Fit Index (GFI) = 0.812
Adjusted Goodness of Fit Index (AGFI) = 0.756
Parsimony Goodness of Fit Index (PGFI) = 0.628
247
Completely Standardized Solution THETA-DELTA MD1 MD2 MD3 CUL1 CUL2 CUL3 -------- -------- -------- -------- -------- -------- 0.470 0.383 0.485 0.384 0.364 0.324 THETA-DELTA INDI1 INDI2 INDI3 TOP1 TOP2 TOP3 -------- -------- -------- -------- -------- -------- 0.391 0.876 0.607 0.488 0.294 0.233 THETA-DELTA COR1 COR2 COR3 LINE1 LINE2 LINE3 -------- -------- -------- -------- -------- -------- 0.302 0.313 0.464 0.515 0.345 0.235 THETA-DELTA OPPO1 OPPO2 OPPO3 DES1 DES2 DES3 -------- -------- -------- -------- -------- -------- 0.202 0.215 0.350 0.259 0.218 0.352 THETA-DELTA EVA1 EVA2 MON1 MON2 -------- -------- -------- -------- 0.596 0.529 0.463 0.528
248
Appendix-F
COMPLETE LISREL RESULTS OF STRUCTURAL
MODEL
NOTE: MD = Management Development Effectiveness;
Culture = Organizational Learning Culture;
Indi = Individual Initiative;
Top = Top Management Support;
Corp = Link to Corporate Strategy;
Moni = Monitoring and Evaluation;
Line = Line Manager Support;
Skill = Opportunities for Skill Utilizations;
Design = MD Program Design
Standardized Solution
LISREL Estimates (Maximum Likelihood) LAMBDA-Y MDEFFC1 0.889 MDEFFC2 0.846 (0.103) 8.217 MDEFFC3 0.796 (0.103) 7.717 INDI1 0.887
249
INDI2 0.390 (0.100) 3.882 INDI3 0.653
(0.101) 6.451 TOP1 1.092 TOP2 1.172 (0.116) 10.058 TOP3 1.134 (0.108) 10.538 CORPO 1.030 CORPO2 1.085 (0.093) 11.713 CORPO3 0.892 (0.089)
10.025 LINE1 0.965 LINE2 1.097
(0.116) 9.434 LINE3 1.147 (0.114) 10.093 eva1 0.718 eva2 0.633
(0.122) 5.173 moni1 1.141 (0.173)
250
6.615 moni2 1.181 (0.179) 6.594 OPPO1 1.115 OPPO2 1.039 (0.068) 15.297 OPPO3 1.033 (0.078) 13.255 DESIGN1 0.965 DESIGN2 0.919 (0.068) 13.443 DESIGN3 0.824 (0.067) 12.282 LAMBDA-X CUL1 0.944 (0.086) 10.947 CUL2 1.094 (0.093) 11.700 CUL3 1.141 (0.095) 12.014
251
BETA
MD Indi Top Corp Moni Line
-------- -------- -------- -------- -------- --------
MD - - 0.426 - - - - - - - -
(0.116)
3.682
Indi - - - - 0.520 - - - - 0.225
(0.125) (0.119)
4.178 1.885
Top - - - - - - - - - - - -
Corp - - - - 0.671 - - - - 0.231
(0.109) (0.094)
6.142 2.454
Moni - - - - - - - - - - - -
Line - - - - 0.395 - - - - - -
(0.131)
3.020
Skill - - - - 0.198 - - - - 0.579
(0.099) (0.110)
1.991 5.242
Pro - - - - - - 0.216 0.590 - -
(0.081) (0.116)
252
2.656 5.106
BETA
Skill Pro
-------- --------
MD 0.241 0.228
(0.094) (0.086)
2.553 2.640
Indi - - - -
Top - - - -
Corp - - - -
Moni - - - -
Line - - - -
Skill - - - -
Pro - - - -
GAMMA
Learning
--------
MD - -
253
Indi - -
Top 0.736
(0.093)
7.886
Corp - -
Moni 0.678
(0.120)
5.645
Line 0.349
(0.127)
2.736
Skill - -
Pro - -
254
PSI
Note: This matrix is diagonal.
MD Indi Top Corp Moni Line
-------- -------- -------- -------- -------- --------
0.513 0.527 0.458 0.296 0.540 0.520
(0.123) (0.137) (0.101) (0.068) (0.166) (0.112)
4.176 3.836 4.529 4.318 3.241 4.626
PSI
Note: This matrix is diagonal.
Skill Pro
-------- --------
0.477 0.494
(0.079) (0.088)
6.060 5.629
Squared Multiple Correlations for Structural Equations
MD Indi Top Corp Moni Line
-------- -------- -------- -------- -------- --------
0.487 0.473 0.542 0.704 0.460 0.480
Squared Multiple Correlations for Structural Equations
Skill Pro
-------- --------
0.523 0.506
255
NOTE: R² for Structural Equations are Hayduk's (2006) Blocked-Error R²
Reduced Form
Learning
--------
MD 0.472
(0.077)
6.099
Indi 0.527
(0.079)
6.647
Top 0.736
(0.093)
7.886
Corp 0.641
(0.081)
7.915
Moni 0.678
(0.120)
5.645
Line 0.640
(0.095)
6.766
256
Skill 0.516
(0.073)
7.025
Pro 0.539
(0.075)
7.208
Squared Multiple Correlations for Reduced Form
MD Indi Top Corp Moni Line
-------- -------- -------- -------- -------- --------
0.222 0.277 0.542 0.411 0.460 0.409
Squared Multiple Correlations for Reduced Form
Skill Pro
-------- --------
0.266 0.290
257
Goodness of Fit Statistics
Degrees of Freedom = 335
Minimum Fit Function Chi-Square = 765.108 (P = 0.0)
Normal Theory Weighted Least Squares Chi-Square = 725.889 (P = 0.0)
Estimated Non-centrality Parameter (NCP) = 390.889
90 Percent Confidence Interval for NCP = (316.986 ; 472.529)
Minimum Fit Function Value = 4.581
Population Discrepancy Function Value (F0) = 2.341
90 Percent Confidence Interval for F0 = (1.898 ; 2.830)
Root Mean Square Error of Approximation (RMSEA) = 0.0736
90 Percent Confidence Interval for RMSEA = (0.0703 ; 0.0919)
P-Value for Test of Close Fit (RMSEA < 0.05) = 0.000
Expected Cross-Validation Index (ECVI) = 5.197
90 Percent Confidence Interval for ECVI = (4.754 ; 5.686)
ECVI for Saturated Model = 4.862
ECVI for Independence Model = 60.953
Chi-Square for Independence Model with 378 Degrees of Freedom = 10123.080
Independence AIC = 10179.080
Model AIC = 867.889
Saturated AIC = 812.000
Independence CAIC = 10294.551
Model CAIC = 1160.690
Saturated CAIC = 2486.329
Normed Fit Index (NFI) = 0.928
Non-Normed Fit Index (NNFI) = 0.956
Parsimony Normed Fit Index (PNFI) = 0.826
258
Comparative Fit Index (CFI) = 0.960
Incremental Fit Index (IFI) = 0.960
Relative Fit Index (RFI) = 0.919
Critical N (CN) = 92.598
Root Mean Square Residual (RMR) = 0.174
Standardized RMR = 0.112
Goodness of Fit Index (GFI) = 0.763
Adjusted Goodness of Fit Index (AGFI) = 0.713
Parsimony Goodness of Fit Index (PGFI) = 0.630
259
Completely Standardized Solution
LAMBDA-Y MDEFFC1 0.726 MDEFFC2 0.773 MDEFFC3 0.699 INDI1 0.812 INDI2 0.345 INDI3 0.609 TOP1 0.731 TOP2 0.810 TOP3 0.853 CORPO 0.806 CORPO2 0.851 CORPO3 0.741 LINE1 0.718 LINE2 0.790 LINE3 0.864 eva1 0.531 eva2 0.523 moni1 0.812 moni2 0.805 OPPO1 0.889
260
OPPO2 0.889 . OPPO3 0.810 DESIGN1 0.858 DESIGN2 0.870 DESIGN3 0.809 LAMBDA-X CUL1 0.759 CUL2 0.796 CUL3 0.811 Correlation Matrix of ETA and KSI MD Indi Top Corp Moni Line -------- -------- -------- -------- -------- -------- MD 1.000 Indi 0.613 1.000 Top 0.530 0.667 1.000 Corp 0.486 0.577 0.721 1.000 Moni 0.393 0.357 0.500 0.435 1.000 Line 0.502 0.564 0.652 0.668 0.434 1.000 Skill 0.510 0.458 0.575 0.549 0.350 0.707 Pro 0.450 0.335 0.472 0.473 0.684 0.400
261
Learning 0.472 0.527 0.736 0.641 0.678 0.640 Correlation Matrix of ETA and KSI Skill Pro Learning -------- -------- -------- Skill 1.000 Pro 0.325 1.000 Learning 0.516 0.539 1.000
PSI
Note: This matrix is diagonal.
MD Indi Top Corp Moni Line
-------- -------- -------- -------- -------- --------
0.513 0.527 0.458 0.296 0.540 0.520
PSI
Note: This matrix is diagonal.
Skill Pro
-------- --------
0.477 0.494
262
Regression Matrix ETA on KSI (Standardized)
Learning
--------
MD 0.472
Indi 0.527
Top 0.736
Corp 0.641
Moni 0.678
Line 0.640
Skill 0.516
Pro 0.539
