SOCIAL CAPITAL, KNOWLEDGE SHARING,

AND PERFORMANCE

Krishna Fongtanakit

A Dissertation Submitted in Partial

Fulfillment of the Requirements for the Degree of

Doctor of Philosophy (Development Administration)

School of Public Administration

National Institute of Development Administration

2013

ABSTRACT

Title of Dissertation Social Capital, Knowledge Sharing, and Performance

Author Miss Krishna Fongtanakit

Degree Doctor of Philosophy (Development of Administration)

Year

2013

The purpose of the study is to examine the linkage of the three types of social

capital in organization which can enhance knowledge sharing and influence to

organizational performance. The conceptual model is deployed from the Nahapiet and

Ghoshal’s model (1998); and the linkage among the three types of social capital is

developed from Tsai and Ghoshal’s argument (1998), and Uphoff (1999). The study

explores Bandura’s cognitive theory (1977, 1986, 1989, and 2001) to develop the

proposed model.

The approach is quantitative research which questionnaire is designed from

the theories and previous studies. Convenient data is collected from a 167 branches

including 1,440 respondents in the Bangkok area, Region 6 and 12 since all the

regional managers are willing to collect the questionnaires launched through the mail.

Structural Equation Model is extrapolated by using Amos version 21.0 for

Windows in analyzing the statistical values. The SEM approach involved the

confirmatory approach to model specification. The factor analytic model approach

consisted of four main constructs of interest- three types of the social capital and the

knowledge sharing, and a CFA to statistically test how and the extent to which the

observed variables were linked to their underlying latent factors. An integrated SEM

was then proposed which incorporated the potential outcomes of the knowledge

sharing as mediating the relationship between the social capital and the performance.

The factor analytic model, utilizing CFA approach provided valuable insight for

model modification to achieve a better data to model fit, and helped to determine the

most relevant indicators for the study constructs to test the hypothesized structural

model.

iv

The model re-specification resulted in a final SEM reflective of the results

from the CFA was validated by various goodness of fit indices. The convergent

validity, the discriminant validity, and the nomological validity were tested. The

hypothesized model was statistically supported with the collected data. The research

confirmed the three types of social capital were linked. Cognitive social capital was

the exogenous variable affected to structural social capital relational social capital,

and knowledge sharing, which direct and indirectly causing to the organizational

performance. Three types of social capital and the knowledge sharing were interpreted

as factors which increased the organizational performance. All significant paths were

positively related to the organizational performance. The findings provided empirical

evidence that cognitive social capital had the strongest total effects to performance

while relational social capital had the strongest direct effect to performance.

Additionally, knowledge sharing enhanced effects from the three linkage of social

capital to boost organizational performance.

ACKNOWLEDGEMENTS

In completing this dissertation, I would like to express deep gratitude to my

advisors, Associate Professor Suchitra Punyaratabandhu, Associate Professor

Duanpen Teerawanviwat for their persistent guidance and advice throughout the

process of this research.

I am also sincerely thankful to all those who helped me grow academically

and intellectually and guided my work in this dissertation, in particular, Professor

Ponlapat Burakom- both teacher and friend, for his continuous guidance and support

from the moment I entered to Ph.D. Program.

In addition, I am indebted to all those who assisted me and supported my work

particularly the NIDA librarians, and the faculty members who participated in my

study. I would also like to extend deep gratitude to the bank members who support

me for answering and collecting data.

Of course, all errors in this dissertation remain my sole responsibility.

On the last note, I am most grateful to my Mom-Premjit who is always be my

inspiration to persist and keep going.

Krishna Fongtanakit

October 2013

TABLE OF CONTENTS

Page

ABSTRACT iii

ACKNOWLEDGEMENTS v

TABLE OF CONTENTS vi

LIST OF TABLES ix

LIST OF FIGURES x

CHAPTER 1 INTRODUCTION 1

1.1 Significance of the Study 1

1.2 Objectives of the Study 7

1.3 Scope of the Study 7

1.4 Limitation of the Study 8

1.5 Benefits of the Study 8

1.6 Organization of this Study 9

CHAPTER 2 REVIEW OF THE LITERATURE 10

2.1 The Conceptual Model 11

2.2 Cognitive Social Capital 17

2.3 Structural Social Capital 22

2.4 Relational Social Capital 27

2.5 Knowledge Sharing 34

2.6 Organizational Performance 38

2.7 Summary 45

CHAPTER 3 RESEARCH METHODOLOGY 47

3.1 Research Design 47

3. 2 The Sample 49

3.3 Operational Definitions 51

3.3.1 Dependent Variable 51

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3.3.2 Independent Variable 51

3.4 Tools 56

3.4.1 Questionnaires 56

3.4.2 Scale Construction 57

3.4.3 Items 58

3.4.4 Quality Assessment 59

3.4.5 Face Validity 59

3.4.6 Reliability 59

3.5 Variables and Measurements 60

3.6 Data Collection and Procedures 64

3.7 Data Analysis Procedures 64

3.7.1 Construct Validity 64

3.7.2 Structural Equation Model (SEM) 67

3.8 Conclusion 69

CHAPTER 4 FINDINGS 71

4.1 The Measurement Model 71

4.1.1 Exploratory Factor Analysis (EFA) 71

4.1.2 Item Reliability Analysis 72

4.1.3 Confirmatory Factor analysis (CFA) 75

4.2 The Structural Model: Influence of Social Capital 79

and Knowledge Sharing on Performance

4.3 The Revised Model 86

CHAPTER 5 CONCLUSION 93

5.1 Discussion 93

5.2 Implications 97

5.3 Recommendations for Future Research 98

5.4 Contributions 98

5.5 Limitations 100

5.6 Conclusion 102

BIBLIOGRAPHY 105

APPENDICES 140

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Appendix A Questionnaire in Thai 141

Appendix B Abbreviations and Symbols 144

BIOGRAPHY 147

LIST OF TABLES

Tables Page

2.1 Exogenous and Endogenous Variables 42

3.1 Gross Provincial Product, Number of Branches and Employees 49

3.2 The Sample 50

3.3 Criteria for Scoring 57

3.4 Items developed for Cognitive Social Capital 60

3.5 Items developed for Structural Social Capital 61

3.6 Items developed for Relational Social Capital 62

3.7 Items developed for Knowledge Sharing 63

3.8 Indices for Model Assessment 68

4.1 EFA of Questionnaire Variables 72

4.2 Cronbach’s Alpha 73

4.3 Item Correlations for CFA and SEM Analysis 74

4.4 Summary of Measurement Scales 76

4.5 Statistical Fits in the Measurement Model 78

4.6 Correlations and AVE 78

4.7 Squared Multiple Correlations of the Model 82

4.8 Standardized Regression Weights of the Structural Model 82

4.9 Standardized Effects to Performance 83

4.10 Indirect Effect Path 85

4.11 Remaining Items 86

 

LIST OF FIGURES

Figures Page

2.1 Linkages among Social Capital Types 14

2.2 Relationship of Three Types of Social Capital and Knowledge

Sharing

15

2.3 Proposed Conceptual Model 17

3.1 Relationships between Latent and Manifest Variables 67

4.1 The Measurement Model 77

4.2 Structural Model Results 80

4.3 Simplified Results Model (n = 167) 81

 

 

 

 

CHAPTER 1

INTRODUCTION

1.1 Significance of the Study

The aim of this study is to examine the linkages of the three types of social

capital which can enhance knowledge sharing and influence on organizational

performance. This study focuses on the Government Savings Bank of Thailand

(GSB), a state-owned enterprise, which is the biggest state enterprise bank in terms of

assets, deposits, NPLs’ to loans, and is relatively older than other state enterprises.

Most state-owned enterprises in Thailand have ceased to function. Some

organizations, however, have survived with strong subsidies from an annual

government budget. Therefore, the question is what has made this organization

remain healthy, energetic, and profitable without any support from the government

budget, even with its slogan “Guaranteed by the Government.”

There are many possible approaches to epitomize organizational performance.

From the industrialization era, social theorists try to find out “what makes an

organization effective.” Not only theories in the organizational sciences but also other

social sciences contribute in some techniques to searching for the determinants that

make organizations more effective. For instance, marketing concentrates on

increasing revenues and market shares, while the interest of financial concepts focuses

on the sources and uses of funds utilize in the organization. Production and operations

concern the managerial decisions regarding product design and the production system.

The main objective of production is to produce the goods and services in the most

efficient and economical way. Accounting develops and provides accounting

standards and rules for profit and non-profit organizations presenting useful financial

reporting, characterizing and analyzing healthy organization via various financial

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sheets. Unlike other social scientists, organization theorists focus on the cooperative

systems (Barnard, 1938) composed of people and groups environmental influences.

Organizational effectiveness introduces the problems inherent in defining and

measuring effectiveness. There are lists of different determinants that have led to the

conclusion that organizational effectiveness means different things to different people,

which also reflects the different interests of the evaluators. Of course, one might argue

that organizational effectiveness requires multiple determinants. There is no best

criterion for evaluating an organization’s effectiveness; thus, this study investigates

how the social capital in the organization affects the organizational performance.

Organizational theories suggest that organizations can perform better than

competitors in the same market depending on their competitive advantage (Porter,

1985); a state of competitiveness of the organization reached through a level of

efficiency and productivity which ensures a sustainable market presence (Boulescu,

Ghita, and Mares, 2002). Efficiency means the extent to which objectives are

achieved (Drucker, 1999) in terms of minimal cost, which refers to the rates of the

resources usage in achieving the objectives (Roger and Wright, 1998). Effectiveness

means “to do planned things well” (Drucker, 1999), as for example with precision in

achieving targets and the achievement of objectives (Perrow, 1967).

As proposed by Kaplan and Norton, the balanced scorecard emerged in the

early 1990s. The balanced scorecard contains a set of performance measures including

financial performance, customer relations, internal business processes, and

organizational learning and growth activities (Kaplan and Norton, 2000). Advocates

of the balanced scorecard suggest that organization should develop and use its own

scorecard measures to reflect its goals and strategy. As a model of performance

measurement, the GSB under the supervision of the Ministry of Finance was

encouraged to adopt this strategic instrument to measure organizational performance

as well. The GSB’s balanced scorecard is implemented by translating the GSB’s

vision and strategy into operational measurements. The holistic scorecard creates

shared understanding among bank staffs to contribute their efforts to firm success.

The GSB management team has linked this strategic tool to support the

provisions of incentives to individual remuneration by transforming performance

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criteria to each subdivision and individual. Since 2004, the key performance

indicators (KPIs) were communicated and assigned to organizational unit, bank

branch and individual. Although the bank’s KPIs includes financial and non-financial

measures, the bank branches’ KPIs are mostly financial dealings reflecting their main

functions for examples- the economic profit, the amount of net deposit, the growth of

assets. This study uses the bank branch as a unit of analysis for scrutinizing what

makes this organization perform well.

Although the conventional views of organizational leadership have generally

assumed that leaders are the key factor in performance and organizational success,

Lieberson and O’Conner (1972) found that leaders have little impact on

organizational performance because they are constrained by situational factors.

Sociologists have employed various mediating variables to measure and describe the

impact of leadership on organizational performance, such as organizational structure,

communication, conflicts, and organizational devices (Blau and Scott, 1962), and

sales, earnings, and profit margins (Lieberson and O’Conner, 1972). According to

prior literature, social capital and knowledge sharing were examined in terms of their

impacts on organizational performance (Batiargal, 2000; Fredette, 2009; Kim, Lee,

Paek, and Lee, 2013; Wu, 2008; Wu and Leung, 2005). The current study examines

social capital and knowledge sharing as an intangible resource affecting

organizational performance.

As mentioned in the previous section, organizational theorists indicate that

employee behavior is critical for an organization’s efficiency and effectiveness.

Several theories have been referred to by researchers to explain how team

performance is affected by different structures and diverse memberships. Some

researchers have explored the role of team processes that link diversity and

performance variables (Kilduff, Angelmar, and Mehra, 2000; Pelled, Eisenhardt, and

Xin, 1999). The main context factors that have been investigated are task

characteristics, organizational culture, strategic industry context, and temporal effects.

Haas (2010) analyzed 30 empirical studies on direct diversity-performance effects.

The reviews provided contradicting evidences; finally, this review concluded that

there is no general rule concerning what the right combination of individuals will be

for a successful team regarding performance.

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According to the resource-based view literature, organizational theorists have

been concerned with understanding why some organizations perform better than

others and have frequently looked to the resource-based view of the firm as a model

for explaining the sustained competitive advantage that some organizations possess

(Barney, 1991; Conner, and Prahalad, 1996.). The resource-based view emphasizes

that a firm utilizes its resources and capabilities to create a competitive advantage that

ultimately results in superior value creation. Armit and Schoemaker (1993) explained

that resources are stocks of available factors that are possessed by the organization,

and capabilities are an organizational capacity to organize and manage resources.

Organizational resources and capabilities are strengths that organizations can

use to conceive of and implement their strategies. Most analysts are concerned about

tangible resources—physical capital—and ignore intangible resources or capital in the

organization, such as social capital and cultural capital. Unlike other researchers, who

see such organizational advantage as accruing from the particular capabilities that

organizations have for creating and sharing knowledge, Nahapiet and Ghoshal (1998)

developed the notion that social capital within an organization is likely to be a source

of competitive advantage for the firm. They argued that social capital facilitates the

creation of new intellectual capital; an organization in the institutional setting is

conductive to the development of high levels of social capital; and it is because of

their more dense social capital that firms, within certain limits, have an advantage

over markets in creating and sharing intellectual capital and organizational-level

performance. In other words, both of them assert that networks of strong interpersonal

relationships within an organization ultimately facilitate its success.

Regarding to Nahapiet and Ghoshal finding that social capital can create and

share intellectual capital; this current study develops the model by observing

knowledge sharing as mediator variable influenced to organizational performance.

Literatures reveal that knowledge sharing is positive relationship with performance

(Cummings, 2004; Kraidan and Goulding, 2006; Weber and Weber, 2010).

This dissertation will particularly examine the Government Savings Bank

(GSB), a state-enterprise. The GSB was established in 1913, the first public bank in

Thailand. A key reason for examining the GSB is that this state enterprise has long

been sustainable for a hundred year. There are few organizations in Thailand which

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have lasted over 100 years without any support or subsidy from the governmental

budget. Generally, organizational theorists have used a biological metaphor with

respect to the life of organizations (Camazine, 2003). Organizations are born, grow,

and need continual nourishment for survival. Organisms themselves are shaped by

natural selection: those that perform well are able to persist, and those that perform

poorly will not survive.

Another reason for focusing on the GSB, it is one of the largest banks in

Thailand. In terms of state-enterprise banks, the GSB is the largest bank in terms of

capital funds, and the oldest bank among the state banks: the Bank for Agriculture and

Agricultural Cooperatives, the Export and Import Bank, the Government Housing

Bank, the Islamic Bank, the SME Bank, and the Thai Military Bank. Even though the

comparison to Thai commercial banks has been made in banking industry, GSB

performance has always been ranked at the top or the second in terms of assets size,

deposits, loans, and NPLs’ to loans.

The GSB operational procedures seem to be more complex and risky rather

than other state banks or commercial banks. As a state enterprise and governmental

mechanism, the GSB has responsible for making revenues to the state, supporting

governmental populist policies, mobilizing savings throughout the country by

encouraging people habits to save money, providing small loans and banking services

for all walks of life to be able to easy access to the bank.

In the banking industry, banks are traditionally established by investors and

expand its capital by raising funds in the capital market. As the state financial

institutes in Thailand, all banks were instituted by the government policies and

expand capital funds by government budget. For example, the government regularly

increased capital funds to the Bank for Agriculture and Agricultural Cooperatives

(cabinet resolution 1996, 1999, and 2012); periodically supplied government budget

to enlarge capital funds for expanding services to the exporters’ customers of the

Export and Import Bank (cabinet resolution 1998, 2008, 2009, and 2012); made

available for enlarging funds to provide housing loan for the Government Housing

Bank (2010, 2012), and supported the additional state banks in a regular basis.

Although the government regularly allocated budget to support the state enterprise

6

 

 

banks, it is the fact that the GSB has never been granted from any other source except

the King Rama IV donation for establishing a small savings entity for educating Thais

to save money.

Furthermore, this particular bank is attractive for studying because social

capital effect in state-enterprise bank is unknown. This study is among the first to

examine social capital and knowledge sharing as an organizational resource.

Importantly, empirical research on social capital is needed to help clarify and

strengthen the concept theoretically in order to appropriately apply it with the specific

context. Previous studies in the banking industry have not adopted an integrated

model that explores the organizational performance through the linkages of the three

types of social capital and knowledge sharing. The research study extends social

capital and knowledge sharing by examining the impacts and effects on the formal

organization such as state enterprise bank.

Social capital and knowledge sharing are particularly important to the state

enterprise bank because it enhances organizational effectiveness, yet few empirical

studies have been conducted to examine the particular outputs or effects. Thus, the

aim of this study is to analyze how the level of social capital in the GSB impacts its

performance. According to the literature review, Guiso, Sspienza, and Zingales’

(2004) results also show a positive and significant link between social capital and the

efficiency of banking industries. Shipilov (2006) analyzed social capital in Canadian

investment banks and the research results show that firm networks affect bank

performance. On the other hand, Naghavi, Salavati, and Movahed (2011) studied

social capital in governmental, private, and newly-privatized banks in Iran; the

research results show that social capital is not affected by the governmental or private

structure of a bank, but the most influencing factor which decreases social capital is

privatization.

Little is known about social capital and knowledge sharing effect in state

enterprise banks as no known empirical studies exists which examine the outcomes of

social capital and knowledge sharing relevant to state enterprise bank performance.

The relevance of social capital and knowledge sharing theories in state enterprise

bank performance is an area of interest with much yet to be empirically investigated.

7

 

 

An empirical study needs to be investigated social capital and knowledge

sharing in state enterprise bank in Thailand. Many researches utilize social capital and

knowledge sharing has been conducted from different cultures and contexts.

According to Hofstede (1994), the present view of management was established in the

western-oriented frame of reference, especially the Anglo-American orientation that

many apparent realities are only social constructs and are therefore subject to change.

Organizational theories and concepts might not apply in the Thai organizational

culture and contexts. Consequently, there is a need for empirical evidence to support

social capital and knowledge sharing concepts in Thai bureaucratic organization.

1.2 Objectives of the Study

The goal of this research is to examine, empirically, particular concept of

social capital and knowledge sharing directly and indirectly influence on

organizational performance. Secondly, the study focuses on how the three types of

social capital interact and influence knowledge sharing and organizational

performance. Thirdly, this research study examines the manifest variables of social

capital and knowledge sharing in Thai context.

1.3 Scope of the Study

This study investigates the Government Savings Bank, state-own enterprise

bank, one of the biggest banks in Thai banking industry. The research study examines

167 out of a total 598 bank branches in 2011. The 167 branches are taken from five

regions—Regions 1, 2, and 3 located in the Bangkok area. Region 6 is located in the

upper-central part of Thailand comprising six small provinces: Nakhon Sawan, Chai

Nat, Uthai Thani, Phichit, Phetchabun, and Lop Buri. Region 12 is located in the

north-east including five provinces: Ubon Rachathani, Buri Ram, Surin, Yasothon,

and Si Sa Ket. In total, the research study observed social capital in 167 bank

branches in 12 provinces throughout the country.

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This dissertation utilizes quantitative methodology and cross-sectional study.

Respondents are bank branch staff. Amos 21.0 was deployed for analyzing and

evaluating the research model.

1.4 Limitations

Since time and budget were limited for the present study, the dissertation

utilizes a cross-sectional design, whereas Adler and Kwon (2002) propose that

longitudinal studies are necessary to develop understanding of the dynamic interplay

between human and social capital. The study was also limited to the accuracy of the

respondents’ responses, which is far beyond the control of the researcher. A selective

sample area is one of the limitations in this study. Although the respondents are 1,440

within 167 branches, it might be another limitation for advocating that data are

represented the bank population.

1.5 Benefits of the Study

This research study is expected to contribute to scholarly knowledge. The

research results will enhance academic knowledge in relation to social capital and its

influence on firm performance in the Thai context. The study examines to current

situations that might impact the concept of social capital, and this topic has not been

sufficiently researched. Particularly, a study of this topic in a different context by

adopting reliable and accurate research methods meeting international standards will

be useful to Thai academics. This will lead to the creation of temporary knowledge

that provides practical knowledge that can be used in the future. In particular, the

academic progress in the development administration will be more strengthen because

a big state enterprise bank in Thailand was tested to show why and how the bank

perform well.

The results of the study concerning the social capital influences on

organizational performance can be used to examine the involved authorities’

performances in both their proactive and defensive activities in relation to the

9

 

 

National Economic and Social Development Plan, which emphasizes social capital

and economic development. Those that are involved in administration and politics,

and policy and planning, will have a better understanding of the Thai social capital in

the bureaucratic organizations, especially study in the state enterprise bank.

Further, the research results provide an understanding for the improvement of

the social capital of Thai organizations. Based on the results of the study, one will

have a better understanding of the linkages three types of social capital that can boost

knowledge sharing and influence on organizational performance. Leaders and

management teams in organizations can improve their performance via their

enhancement of social capital.

Finally, the research findings will benefit development administrators in terms

of organizational implementation and studying a real case will help to improve the

social reality. Managers routinely confront the complexities inherent in goal

attainment; from this study they can obtain reasonably valid information for assessing

their organization’s effectiveness.

1.6 The Organization of this Dissertation

This dissertation is organized into five chapters. Chapter I begin with the

statement of significance for the study, and then provide a broad view of the research

direction with a brief elaboration. Chapter 2 comprehensive reviews the literatures of

various paradigms, theoretical base of the study, and correspondingly the conceptual

model and research hypotheses are proposed. Then, Chapter 3 describes the

methodology of the research, measurement scales, tools, and variables are discussed,

followed by Chapter 4, which presents the research findings. Chapter 4 focuses on the

interpretation of the statistical results, reliabilities and validities of the constructs,

measurement model and structural model are tested. The last section, Chapter 5,

draws out discussion, conclusions based on the findings, the implications of the

findings, assesses the utility of the social capital concept in studying in the state

enterprise bank—the Government Savings Bank.

10  

CHAPTER 2

REVIEW OF THE LITERATURE

This chapter begins with the development of the conceptual model. Then, all

of the variables related to the model construct were reviewed from previous studies.

In the conceptual model, there are four independent variables which are: (1) cognitive

social capital, (2) structural social capital, (3) relational social capital and (4)

knowledge sharing. The dependent variable is branches performance using the KPI’s

of the branch managers, which represents branch. Branch performance (PERFORM)

was archived from the bank data.

Cognitive social capital (COGNITIVE) is comprised of shared values and

goals. Structural social capital (STRUCTURAL) is considered as the frequency of

relationships among members, the affections among members in the community, and

the frequency and period of time spent in communicating and participating in the

bank’s activities. Relational social capital (RELATIONAL) can be defined as the

individual trust among members and the organization and the employees’

commitment to the organization. Knowledge sharing (KSHARING) refers to the

individual’s attitude toward transferring and receiving knowledge from person to

person, person to group, and person to organization.

The section 2.1 describes how the conceptual model was constructed. The

section 2.2 to 2.6 summarizes the measurement of variables. Previous literatures led

the present author to assemble the indicators of each variable for determining the best

view of construct validity. The definitions and characteristics of variables are clearly

defined and cover important aspects of the content universe. The section 2.7

concludes the conceptual model of the study explaining the linkage of social capital

related to knowledge sharing and influenced to organizational performance.

 

11  

2.1 The Conceptual Model

Based on Nahpiet and Ghoshal’s work, this dissertation develops the initial

step in conceptualizing the conceptual model. Also, the structure of social capital here

has been modified based on Tsia and Ghoshal’s model (1998), which initially

observed how the three types of social capital interact and influence one another and

facilitate value creation to organization. They proposed that structural social capital

will be positively influenced and associated with cognitive social capital.

Unfortunately, it appeared that structural social capital was not a prerequisite for

creating a shared vision. Although the study spotlights the linkages of the three types

of social capital, a major change in the model is that cognitive social capital is a

prerequisite factor directly affecting structural social capital and relational social

capital, and also indirectly affecting relational social capital via structural social

capital. Consequently, this research study assumes that the three types of social capital

are linked and interact together as resources within the organization; they serve to

enhance organizational performance.

Before discussing the construction of the conceptual model for this study, it is

necessary to investigate what social capital is. Social capital can be understood as a

set of informal norms (OECD, 2001; Putnam, 2000) and values common to the

members (Fukuyama, 1995; Halpern, 2005) of a specific group that allows cooperation

(Field, 2003; Lin, 2001) among them. Therefore, it is a component of the social theory

that is being considered as a key element for human and economic development

(Macke and Dilly, 2010), which can improve the efficiency of society by facilitating

coordinated actions (Bourdieu, 1997; Putnam, 2000).

Attempts to more thoroughly conceptualize social capital have been broadly

described by many scholars identifying different characteristics- as an asset embedded

in the relationship of individuals, communities, networks, or societies (Burt, 1997;

Coleman, 1990; Nahapiet and Ghoshal, 1998; Walker, Kogut, and Shan, 1997); as a

kind of capital (Bourdieu, 1990); and as a moral resource (Hirschman, 1984). This

research identifies social capital as an asset embedded in the relationship of

individuals, strong ties of networks, and the mental process of actors in the network.

12  

Social capital has been posited at several levels of analysis drawing on

different perspectives. Researchers use the level of social capital in describing the

attributes of nations or geographic regions (Bankston and Zhou, 2002; Coleman,

1988; Fukuyama, 1995; Portes, 1998; Putnam, 1995); communities (Putnam, 1993b);

individual networks (Burt, 1992); firms in their interactions with other firms (Baker,

1990); individual actors (Belliveau, O’Reilly and Wade, 1996); and aggregate

component of groups (Buy and Bow, 2002; Kilpatrick, Bell, and Falk, 1998; Newton,

1997; Sander, 2002). Social capital thus crosses several levels of analysis and has

been described using both a macro (society, nation, and region), meso (group), and

micro (individual) lens (Paxton, 1999). This study considers the organization as a

collective, net social capital was resulted from the capability of all internal resources,

as well as human resources and their relations within the organization. Social capital

is identified as aggregate elements of members in the network of bank branch.

Members in the network engage individual capabilities and efforts in reaching the

goals.

From a survey of the literatures, it was found that there are few researches that

investigate the linkages among the three types of social capital. Analyzing relevant

journal articles from 1989 through 2008 yielded 245 articles. Payne, Moore, Griffis,

and Autry (2010) found that those articles focused primarily on theory

conceptualization, measurement, and level of analysis.

Currently, Sechi, Borri, Lucia, and Celmins (2010) utilized Tsai and Ghoshal’s

model to investigate the dynamics of social learning in territories with regards to

environmental knowledge in the Republic of Latvia. They studied types of social

capital and an environmental dimension as well as the linkage among such types. The

main results provided support for Tsai and Ghoshal’s works, according to structural

and cognitive social capitals were significantly related to relational social capital and

enable knowledge exchange. They found divergent results from Tsai and Ghoshal’s

main pattern. Significant unexpected causal effects were found; there were negative

correlations between structural social capital and cognitive social capital, and a

negative effect of cognitive social capital on knowledge acquisition. However, they

asserted that the discrepancy may rely on the different context.

13  

With respect to these ideas, the study hypothesizes how the three types of

social capital interact among themselves and how they influence knowledge sharing,

which in turn influences organizational performance. However, the current study

examines the linkage of social capital in different model. It is considered that

cognitive social capital caused social strong ties and relational social capital rather

than structural social capital fostered cognitive social capital and relational social

capital. This assertion is derived from multiple schools of thought within the social

structure search for what makes people “build, continue, or reconstitute” their

network ties. Regarding this issue, the theory of human actions is explained from

various views, including theories of self-interest (Smith, 1776), social exchange

(Blau, 1968; Homans, 1961; Thibaut and Kelley, 1959), mutual or collective interest

(Olson, 1971), and the cognitive theories (Bandura, 1977, 1986, 1989, 2001).

From the cognitive perspective (Rousseau, 1767; Hegel, 1910; Alberson,

Aronson, McGuire, Newcomb, Rosenberg, and Tannenbaum, 1968), the theory

stresses what members think other group members know and like. The balance theory

of Heider (1946) asserts that if two people are friends, they may have the same criteria

for the assessment of an object. When people interact in small groups, similar

evaluations of an object are a key indicator in explaining how communication ties are

created within a group and the development of partnership within groups.

Human behavior is related to the agent’s beliefs and desires that lead to bodily

actions, and these beliefs are derived from the mental model (Johnson-Laird, 1983).

For this reason, Bandura (1977, 1986, 1989, and 2001) argued that mental states cause

human actions. His works contribute to social cognitive theory, self-efficacy, and

personality psychology. Bandura’s analyses became known as social cognitive theory.

According to Bandura’s cognitive theory, when people believe that they are

motivated to build their social network more in tune with their own values and the

kinds of relationships that they engage in, then people tend to form different kinds of

relationships with different people. Human behavior, as it is purposive, is regulated by

forethought: people set goals for themselves and they plan courses of action that will

likely meet the desired and positive outcomes. Additionally, in this context, people

established strong ties with others like them and refrain from behaving in ways that

violate their personal standards because it can cause them to disapprove of

14  

themselves. With other people with whom they are typically not that close, they

develop weaker ties and this helps them to address a larger variety of what are most

likely more specific needs.

As pointed out by Uphoff (1999), the cognitive category of social capital

derives from mental processes and resulting ideas, and is reinforced by culture and

ideology, specifically the norms, values, attitudes and beliefs that contribute to

cooperative behavior and mutually-beneficial collective action. According to Uphoff

and Wijayaratna (2000) and Krishna and Uphoff (2002), cognitive social capital

predisposes people to mutually-beneficial collective action.

In line with these theories, this study developed a model by assuming that the

cognitive social capital is only exogenous variable directly caused structural and

relational types; and indirectly effect to relational social capital via structural social

capital (Figure 2.1).

Figure 2.1 Linkages among Social Capital Types

2.1.1 Social Capital, Knowledge Sharing, and Performance

Types of social capital of Nahapiet and Ghoshal’s framework have become the

most influential in studying social capital and intellectual capital. Another

contribution in this direction has been examined by Adler and Kwon (2002) who have

expressively rename the intellectual capital to knowledge sharing. Since then, most of

the past studies highlight the importance of social capital as a driver for knowledge

sharing in organizations (Adler and Kwon, 2002; Coleman, 1988; Fukuyama, 1995;

15  

Hazleton and Kennan, 2000; Inkpen and Tsang, 2005; Nahapiet and Ghoshal, 1998;

Widen-Wuff, 2004). Such authors point out how different types of social capital may

enable the sharing of different kinds of knowledge.

Figure 2.2 shows the relationships among the three types of social capital and

knowldge sharing. It is hypothesized that cognitive social capital is the exogenous

variable that causes other variables in this model. The next stage will explain the

influences of the three types of social capital and knowledge sharing on organizational

performance.

Figure 2.2 Relationships of Three Types of Social Capital and Knowledge

Sharing

A large number of research studies on Nahapiet and Ghaoshal’s model have

been carried out worldwide and a growing number of practical cases on different

forms of social capital are being reported (Bock, Zmud, Kim, and Lee, 2005; Borgatti

and Cross, 2003; Chui, Hsu, and Wang, 2006; Huysman and Wulf, 2005; Inkpen and

Tsang, 2005; McFadyen and Cannella, 2004; Thomas-Hunt, Ogden, and Neale, 2003;

Tsai, 2002; Tsai and Ghoshal, 1998; Wasko and Faraj, 2005; Widen-Wuff, 2004;

Wulff and Ginman, 2004; Yli-Renko and Autio, 2001).

In the field of organization studies, there have been numerous research studies

observed the relationships of social capital and business success (Kilkenny, Nalbarte,

and Besser, 1999), performance (Batjargal, 2000; Fredette, 2009; Wu, 2008; Wu,

and Leung, 2005), innovation (Cook, and Clifton, 2004; Landry, Amara, and Lamari,

2000), revenue (Jenssen, and Greve, 2002; Johnson, Suarez, and Lundy, 2002), sales

16  

and value added (Chen, Tzeng, Ou, and Chang, 2007; Fafchamps, and Minten, 2002;

Lechner, Dowling, and Welpe, 2006; Smerek, and Denison, 2007; Westlund, 2006;

Zhang, and Fung, 2006), launching a new venture (De Clerk, and Arenius, 2003),

profits and employment (Bosma, Van Praag, Thurik, and De Wit, 2004; Chen, Tzeng,

Ou, and Chang, 2007), growth (Cook, and Clifton, 2004; Cook, Clifton, and Oleaga,

2005; and Cook, 2007; Lou, Griffith, Liu, and Shi, 2004; Westlund, and Nilsson,

2005), return on investment (Chen, Tzeng, Ou, and Chang, 2007; Lock Lee, 2008;

Lou, Griffith, Liu, and Shi, 2004), return to asset (Smerek, and Denison, 2007;

Zhang, and Fung, 2006), market-to-book ratios (Lock Lee, 2008; Smerek, and

Denison, 2007), total shareholder return (Lock Lee, 2008), and etc.

It can be seen that a number of previous researches have been conducted to

focus on the relationship of social capital and knowledge sharing, or examine whether

the relationships of social capital is able to enhance organizational performance or

create the capabilities of organization. It is rare to investigate the linkages of the three

types of social capital, knowledge sharing, and performance (Chui, and Hsu, 2006;

Kim, Lee, Paek, and Lee, 2013; Sechi, Borri, Lucia, and Celmins, 2010). For this

reason, it is a significant study to observe the relationships among those factors.

Additionally, most of the literatures on Thailand examine themes of the

community, such as good governance (Albritton and Bureekul, 2002), psychosocial

well-being among adolescents in the Northeast region (Luang-Ubol, 2010),

decentralization in the municipal government (Mahakanjana, 2004), public goods

(Potipiti, 2010), community movements (Kata, 2004 and Leknoi, 2008), distance

learning in rural areas (Yiengprugsawan, Seubsman, and Sleigh, 2011), political

participation in local politics (Kanchanakit, 2004), village migrant networks (Curran,

Garip, Chung, and Tangchonlatip, 2005), and community knowledge management

(Wanthanang, 2010). Although there have been studied in communities, it cannot be

found any literature result in the field of organization study. It is attraction for

empirically investigating themes of the organization performance, specifically in the

banking industry.

Based on the findings of prior studies as well as deductive reasoning, the

model hypothesizes that the linkages of social capital are expected to be positively

effects on knowledge sharing in organization and increase the organizational unit’s

17  

performance that enhances the overall performance of the organization. Knowledge

sharing is also expected to mediate the effects of social capital on organizational

performance. The hypothesized structural model of social capital, knowledge sharing,

and performance are depicted in Figure 2.3. This causal model is empirically

investigated using the GSB as a case study.

Figure 2.3 Proposed Conceptual Model

2.2 Cognitive Social Capital

As the concept of cognitive social capital rooted in the mental process among

thought, affect, and action, there are multiple schools of thought within the social

cognitive theory including theory of self-interest (Smith, 1776), social cognitive

(Bandura, 1977, 1986, 1989, 2001). Social cognitive theory (Bandura, 1977, 1986) is

helpful for understanding and predicting both individual and group behavior and

identifying the methods in which behavior can be modified or changed. Bandura’s

theory places strong emphasis on human cognition, and he asserts that cognition

interacts with behavior, personality and the environment—human actions result from

the mind as an active force that constructs one’s reality, selectively encodes

information, and performs behavior on the basis of values and expectations. A

person’s owns reality is thus defined as the interaction of the environment and one’s

cognitions, which can change over time though the learning process.

18  

Social cognitive theory is highly relevant to organizational studies (Simon,

1956). Simon investigated decision-making theory and summarized how the cognitive

theory is highly relevant to leadership, job performance, motivation, and control

systems. As mentioned in chapter 1, this study hypothesizes that the cognitive social

capital is linked to structural and relational social capitals. The next step is to explain

the role of the cognitive social capital links to knowledge sharing and performance.

Nahapiet and Ghoshal (1998) posit cognitive social capital that refers to

“shared representations, interpretations, and systems of meaning among parties” that

enable individuals within the network to make sense of information and to classify it

into perceptual categories. It facilitates the exchange of information that allows

individuals to share each other’s thinking processes. Shared goals can motivate team

members to share knowledge and cooperate with each other (Arnett and

Badrinarayanan, 2005).

Some schools of thought assert that the cognition is imperative in relation to

the fundamental rationale of bounded rationality in group thinking and action.

Because people observe, interpret and evaluate the world according to their categories

or mental frameworks of perception, interpretation and evaluation (Davis and

Thompson, 1994). Humans are rationale; therefore, expectation, belief, self perception,

goals, and intentions derive give shape and direction to their behavior (Bandura,

1986). Uphoff (1999) pointed out that the cognitive category of social capital derived

from mental processes and resulting ideas, attitudes, and beliefs that contribute

cooperative behavior and mutually beneficial collective action.

According to Inkpen and Tsang, 2005, they argued that the cognitive stems

from different mental models. In order to motivate individuals to share knowledge,

members’ cognition would help in the achievement of this knowledge, welding

processes to a great extent. Shared visions and goals can act as a bonding mechanism

between network members. These bonding mechanisms allow members within a

network to feel comfortable sharing resources and knowledge.

Within the organizational context, members can contribute more effectively

when they understand how their work fits with the organization’s vision, mission, and

goals. Organizational motivation may increase levels of employee participation in

knowledge sharing (Kollock, 1998). However, an increased sense of group identity

19  

and attitude can better create knowledge sharing in organizations (Grant, 1996; Kogut

and Zander, 1992; Spender, 1996). Gagné (2009) found that cognitive social capital is

positively related to having positive attitudes toward knowledge sharing.

In social cognitive theory, Bandura (1986) believes that self-regulation of

motivation and performance attainments are governed by self-regulatory mechanisms.

Cognitive psychology explains the central role in this regulatory mental process that

works through people’s beliefs in their personal efficacy. People believe in their

capabilities to mobilize the motivation, cognitive resources, and courses of action

needed to exercise control over events in their lives. People with the same skills may

perform poorly, adequately, or extraordinarily, depending on whether their self-beliefs

of efficacy enhance or impair their motivation and problem-solving efforts.

Performance success strengthens self-beliefs in capability; failures create self-doubts.

Bandura (1989) asserts that human self-direction and self-motivation operate

partly through people’s internal standards and their evaluation of their own behavior.

People seek self-satisfactions by adopting goals and evaluating one’s progress in

relation to goals. Goals can improve individuals’ psychological well-being and

accomplishments in terms of providing a sense of purpose and direction, guiding and

motivating performance as well as helping to build people’s beliefs in their

capabilities. Thus, he postulates that perceived self-efficacy enhances organizational

performance.

The cognitive dimension of social capital, described by Nahapiet and Ghoshal

(1998), means that as human interacts with one another as part of a collective, they

are able to develop a common set of goals and a shared vision for the organization. In

addition, Coleman (1990) has affirmed that shared visions and goals, and the

collectively-held values that underlie them, help to promote integration and create a

sense of shared responsibility and collective action. Shared goals are the extent to

which team members share a common understating of achievement of group tasks and

outcomes (Inkpen and Tsang, 2005). The cognitive dimension reflects the degree to

which team members are committed to defined and accepted goals. Shared values can

be considered the key elements of high performance organizations and teams, while

the members of the organization bring their best efforts to its success and are

committed to it.

20  

The key facet of the cognitive dimension is considered as shared vision and

shared goals (Chui, Hsu, and Wang, 2006). Nahapiet and Ghoshal’s as well as Tsai

and Ghoshal’s models explain the concept of cognitive social capital as the shared

vision and shared goals of members in the organization. Shared vision is defined as

members in the organization that are enthusiastic about pursuing the organizational

vision, including members sharing the same ambition at work. Sharing goals means

that members are enthusiastic about pursuing the collective goal, enthusiastic about

pursuing the mission and they know what and how to achieve important work.

Previous studies were thoroughly reviewed, and they give a picture of

cognitive social capital as the primary variable, called the exogenous latent variable,

as the causal factor influenced to other factors in the model. Cognitive social capital is

the latent variable that is related to a set of manifest variables, as discussed below.

Shared vision means the conception of a person seeing him or her as one of

the individuals in the group (Nahapiet and Ghoshal, 1998). Tsai and Ghoshal (1998)

noted that a shared vision embodies the collective goals (Naghavi, Salavati, and

Mavahed, 2011) and aspirations of the members of an organization in proper ways of

acting in a social system. Employees view themselves as partners in charting the

direction of the organization (Sinkula, Baker, and Noordewier, 1997) and future

achievements (Chen, Chang, and Hung, 2007).

When the organization’s members have the same perceptions about how to

interact with one another, they can avoid possible misunderstandings in their

communications and have more opportunities to exchange their ideas, information, or

resources freely. An organization’s members that share a vision will be more likely to

become partners—sharing, exchanging, integrating, and combing resources (Darvish

and Nikbakhsh, 2010), helping others solve their professional problems and providing

a better way to meet organizational missions and goals (Chiu, Hsu, and Wang, 2006).

Hoe and McShane (2002) defined shared vision as a clear, common, specific

picture of a truly-desired future state, one that creates a sense of support and inspires

people with a compelling common identity and sense of purpose. Members who

shared the same picture to organization, they prioritized important work.

A shared vision can be defined as the capability to perceive and interpret

information, to formulate problems, to generate alternative solutions, to define the

21  

decision making process, and to reach a consensus (Watson, Kumar, and Michaelsen,

1993; Janssen, Vliert, and Veenstra, 1999; Kilduff , Angelma, and Mehra, 2000 quoted

in Fernandez and Gardey, 2010).

Cognitive social capital can be defined in terms of shared goals. For example,

shared goals can be seen as the degree to which one has collective goals, missions,

and visions that are similar to those of others (Wong, Wong, Hui, and Law, 2001).

With shared goals, members in in the community can cooperate in actions aimed at a

common destination and for the final benefit of the organization (Cohen and Prusak,

2001); the individuals then work together as a team, supporting and encouraging each

other.

Shared goals are the primary dimension of cognitive capital. The goals are

shared when members of a network share a common understanding and approach to

achievement of network tasks and outcomes (Inkpen and Tsang, 2005). Shared goals

can be considered the force that hold people together and let them share what their

willing to contribute their efforts to achieve goals. The ability of people to work

together for common purposes in groups and organizations consists of a certain set of

informal values and norms shared among members of a group that permit cooperation

among them (Fukuyama, 1995, 1997) . A shared goal can be viewed as the mutual

responsibilities or bonding mechanism that help different parts of a network integrate

and share knowledge in order to reach the goals (Anderson, 1990, Schnake and

Cochran, 1985). With collective goals, organization members tend to believe that

other employee’s self-interest will not affect them adversely and they all contribute

their efforts to help achieve their mutual goals (Chow and Chan, 2008).

When there is a total agreement on the organization’s vision across all levels,

functions and divisions, all employees are committed to the goals of the organization.

They view themselves as partners in changing the direction of the business unit and

there is a commonality of purpose in such organization (Ma’atoofi and Tajeddini,

2010). Shared goals can be seen in terms of the mission that members in the

organization want to accomplish; members in the organization for example

concentrate on achieving its mission, values, and objectives. An organization’s

members agree on what is important at work, and members are enthusiastic about

22  

pursuing the collective goals and mission of the whole organization (Chow and Chan,

2008).

From the literature review, it can be concluded that a shared vision embodies

the collective goals and aspirations of the members of an organization, members are

enthusiastic about pursuing the organization’s vision (Chen, Chang, and Hung, 2007;

Inkpen and Tsang, 2005; Nahapiet and Ghoshal, 1998, and members share the same

ambition at work (Darvish and Nikbakhsh, 2010; Tsai and Ghoshal, 1998). Shared

goals represent the force that hold people together and let them share what they are

willing to contribute in terms of efforts to achieve goals (Inkpen and Tsang, 2005).

Members in the organization are enthusiastic about pursuing the collective

goals. The members are working toward the specific goals, and demonstrate a

commitment to the values and beliefs that guide to collaboration. When a shared goal

is present in the network, members have the same enthusiasm about pursuing the

mission (Chow and Chan, 2008; Wong, Wong, Hui, and Law, 2001); thus, it can

encourage members to agree on what is important for work (Chow and Chan, 2008).

Cognitive scientists have confirmed shared vision and goals play a remarkable

powerful, performance-driving function.

2.3 Structural Social Capital

Individuals interact with one another as part of a collective; they are better

able to develop a common set of goals, and shared vision for the organization

(Coleman, 1990). Leena and Van Buren (1999) explain the phenomenon associability

and conclude that the cognitive aspect is reinforcing the structural and relational

components of social capital. People, who share the same mental models about their

work, are also more likely to interact with one another resulting to the strong ties

(Mohammed and Dumville, 2001).

Leena and Pil (2006) stated that the structural social capital refers to the

connecting among actors with whom and with what frequency they share information.

The organization can be viewed as a social network. Social network theory defines

society as built up of individuals in various forms, with weak and strength ties. A

number of researches has confirmed that strong social ties provide firms with access

23  

and resources, such as knowledge to reduce costs (Bonner, Kim, and Cavusgil, 2005;

Luo, 2003). Strong social ties allow the flow of valuable information or knowledge

into the actors to behave proactively and innovatively regarding the firms (Luo, 2003;

Walter, Auer and Ritter, 2006). This flow of knowledge may take the form of

information and know how, skills, management capabilities, and market knowledge

(Kale, Singe and Perlmutter, 2000), which can leverage to improve firm growth and

overall firm performance (Bonner, Kim, and Cavusgil, 2005).

The interactions between human thought and the organizational social context

can create organizational knowledge. A social tie is also relevant for examining

individual action such as knowledge sharing within a collection. Nahapiet and

Ghoshal (1998) relied on Granovetter’s (1992) concept of social capital as an

integrative framework for understanding the creation and sharing of knowledge in

organizations. They argued that organizations have unique advantages for creating

knowledge over more open setting.

The literature on social networks suggests that workplace social network ties

can be used as a vehicle to transfer important work-based information and knowledge

throughout the organization (Levin and Cross, 2004; Marouf, 2007; Sparrowe, Liden,

Wayne and Kraimer, 2001). The findings from Laila’s research results (2007) have

indicated that the strength of relationships contributes in a significant way to the

sharing of public and private knowledge in the organization.

Frequent and close social interactions permit actors to know one another, to

share important information, and to create a common point of view. Thus, the social

ties interaction network is likely to be perceived as trustworthy by others in the

network, and people are willing to share knowledge and information through their

social strong ties (Hansen, 1998, 1999).

According to several authors, the strength of the interpersonal connection can

also affect how easily knowledge is transferred (Szulanski, 1996; Uzzi, 1997; Hansen,

1999). Strong ties for example can influence the value of knowledge via screening

and matching, and their research results also show that the strengths of the firm’s ties

can influence the transfer of knowledge and increase the firm’s capabilities (Cohen

and Levinthal, 1990; Uzzi and Lancater, 2003).

24  

Uzzi (1997) has asserted that an organization that lacks frequent and extensive

communication among members is unlikely to share knowledge, as the weak ties

among members in units are unable to share knowledge. The factors that inhibit

knowledge sharing include close and frequent interactions between members on the

team leading to unit effectiveness because of the time integration of knowledge across

individuals.

Mutual benefits can also be seen to create cooperation and relations, as

organizations that synergize rapidly and establish new strategic partnerships can

experience substantial results. The amount of information sharing is related to the

quality of group decisions (Larson, Christensen, Franz and Abbott, 1998). The

knowledge sharing by a large proportion of group members should also make each

member more aware of other group members’ roles in the team. By sharing with one

another, members learn about the responsibilities of each group member. Knowledge

of each group’s members’ roles makes task behavior more visible and at the same

time clarifies expectations and accountability. If members of networks engage in the

sharing knowledge it can enhance the group’s performance (Wagner, 1995).

The performance of firms can be benefit from network ties in the form of

access to information and resources and more rapid product development.

Cooperative behavior in the organization requires knowledge of an individual’s

inclination to cooperate and the contextual stimulation for cooperation. Such

cooperation behavior is fundamental to how people deal with interpersonal

relationships, how they interact with others, and their openness to the influences that

stem from the situation.

Strong networks reduce the transaction costs associated with a business

relationship, facilitating the exploitation of profitable actions and making simpler the

achievement of economic aims by involved partners (Walker, Kogut, and Shan,

1997). Strong ties allow a firm to develop reliable and effective communication

channels with its customers, reducing the uncertainty about economic performance

outcomes (Hite 1999; Nohria 1992). Several research findings have revealed the

positive impact of social strong ties on performance (Cross and Parker 2004; Cross

Borgatti, and Parker, 2001).

25  

This study expects that the strong ties will be positively related to job

performance. Specifically, when members exchange and share information as well as

knowledge with a larger proportion of other members, the group should benefit in

terms of greater cooperation, greater information sharing, a stronger sense of

accountability, greater agreement on expectations, and higher engagement in goal

attainment.

Repeated and long-lasting relationships between the actors in the network are

key characteristics of social networks (Podolny and Page, 1998). Sociologists for

example have identified strong ties among members in the networks that they

associate with frequently—people establish in-depth connections that reinforce their

personal beliefs and provide them with the support required to face life’s challenges;

further, people pay more attention to the development of their connections to increase

their success. Such ties can be defined as the degree of the support received for the

transfer of goods, services, and information, and the level of relational embeddedness

and strong social attachment promotes the cohesion among the members in the

networks (Kale, Singh, and Perlmutter, 2000; Uzzi, 1996).

In terms of tie strength, literatures amorphous characterize in various ways.

However, it can be measured in three areas—interactions, affection, and time spent

(Krackhardt, 1992). The literature led the present author to define structural social

capital as one of the endogenous latent variables in the model. The measurement of

each manifest variable is defined and described below.

According to the social network theories, the strength of ties means that there

is a very relationship with members in the organization. In other words, good

relationships and good services characterize the tie. (Chiu, Hsu, and Wang, 2006;

Krackhardt, 1992; Smith, Collins, and Clark, 2005). Peng and Luo (2000) argued that

Guanxi, a good connection and relationship among Chinese firms, affects resources

and business information, increases sales growth (Park and Luo, 2001), and improves

macro organizational performance.

Another characteristic of strong ties is frequency of interactions (Gilsing and

Nooteboom, 2004; Grannovetter, 1973), and the recency of contacts (Lin, Dayton, and

Greenwald, 1978). Interaction perhaps represents the frequency of communication

among members of the communities (Chiu, Hsu, and Wang, 2006; Leenders, Engelen,

26  

and Kratzer, 2003), the number of times of collaboration (McFadyen and Cannella,

2004), and frequency of participating in meetings and associations (Hansen, 1998,

1999; Landry, Amara, and Lamari 2002). Strong ties are also portrayed in terms of

the length of the communication (Chiu, Hsu, and Wang, 2006; Leenders, Van

Engelen, and Kratzer, 2003; Reagans and McEvily, 2003).

Krackhardt (1992) has explained that social strong ties can be viewed in terms

of affection. He defines affection as the motivation to treat others in positive ways.

Strong ties are also portrayed in terms of love and repeated and prolonged interactions

among members or parties (Krackhardt, 1992; Uzzi, 1997). The more social inter-

actions are undertaken by exchange partners, the greater the intensity enhances

(Larson, 1992; Ring and Van de Ven, 1994).

Krackhardt (1992) also has identified strong ties as close-knit bonding. Reagan

and McEvily (2003) argue that the strength of ties is based on closeness. Chiu, Hsu,

and Wang (2006) noted that social interaction ties represent close relationships. Strong

ties are comprised of interpersonal closeness (Balkundi and Harrison, 2006;

Granovetter, 1973; Hansen, 1999; Moran, 2005), the emotional intensity of the contact

with the social network (Levin and Cross, 2004; Smith, Collins and Clark, 2005), and

intimacy (Easley and Kleinberg, 2010).

In the social networks, strong ties facilitate the information flow (Nahapiet and

Ghoshal, 1998; Tsai and Ghoshal, 1998), and members in the networks easily ask for

advice from other members (Dakhli and Clereq, 2004). Researchers explain social

ties as follows: when members in the organization face a problem, they have

opportunities to ask for advice or help from other members (Larson, 1992; Ring and

Van de Ven, 1994). Strong ties encourage greater motivation for helping and

supporting each other in the networks and normally exhibit easy access. Grannovetter

(1982) has explained for example that people that feel insecure in their immediate

environment are more likely to resort to the development of social strong ties for

protection and the reduction of uncertainty. Affection provides more assistance and

support to one another (Seibert, Kraimer, Liden, 2001). A network of advice

interactions stems from routine work problems and a network of love in relationships

in the firm (Krackhardt, 1992).

27  

Granovetter (1973) proposes that the strength of a tie is probably a linear

combination of the amount of time. Several theorists have also explored the idea that

strong ties have developed through time (Balkundi and Harrison, 2006; Chiu, Hsu,

and Wang, 2006; Granovetter, 1973; Hansen, 1999; McFadyen and Cannella, 2004).

Krackhardt (1992) argues for the importance of strong relationships, where people

have known each other for a long time and have developed affection for each other.

Frequency of organizational meetings as well as participating in the organizational

activities increased the strength of ties (Landry, Amara, and Lamari, 2002).

2.4 Relational Social Capital

The third dimension of social capital is relational. Tsai and Ghoshal

(1998) asserted that shared vision, the key manifestations of cognitive social

capital, may encourage the development of relational social capital. Social

interaction ties may inspire trust and perceived trustworthy which represent the

relational dimension (Krackhardt, 1992; Nelson, 1989).

Tsai and Ghoshal defined the relational dimension of social capital as assets

that are rooted in these relationships, such as trust and trustworthiness. Trust is a

characteristic of an association, but trustworthiness is an element of an individual

actor engaged in the affiliation (Barney and Hansen, 1994).

Researchers have suggested that trust is one key aspect of the relational social

capital and a facilitator of collective action (Coleman, 1990; Fukuyama, 1995). The

theme of relational social capital can be linked to work commitment, which refers to

the individual accepting an organizational goal and desiring to make efforts for the

benefit of the organization (Mowday, Steers, and Porter, 1979). Relationships have

often been referred to cooperative advantage. Commitment and trust are key factors in

enhancing successful relationships (Morgan and Hunt, 1994). Trust generally is

viewed as an essential ingredient for successful relationships (Berry, 1995, Morgan

and Hunt, 1994). Similarly, commitment is recognized as an essential ingredient for

successful long-term relationships (Dwyer, Schurrm and Oh, 1987; Morgan and Hunt,

1994). The achievements of mutual gain are developed through credible relationships

which require such attributes as trust and commitment between partners (Kwon,

2011).

28  

Researchers have asserted that strong ties are typically associated with trust

and facilitate the flow of information (Gulati, 1998; Rowley, Behrens and Krackhardt,

2000). Trust plays a key role in the willingness of network actors to share knowledge

(Nahapiet and Ghoshal, 1998; Tsai and Ghoshal, 1998). A lack of trust may lead to

competitive confusion about whether or not a network firm is an ally (Powell, Koput,

and Smith-Doerr, 1996). Trust is process based, in the sense that members regularly

test each other’s integrity—as trust develops over time, opportunities for knowledge

sharing between network members’ increase, and trust can be analyzed as the

fundamental energetic element of networks. Confidence in others is also essential to

accepting the value of information, knowledge, referrals, and promises that are

supported by the networks (Cross, Borgatti and Parker, 2001; Hansen, 2002; Borgatti

and Cross, 2003).

Hausman (2001) proposed that trust and commitment are relationship strength

that influences the efficiency of firms. This statement has been empirically supported

in a variety of inter-firm relationships (Gilliland and Bello, 2002; Hausman, 2001).

Previous scholars show that relational social capital is defined as one of the

exogenous latent variables which are comprised of trust and commitment.

Trust stimulates, in particular, people to recognize the quality and the quantity

of transferring knowledge and of simultaneously evaluating the outcome of

knowledge exchange. From another point of view, trust is not only a necessary

condition but also a product of knowledge exchange and sharing (Davenport and

Prusak, 1998). Mutual trust among organization members could facilitate knowledge

flow thoroughly and transparently within the organization (Nahapiet and Ghoshal,

1998). Additionally, Davenport, Davies and Grimes 1998’s study of collaborative

RandD project teams also supports this assertion. They found that mutual trust among

team members would help remove the barriers of knowledge communication, enhance

the quality and quantity of exchanged knowledge, and promote the efficiency of

knowledge communication. People who are easy going tend to be more trustworthy in

the network partner (Leena and Van Buren, 1999)

According to Mishra and Morrisey (1990), organizational trust facilitates open

communication in organizations, sharing of information, and participation of the

employees in decision making and thus increasing their productivity. Realization of

29  

the climate of trust in organizations results in job satisfaction, organizational

commitment, clarification of roles, and increase performance.

Trust is the key success factor that impacts banking activity and banking

performance (Mukherjee and Nath, 2003). Because of its nature, banking contracts

belong to a special type of contract where trust between parties is essential. Argyris

(1964) argued that the degree of trust and respect between management and

employees has a direct effect on the performance of the organization. A low level of

trust or distrust makes employees frustrated and aggressive as they attempt to go

outside the rules of management and set inappropriate goals that do not contrubute to

organizational performance.

Trust is multifaceted and takes a variety of forms, for example, reputation-

based trust, where referrals and gossip are used to gauge others. Burt (1992) has

acknowledged that “providing a reliable flow of information…is a matter of trust, of

confidence in the information passed and the care with which contacts look out for

your interests.” A trust relation is less likely to betray each other’s (Krackhardt, 1990;

McEvily, Perrone and Zaheer, 2003).

Trust is an important factor for running a business (Greiling, 2007; Zaheer and

Venkatraman, 1995). The positive effect of trust on task performance has been proven

by Costa, Roe and Taillieu (2001). Their research confirms the importance of trust for

the functioning of teams in organizations. Smith and Barclay (1997) show that

perceptions of mutual trustworthiness and trusting behaviors were positively related to

task performance and mutual satisfaction. Mutual high trust reinforces and escalates

exchanges between the parties (Blau, 1964).

Organizations can reduce transaction costs by increasing trust. Members trust

in their organization’s possible influence on its effectiveness and efficiency, and trust

among groups in the organization is also a key element of the cooperative

relationships that enable extra performance (Pierce and Gardner, 2004).

Social exchange arguments also can be used to support the effect of trust

propensity to outcomes. According to Rotter (1980), the research result shows that

individuals with a high trust propensity would themselves act more in a cooperative,

pro-social, and moral manner across contexts and situations. Researchers have tended

to support this claim, as higher scores on trust tend to be associated with increased

30  

help offering, and decreased cheating (Rotter, 1980; Stack, 1978; Colquitt, Scott, and

LePine, 2007).

Trust between employees and organization facilitates management, effective

use of resources, and affects all activities of the organization (Conn, 2004; Cross and

Cummings, 2004; Wayne, Shore and Liden, 1997), which is shown as an important

factor in the improvement of organizational performance (Jones, 2001; Mayer, Davis,

and Schoorman, 1995; Musacco, 2000).

Trust is the expectation that arrives within a community of regular, honest, and

cooperatives behavior. This study examines individual trust in the organization.

Individual trust captures the interpersonal facets of trust, such as a belief that

members will help others out of difficulties, that all members are willing to give a

hand in collective goals, the belief that other members will not be harmful to their

work or tackling thorny problems, and the belief that everybody will act in line with

the aims of the organization and that they would be honest.

Trust reflects an individual’s beliefs in other members’ non-opportunistic

behavior, promise keeping, behavior consistency, and trustfulness (Chui, Hsu and

Wang, 2006). Trust bears great importance in the establishment of social relations

(Yilmaz and Atalay, 2009; Sparito, 2001). In this sense, trust means the willingness of

members to be vulnerable to help other members out of difficulties (Mayer, Allen,

and Smith, 1993).

According to Fukuyama (1995), trust is the expectation that rises in a society

where all the members act in line with the shared norms, regularly, honestly and

cooperatively. Trust can be defined as the set of beliefs that the group is well-

intentioned, fair, and constructive, and is based on ethical norms (Carnevale and

Wechsler (1992). It is the belief that the organizational members will always try and

help other members out if one gets into difficulties (Chow and Chan, 2008).

As Blau (1964) described the trust process, individuals initiate an exchange by

making an investment in another party by offering a favor. The others will be

motivated to reciprocate their favor with a similar return. Thus, in organizational trust,

members are willing to give a hand when others need it (Chow and Chan, 2008).

Trust can be viewed as an agreement between person, group, or organization

and another person confirming that they would keep his rights safe in economical and

31  

social exchange (Hosmer, 1995; Brown, Erwin, Petkov, 2006). Mayer, Allen, and

Smith (1993) proposed that trust is the expectation that the other party’s act can have

important results. According to Leena and Van Buren (1999), trust means the belief in

and acceptance of the ability of individuals to contribute their efforts to helping others

collectively.

Trust can be viewed in relation to the organizational culture, one that

encourages people to engage in solving problems and making the job easier. Certain

environmental conditions allow a person to reliably expect to be able to obtain and

use the resources made available through his or her contacts (Gambetta, 1988; Ring

and Van de Ven, 1994; McAllister, 1995; Nahapiet and Ghoshal, 1998). Mutual trust

among members means that other members will not cause harm in their work (Chow

and Chan, 2008). Luhmann (1979) cited in Yilmaz and Atalay (2009) states that trust

can be viewed as the belief of a person that the acts of the other consider his or her

own good.

Gabarro (1978) bases the concepts of trust on the openness in the behavior of

two people against each other because of several reasons. The reasons are explained

that the other person does not have any ill intentions and acts considerably, not

capriciously. Mooradian, Renzi and Matzler (2006), and Wekselberg (1996) defined

trust as the belief that other party is willing to act in a way that would not cause any

trouble or create any risk for him. Gilbert and Tang (1998) note the belief that

everybody would act in line with the aims of the organization and they would be

honest. Trust seems to include the idea that a person like oneself is less likely to

engage in betrayal (Moran, 2005). Additionally, trust is the belief that most people are

sincere, fair, and have good intentions (Mooradian, Renzi and Matzler, 2006), and

other parties are willing to act in a way that would not cause any trouble or create any

risk for him/her (Wekselberg, 1996). In addition, Gilbert and Tang (1998)

characterized trust as the belief that everybody would act in line with the aims of the

organization and they would be honest with others.

Trust in the firm is the positive expectations of an employee about the

applications and policies of the organization, even in risky situations, and the support

of the organization (Lewicki and McAllister 1998; Yilmaz, 2008). Employees trust in

the organization when they have heard that it has benefits to them (Clegg, Pitsis,

32  

Rura-Polley, and Marosszeky 2002). Organizational trust increases employees’ self-

assurance and erases their fear of the rules of the organization (Humprey, 1995;

Rehfeld, 2001). According to Sashkin and Burke (1990), trust is the employees’ belief

in the administration, which makes them fulfill all the orders without questioning.

Relational social capital can be defined as commitment to organization.

Commitment refers to a psychological state the binds the individual to the

organization (Allen and Meyer, 1991). Affective commitment is a mindset of the

employee that is affectively committed to strongly identifying with the goals of the

organization and desires to remain a part of it. Committed employees are willing to

put in a great deal of effort that goes beyond normal expectations to help the

organization to succeed. As Meyer and Allen (1997) argue, affective commitment is

positively related to individuals’ willingness to commit extra effort to their work, and

this is the kind of commitment that can be expected to be related to the willingness to

donate and receive knowledge.

Hinds and Pfeffer (2003) sum up that that the individuals that are more

committed to the organization, and have more trust in both management and

coworkers, are more likely to share their knowledge. A number of research studies

have specifically investigated the relationship between commitment and knowledge

sharing and confirm affective commitment as an important variable in explaining

knowledge sharing (Hislop, 2003; Hoff and Weena, 2004; Jarvenpa and Staples,

2001; Kelloway and Barling, 2000; Scarbrough, 1999; Smith and McKeen, 2002).

These literatures lead us to expect that affective commitment positively influences the

extent to which people share their knowledge. Based on these studies, a model is

presented in which affective commitment is positively related to knowledge sharing.

The conceptual model also supported by Smith and McKeen (2002) that commitment

to the organization is an important part of a knowledge-sharing culture.

It is commonly believed that committed employees will also work harder and

be more likely to “go to the extra mile” to achieve the organizational performance and

objectives. Kanter (1968) views organizational commitment as the willingness of

workers to devote energy and loyalty to an organization. Buchanan (1974)

conceptualizes commitment as a partisan, affective attachment to the goals and values

of the organization, to one role in relation to the goals and values, and to the

33  

organization for its own sake. Porter, Crampon and Smith (1976) identify organization

commitment as the relative strength of an individual’s identification with involvement

in a particular organization (Mowday, Steers, and Porter 1979).

Meyer et al. (1993) and Baugh and Roberts (1994) found that committed

employees had high expectations of their performance and therefore they performed

better. Committed employees give a big contribution to organizations because they

perform and behave in achieving the organizations' goals. Committed employees are

proud and happy to say that they are members of the organization, and people that are

committed to their organization believe in it and feel good about it; they do the best

for the organization (George and Jones, 1996).

Affective commitment has been most strongly linked to positive work-related

behaviors (Meyer, Stanley, Herscovitch and Toponysky, 2002; Coleman, Irving, and

Cooper, 1999. Varieties of research indicate that there is an obvious link between the

affective commitment of an employee and his or her job performance (Ali, Karamat,

Noreen, Khurram, Chauadary, Nadeem, Jamshaid, and Farman 2011; Chen,

Silverthrone and Hung, 2006; Clarke 2006; Cohen, 1996; Sinclair, Tucker, Cullen,

and Wright, 2005; Dunham, Grube and Castaneda, 1994; Khan,Ziauddin, Jam and

Ramay 2010; Rashid, Sambasvani and Joari, 2003; Shore, Barksdale and Shore, 1995;

Suliman and Lles, 2000).

Although Allen and Meyer provided three types of commitment measurement,

this study deploys only the affective commitment to measure an employee’s

attachment to the GSB and the bank’s goals. Finegan (2000) claimed that each type of

commitment produces effects differently and separately. Researchers also confirm

that three types of commitment are distinguishable from each other. Each facet of

commitment is exclusive and can be used to clarify the commitment of the employee

within the organization (Bergmann, Lester, De Meuse and Grahn, 2000; Meyer et al,

2002; Meyer and Allen, 2004).

In conclusion, relational social capital concludes trust (Gulati, 1998; Rowley,

Behrens, and Krackhardt, 2000) and trustworthy (Chui, Hsu, and Wang, 2006; Cross,

Borgatti, and Parker, 2001; Hansen, 2002; Borgatti and Cross, 2003) among members

in the network, , member’s trust in organization (Nahapiet and Ghoshal, 1998), and

34  

affective commitment to organization (Allen and Meyer, 1991; Ali, Karamat, Noreen

et al., 2011; Hinds and Pfeffer, 2003).

2.5 Knowledge Sharing

Authors’ points out the types of social capital are enabling the sharing of

different kinds of knowledge (Adler and Kwon, 2002; Coleman, 1988; Fukuyama,

1995; Hazleton and Kennab, 2000, Inkpen and Tsang, 2005). Knowledge sharing

comprises a set of shared understandings related to providing employees with access

to relevant information and building and using knowledge networks within the

organization (Hoegl, Parboteeah and Munson, 2003). Knowledge sharing can occur at

individual and organizational levels (Calantone, Cavusgil, and Zhao 2002;

Scarbourough, 2003). However, this study aims to highlight the individual level.

Knowledge sharing refers to the activities of transferring or disseminating

from one person, group organization to another (Lee, 2001). Knowledge sharing is

similar to knowledge transfer, but the “sharing” term often refers to the exchange of

knowledge that does not have a clear objective and does not require knowledge

utilization as with knowledge transfer (King and Marks, 2004). Although person-to-

person transfer may be relatively inefficient, it can be very effective when the

objective and intended use of the transfer is clear (Zainol and Zaki, 2010).

Knowledge sharing involves a set of behaviors that aid in the exchange of

acquired knowledge (Chow and Chan, 2008). Many theories have shown statistically

various determinants that influence knowledge sharing in the organization (Bock and

Kim, 2002; Ramasamy, Goh and Yeung, 2006; Wong, Wong, Hui, Law, 2001). Many

authors have also theorized that social capital contributes to knowledge sharing and

that knowledge sharing also is one of the key benefits of firm performance (Gulati, 1998;

Sandefur and Laumann, 1998). A growing number of studies show that knowledge

sharing has contributed positively to firm performance (Abrams, Cross and Levin,

2003; Cumming, 2004; Gupta and Govindarajan, 2000; Hansen, 1999; Kulp, Lee, and

Ofek, 2004; Spencer, 2003).

Knowledge sharing can be explained as attitudes; or willingness to donate, and

receive information. Knowledge is about beliefs, values, and commitment (Nonaka

35  

and Takeuchi, 1995). Here knowledge sharing is defined as one of the endogenous

latent variables.

A firm can successfully promote a knowledge-sharing culture by changing

employees’ attitudes and behaviors to promote willing and consistent knowledge

sharing (Connelly and Kelloway, 2003; Lin and Lee, 2004). Chow and Chan (2008)

characterize knowledge sharing as the degree of one’s favorable, perceived as

important thing, and the belief in sharing.

As Meyer and Allen (1997) argue, affective commitment is positively related

to individuals’ willingness to commit extra effort to their work, and this is the kind of

commitment that can be expected to be related to the willingness to donate and

receive the knowledge. Willingness and eagerness are attitudes of people toward

knowledge sharing.

Willingness implies a positive attitude to other members of a group, a

readiness to reply to colleagues kindly. De Vries, Van den Hooff, and Ridder (2006)

argue that actors are willing to provide access to their personal knowledge, but they

expect others to behave similarly. Members of a group will not begin to actively

share their knowledge if they are not sure whether others are also willing to contribute

to the group.

Knowledge sharing is the group norm of reciprocity (Coleman, 1988, Putnum,

1993). The collectivism norm salient within the social structure can create a

successful public good in the form of shared intellectual capital (Nahapiet and

Ghoshal, 1998). Thus, group norms result in personal attitude willingness.

Eagerness, as well, implies a positive attitude to actively show knowledge

about a certain subject. Van den Hooff, De Ridder and Aukema (2004) define it as the

extent to which an individual has a strong internal drive to communicate his or her

individual intellectual capital to other group members. An actor that is willing to

contribute knowledge will disburse his or her knowledge to others. People are eager

to let others know what they know because they themselves consider it valuable and

expect their individual knowledge to be appropriated by others (De Vries, van den

Hooff, and de Ridder, 2006).

Wasko and Faraj (2005) suggest that employees are motivated when they

think that knowledge sharing behaviors will be worth the effort and are able to help

36  

others. Therefore, the expectation of individual benefits can encourage employees to

share knowledge with colleagues. As Hall (2001) has argued, people are more willing

to share their knowledge if they are convinced that doing so is useful—if they have

the feeling that they share their knowledge in an environment where doing so is

appreciated and where their knowledge will actually be used.

Personal attitude towards the willingness and eagerness to share knowledge

will not be effective if the actors do not act in reality. Knowledge sharing success

depends on behavioral factors (Ismail and Chue, 2005). This study focuses on

individual behavior as a mechanism that creates knowledge sharing effectiveness.

Knowledge sharing refers to the disbursement of one’s’ knowledge and

experience affected to others. It is manifested that change in the knowledge sharing in

organization can be measured changes in performance (Argote, Ingram, 2000). This

definition implies that the knowledge sharing behavior consists of both bringing and

getting knowledge. Ardichvill, Page and Wentling (2003) note that knowledge sharing

consists of both the supply and demand of new knowledge. Other researchers have

made a distinction between similar processes, but mostly in terms of one active and

one more passive process (De Leeuw van Weenen, 2002). Van der Rijt (2002) made a

distinction between donating and receiving information, active donor and passive

receiver (Olernkamp, 2001) or donating knowledge and collecting knowledge (Van

den Hooff and Van Weena, 2004).

According to Van den Hooff and De Ridder (2004), knowledge donating is

defined as “communication based upon an individual’s own wish to transfer

intellectual capital” and knowledge collecting as “attempting to persuade others to

share what they know.” Consequently, these two distinct processes are active in the

sense that one is either engaged in active communication with others for the purpose

of transferring knowledge, or consulting others in order to gain some access to their

intellectual capital (Hooff and Weena, 2004).

Davenport and Prusak (1998) indicated that knowledge is personal, and that

the willingness to contribute knowledge to colleagues has just begun to be seen as

effective in the management of the knowledge resources in the organization. The

purpose of contributing knowledge is that it becomes collective knowledge for the

37  

organization over time, and a record of the stock of knowledge can be maintained and

made available to the organization.

Knowledge sharing can be distinguished as the collection of knowledge. Lin

(2007) argues for example that knowledge collecting consists of the processes and

mechanisms of gathering information and knowledge from internal and external

sources. The process of knowledge collecting in which organizational knowledge

becomes group and individual knowledge involves the internalization and

socialization of knowledge.

Knowledge collecting represents a key aspect of a successful project (Hansen,

1999), and improves performance (Jantunen, 2005). A firm with proficiency in

gathering and integrating knowledge is more likely to be unique, rare, and difficult for

rivals to replicate, and hence has the potential to sustain and perform well. This study

expects that the employee that both donates and collects knowledge to and from

colleagues respectively is likely to perform well and make the organization better in

terms of long-run competitiveness.

Most theorists advocate that successful knowledge management could be

obtained through organizational culture and behavior (Davenport and Prusak, 2000),

suitable technology (Lee and Ahn, 2007), and the reward system. However, the

research results show that there is no relationship between rewards and knowledge

sharing (Bock and Kim, 2002; Kohn, 1993). In fact, the individual plays significant

role in knowledge sharing (Constant, Kiesler and Sproull., 1994; Goodman and Darr,

1998; Hansen, 1999; Jarvenpaa and Staples, 2001; Lee and Ahn, 2007; Nonaka and

Takeuchi, 1995). Individuals can be satisfied with the confidence in their ability to

contribute to the organization or to help others (Constant et al., 1994; Kankanhalli et

al., 2005).

According to the Theory of Reasoned Action (Fishbein and Ajzen, 1975),

human beings are usually quite rational and make systematic use of the information

available to them. A person’s performance of a specified behavior is determined by

his behavioral intention to perform the behavior. The intention is jointly determined

by the person’s attitude toward the behavior. The person’s belief in the behavior leads

to certain outcomes and his/her evaluations of these outcomes.

While economic exchange theory concerns extrinsic benefits, social exchange

theory concerns intrinsic rewards (Blau, 1964). On the other hand, the benefits

38  

involved in social exchange tend to engender feelings of personal obligation,

gratitude, and trust. Participation enhances a person’s personal reputation in the

network. Members attempt to maintain their reputation because it is an important

asset to guarantee that one is valued within collective or organization (Jones, Hesterly

and Borgarri, 1997).

This study follows Nahapiet and Ghoshal’s model for explaining the

individual’s attitude toward knowledge sharing. The study expects that people that

have intentions to render their knowledge would seem to mainly foster a sense of

social exchange relationship. Knowledge sharing is a very individualistic behavior.

Knowledge sharing allows employees to experience a large scope and depth of

association in the organization, and employees that associate to a great extent among

organizational members tend to have positive attitudes toward knowledge sharing.

Knowledge sharing, in this study, incorporates three main themes: attitude of

sharing (Coleman, 1988, Hall , 2001; Ismail and Chue, 2005; Nahapiet and Ghoshal,

1998; Putnum, 1993; Wasko and Faraj, 2005), willingness to donate knowledge

(Ardichvill, Page and Wentling, 2003; Argote, Ingram, 2000; De Leeuw van Weenen,

2002; Van den Hooff, De Ridder and Aukema, 2004; Van der Rijt, 2002), willingness

to collect knowledge (Ardichvill, Page and Wentling, 2003; Argote, Ingram, 2000; De

Leeuw van Weenen, 2002; Van den Hooff, De Ridder, and Aukema, 2004; Van der

Rijt, 2002).

2.6 Organizational Performance

The concept of organizational performance has been defined in different

moments by the specialized theorists. In academic, the school achievement is

represented by an average of school grade; while the university performance is

benchmarked with research performance. In business, organizational performance is

traditionally assessed by accounting statements, especially the profit and loss

statement. Organization performance is a comparative analysis of performance and

goal settings. Generally, there are various measurements analyzed: financial

performance, market performance, shareholder value performance, and production

capacity performance.

39  

Organizational performance and effectiveness are most often used and related

issues. Although the study of organizational performance has been widespread with

challenges for decades, it still remains an important topic for the academic studies.

The challenges take account of the lack of consensus in defining organizational

effectiveness and determining what dimensions of performance should be measured

and how they should be measured.

According to the classical organizational theorists, Fayol (1916), Gulick

(2004, 1937), Taylor (2004, 1912) and Weber (2004, 1922) tried to analysis

organizational effectiveness in terms of the efficiency that resulted from the

implementation of principles of management. The greatest contributions to

organizational theories focused on task performance. Since then, copious theories,

concepts, and frameworks have been proposed in the continuing discussion.

During 1950s, the General Electric Company, a multi-national corporation,

developed and incorporated a set of performance measurements for its departments

such as short-term profitability, market share, productivity, product leadership,

personnel development, employee attitudes, public responsibility, balance between

short-range objectives and long-range goals.

Organizational performances indicators are constructed via the experiences

people regular encounter those organizations. The corresponding tools have been

developed and considered a wide range of indicators which are believed to drive

organizational performance. In 1990s, one of the most popular measurements has

been developed by the Harvard Business School called the balanced scorecard. At that

time, a similar approach was built up by the European Foundation for Quality

Management as well.

It has been accepted that the balanced scorecard procedure is a high quality

instrument for structuring an array of performance measures. It links between the

espoused strategies of an organization and the performance measures. It measures,

monitors, and controls in four major areas (financial, customer, business process, and

innovation and learning) which organizational performance measures are to be

devised. This specific approach requires a focus on “the key success factors” that are

believed to generate enough performance measures.

40  

From literatures reviews, organizational performance or effectiveness are

described as goal accomplishments (Barnard, 1938; Ezioni, 1964; Price, 1968; Hall,

1978), ability to acquire resources from its environments (Georgopolous and

Tannenbaum, 1957; Yuchtman, and Seashore, 1967; Katz and Khan, 1965), balanced

scorecard (Kaplan and Norton, 1992).

As described earlier, organizational performance is one of the most important

criteria for measuring organizational outcomes and success. Campbell, McHenry and

Wise (1990) define performance as the observable things people do that are relevant

for the goals of the organization. Therefore, organizational performance is

multidimensional; there is not one outcome, one factor or one anything that can be

pointed to and labeled as job performance.

Organizations always make investment to develop and improve their

employee effectiveness. By measuring performance how well one performs in his or

her job depends on several factors such as goal settings in terms of financial

indicators, the personality, the general cognitive ability, the job involvement, and the

environment of work. As well, the job performances of the overall branch managers

in this study are also multidimensional factors. The GSB utilizes the performance

appraisal system to measure its staff performance and effectiveness. The performance

appraisal report contains many elements; however, it can be separated into two

parts—the first section consists of a number of operating goals; and the latter is

organizational citizenship behavior. The proportion of value weighting is 70:30. This

means that the bank pays more attention to the branch manager in reaching the

operating goals than the behavior. The study uses the operating goals as the end result

to measure performance because the bank’s measurements are easily perceived as

being measurable and not ambiguous as with the concepts of personality,

sportsmanship, altruism, courtesy, consciousness, and other subjective factors, which

can be argued.

The first part of the performance appraisal is the operating goal, which is

measured in terms of financial performance. Similar to most organizations, a good

financial performance is the key driver. It is an objective measure for assessing how

well an organization performs its daily activities and operations and how it is able to

41  

generate revenues. It is an indicator of the general financial health of the organization

over a given period of time.

The branch manager is expected to be deeply engaged in the bank’s

performance, and he/she is appraised according to a systematic and periodic process

that assesses job performance and productivity in relation to certain pre-established

criteria and organizational objectives. The goal set of each branch varies depending

on economic factors. For example, the goal setting in the Bangkok metropolitan is

actually higher than in the regions. Of course, the provincial branches are more

accountable than the district branches. Goal settings among branches are freely

negotiated.

As mentioned above, this study focuses on the job performance of the branch

manager. According to the bank performance appraisal system, each branch manager

reports his or her operating performance to the bank every month and quarterly. At

the end of the year, the branch performance is rated, ranked, and appraised by his or

her supervisors in terms of percentage compared to the goal set.

A rating point system is used for job performance. The performance in this

study was depicted as the dependent variable. In terms of the structural equation

model (SEM), it is so-called the purely endogenous variable, which is entirely

determined by the states of other variables in the system.

The main idea of this research is to link the social capital concept with the

mediating connections of knowledge sharing to performance. It is reasonable to think

that differences in financial performance factors are influenced by the linkages of

social capital; as well as the impact of knowledge sharing.

Exogenous and endogenous variables of the model are presented in Table 2.1.

A set of variables are constructed to observe and measure the factors.

42  

Table 2.1 Exogenous and Endogenous Variables

Latent Variables Manifest Variables

Exogenous variable

Cognitive Social Capital

1. Understand organizational vision (Cohen, 1990;

Nahapiet and Ghoshal, 1998)

2. Method of work (Coleman, 1990; Darvish and

Nikbaklish, 2010)

3. Enthusiastic (Nahapiet and Ghoshal, 1998; Tsai

and Ghoshal, 1998; Chen, Chang, and Hung,

2007)

4. Plan to achieve goal (Chow,and Chan, 2008;

Fukuyama, 1995,1997; Inkpen and Tsang, 2005)

5. Goal challenge (Naghavi, Salavati, and Mayahed,

2011)

6. Goal attainment (Andersen ,1990; Schnake and

Cochran, 1985; Sinkula, Baker, and Noordewier,

1997)

7. Prioritized important work (Hoe and McShare,

2002; Kilduff, Angelma, and Meha, 2000)

8. Deploy organization mission (Cohen and Prusam,

2001; Ma’atoofi and Tajeddini, 2010; Wong,

Wong, Hui, and Law, 2001)

Endogenous Variables

Structural Social Capital

1. Good relationship with peers (Chui, Hsu, and

Wang, 2006; Hanzen, 1999; Larson, Christensen,

Franz, and Abbott, 1998Uzzi, 1997)

2. Ability to help people (Cohen and Levinthal,

1990; Uzzi and Lancater, 2003)

3. Willingness to work with others (Cohen and

Levinthal, 1990; Uzzi and Lancater, 2003)

4. Willingness to support others (Wager, 1995;

Walker, Kogut, and Shan, 1997)

5. Willingness to serve others (Cross and Parker,

2004; Cross, Borgetti, and Parker, 2001;

Grannovetter, 1992)

43  

Table 2.1 (Continued)

Latent Variables Manifest Variables

- Structural Social Capital

(cont.)

6. Ability to help people (Grannovetter, 1992)

7. Willingness to work with others (Levin and Cross,

2004; Sparrowe, Linden, Wayne, and Kraimer,

2001)

8. Willingness to support others (Levin and Cross,

2004; Sparrowe, Linden, Wayne, and Kraimer,

2001)

9. Willingness to serve others (Levin and Cross,

2004; Sparrowe, Linden, Wayne, and Kraimer,

2001)

10. Close to peers (Kale, Singh, and Perlmutter, 2000;

Krackhardt, 1992; Podolny and Page, 1998)

- Relational Social Capital

1. Be honest (Gulati, 1998; Powell, Koput, and

Smith-Doerr, 1996; Rowley, Behrens, and

Krackhardt, 2000)

2. Be trustworthy (Chui, Hsu, and Wang, 2006;

Cross, Borgatti, and Parker, 2001; Hansen, 2002;

Borgatti and Cross, 2003

3. Easy going (Leena and van Buren, 1999; Pierce

and Gardner, 2004; Rotter, 1980)

4. Be ethics (Argyris, 1964; Carnevale and Wechsler,

1992; Colquitt, Scott, and LePine, 2007

Krackhardt, 1990; McEvily, Perrone, and Zaheer,

2003; Rotter, 1980; Stack, 1978

5. Trust in organization (Mishra and Morrisey (1990;

Nahapiet and Ghoshal, 1998

6. Committed to the organization (Allen and Meyer,

1991; Ali, Karamat, Noreen, Khurram, Chauadary,

Nadeem, Jamshaid, and Farman 2011; George and

Jones, 1996; Hinds and Pfeffer, 2003; Kanter,

1968; Porter, Crampon, and Smith,1976

44  

Table 2.1 (Continued)

Latent Variables Manifest Variables

- Knowledge sharing

(KSHARING)

1. Attitude of sharing (Coleman, 1988, Hall (2001;

Ismail and Chue, 2005; Nahapiet and Ghoshal,

1998; Putnum, 1993; Wasko and Faraj, 2005)

2. Willingness to donate knowledge (Ardichvill,

Page, and Wentling, 2003; Argote, Ingram,

2000; De Leeuw van Weenen, 2002; Van den

Hooff, De Ridder, and Aukema, 2004; Van der

Rijt, 2002)

3. Willingness to collect knowledge (Ardichvill,

Page, and Wentling, 2003; Argote, Ingram,

2000; De Leeuw van Weenen, 2002; Van den

Hooff, De Ridder, and Aukema, 2004; Van der

Rijt, 2002)

- Performance

(PERFORM)

Performance appraisal result from bank’s KPIs

obtained from bank data (Kaplan and Norton, 2000)

The literature supports the conceptual model of this study; however, it is

challenging to observe whether social capital and knowledge sharing influence

organizational performance in different contexts and whether it can be applied to the

Thai context, especially to the bank being discussed here or not. The results from the

data collection will be processed to confirm the theories. The current study

hypothesizes that cognitive social capital is exogenous factor and produces the

positive effects on structural social capital, relational social capital, knowledge

sharing, and performance. The next hypothesis is structural social capital is positive

influenced on rational social capital, knowledge sharing, and performance. As the

results, relational social capital has positive relation to knowledge sharing and

performance as well. Finally, knowledge sharing is positive effect to performance.

45  

The relationships among the variables mentioned above are depicted by

means of the Amos scheme. In general, the structural equation models are

schematically portrayed using the particular configurations of four symbols. Circles or

ellipses represent observed latent factors, squares or rectangles represent observed

variables, single-headed arrows represent the impact of one variable on another, and

double-headed arrows represent the covariance or correlations between pairs of

variables. All of the variables in this model were derived from various literatures for

answering the research objectives. This proposed model was developed and theories

were tested for these relationships. The model summarized in Figure 2.1 is an

integration of the linkages of social capital selected because of their applicability to

understanding a specific aspect of the knowledge sharing which affects its

performance.

2.7 Summary

The conceptual model shows that organizational performance depends on

knowledge sharing and the linkages of social capital, which are relational, structural,

and cognitive. In addition, knowledge sharing is influenced by the three types of

social capital. Additionally, relational social capital depends on structural social

capital and cognitive social capital, where structural social capital is influenced by

cognitive social capital.

In building the particular model, four configurations are shown in the

analytical process:

1) The path coefficient for the regression of he observed variable onto

the unobserved latent variable,

2) The path coefficient for regression of one factor onto another

factor,

3) Measurement error associated with observed variables, and

4) Residual error in the prediction of unobserved factor.

46  

As noted earlier, the schematic representations of models or path diagrams

provide a visual portrayed of the relations which are assumed to hold among the

variables according to the literature. The results and discussion of this model are

presented in chapter 4 and 5. The next chapter describes the methodology of the

study.

 

47  

CHAPTER 3

RESEARCH METHODOLOGY

As reviewed in the previous chapters, the conceptual framework and path

diagram were developed. This chapter addresses the approach to the study. It provides

an explanation of the research methodology used to conduct this study. The steps of

quantitative method are used as follows:

3.1 Research design

3.2 Sampling Design

3.3 Operational definition

3.4 Tools

3.5 Variables and measurement

3.6 Data collection procedures

3.7 Data analysis

3.8 Conclusion

3.1 Research Design

This research adopted a quantitative method by using a cross-sectional design

on the Government Savings Bank, which is an old, large and complex organization,

comparing members in different areas. Generally, the main task of a cross-sectional

approach is to compare the examinees concerning different characteristics, and to

allow researchers to explore the relationships among variables as they naturally occur

without any manipulation of the situation. Payne, Moore, Griffis and Autry (2010)

found that most empirical studies on social capital utilized a cross-sectional approach.

Thus, a cross sectional study is the best way to determine prevalence and is useful in

identifying the associations that can then be more rigorously studied using a cohort

study or randomized controlled study. It was assumed that this study responded to

these advantages. This study was not respond to longitudinal studies, which require

48

enormous amounts of time and are often quite expensive, and sometimes participants

drop out of the study, shrinking and decreasing the data collected.

Within the quantitative framework, the structured rank scale questionnaire

survey tool is used to measure social capital and knowledge sharing. Members in the

branch, considered as the basic unit of social capital accumulation, were asked to rate

items in the questionnaire. Generally, the personal cognitive, social structure ties, and

social relations emerge because social norms are enforced to shape the behavior of

members in the organization. Although respondents were asked individually, social

capital was apprehended as accumulations from individual to branch. Thus, individual

rating scales were calculated to represent the overall picture of branch.

In the social capital literature, Burt (1992) defined social capital at the

individual level of analysis as the friends, colleagues, and more general contacts

through which one receive opportunities to use his or her financial and human capital.

Coleman’s (1988) work concerns social capital as a resource for persons. Kilby

(2002) states that social capital exists within levels or scales as one feels that he or she

belong to family, community, profession, country, etc. At the same time, Adler and

Kwon (2002) support this, stating that social capital's sources lie in the social

structure within which the actor is located. The literature suggests that the tools

needed to measure social capital at the level of the employed individual are very

different from those needed to measure social capital at the level of households,

communities, organizations, or countries (Kassa and Parts. 2008; Lillbacka, 2008).

Thus, social capital can be thought of as having an individual and an aggregate

component (Buys and Bow, 2002; Newton 1997; Slangen et al., 2003; Singh, 2005;

Uzzi and Lancaster, 2003). That is, social capital belongs to the group and can be used

by the group or individuals within the group (Kilpatrick et al. 1998; Sander 2002).

Moreover, Brewer (2003) states that although social capital was originally conceived

as a community-wide concept, it should be observable at the individual level. That is

why this study focuses on the individual level.

The items were used to measure the manifest variables constructed from the

previous literatures. Before collecting the data, the questionnaire was tested and

retested to ensure that the questions are measuring what they were intended to

measure and were a reliable and valid measurement as well as practical.

49

3.2 The Sample

For this study 167 branches were selected: 75 from the Bangkok metropolis

and 92 from provincial branches (see Table 3.1). Questionnaires were sent out to all

employees in each of the 167 branches. The responses were then aggregated to the

branch level, which is the unit of analysis in this study.

Table 3.1 Gross Provincial Products, Number of Branches, and Employees

Province Gross Provincial Product

(Baht per year)

Branches

(Unit)

Employees

(Person)

1. Bangkok metropolis 456,911 75 1,002

2. Lop Buri 86,862 9 92

3. Nakhon Sawan 70,035 11 126

4. Chai Nat 67,078 6 59

5. Uthai Thani 61,356 3 43

6. Pichit 57,167 7 59

7. Petchabun 53,715 8 78

8. Ubon Ratchathani 44,800 17 133

9. Buri Ram 39,761 10 77

10.Su Rin 37,525 7 75

11. Yasothorm 34,181 6 75

12. Si Sa Ket 34,042 8 72

Total 167 1,891

Source: Office of the National Economic and Social Development Board, 2012;

The GSB Annual Report, 2011.

Questionnaires were administered to a total of 1,891 employees, producing

1,725 returns, and with an overall response rate of 91.22% within the selected

branches. A summary is provided in Table 3.2.

50

Table 3.2 The Sample

Region Branch (unit) Employee Response Rate

Bangkok 75 1,002 901 89.92

Region 6 44 457 424 92.78

Region 12 48 432 400 92.59

Total 167 1,891 1,725 91.22

The unit of analysis of this study is bank branch level. Bank performance is

critically dependent on the effective performance of each branch. A branch manager

is responsible for all functions of the branch and ensures that the branch’s goals and

objectives are met. Branch manger delegates tasks to members in the team. Therefore,

the values of good services derive from the employees’ capabilities of delivering

remarkable results (Gelade and Yong, 2005). Branch performance is resulted from

individual performance in the team. Branch success depends on the effectiveness of

teamwork in that network. Good teamwork is strongly related to good performance.

Teamwork in this study means the overall social capital of the branch: - members

have clear goals and responsibilities consistent with the bank’s culture and core

values. Members in a team mutually create strong sense of honesty, confidence, and

team spirit through reinforcement, shared activities, trust, commit, and supports

development for sharing knowledge to create the network success.

The unit of analysis for this study was the bank branch, not the individual.

Level of social capital and knowledge sharing of each branch were aggregated from

calculating the total value of each item marked by individual’s employees in each

branch divided by numbers of staff. Then, the weighted average values of items from

individuals were summarized to represent values of items of each branch.

This study perceived social capital as group level (Bourdieu, 1986; Coleman,

1988; Putnam, 1993). Social capital was derived from the classical theory that is

because the workers as individual invest and acquire certain capital of their own,

develop and maintain capital as a collective asset to enhance group member’s quality

of work life. Social capital was represented by aggregating the size of the group

51

network and the volume of capital possessed by members (Bourdieu, 1986). Social

capital was specified by its effect in particular individual action (Coleman, 1990).

3.3 Operational Definitions

The following sections describe the operational definition of each variable.

The dependent variable was the branch performance resulting from its branch KPI.

The independent variables were constructed in this model for the associations of

social capital, and knowledge sharing. The literature and previous studies led the

researcher to develop items to measures these variables as follows.

3.3.1 Dependent Variable

3.3.1.1 Performance

Data were archived from the databank. According to the bank branch

appraisal system, the regional manager appraises branch performance in terms of

percentage from the existing records compared to its branch KPIs settings. The one

that reaches the goal settings will get the maximum 100 percent and lower according

to its performance. Performance ranking is published in the regional quarterly

meeting.

One might argue that bank branches operate in a variety of local

environments. Some branches are located in wealthy communities and some in

deprived communities. For these reasons, the senior bank management set the targets

differently according to the branch size and location, especially regarding the

differences in the local micro-economy surrounding the branch. Thus, the performance

measurement system as precise and valid concerning whether the branch had achieved

its goal set.

3.3.2 Independent Variable

3.3.2.1 Cognitive Social Capital

According to the theoretical framework and the previous studies, it can

be seen that shared vision and shared goals were defined similarly, differently, and

52

with mixed definitions. The cognitive social capital, therefore, can be measured as

shared vision and shared goals.

3.3.2.2 Shared Vision

Shared vision can be demonstrated as the common view of members,

interests, intense and eager enjoyment to contribute to the organization, sense of

responsibility, and the sense of self-efficacy in achieving goals, missions, and task

settings. Shared vision can be viewed as a bonding mechanism that helps different

parts of an organization to integrate or combine resources (Darvish and Nikbakhsh,

2010) and the aspirations of the members of an organization in proper ways of acting

in a social system (Tsai and Ghoshal, 1998; Naghavi, Salavati and Mavahed, 2011).

Chiu, Hsu, and Wang (2006) proposed 3 items to measure shared vision and shared

goals. Ma’atoofi and Tajeddini (2010) defined shared vision as a total agreement on

the organizational vision across all levels of functions and divisions, and offered 3

items to measure it. Tsai and Ghoshal (1998) argued that within a firm cognitive

capital is embodied in a shared vision, i.e., collective goals and the aspiration of the

parties, and is present when partners have similar perceptions of common goals and

how they should interact.

3.3.2.3 Shared Goals

Inkpen and Tsang (2005) defined shared goals and cultures as the

primary types of cognitive capital. They argued that goals are shared when members

of a network share a common understanding and approach to the achievement of

network tasks and outcomes. Shared goals can be described as the degree to which

one has collective goals, missions, and visions with other people (Wong, Wong, Hui

and Law, 2001). It is important for any partnership to be successful that it is based on

shared goals. People are willing to share mutual interests, and work towards the same

goals. The joint work is successful for both parties, and a collaborative relationship

develops because of their shared goals.

Therefore, it can be concluded that cognitive social capital can be

defined as the transmission and shared understanding of social knowledge associated

with shared vision (Chui, Hsu and Wang, 2006; Darvish and Nikbaksh, 2010;

Fermandez and Garder, 2010; Ma’atoofi and Tajeddine, 2010, Naghavi, Salavati, and

53

Movahed, 2011, Nahapiet and Ghoshal, 1998; Sinkula, Baker and Noordewier, 1997;

Tsai and Ghoshal, 1998, Wong, Wong, Hui and Law, 2001, Zheng, 2008), shared

goals (Chow and Chan, 2008; Cohen and Prusak, 2001; Inkpen and Tsang, 2005;

Chen, Chan and Hung, 2008, Wong, Wong, Hui and Law, 2001), sense of mission

(Wong, Wong, Hui, and Law, 2010), ambition to work (Chow and Chan, 2008) , and

the aspiration of one in seeing the collective goals and how they should interact (Tsai

and Ghoshal, 1998) to achieve goals that can assist members in leaning what work is

important.

3.3.2.4 Structural Social Capital

Structural social capital, in this study, focused on the social strong ties.

Strength of ties means the access or pathway members have to each other based on

structural arrangements. Strong ties can be seen in terms of good relationship,

frequency of interactions among members, frequency of discussion/ communication,

and the proximity of interaction that characterizes ties among members.

Structural social capital can be defined as affection (Chui, Hsu and

Wang, 2006; Erickson and Yancey, 1980). Affection in strong ties can be measured in

terms of emotional intensity and intimacy, and close relationships, a more assistance

or support of one another, and whether they are relative and confidential.

Time spent among members in their network can be illustrated as

structural social capital (Chui, Hsu and Wang, 2006; Grannovetter, 1973; Krackhardt,

1992). Time spent can be measured in terms of the length of time that two actors

spend with each other, and the extended interaction period of time.

From the previous literatures, it can be concluded that strength of ties

is composed of three manifest dimensions: interaction (Chui, Hsu, and Wang, 2006;

Gilsing and Nooteboom, 2004; Grannovetter, 1973; Krackhardt, 1992; Landry,

Amara, and Lamari, 2002; Lin, Dayton and Greenwald, 1978; Leenders, Van

Engelen, and Kratzer, 2003; McFadyen and Cannella, 2004), affection (Chui, Hsu,

and Wang, 2006; Erickson and Yancey, 1980; Lin, Ensel, and Vaugin, 1981;

Krackhardt, 1992; Friedkin, 1980; Grannovetter, 1973; Moran, 2005; Nahapiet and

Ghoshal, 1998; Ring and Van de Ven, 1994; Seibert, Kraimer, and Liden, 2001;

Smith, Collins, and Clark, 2005; Tsai & Ghoshal, 1998), and time spent (Chui, Hsu,

and Wang, 2006; Grannovetter, 1973; Krackhardt, 1992).

54

3.3.2.5 Relational Social Capital

Relational social capital can be defined as the characteristics and

quality of the relationship between members and the organization. It is the mutual

confidence that a member has in exchange transactions that other member will not

exploit one’s vulnerabilities. It can be concluded from the previous literature that

relational social capital comprises trust and affective commitment.

Trust can be measured in terms of the individual and the organization.

Trust means trustworthiness, being sincere, reliable, the belief in good intent and in

people’s reliability, and belief in their perceived openness. When trust occurs, it can

be seen that members will always try to help each other out of the difficulties, and

give a hand when others need cooperation. People are always doing things for each

other (Coleman, 1988). Members contribute to their organization as an obligation, or

to repay a debt.

The affective commitment in this model refers to employees’

emotional attachment to, identification with, and involvement in the organization

(Allen and Meyer, 1990). Affective commitment can be measured as the attachment

of an individual’s fund of affectivity and emotion to the group (Kanter, 1968), as a

partisan, affective attachment to the goals and values of the organization (Buchanan,

1974), to one’s role in relation to goals and values, and to the organization for its own

sake, apart from its purely instrumental worth. Porter, Crampon and Smith (1976)

defined organizational commitment as the relative strength of an individual’s

identification with and involvement in a particular organization. An employee that is

affectively committed strongly identifies with the goals of the organization and

desires to remain a part of the organization.

Therefore, relational social capital can be defined as trust (Coleman,

1980), and affective commitment to organization (Allen and Meyer, 1990; Porter,

Crampon and Smith 1976)

3.3.2.6 Knowledge Sharing

Knowledge sharing is the attitudes and behavior of members in an

organization. Davenport (1997) defined sharing as a voluntary act. Sharing implies a

conscious act by an individual that participates in the knowledge exchange even

though there is no compulsion to do so. It is the mutual perspectives, ideas, and

55

intentions that competitive advantage results from sharing, collaborating synergistically

toward common outcomes.

Sharing knowledge is defined as the exchange process among

members in organization; Members mutually gain knowledge from one another,

evaluate, and integrate knowledge to strengthen their capacity to create sustainable

development for their organization. Sharing knowledge requires a process of mutual

perspective taking where distinctive individual knowledge is exchanged, evaluated,

and integrated with others in the organization. Knowledge sharing implies a relation

between at least two parties, one that possesses knowledge and the other that acquires

knowledge. Hinds and Pfeffer (2003) distinguished both attitude and motivation

factors to define knowledge sharing. Attitude factors are primarily related to an

individual’s ability to share knowledge; motivational factors concern their willingness

and eagerness to share. From the previous literature and studies, it was seen that

knowledge sharing process can be measured with three manifest variables: attitude,

donating, and collecting knowledge.

Attitude to share the knowledge can be operationalized as the degree to

which one has a favorable evaluation of performing the knowledge sharing behavior.

Knowledge sharing is about beliefs, values, and commitment (Nonaka and Takeuchi,

1995). Intension to share knowledge is mainly influenced by an employee’s attitude

towards knowledge sharing (Chatzoglou and Vraimaki, 2009). The attitude of sharing

is used to describe individuals’ behavior from satisfying their individual needs,

focusing on both common and individual goals. It is also refers to the individuals’

feeling when sharing the knowledge with other members, such as good, bad, of worth,

or enjoyable. They believe that their daily work performs well because of its

contribution to work knowledge. Knowledge sharing will help members in networks

achieve their organizational objectives. Individuals perform well because they are also

more willing and eager to both donate and collecting knowledge (Pascoe, Ali and

Warne, 2002). They behave as though it were a normal thing.

Donating knowledge is the behavior of the individual in providing

access to personal knowledge. Individuals share information, skills, experience, and

what they are good at with others in the organization, and they see the benefits of

donating information and a shared common understanding for the creation of

intellectual capital, and actors exchange information with each other. De Vries, van

56

den Hooff and Ridder, (2006) deployed 4 items to measure knowledge donating. Van

den Hooff and Van Weena (2004) utilized 6 items to determine the donation of

knowledge.

Collecting knowledge is the opposite side of donating knowledge. It is

a process on the demand side; employees are confident of receiving information from

the donor. Collecting knowledge implies a positive behavior to actively show their

individual knowledge considered as valuable and appreciated by others. De Vries,

et.al. (2006) deployed 4 items to measure knowledge collecting. Van den Hooff and

Van Weena (2004) utilized 8 items to determine the collection of knowledge.

3.4 Tools

3.4.1 Questionnaires

The current study used a questionnaire for collecting data. Payne, Moore,

Griffis, and Autry (2010) observed that 109 articles use social capital as the key

research construct, rather than merely mention the term, and found that 80 articles in

empirical research used questionnaires. Of the 80 reviewed articles, social capital was

utilized as an independent variable. Explaining performance is a popular goal for

social capital studies. The performance in this study was measured at multiple levels

of analysis, including the individual, group, project, and organizational levels.

The questionnaire was designed in Thai and translated into English later on.

Sentences requested both optimistic and pessimistic perspectives. The questionnaire

was developed to obtain information about three types of social capital and the

knowledge sharing. It comprises three parts; part one requires a respondent to answer

about his/her demographic data; in part two, the respondent has to indicate the extent

to which he/she agreed or disagreed with 51 formulated items related to the

independent variables; and part three is an open area for any comment or suggestion.

Items were measured on a 5-point Likert scale. The score rating was weighted from 1

to 5. The criteria for assigning scores both positive and negative statements are shown

in Table 3.3.

The self-administered questionnaires were sent via the banking postal delivery

to the bank branch staff to complete. This method is convenient and appropriate for a

57

large number of people because it is simple, time effective, and an economical way of

collecting a large amount of raw data for the purpose of statistical analysis. There was

no problem about the return rate of the questionnaire because the regional managers

were willing to collect the questionnaires. Since this research studies a single

organization, answering in a “nameless” questionnaire, the respondents felt free to

rate each item without any problems; and make sure that the analysis would be

restricted to an aggregated level that would prevent the identification of any

individual or branch unit. All the completed questionnaires had been mailed back to

the researcher via the bank mailing sysem.

Table 3.3 Criteria for Scoring

Statements Least

likely

Less

likely

Not less

and not

much

More

likely

Most

likely

Positive 1 2 3 4 5

Negative 5 4 3 2 1

3.4.2 Scale Construction

From the literature review, it was found that the independent variables in this

area could be designed according to items which represented the content construct.

Krishna and Sharader (1999) indicated that the scale of social capital may have to be

constructed separately for each different context, while instruments can be devised

that will assist in the construction of such a scale among each of these different

contexts.

The items for the scales were developed by extending theorists’ arguments and

drawing on existing questions from previous studies. For example, the social capital

scales were drawn from Nahapiet and Ghoshal (1998), Grannovetter (1973),

Krackhardt (1992) and Fukuyama (1995). The commitment scales were derived from

the Myer, Allen, and Smith’s (1993) affective commitment. The knowledge sharing

scales were deployed from Van den Hooff and Van Weena (2004), Van den Hooff

58

and Hendrix (session D-3). For each set of measure, a starting set of criteria led to the

formation of questions that related to a series of theorized underpinning dimensions.

The scale construct for the independent variables is a subjective measurement.

In this survey, the researcher used negative sentences to minimize the acquiescence

problem (tendency of a respondent to agree with a statement without considering the

content of the item) and extreme response bias. The respondents were forced to

consider the question and hopefully evaluate their degree of either agreement or

disagreement by checking the meaningful answer—one of five response categories for

each item. Ten negative questions completely reversed the scales by transforming and

recoding them into different variables in order to save the raw scores.

3.4.3 Items

Items were derived from previous studies; however, some sentences were

modified in conformity with the Thai context. The respondents were asked questions

in the Thai language. The 51 items were designed to measure the independent

variables in the study. Eight items were designed to measure cognitive social capital,

16 items were created to illuminate the ties strength, which represents structural social

capital. Twelve items were developed to determine relational social capital. Lastly,

and 15 items were depicted to test knowledge sharing.

The tone and mood of a sentence were re-contoured to the bank culture For

example, the item, “I have a very good relationship with my colleagues,” was

identified by expanding it into four questions for describing this sentence. The good

horizontal links in and organization were magnified as follows: I like joining my

colleagues’ wedding party/and other relatives’ wedding parties; I like joining the

Buddhist monk ordination ceremony of my colleagues’ son; When my colleagues get

sick, I present them with a gift basket; and I always join a funeral ceremony out of

respect for the departed person.

According to the literature review, “knowledge” has been defined in general

terms. In a bureaucratic organization, tacit knowledge development is derived from

relationships, social networks, communities of practice, which is completely different

in the working climate. “Knowledge” in the Thai context might be construed in a

different way. The present author I constructed three items related to knowledge

59

sharing as follows: “When the branch manager is furious, we will talk in a whisper,”

“I will tell my colleague who is/are the VIP customer(s)” and “My colleagues will

provide the secret information to me.”

The items were selected and developed in accordance with content validity. To

make sure that the study was able to scientifically answer the question, it is intended

to answer, different people were piloted to comment and make suggestions for

improving the items. Questionnaire was also sent to three institutions—

Chulalongkorn University, University of the Thai Chamber of Commerce, and Sasin

Graduate Institution of Business Administration—in order to modify the items. Then,

the questionnaire designed was pre-tested with the bank staff excluding in the sample

size.

Transition questions were used to make different areas flow well together. To

make the questionnaire clear, easy to follow, and well presented, the 51 items were

grouped by sequential access with part “I,” and then followed with part “colleagues.”

An attempt was made to provide evidence that the bank staff they behaved in practice

in the way that the present author thought that they should.

3.4.4 Quality Assessment

Researchers exploited face validity and reliability to assess the quality of items

constructed.

3.4.5 Face Validity

To assess the quality of items, face validity was utilized. Face validity is the

extent to which the content of the items is consistent with the construct definition,

based solely on the theories and the researcher’s judgment, as explained in the

previous section, as items developed.

3.4.6 Reliability

Reliability is one of the key statistical requirements of quantitative research. It

is common in exploratory study for the survey instrument to be subject to a reliability

examination. Similar to numerous exploratory researches, this study used the

Cronbach Alpha (α) to test the reliability of each measure. The threshold for the

Cronbach alpha is the higher the coefficient alpha, the better. According to

60

Tabachnick and Fidell, (2007) and Hair (2010), the alpha treats any covariance among

items as a true-score variance, even if the items co-vary for spurious reasons. A

commonly-accepted rule of thumb for describing internal consistency using

Cronbrach’s Alpha is as follows: α ≥0.9 = excellent, 0.8> α ≥ 0.9 = good, 0.8> α ≥

0.7 = acceptable, 0.7>α ≥0.6 = questionable and 0.6> α ≥ 0.5 = poor (Cortina, 1993;

Cronbach, 1957; Kline, 1999; Pallant, 2007).

3.5 Variables and Measurements

Operational definition leaded to construct various manifest variables for four

variables. Items were developed to explain the variables. Table 3.4, 3.5 3.6 and 3.7

showed items construct for cognitive social capital, structural social capital, relational

social capital, and knowledge sharing, respectively.

Table 3.4 Items Developed for Cognitive Social Capital

Item Acronym

- I am enthusiastic about pursuing the bank’s vision. VISION

- I propose a super intelligent service method to my branch. METHOD

- I am enthusiastic about pursuing the collective goals. ENTHUS

- I and my colleagues mutually plan to achieve goals. PLAN

- It is boring that my goal is increasing every year (R). INCREASE

- In my branch, we mutually act to attain the goal. GOAL

- Every job is equally important (R). EQUALW

- I use the appropriate tools to support the mission of my branch. MISSION

Regarding to structural social capital, it was developed 2 items to measure

interactions (Chui, Hsu and Wang, 2006; 2 items measured affections, and 2 items

61

developed to determine time spent. This study deployed 8 items to verify structural

social capital.

Table 3.5 Items Developed for Structural Social Capital

Item Acronym

- I dislike joining my colleagues’ wedding party / and other

relatives’ wedding party (R).

MARRY

- I dislike joining the Buddhist monk ordination ceremony of my

colleagues’ son (R).

MONK

- When my colleagues get sick, I present them with a gift basket. SICK

- I always join a funeral ceremony out of respect for the departed

person.

DEAD

- My colleagues believe that I can help them when they face

problems.

DEPEND

- My colleagues want to work with me. COWORK

- I support my colleagues for promotion. GROWTH

- I am very close to my colleagues, like members of their family. FAMILY

- When I face a problem, I have never asked my colleagues for

advice or help (R).

QUIET

- I lend my help / serve my colleagues. SERVICE

- It is a normal thing that colleagues make mistakes. FORGIVE

- I accept my colleagues’ ability. ACCEPT

- I spend my free time assisting my colleagues. SUPPORT

- I spent my free time on the bank activities. HOLIDAY

- I contribute my time to customers. TIME

- I always hold a lengthy of discussion with my colleagues. DISCUSS

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Table 3.6 Items Developed for Relational Social Capital

Item Acronym

- My colleagues are honest. HONEST

- My colleagues help me when I ask them. HELP

- My colleagues always make the job difficult (R). TROUBLE

- My colleagues behave in line with the bank’s ethics. ETHIC

- My bank is secure. SECURE

- My bank is transparent. TRANSPAR

- I propose products and services suited to the customers. PRODUCT

- I compare products with the products of other banks, COMPARE

- I do my work as assigned (R). ONLY

- I really feel as if my bank’s problems are my own. PROBLEM

- I have to be clear when someone complains about the bank. HEAR

- My bank has a great deal of personal meaning for me. GSB

According to Lee and Ahn, 2007; Chow and Chan, (2008), 3 items was used

to define trust. Kwon and Suh (2004) deployed 10 items to measured level of trust and

3 items to measure commitment in supply chain relationships. Romano (2003)

conceptualized and operationalized 10 items to clarify trust. Morgan and Hunt (1994)

exploited 7 items to indicate trust. As well as, Colquitt, Brent A. Scott, and Jeffery A.

LePine (2007) use 6 items to measure ability to trust. The trust construct was

measured with 7 items and 4 items was designed to capture commitment (Garbarino

and Johnson, 1999). With regard to the literature, most researchers utilized 6 items of

Meyer, Allen and Smith’s scale (1993) to measure commitment to organization. This

study deployed 12 items to measure relational social capital.

63

Table 3.7 Items Developed for Knowledge Sharing

Item Acronym

- Whenever I learn something new, everyone tells me about it. NEW

- Shared skills/knowledge/information seems to work added. FLOW

- Shared skills/knowledge/information seems to achieve the goal. ACHIEVE

- It wastes time to share skills/knowledge/information (R). BUSY

- When the branch manager is furious, we talk in a whisper. MOOD

- I share the information I have with colleagues when they ask me

to.

ASK

- I partly share my skills with colleagues when they ask me to (R). N-ALL

- Having had a training course, I am able to provide knowledge to

my colleagues.

TRAIN

- I prefer discussing in the knowledge forum. EXCHANGE

- I will tell my colleagues who are VIP customers. CUSTOMER

- Colleagues share information with you. FRIEND

- I double check when colleagues provide information (R). VALID

- Having had a training course, colleagues provide knowledge to

you.

TEACH

- Colleagues prefer to discuss for improving the work process. IMPROVE

- My colleagues provide the secret information to me. DATA

Wu (2008) deployed 4 items to signify information sharing. Van den Hooff

and van Weenen (2004) developed 6 items for measuring knowledge donating and 8

items for identifying knowledge collecting. Van den Hooff and Hendrix (2004)

distinguished 4 items as eagerness to share knowledge and identify 5 items for

64

willingness to share. Box and Kim (2002) identified 6 items to measure attitude to

share, 5 items to clarify intention to share, and 7 items to signify the behavior to

share. Davenport and Prusak (2000); Hsu, Ju, Yen and Chang (2007) utilized 8 items

to evaluate knowledge sharing behavior. This research developed and utilized 15

items to illustrate knowledge sharing.

3.6 Data Collection and Procedures

The questionnaire developed by the researcher was used to gather the data.

The 1,891 questionnaires were sent to 167 selected branch managers during April,

2013. A letter embedded into a pack of questionnaire introduced the study and the

researcher, and contained the bank approval letter. The assurance of confidentiality

was informed in the letter; as well as contact information of the researcher in case the

respondent had any question about the study. Questionnaires were distributed to each

branch equivalent to numbers of branch staff obtaining data from an internal bank

manpower record. As requested of the researcher, branch manager was asked to

gather questionnaires, and sent back to the researcher via the bank mail. The entire

data collection process was complete during May, 2013. 1,440 questionnaires were

sent back to the researcher.

3.7 Data Analysis Procedures

Data collected from the 1,440 respondents were managed as follow: -

cleansing data, then, averaging value of item in each branch by summing up each item

values divided by number of staff to represent item value of branch. Data were

analyzed with a principal component factor analysis to examine the factorial validity

of the scales.

3.7.1 Construct Validity

This research study examines the reliability and validity of the survey

instruments using a robust approach—the SEM technique. With this technique,

validity and reliability are examined using the Confirmatory Factor Analysis (CFA)

approach. Construct validity is made up of four components: face validity, convergent

validity, discriminant validity, and nomological validity.

65

Convergent validity was utilized when items to measure a common underlying

factor all have relatively high standardized loading on the hypothesized factor (Kline,

2005). Convergent validity is the extent to which the indicators of a specific construct

“converge” or share a high proportion of variance in common. There are three

measure requirements in convergent validity: factor loading, average variance

extracted (AVE), and reliability.

According to Hair et al. (2006), a good standardized loading factor of each

measurement latent variable quantified from the manifest variable should be above

0.5 and preferably 0.7 or higher. All loadings were significant, as required for

convergent validity. The AVE should be 0.5 or higher to suggest adequate convergent

validity. AVE estimates also should be greater than the square of the correlation

between that factor and other factors to provide evidence of discriminant validity.

Lastly, the construct reliability should be .7 or higher to indicate adequate

convergence or internal consistency.

In the formula above λ represents the standardized factor loading of items.

Therefore, for n items, the AVE was computed as the sum of the squared standardized

factor loadings divided by the number of items, as shown above. As mentioned

above, an AVE of .5 or higher indicates adequate convergent validity. An AVE of

less than .5 indicates that on average, there was more error remaining in the items

than there was variance explained by the latent factor structure imposed on the

measure.

The third requirement for the convergent validity was construct reliability

(CR). The CR was computed from the sum of factor loadings (λi), squared for each

construct and the sum of the error variance terms for a construct (δi) using the above

formula. The rule of thumb for a construct reliability estimate is that .7 or higher

suggests good reliability. Reliability between .6 and .7 may be acceptable provided

that other indicators of a model’s construct validity are good. High construct

reliability indicates that internal consistency exists.

nVE

n

ii

1

2

66

Discriminant validity is the extent to which the construct is truly distinct from

other constructs. According to Cambell and Fiske (1959), and Blunch (2008),

discriminant validity is assessed by comparing the AVE of each construct with the

shared variance between constructs. If the average variance extracted estimates should

be greater than the corresponding squared interconstruct correlation estimates (SIC).

If they are, this indicates that the measured variables have more in common with the

construct they are associated with than they do with the other constructs.

Farrell (2010) asserted that discriminant validity establishment is crucial for

conducting a latent variable analysis. Without it, researchers cannot be certain

whether results confirming hypothesized structural paths are real or whether they are a

result of statistical discrepancies. Discriminant validity means that a latent variable is

able to account for more variance in the observed variables associated with it than a)

measurement error or similar external, unmeasured influences; or b) other constructs

within the conceptual framework. If this is not the case, then the validity of the

individual indicators and of the construct is questionable (Fornell and Larcker, 1981).

Nomological validity, developed by Cronbach and Meehl (1955), is a subset

of construct validity. The nomological network includes the theoretical framework

construct for measurement, an empirical framework showing how the constructs can

be measured, and specification of the linkages among these two frameworks. Thus,

the nomological validity is to test the linkage of theoretical realm with the observable

result. To demonstrate the nomological validity in this model, the theoretical

framework construct for measurement is positively and significantly related based on

the social capital and knowledge sharing theories.

The measurement model was assessed to explore the causal relationships

among the association of social capitals, and the mediating of knowledge sharing,

which affect the performance of the organization. The measurement model was used

to test the congruence of the causal relationships from the theoretical assumption and

the empirical data by using the maximum likelihood estimation method run by AMOS

version 21.0. The statistical significance was accepted with an alpha at level 0.05.

n

i

n

iii

n

ii

CR

1 1

2

1

2

)()(

)(

67

Generally, structural equation method can be decomposed of two sub-models:

a measurement model and a structural model. The measurement model defines the

relations between the observed and unobserved variables. It provides a link between

the scores on a measuring instrument and the underlying constructs they are designed

to measure. The measurement model, then, represents the CFA model described in

this study. In contrast, the structural model defines the relations among the

unobserved variables that directly or indirectly influence the changes in the value of

certain other latent variables in the model.

None of the variables in this study was directly observed, called the latent

variables. Latent variables can be examined and measured by using a set of observed

items measuring behaviors, also called manifest variables. Associated with each

observed variable is an error term, and with the factor being predicted, a residual

term; there is an important distinction between the two. Error is relevant to observed

variables depicting that measurement are imperfect indicator of such a concept.

Measurement error derives from two sources: random measurement error and error

uniqueness. Residual terms represent error in the prediction of endogenous factors

from exogenous factors. Both measurement and residual error terms represent

unobserved variables. Unlike those associated with most other SEM programs, Amos

path diagrams provide these error variables as circle enclosures by default.

Figure 3.1 Relationships between Latent and Manifest Variables

3.7.2 Structural Equation Modeling (SEM)

Structural equation modeling was used to test the cause and effect relationship

among the main constructs of the hypothesized model. Structural equation modeling

can be either a regression analysis with a factor analysis or a path analysis with a

factor analysis. The SEM provides a family of related statistical techniques (Kline,

68

2005). In this study, the model consists of two parts: the structural model and the

measurement model. The structural model describes the causal connections among the

latent variables. The mapping of these connections was the main purpose of the

analysis. The measurement model describes the connections between the latent

variables and their manifest indicators (Blunch, 2008).

Amos 21.0 was deployed for evaluating the research model and the hypotheses

proposed. It is important to examine the “fit” of an estimated model to determine how

well it models the data. For the assessment of the fit for the hypotheses, the study used

the overall fit measures.

Table 3.8 Indices for Model Assessment

Indices Assessment Criteria

Name Abbreviator

Chi-square fit

index

- Also called discrepancy or

model Chi-square

- How it quantifies the

differences between the

observed and the estimated

covariance matrix

- Very sensitive to a larger

sample size

p value: >.05: acceptable

Relative chi-

square

CMIN/DF - Also called normal or

normed Chi-square

- This is the chi-square fit

index divided by degrees of

freedom.

- Less dependent on sample

size

<2: good fit (Ullman, 2001);

<3: adequate fit (Kline, 2005);

<5: cutoff (Schumacker &

Lomax, 2004).

Goodness of

Fit index

GIF - Sample based, analogous

to R2

= 1.0 perfect fit;

>.95: good fit;

>.90: adequate fit;.(Kline,

2005)

69

Table 3.8 (Continued)

Indices Assessment Criteria

Name Abbreviator

Comparative

fit

index

CFI

CFI - The degree of fit between

the hypothesized and null

measurement models

- The least dependent on

sample size

>.95: good fit;

>.90: adequate fit; (Bentler,

1990; Bentler & Bonett,1980)

Tucker Lewis

Index or

Nonnormed

fit index

TLI or NNFI - A relative fit index that

compares the model being

tested to a baseline model

(null model), taking into

account the

degree of freedom

- Relatively independent on

sample size

>.95: good fit;

>.90: adequate fit; (Tucker &

Lewis, 1973)

Root mean

square

error of

approximation

RMSEA - How well a model fits a

population square

error of not just the sample

used for estimation

- Less dependent on sample

size

<.05: good fit;

<.08: adequate fit

<.10: cutoff; (Browne &

Cudeck, 1993)

3.8 Conclusion

This chapter restated the proposed model and provided information for data

collection. The survey instrument was used to achieve the research objectives by

using questionnaire developed and constructed from various literatures. Krishna

(2007) cites that social capital, like gross national product, is a theoretical construct. It

cannot be measured directly but must be assessed instead in terms of its elemental

components. The elements of social capital are mostly not directly observable. People

carry inside their heads the experiences and expectations that make them behave in

certain ways. The proxy measure of social capital in one social setting will not clear

when similarly observed within other settings.

70

The respondents are the bank branch staff working in the Bangkok

metropolitan area, Region 6 and 12 in Thailand. However, the unit of analysis is

branch level. The dependent variable is the scale rating for each branch, resulting

from the branch’s KPI. The 51 items as independent variables were developed from

previous studies and test-retested to make sure that the scales construct was valid and

reliable. The structural equation model by using Amos Program version 21 was

deployed for depicting, hypothesizing, developing, and measuring the goodness of fit.

Finally, statistically fit indices were chosen to assess the SEM fit with the data. The

results are presented in the next chapter.

The rest of the paper is comprised of chapter 4 and 5. Chapter 4 explores

quantitatively, at the branch level, the influence of social capital and knowledge

sharing on the bank’s performance. Chapter 5 draws out the implications of the

findings and assesses the utility of the social capital concept and knowledge sharing in

studying Thai contexts. 

 

71  

CHAPTER 4

FINDINGS

The primary objective of the study was to examine the relationships among

social capital, knowledge sharing, and performance in the Government Savings Bank

of Thailand. The structural equation model was used to test the theories. Therefore,

this chapter reports the research results of the statistical data analysis proposed in

chapter 3. The research questions guided the achievement of the purpose of this study.

This chapter is divided into three sections:

4.1 The Measurement Model

4.2 The Structural Model: Influence of Social Capital and Knowledge Sharing

on the Performance Model

4.3 The Revised Model

4.1 The Measurement Model

4.1.1 Exploratory Factor Analysis (EFA)

The model generation started with exploratory factor analysis, then, followed

by a confirmatory analysis to test the measurement model. Exploratory factor analysis

is classical technique for mapping the dimensionality of a data set. The initial items

included 51 indicators proposed for the four construct factors. A principal component

factor analysis utilized varimax rotation extracted. The results showed that the KMO

measure of sampling adequacy was met with a value of .86, and the Bartlett’s Test of

Sphericity was significant at the .00 level, indicating that the correlations among the

survey items were significant and the strengths of the relationships among the

variables were appropriate for interpretation. An EFA included the remaining 16

variables which resulted in four factors with eigenvalues over 1.0 explaining 51.29%

of the total variance. Eigenvalues ranged from 14.29 to 2.35 for all factors extracted.

The factor loading ranged from .69 to .91. Factor 1, 2, 3, and 4 were named as

 

72

cognitive, relational, structural, and k-sharing, respectively, in accordance with the

extraction. 35 items were removed from the result of factor analysis.

Table 4.1 EFA of Questionnaire Variables

Component Factor1: Cognitive

Factor2: Relational

Factor3: Structural

Factor4: Ksharing

VISION .84 .03 .05 .03 GOAL .82 .15 .08 .02 ENTHUS .82 .07 .04 .25 PLAN .81 .16 .03 .04 METHOD .81 .11 .04 .27 FAMILY .75 .03 .91 .21 DEPEND .75 .01 .80 .11 FORGIVE .74 .09 .79 .06 SUPPORT .71 .08 .79 .05 HONEST .30 .09 .05 .78 ETHIC .36 .09 .05 .76 TRANSPAR .34 .04 .10 .75 MOOD .15 .75 .06 .04 ASK .20 .71 .12 .22 TRAIN .23 .70 .02 .05 FRIEND .08 .69 .04 .05 Eigenvalues % of variance

14.29 29.17

5.78 11.80

2.72 5.54

2.35 4.79

4.1.2 Item Reliability Analysis

In the scale construct process, the questionnaire was reviewed based on the

theoretical framework and the guidance of the experts from various universities. The

questionnaire initially included 51 items; after testing with EFA, the variables were

eliminated to 16 indicators. The four factors extracted were tested as individual scales

to measure the extent to which multiple indicators represented the constructs.

Cronbach’s reliability alpha was calculated to assess the internal consistency for all

scales. The result showed alpha range from .75 to .96 presented in Table 4.2. The

alpha on standardized items for all scales met the minimum level of acceptability.

73

Table 4.2 Cronbach’s Alpha

Cronbach's Alpha Meaning

OVERALL .96 Excellent

COGNITIVE SOCIAL CAPITAL .94 VISION .93 Excellent METHOD .91 Excellent ENTHUS .91 Excellent PLAN .91 Excellent GOAL .93 Excellent STRUCTURAL SOCIAL CAPITAL .92 FAMILY .89 Very good DEPEND .90 Excellent FORGIVE .88 Very good SUPPORT .91 Excellent RELATIONAL SOCIAL CAPITAL .87 HONEST .87 Very good ETHIC .75 Adequate TRANSPAR .83 Very good

K SHARING .90 MOOD .88 Very good ASK .86 Very good TRAIN .84 Very good FRIEND .85 Very good

A total of 17 items correlation table with mean and standard deviations was

shown in Table 4.3. The 17 items were significant correlated with each other. All

correlations were greater than .50 at the level of .01 (two tailed, N = 167).

78

Table 4.3 Items Correlations for CFA and SEM Analysis

Observed variables 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 1.ENTHUS 1 2.METHOD .75** 1 3.VISION .75** .85** 1 4.PLAN .68** .83** .86** 1 5.GOAL .65** .67** .75** .74** 1 6.FAMILY .62** .66** .71** .68** .78** 1 7.DEPEND .65** .67** .70** .67** .68** .76** 1 8.FORGIVE .64** .63** .68** .62** .68** .82** .76** 1 9.SUPPORT .61** .68** .70** .63** .65** .73** .69** .73** 1 10.HONEST .70** .67** .68** .62** .65** .62** .60** .64** .67** 1 11.ETHIC .64** .66** .73** .65** .74** .68** .66** .66** .69** .70** 1 12.TRANSPAR .59** .63** .65** .61** .65** .62** .62** .63** .69** .60** .76** 1 13.MOOD .62** .58** .63** .62** .64** .68** .68** .64** .67** .59** .70** .62** 1 14.ASK .55** .59** .59** .57** .55** .61** .51** .61** .61** .55** .57** .56** .62** 1 . 15.TRAIN .55** .59** .66** .64** .59** .63** .57** .62** .61** .59** .62** .61** .67** .71** 1 16.FRIEND .60** .65** .71** .74** .68** .65** .62** .60** .62** .55** .67** .61** .71** .69** .74** 1 17.PERFORM .75** .78** .82** .78** .79** .78** .75** .77** .77** .75** .79** .73** .72** .67** .71** .78** 1 Mean 4.35 4.51 4.48 4.49 4.43 4.33 4.37 4.39 4.23 4.24 4.20 4.15 4.24 4.30 4.35 4.33 4.01S.D. .27 .27 .26 .26 .31 .34 .26 .31 .31 .31 .30 .31 .34 .28 .25 .22 .48 Note: ** Correlation is significant at the 0.01 level (2 tailed) N=167

74  

75  

4.1.3 Confirmatory Factor Analysis (CFA)

The factors extracted as a result of the EFA provided evidence to identified

and assess the proposed model. A CFA was further utilized to test the measurement

models for each study construct, before examining the structural model. According to

the different hypothesized models, the confirmatory factor analysis model was used

individually to estimate the relationship between each the latent variable and related

items. The measurement-testing model focused on the linear functions between the

latent variables and their observed indicators in the model. Four measurement sub-

models—(1) cognitive social capital, (2) structural social capital, (3) relational social

capital, and (4) knowledge sharing, were examined by using the Amos 21.0 software

program.

The four CFA solutions were derived from the validated data on 167 branches.

According to the rule of overall fit measures, p-value must be greater than 0.05; the

CMIN/DF should not be greater than 3.0; the GFI, CFI, and TLI must be greater than

0.9; and the RMSEA should be less than 0.08.

The five constructs were allowed to co-vary freely in the CFA model. Model

estimation was done using the maximum likelihood approach, with the item

correlation matrix as input. Table 4.4 presents the summary of measurement scales.

The assessment of the measurement model of the five factors is presented in Figure

4.1.

76

Table 4.4 Summary of Measurement Scales

Construct Measure Loading

VISION I am enthusiastic about pursuing the bank’s vision. .94

METHOD I have proposed a super intelligent service method to my branch.

.90

ENTHUS I am enthusiastic about pursuing collective goals. .81 PLAN My colleagues and I together plan to achieve goals. .90 GOAL In my branch, we mutually act to attain goals. .82 FAMILY I am very close to my colleagues as though I were a

member of their family. .90

DEPEND My colleagues believe that I can help them when they face problems.

.85

FORGIVE It is normal for colleagues to make mistakes. .89 SUPPORT I spend my free time assisting my colleagues. .84

HONEST My colleagues are honest. .80 ETHIC My colleagues behave in line with the bank’s ethics. .89 TRANSPAR My bank policies are transparent. .82 MOOD I share the information I have with my colleagues when

they ask me to. .82

ASK I share the information I have with my colleagues when they ask me to.

.79

TRAIN Having had a training course, I provide knowledge to my colleagues.

.84

FRIEND Colleagues share information with you. .88 PERFORM Percentage of performance success compare to goals. 1.00

77

Figure 4.1 The Measurement Model

78

The measurement models depicted the relationships among the independent

variables based on their CFA structure models. The measurement model resulted in

acceptable fit indices to the data shown in Table 4.5.

Table 4.5 Statistical Fits in the Measurement Model

MODEL P value CMIN/DF GFI CFI TLI RMSEA

0.00 2.06 .90 .96 .95 .08

Additionally, the convergent validity of the scales was verified by using three

criteria by Fornell and Larcker (1981): 1) all factor loadings should be significant at

0.5, and ideally 0.7 or higher; 2) the average variance extracted (AVE) by each

construct should exceed the variance due to measurement error for that construct and

should exceed 0.5, and 3) construct reliability between .6 and .7 may be acceptable

provided that the indicators of a model’s construct validity are good. For the current

measurement model, all loadings were above the 0.7 threshold (see Table 4.6). The

AVE ranged from .69 to 1.00. The composite reliabilities of the constructs ranged

from .73 to .79. Hence, all three conditions for convergent validity were met. Table

4.6 shows correlations and AVE.

Table 4.6 Correlations and AVE

Construct AVE CR Squared Inter-construct Correlation

(SIC=IC*IC)

COGNI STRUCT RELAT KSHARE PERFORM

COGNITIVE 0.77 0.79 0.77

STRUCTURAL 0.76 0.78 0.74 0.76

RALATIONAL 0.70 0.74 0.22 0.23 0.70

K-SHARING 0.69 0.73 0.07 0.09 0.13 0.69 0.03

PERFORMANCE 1.00 0.07 0.05 0.11 0.03 1.00

79

Further, the discriminant validity of the scales was assessed using the

guideline suggested by Kline (2005): the corresponding squared inter-construct

correlation estimates (SIC) should be less than the construct average variance

extracted (AVE). If they are, this indicates the measured variables have more in

common with the construct they are associated with than they do with other

constructs. AVE estimates in the Table 4.6 are larger than the corresponding squared

inter-construct correlation estimates. Hence, the test of discriminant validity was

acceptable. This study concluded that the scales have sufficient construct validity.

Finally, the nomological validity was tested by examining whether the

correlations between the constructs in the measurement model made sense. The

construct correlations were used to assess this. Two indicators were used to

demonstrate the nomological validity: the construct had to be positively related based

on the theories reviewed, and the construct model all correlations had to be positive

and significant. In this model, the correlations were significant at the level 0.001,

which met the requirement.

4.2 The Structural Model: Influence of Social Capital and Knowledge

Sharing on Organizational Performance

Building on the results of the measurement modeling illustrated in the

previous section, this section contains a series of structural models which test the

theoretical arguments laid out in the chapter 2 and illustrated in chapter 3. This cross-

sectional evaluation allows an investigation of the relationships among cognitive

social capital, structural social capital, relational social capital, knowledge sharing,

and performance. Since the measurement models were supported through the good fit

indices, the structure models for this study were then used to investigate the

relationships among the variables.

The structural model reflecting the assumed linear, causal relationships among

the constructs was tested with the data collected from the validated measures. The

model fit indices were within the accepted thresholds: CMIN/DF =2.06, GFI= .90,

CFI= .96, TLA = .95 and RMSEA= .08.   

80

             

Figure 4.2 Structural Model Results

The resulted SEM model from Amos 21.0 was described graphically in Figure

4.2. The model analysis was conducted to determine the causal effects among the

variables of cognitive social capital, structural social capital, relational social capital,

knowledge sharing, and performance. Figure 4.2 showed the results of model tests.

The software provided statistical results in the figure: factor loadings of manifest

variables in each latent variable, the explanatory power of the research model and the

percentage of explained variance in the endogenous latent variables, and the path

coefficient values. The result showed that all manifest variables were highly

correlated to the latent variables indicating that all factors are well constructed. All

paths exhibited strong positive and significant effect on performance. In addition, the

explanatory power of the research model was very high indicating that the hypotheses

were able to effectively explain or greater predictive power.

The fitted model was simplified to illustrate the level of significant of path

coefficient. As shown in Figure 4.3, all path coefficients were significantly at the level

of .001, .01, and .05 (*** p<.001, ** p<.01, * p<.05,). In terms of the relationships

among factors, the results showed that all factors were positive associations with

organizational performance; all hypotheses were supported.

81

Cognitive social capital as the sole exogenous variable directly and/or

indirectly influenced the four endogenous variables: structural social capital,

relational social capital, knowledge sharing, and their roles in promoting the

performance level. Structural social capital had significantly positive impact on

relational social capital, knowledge sharing, and performance. Similarly, relational

social capital showed strong positive effect on knowledge sharing and performance.

Knowledge sharing exhibited positive and significant path to performance as well.

The explanatory power is also account for high percentage of variance of the

model. The SEM model explained approximately 87 percent of variance in

performance. Approximately, R-square values showed 79, 83, and 74 percent of

variance in knowledge sharing, relational social capital, and structural social capital

were explained by the model.

               

Figure 4.3 Simplified Results Model (n = 167)

Table 4.7 illustrates the Squared Multiple Correlations of the structural model.

The coefficient of the multiple correlations takes values between zero and one; a

higher value indicates better predictability of the dependent variable from the

independent variables. The result showed that the squared multiple correlation of the

performance was .87, whereas the squared multiple correlation of the structural social

capital was at a valued of .74, relational social capital .83, and knowledge sharing at .79.

82

Table 4.7 Squared Multiple Correlations of the Model

Estimate

STRUCTURAL .74

RELATIONAL .83

KSHARE .79

PERFORMANCE .87

Table 4.8 Standardized Regression Weights of the Structural Model

Parameter

Estimate Standardized

Estimate S.E. C.R.

COGNITIVE STRUCTURAL 1.04 .86*** .08 11.99

COGNITIVE RELATIONAL .47 .47*** .11 4.18

STRUCTURAL RELATIONAL .40 .48*** .10 4.20

COGNITIVE KSHARE .30 .27* .14 2.07

RELATIONAL KSHARE .39 .36* .17 2.25

STRUCTURAL KSHARE .28 .30* .12 2.23

COGNITIVE PERFORMANCE .49 .26** .17 2.91

KSHARE PERFORMANCE .31 .18* .15 2.02

RELATIONAL PERFORMANCE .62 .33** .22 2.82

STRUCTURAL PERFORMANCE .35 .22* .15 2.34

Note: * p<.05, ** p<.01, *** p<.001

The estimate and the standardized regression coefficients were explained in

order to determine the validity of the hypothesized paths. The statistical significance

of all structural parameter estimates are illustrated in Figure 4.2, and shown in Table

4.7. Standardized estimates are used when comparing direct effects on a given

endogenous variable in a single group study. Table 4.8 shows that the critical ratio

(CR) value is greater than 1.96 for a regression weight, and that the path was

83

significant at the .05 level or better. In the standardized estimate column, three

asterisks (***) indicate a significance smaller than .001; two asterisks indicate

significance at the level of .01. All paths in the hypothesized model are significant at

the level of .001, .01, and .05, accordingly.

The predictors of cognitive social capital showed a significant amount of

variance in the full structural model; the path flowing from cognitive social capital to

structural social capital (standardized estimate .86, C.R.= 11.99, p=.001); the path

flowing from cognitive to relational social capital(standardized estimate .47, C.R. =

4.18, p =.001); the path flowing from cognitive social capital to knowledge sharing

(standardized estimate .27, C.R.= 2.07, p=.05); and the path flowing from the

cognitive social capital to performance (standardized estimate .26, C.R.= 2.91, p=.01).

Similarly, the path flowing from structural social capital to relational social

capital (standardized estimate .48, C.R. = 4.20, p=.001); the path flowing from

structural social capital to knowledge sharing (standardized estimate .30, C.R. = 2.23,

p=.05); and the path flowing from structural social capital to performance

(standardized estimate .22, C.R. = 2.34, p=.05) were significant.

As well as, the path flowing from relational social capital to knowledge

sharing (standardized estimate .36, C.R. = 2.25, p=.05); and the path flowing from

relational social capital to performance (standardized estimate .33, C.R. = 2.82, p=.01)

were significant. Finally, the path flowing from knowledge sharing to performance

was significant at the level of .05; the standardized estimate = .18, C.R. = 2.02.

Table 4.9 Standardized Effects to Performance

EFFECT ON PERFORMANCE

DIRECT INDIRECT TOTAL

COGNITIVE 0.26 0.63 0.89

STRUCTURAL 0.22 0.24 0.46

RELATIONAL 0.33 0.06 0.39

K-SHARING 0.18 0.00 0.18

84

Several causal relationships between factors were found to be significant.

Amos 21.0 analyzed both the direct, indirect, and total effects to explain how the

exogenous variable influenced the endogenous variables. Additionally, latent

variables are a hypothetical construct derived from other observed indicators in a

causal full model. The analyses of the direct, indirect, and total effects are presented

in Table 4.9. For instance, the cognitive social capital had the strongest total effect on

performance value at .89, whereas the other factors—structural social capital,

relational social capital, and knowledge sharing totally affected performance at .46,

.39, and .18, respectively.

The path coefficients in Table 4.9 indicate that relational social capital, with

the strongest direct effect, had a significant influence on performance at 0.33, whereas

cognitive social capital, structural social capital, and knowledge sharing had a direct

effect on performance at 0.26, 0.22, and 0.18, respectively.

In addition, the path diagram was decomposed the associations among several

factors in the model to explain the magnitude of the indirect effects. The magnitude of

the indirect effects was determined by taking the product of the path coefficients

along the path way between the causally related variables. Table 4.10 showed the

magnitude of indirect effect between cognitive social capital, structural social capital,

and relational social capital were estimated by multiplying the path coefficient from

one factor through its effect on the other.

The results also indicate that the cognitive social capital affects organizational

performance directly and indirectly via its direct effect on structural, relational, and

knowledge sharing. The indirect effect of cognitive social capital was .63, which was

greater than the direct effect (.26). The indirect routes were generated into 7 paths.

The indirect path from cognitive-structural-performance was the highest value

weighted .19 to .63, indicating that this path was contributed 30% to the total indirect

effect. The results also showed that the association of the three types of social capital

that was caused from cognitive social capital effect on performance was 76%. The

relationships of the linkages of social capital indirectly via knowledge sharing can be

boosted 24%.

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Table 4.10 Indirect Effect Path

Indirect Path effect %

Cognitive to Performance 0.63

cognitive=.86 struct =.22 perform 0.19 30

cognitive=.47 rela =.33 perform 0.16 25

cognitive=.27 kshare=.18 perform 0.05 8

cognitive=.86 struct =.48 rela = .33 perform 0.13 21

cognitive=.86 struct =.30 kshare=.18 perform 0.05 8

cognitive=.47 rela =.36 kshare=.18 perform 0.03 5

cognitive=.86 struct =.48 rela = .36 kshare = .18 perform 0.02 3

Structural to Performance 0.24

struct=.48 rela =.33 perform 0.16 66

struct=.30 kshare=.18 perform 0.05 22

struct=.48 rela =.33 kshare=.18 perform 0.03 12

Relational to Performance 0.06

rela= .36 kshare=.08 perform 0.06

A model was hypothesis that organizational performance is directly affected

by structural social capital, and directly via its direct effect on relational social capita,

and knowledge sharing. The results also indicated that the indirect effect of structural

social capital was .24, which was greater than the direct effect (.22). The indirect

routes were generated into 3 paths. The indirect path from structural–relational–-

performance was the highest value weighted .16 to .24, indicating that this path was

contributed 66% to the total indirect effect. The relationships between structural social

capital and relational social capital indirectly via knowledge sharing boosted 34% to

organizational performance.

It was also hypothesis that organizational performance is directly affected by

relational social capital, and indirectly via its direct effect on knowledge sharing. One

indirect route was calculated via its direct effect on knowledge sharing. The results

also revealed that the indirect effect of relational social capital was .06, which was

less than the direct effect (.33).

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4.3 The Revised Model

The process of scale construction was designed with 8 items to determine the

cognitive social capital. Similarly, structural social capital, relational social capital,

and knowledge sharing were assembled into 16, 12, and 15 items, respectively. The

exploratory factor analysis was used to extract the initial indicators. The rotated

component correlation matrix indicated that the compositions of the factors are

distinct and independent from each other. Therefore, 51 items were modified through

the SEM instruments; the final CFA models showed a good fit with the collected data.

The items were then reduced from 51 to 17. The remaining items were shown in

Table 4.11. The factors extracted as a result of the EFA verified data for a reasonable

model to be identified and tested with the confirmatory method. The four latent

factors identified through the EFA were reflected in the final model.

Table 4.11 Remaining Items

Construct Measure Acronym

Cognitive I am enthusiastic about pursuing the bank’s vision. VISION

I have proposed a super intelligent service method to

my branch.

METHOD

I am enthusiastic about pursuing collective goals. ENTHUS

My colleagues and I together plan to achieve goals. PLAN

In my branch, we mutually act to attain goals. GOAL

Structural I am very close to my colleagues as though I were a

member of their family.

FAMILY

My colleagues believe that I can help them when

they face problems.

DEPEND

It is normal for colleagues to make mistakes. FORGIVE

I spend my free time assisting my colleagues. SUPPORT

Relational My colleagues are honest. HONEST

My colleagues behave in line with the bank’s ethics. ETHIC

My bank policies are transparent. TRANSPAR

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Table 4.11 (Continued)

Construct Measure Acronym

K-sharing I share the information I have with my colleagues

when they ask me to.

MOOD

I share the information I have with my colleagues

when they ask me to.

ASK

Having had a training course, I provide knowledge to

my colleagues.

TRAIN

Colleagues share information with you. FRIEND

A confirmatory factor analysis technique was next provided assistance in

refining the measurement models for each factor constructed. The measurement

model was depicted to test the statistical requirement fit indices. Collected data from

167 bank branches which employed 1,440 respondents were tested. The fit of this

measurement model was good enough, showing fit with the collected data. The

regression weight for the structural model demonstrated statistically-significant strong

relationships between the independent variables and the dependent variable.

According to the path diagram in the hypothesized model, the standardize

regression weight estimate revealed that there were positive relationships among the

variables. This research study spotlights one organization—the Government Savings

Bank. The intention of this study was to observe an association with reference to three

types of social capital, which can develop knowledge sharing; and all of them

influenced on the organizational performance. Based on the results of the collected

data analysis with Amos 21.0, the findings were recapitulated to respond to the

objective of the research. The statistical outputs and research results were consistent

with previous researches and the literatures, as mentioned in the preceding chapters.

This study hypothesized that cognitive social capital is the most important

exogenous variable as the causal factor of the hypothesized model. The cognitive

social capital bonds to structural and relational social capitals. Based on the cognitive

model, self-efficacy contributes autonomously to and enhances organizational

performance. Cognitive social capital stimulates team members to engage in a

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network. Within a social network, employees share familiar standpoint, shared views,

or appreciated the nature of the connections between the individuals in an

organization. Interaction within a network can also help exchange information

informally. Cooperation derives from members sharing similar interpretative

frameworks, elucidating the importance of the cognitive dimension of social capital.

The findings showed that cognitive social capital contributes to the creation,

development, and maintenance of social relation. It is also important to note that

cognitive social capital strengthens the member network and facilitates the creation

and transfer of tacit knowledge. The breadth of the cognitive social capital influences

not only knowledge sharing but also enhances organizational performance.

The estimates of the standardized regression weight from cognitive social

capital to other factors were significant high. The results considerably support the

cognitive social capital theory; that is. “…when people believe, they are motivated to

build their social network more in tune with their own values and the kinds of

relationships that they engage” (Bandura, 1986). The findings herein are consistent

with the extant literature reviews.

This study attempted to investigate cognitive social capital as the cause and

link with the other types of social capital. The finding provides additional support for

cognitive social capital as rooted in the mental processes among thought and resulting

ideas, and reinforced by the norms, attitudes and beliefs that contribute to structural

network ties with cooperative behavior and mutually beneficial collective action. The

findings support Krishna and Uphoff’s (2002) proposition that is cognitive social

capital caused and linked other types of social capital. At the same time, the research

results also support Tsai and Ghoshal’s finding that is strong social interaction

(structural) is not a prerequisite for creating a shared vision (cognitive).

The next hypothesized path model showed that structural social capital (social

strong ties) reinforced personal relationship and behavior such as trust, and

commitment. Strong social ties reduce the transaction costs (Blau, 1968) associated

with a business relationship, reducing the uncertainty about economic performance

outcomes. Communication amongst members in organization increase trust and

develops cooperation. It also provides a flow of value information or knowledge to

the organization’s members to behave proactively and innovatively for the firms. The

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flow of knowledge sharing can leverage the improvement of organizational growth

and overall firm performance.

The initially-hypothesized structural model was examined to test the

hypotheses proposed. The three paths of the structural social capital were supported

on the results of the standardized regression coefficients, standardized efforts, and the

critical ratio. The path diagram from structural social capital to relational social

capital, structural social capital to knowledge sharing, and structural social capital to

performance demonstrated the estimates standardized regression weight a statistically-

significantly positive level of .001, .01, and .05, respectively. The standardized

estimations of these path diagrams were measured at .48, .30, and .22. The estimate of

squared multiple correlations values .74. The statistical results also significant

supported structural social capital; that is, “…closure networks are powerful because

close contact among members facilitates monitoring and enforcement of common

expectations and norms which can reduce the transaction cost (Coleman, 1982; Blau,

1964; 1968).” The results indicated that the structural social capital stimulate trust and

trustworthiness (Tsai and Ghoshal, 1998) which characterize relational social capital.

The findings confirm that members in the network interact more frequently; their

trusting and committing relationships will be converted into knowledge sharing, and

performance. Literatures on ties strength put in the picture of strong ties interactions

allow actors to know another to share important information, and create a common

point of view to enhance the performance (Krackhardt, 1992; Nelson, 1989). The

findings showed that strong ties had a significant, positive effect on relational social

capital, knowledge sharing, and performance; the results also supported Tsai and

Ghoshal’s model.

Prior studies have consistently found that knowledge sharing is positively

related to strong ties (Wellman and Wortley, 1990; Tsai and Ghoshal 1998) found that

social interaction ties had a strong effect on trust in the context of resource exchange

and production innovation within the organization. Additionally, Chui, Hsu, and

Wang (2006) found that strong social ties had indirect effects on knowledge quality

via trust.

Subsequently, it was as well hypothesized that higher relational social capital

enhances the willingness to share knowledge in organization, reduces cost and

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improves performance. The knowledge sharing attitude and behavior may emerge

when relational social capital exists. The conditions of relational social capital carry

on economic performance. Relations high in trust and members committed to the

organization imply more efficiency in the organization. Trust facilitates social and

resource exchange, increases communication, and enhances cooperation between

individuals. High levels of trust ultimately increase knowledge sharing and enhance

teamwork. When members act at a higher level of interpersonal relationships, the time

and effort for acquiring information are reached quickly as members more readily

share information and knowledge to enhance their performance. Interpersonal

interactions are also a key component of group cohesiveness, which tends to

contribute to group performance.

The research findings showed that relational social capital was a statistically

significant relationship, positive effect on knowledge sharing and performance. The

two paths of the relational model were also supported on the results of the

standardized regression coefficients, standardized efforts, and the critical ratio. The

statistical outputs showed that the estimates standardized regression weight from

relational social capital to knowledge sharing and performance were at a statistically

positive level of .01 and .05. The paths flowing from relational social capital to

knowledge sharing and performance were .36 and .33, consecutively. The estimate of

squared multiple correlations values was .83. The results indicated that relational

social capital influenced knowledge sharing and performance. The findings had

consistently found to Li and Zhu, 2009; Khan et al., 2011; Matzler, Renzl, Mooradian,

Krogh, and Mueller, 2011; Tsai and Ghoshal 1998; Wu, 2007).

Furthermore, the Amos outputs also showed that relational social capital had

the strongest direct effect on performance; the direct path value was .33, whereas the

direct effect of cognitive social capital, structural social capital, and knowledge

sharing on performance were .26, .22, and .18, respectively. Thus, the findings

supported the hypothesized path models. The corresponding results also supported

previous scholars (Li and Zhu, 2009; Tsai and Ghoshal 1998; Wu, 2007), indicating

that relational social capital especially trust each other and trust in organization

enhances knowledge sharing and organizational performance because it lubricates the

social machinery of the organization that makes the organization function.

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The last hypothesis was that the sharing of operational knowledge improves

organizational performance. An appropriate knowledge is shared amongst members

and effectively utilized can be enhance organizational efficiency. Information flows

create organizational advantage by enhancing the capacity to absorb, assimilate, and

transfer ideas which enhance its strategic assets and facilitate processes that enable the

organization to behave proactively and innovatively. Subsequently, it was presumed

that the relationships between knowledge sharing and organizational performance are

positively linear.

The initially-hypothesized path model of knowledge sharing was examined to

test. One path was supported based on the results of the standardized regression

coefficient at .18, with standard effort = .15, and the critical ratio = 2.02. There was a

positive statistically-significant causal relationship between knowledge sharing and

performance.

Hence, as supported by the findings herein, the sharing and transfer of tacit

and explicit wisdom of individuals and groups within an organization can increase

organizational performance. Consistent with previous research (Wilson and Spoehr,

2010), the research results supported the idea that the sharing of knowledge within an

organization really improves organizational performance. The findings provided

additional support that the three types of social capital contributes to knowledge

sharing and that knowledge sharing is also one of the key benefits of organizational

performance.

Additionally, the Amos output indicated that the standardized total effect of

organizational performance depends on cognitive social capital, structural social

capital, relational social capital, and knowledge sharing. The total effects on

performance value were .89, .46, .39, and .18, accordingly. The research findings

supported the research questions. The total effect of each construct was boosted by the

indirect effect, considerably. According to the analysis of the diagram path, cognitive

social capital had the strongest effect on performance. It is also important to note that

the direct effect of cognitive social capital on performance was .26, whereas the

power of the indirect paths was stronger than the previous path, especially when

passing through knowledge sharing (power = .15).

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The research findings showed structural social capital had the second strongest

effect on performance. The findings revealed that the direct and indirect paths were

likely to be equal to the effect on performance. Additionally, the relational social

capital had the strongest direct effect on performance, whereas its indirect effect was

.06. Finally, knowledge sharing was less power in relation to the performance, as its

direct effect was only .18.

As described earlier, the linkages of the three types of social capital and

knowledge sharing were found to predict successful organizational performance. The

study examine the relationship among the three types of social capital and showed

how each of them contributed to knowledge sharing and organizational performance.

The model supported here suggests that enhancing cognitive social capital may lead to

higher levels of organizational performance. Cognitive social capital was the cause of

the other two types of social capital and they were closely associated together.

Cognitive social capital as an exogenous latent variable exercised positive effects on

structural social capital, relational social capital, knowledge sharing, and increased

organizational performance. The findings also provided a clear picture of the role of

structural social capital by showing how strong ties has significant, directly and

indirectly, accumulated and reinforced to relational social capital, knowledge sharing,

and organizational performance. The finding provided strong support for the

argument that relational social capital facilitates knowledge sharing, and

organizational performance; and this finding was robust at the branch unit levels. The

analysis suggested that the organization should be concerned about the creation of

cognitive social capital as the antecedent of organizational performance.

The next chapter provides the conclusion, limitations, implications, and

recommendations of the study.

 

 

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CHAPTER 5

CONCLUSION

The previous chapter provided an overview of the analytical models,

indicating the effect of the linkages of the three types of social capital and knowledge

sharing on organizational performance. In this chapter, the model as hypothesized is

discussed based on the organizational theories. After discussing the findings and

addressing possible implications, recommendations for future research, contributions,

limitations, and the chapter conclusion are presented. The construction of this chapter

is organized as follows:

5.1 Discussion

5.2 Implications

5.3 Recommendation for Future Research

5.4 Contributions

5.5 Limitations

5.6 Conclusion

5.1 Discussion

In Chapter 1, it was asked, “What makes the organization efficient?”

Definitely, different disciplines have different perspectives. Even in organization

theory, theorists have different criteria leading to conclusions as to what makes the

organization effective. In fact, organizations are indeed the products of individual

human actions. Humans in social networks are the key factor in the creation of the

quality of organizational life; their unique resources create value for the organization,

and according to the resource-based view (Barney, 1991), such unique resources are

central to the organization’s competitive advantage. This study integrates social

capital and knowledge sharing as organizational resources and capabilities into the

research model.

 

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For this reason, it was realized by the present author that social capital is one

of the organizational resources that can be used to achieve sustainable competitive

advantage, as social capital has been viewed as an essential asset for the

organization’s success. The linkages of the three types of social capital are

conceptualized in terms of having the capability of increasing knowledge sharing,

which in turn influences organizational performance.

This research study has examined the bank branches of the Government

Savings Bank; the sample size was 167 branches located in Bangkok and rural areas,

as mentioned in the previous chapter. As reported in chapter 4, the empirical results of

this study generally supported the research hypotheses by revealing the linkage of the

three types of social capital and knowledge sharing that significantly affects

organizational performance. The confirmatory factor models and the structural model

hypothesized were seen to fit the collected data. Additionally, construct validity was

established by examining convergent and discriminant validity, which confirmed that

the hypothesized structural paths were real and that they were a result of statistical

discrepancies. Significantly, the study found that cognitive social capital was the

exogenous variable that directly affected structural social capital, and then indirectly

affected relational social capital, and through knowledge sharing, organizational

performance.

Overall, the findings generally supported the proposed model, which was

deeply rooted in the theoretical foundations of social capital theory and knowledge

sharing. The study was able to sufficiently capture the diversity of the different types

of social capital; the results are a significant step in illustrating how information

sharing may be a mediating variable that helps to explain the different and

occasionally inconclusive empirical results of the link between social capital and

performance in the literature. More importantly, the study shows that different types

of social capital have different degrees of reliance on information sharing as the

mediator that extends their respective effects on the improvement of competitiveness.

In conclusion, this study provided an alternative explanation for the divergent and

conflicting empirical results concerning the link of social capital and knowledge.

This study also produced findings that would be interesting from theoretical

and practical perspectives. First, the results support the importance of social capital

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and knowledge sharing in explaining the GSB bank staffs’ behaviors in the

organization. The findings also offer insights into the value of cognitive social capital

that causes the linkages of the three types of social capital and its effect on knowledge

sharing and organizational performance.

The findings further indicate that cognitive social capital has the strongest

effect on organizational performance—cognitive social capital builds strong social

ties among the network actors in the GSB, and effects trust in and commitment to the

organization. The stronger is the cognitive social capital, the stronger are the ties to

the organizational network, and the higher are the trust and commitment to the

organization. Cognitive social capital increases knowledge sharing that can increase

employees’ competence in improving performance, and it is noteworthy that cognitive

social capital may be an organizational resource that can also facilitate employees’

capabilities within the banking service system.

The statistical research results show the linkage of three types of social capital;

scholars and practitioners in the banking industry have not adopted an integrative

model that explores the effectiveness of organizational performance from a holistic

point of view, and few studies have investigated the linkages of the three types of

social capital or the effects of social capital on knowledge sharing. It is a challenge for

organizational study to examine the linkage of the three types of social capital in

terms of the enhancement of organizational performance.

This study also investigated the individual’s attitudes in each branch and

combined these attitudes for group or unit analysis. As seen in the study, performance

is a result of the behavior of the members in the network, and the social capital and

knowledge sharing in each branch also derived from the individual as the total efforts

to achieve organizational performance. A number of studies have treated social capital

and knowledge sharing as an individual effort and not in terms of collective resources;

they have failed to identify social capital and knowledge sharing as effects that derive

from the action of individuals. Again, it would be interesting for future research to

investigate social capital and knowledge sharing from the point of view of collective

resources.

The findings indicate that all of the types of social capital are strongly

associated with knowledge sharing and have a strong effect on organizational

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performance. It is remarkable that social capital and knowledge sharing can enhance

organizational performance, and this framework is an under-researched subject in the

area social capital and knowledge sharing vis-à-vis the support of organizational

performance (Kim, Lee, Paek, and Lee, 2013). For this reason, it is necessary to

scrutinize this issue in a deeper fashion.

This research differs from previous studies in that it simultaneously

investigates the attribution factors that exert an influence on organizational

performance, and it helps to expand the studies that examine the latent variables in

each factor constructed. The structural model that was developed in this study can be

of benefit for academic resources in terms of testing or postulating the relationships

among the categories of variables.

The research results also reinforce the concept of self-efficacy in the areas of

cognitive development (Bandura, 1983, 1986, 1989, 2001)—cognitive processes take

a variety of forms, and much of human behavior is regulated by the force of the

thought that embodies cognized goals. Personal goal setting is influenced by a

person’s own appraisal of his or her capabilities, and a strong sense of self-efficacy

can enhance one’s personal accomplishments in a variety of ways. People with a high

sense of self-efficacy, for example, have a positive view that guides and supports

them in achieving their desired performance level.

The findings also support the idea of Tsai and Ghoshal (1998); that is, that the

three types of social capital are linked. They also underline the findings of Uphoff and

Wijayaratna (2000) and Krishna and Uphoff (2002), who have asserted that cognitive

social capital predisposes people to collective action that is beneficial to all parties.

Consequently, it is suggested here that cognitive social capital has a strong influence

on the structural and relational social capital within the organization.

The study results additionally reveal that knowledge sharing in the

organization is one of the key driving regarding the improvement of organizational

performance, and that relational social capital has the strongest effect on knowledge

sharing. This finding also supports the idea that the organization requires trust on the

part of everyone in order to create an organizational environment that enhances

knowledge sharing (Serrat, 2009).

These findings have identified four key factors associated with organizational

performance, and a model has been drawn that is coherent enough to challenge the

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prevailing view and provides insights into an alternative basis for organizational

design. The approach taken in the present study can be seen as a move away from

command- and control-type organizations to those in which cooperation constitutes

the social capital and knowledge management within the organization. The results

suggest that this represents a major challenge for theory and for practice. The present

author believes that other theories might also benefit from this model. In general, the

theory of organizational behavior, including the resource-based view theories that

include strong cognitive social strong ties, trust, and knowledge sharing in terms of

process or outcome variables, can benefit from the clarification of their relationships.

5.2 Implications

With regards to academic and theoretical implications, this research makes the

following three contributions: first, a valid factor structure for three types of social

capital and knowledge sharing; second, measurement of each factor in the bank

settings was validated; and third, a structural model involving the three types of social

capital, knowledge sharing, and performance was developed.

According to the literatures reviews, this framework has never been

empirically tested in any kind of setting. Therefore, based on organizational practice,

the major contribution of this research was to explore a valid factor structure of social

capital and knowledge sharing in the Thai contexts using the Structural Equation

Model with one simple data set, and to confirm this factor structure using CFA

models, including statistical requirements.

Regarding the academic contributions, the research extended the validation of

these measurement models by using the multitrait-multimethod matrix approach to

examine validity and evaluate discriminant validity as well as to measure nomological

validity before exploring the structural equation model. The statistical requirements

were reached in this study.

The final academic contribution was to develop the linkage of the three types

of social capital and hypothesized that cognitive social capital is the exogenous

variable constituting structural social capital and relational social capital.

Regarding the practical implications, the research results may provide human

resource management and leaders with insight into how cognitive social capital

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influences other factors. The three types of social capital as well as knowledge sharing

can be created via organizational interventions.

5.3 Recommendations for Future Research

The limitation of the study provided some ideas for future research. To

generalize these findings, more bank branch units need to be explored. Since the

sample size in this study seemed to be adequate, future research in various regions

would likely provide stable outputs.

This study focused on a sole organization. The hypothesized model was

significant in meeting the statistically requirements; however, potential research

should emphasize various organizations in order to stabilize the model.

Based on the Tsai and Ghosal’s (1998) concept, Uphoff and Wijayaratna’s

(2000) and Krishna and Uphoff’s (2002) models, this study hypothesized

relationships among the three types of social capital. The cognitive dimension was

seen to be linked to the structural and relational types of social capital. The research

results supported the previous proposition. There have been few studies exploring the

linkage of the three dimension of social capital. Therefore, it is recommended for

prospective research to look into this issue.

The value of this model for theory development of any of the forgoing

domains, and for the practical application of these theories, will depend on the extent

of the boundary conditions and the validity of the propositions. Therefore, it is hoped

that future researchers will take up the challenge and test these propositions and

examine the boundary conditions.

5.4 Contributions

This investigation of three types of social capital, knowledge sharing, and

organizational performance in combination, makes a significant contribution to the

organizational capability literature as well as to the social capital literature and

knowledge sharing literature. This study has demonstrated the effects of these

exogenous variables on the endogenous variable. That is, as much as the literature has

99  

established the importance of social capital embedded in interpersonal relationships,

the present author believes that it is equally useful and important to recognize that

social capital and knowledge sharing can build important relationships through the

organizational interventions which were suggested in the previous section.

The formation of social capital depends on the organizational interventions

and interaction among the organizational members. As mentioned in the previous

chapters, organizational social capital is rooted in the mental processes among

members’ thought, affect, and action. Human behavior is governed by perceptions and

organizational environments. Expectation, belief, self-perceptions, goals and

intentions give shape and direction to behavior. Human action is viewed as the

product of the central role of the cognitive, the self-regulatory and self-efficacy.

Members in the organization create, maintain, dissolve, and possibly

reconstitute network ties. That is when people believe, they are motivated to build

their social network more in tune with their own values and the kinds of relationships

that they engage in. They establish strong ties and intelligently organize in harmony

with cooperation for mutual benefit.

Social networks empower the collective action that will enhance the rational

decision making at the organizational level or eradicate the irrational decision making.

Social networks form “participation” in the organization. Members participate in

organizational activities, informal meetings, and clubs; they commit to their network

and are willing to exchange their information related to the organizational context.

Their networks have influential power for the collective action that empowers

organizational performance.

Strong interpersonal relationships create trust in wider networks. Trust is

regarded as a source of relational social capital. Trust and honesty are based on

personal experience. Organizational trust builds and retains its advantage through the

dynamic and complex interrelationships among members in the organization. Trust

can reduce cost and improve organizational performance. Trust is one of the most

valuable of the group components and it is essential to the processes of influence and

collaboration, and also promotes group success. Trust within the organization

increases efficiency and effectiveness by encouraging managers to freely exchange

ideas and information. The relational interactions between members influence

performance.

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The interaction of cognitive social capital, structural social capital, and

relational social capital embeddedness is important because it influences the socially

complex micro practices among group members that lie at the core of capacity

performance, and shape the social micro foundations of the organization’s capability

evolution.

Organization and leadership should establish organizational mechanisms to

increase information self-efficacy and connectivity efficacy by creating an

environment conductive to sharing, as well as positive attitudes toward sharing.

Numerous management practices may simultaneously affect a number of the socio-

psychological factors in facilitating or encouraging knowledge sharing, such as work

design, training programs, development performance appraisal, incentive programs,

an open and trusting culture, etc.

5.5 Limitations

In spite of the compelling results that were obtained herein, there are a few

limitations that should be taken into consideration when generalizing the findings to

other populations. Nevertheless this research study established convergent validity

along with the discriminant validity and nomological validity, it is expected that the

present results will be generalizable across banks and other institutions. The issue of

external validity may be of concern when considering the applicability of research

conducted on a bureaucratic banking sample. Without comparative studies, a similar

claim cannot be made for the bank institutions. Thus, care should be taken to ensure

that the results are not interpreted beyond the limits of this study. The present author’s

focus was on examining whether the model of relationships among variables was

consistent with specific causal relationships.

Although the unit analysis was carried out at the branch level, subsequent

research could build on exploratory study by using multi-level modeling. This could

furnish valuable quantitative evidence on the relative importance of the individual

versus organizational determinants of organizational outcomes. It would also be

necessary to conduct more detailed investigation at different levels of the

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organizational hierarchy to fully explore how social capital translates into better

performance.

Nonetheless, the data for this study were collected from one bureaucratic

organization. Furthermore, the data were “convenience collected” since the regional

managers were willing to help collect the data. The analysis has examined a particular

group of bank staff during a specific time period. It would therefore be important to

identify whether the relative importance of organizational social capital and structure

may differ over time and time periods and in other organizational settings, as well as

the leadership in the organization. For example, further research in other bank units or

different banks could cast light on the comparative generalizability of the results

presented here. The degree of social capital within the organization analyzed here

may therefore be unrepresentative of that found in those operating within other units

or institutions.

Another limitation of the study is that the cross-sectional analysis was of a

static nature. However, longitudinal studies could serve to provide temporal

separation of measurement whereby the bank staff could provide information on the

predictor and criteria variables at different points in time, and hence the data and

information would be more useful than in a study like this one. The study focuses on

the sample units in the bank, specificities that can restrain possible generalization of

the findings.

The present findings are an initial step on the road to causality determination.

This should be considered when generalizing the findings to the population because

this sample served as a convenience sample for developing a preliminary framework

that can be used in understanding the importance of competitive resources in the

organization. The comparative models served as a preliminary source of

understanding the potentiality of the Amos program. Model invariance is considered

to be preferred analysis for assessing whether measurement and structural models are

equivalent across groups.

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5.6 Conclusion

This dissertation assesses a theoretical framework for forming an integrative

model which allows for the exploration of the influence of social capital and

knowledge sharing on organizational performance. Additionally, the study examines

the linkages of the three types of social capital, and their effects on knowledge sharing

organizational, which in turn promote organizational performance. The empirical

findings from the initial test of the framework supported the fundamental distinction

made between two principal forms of social capital and knowledge sharing. The

results of the research point to the importance of understanding the cognitive social

capital of the group.

The findings expressed concern over the existing conceptions of the role of the

informal social relationships in the organization. Decades ago, Burns (1977) noted

that Roethlisberger and Dickson saw the informal organization “as receptacle for

observations about the behavior, relationships, the sentiments and belief…taken to be

irrelevant to the formal organization or incompatible within it,” and that Barnard saw

it as “an essential adjunct to the formal organization.” Social capital and the

willingness to share knowledge have been examined with the understanding that they

are central to the real world of organizations.

Social capital provides organizations with greater coherence of action due to

organizational stability and shared understanding. The major benefit of social capital

is that it enables organizations’ members to coordinate their actions to achieve desired

outcomes. Simply stated, investment in social capital produces organizational values.

The findings establish the idea that the concept of social capital seems to be a

very compatible, useful, and important one for the organizations. The organization

must sustain and enhance the original social capital with which they were formed and

broaden it into a variety of key areas.

Organizational executives have a pivotal role in carrying out the following

functions: fostering social capital in order to recruit and develop broad members,

obtain organizational support, develop strategic competitiveness, engage in advocacy,

better group relations, and create a shared mission within the organization and its

employees. Leaders must also decide how and where to invest in social capital and the

103  

knowledge sharing in organizations and they must be active in seeing that social

capital becomes a reality.

Some of the recommendations suggested for leaders are the following: create a

shared vision among members that is in line with the direction of the organization,

thus creating trust in the organization and developing awareness of social networks.

They should also assess their own network, estimating the distance between

individuals and build genuinely reciprocal relationships and assess opportunities to

connect with different groups (Brass and Krackhardt, 1999).

In order to build a shared vision, top management must encourage people to

create visions that will enable them to cope with the organization’s core purposes and

not just the leader’s personal vision. Leaders must also be able to determine the core

values of the organization and define core purposes and envision the desired future by

asking relevant and significant questions; for example: Where do we want to go?

What do we want to create? How can we best operate and work together? It can be

thus seen that is necessary to establish markers that indicated the success of the

organization.

Additionally, trust in the organization can be seen as a key element in the

organization’s successful performance. Cohen and Prusak (2001), for example,

encourage leaders to foster trust by being trustworthy and having open relationships

and by encouraging openness in others—they suggest that organizations should invest

in networks and provide resources to make sure that participation takes place. These

authors additionally recommend recognizing and encouraging others to build social

capital; and last, they encourage the use of storytelling and narratives to reinforce the

concepts of social capital and its benefits.

In creating a knowledge-sharing culture, leaders can utilize new management

techniques to increase the collaboration within their teams, departments, and within

the organization, and they should also communicate their collaborative approaches

clearly and embed them in their business practices. In this way, the results of the

collaboration can be measured. Naturally, trust among the organization’s members is

necessary in order to bring about constructive collaboration. This sharing of thoughts

and idea among the members of the organization will serve as a basis for establishing

the knowledge-creating process within the organization and in this way a sense of

104  

sharing and collaboration will be created from the existing social capital (Bock and

Kim, 2002; Davenport, 1997). Although people may not be willing to accept shared

knowledge from others because of lack of trust (Bircham, 2003), an effort in this

direction must be made.

It should be recognized, however, that an attitude of knowledge sharing in

itself is not sufficient for people to be able to increase organizational productivity

through the exchange of ideas; the infrastructure of technology and services can also

be effective in realizing the goal of knowledge sharing (Ojo and Grand, 2009;

Sanghani, 2009). It should also be recognized that information technology can help

the organization manage and leverage knowledge systematically and actively, and in

order to achieve this, leaders must provide appropriate information technology that is

easy to access and share. This ability to access and share knowledge between

individuals and among the units of the organization can greatly increase the

organization’s performance (Hendricks, 2005).

105  

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APPENDICES

APPENDIX A

QUESTIONNAIRE IN THAI

สาขา .................................................. ภาค..........................

ตาแหนง ผจดการสาขา พนกงาน ......................ระยะเวลาในการทางานทสาขา ........................ป

เพศ หญง ชายอาย ....................ป

สวนท 2: ขอคาถามเกยวกบทนทางสงคม และการแลกเปลยนความร โปรดทาเครองหมาย √ ในชองทใกลเคยงความรสกทานมากทสด1 = ไมเหนดวยทสด 5 = เหนดวยมากทสด

ประเดน 1 2 3 4 5

1 ฉนยดมนการทางานตามวสยทศนธนาคาร2 ฉนเสนอแนะวธการบรการทเหนอความคาดหมายแกทมงาน3 ฉนทมเท ตงใจ ทางานตามวสยทศนและภารกจธนาคาร4 ฉนและเพอนรวมงานมการวางแผนงานรวมกน เพอทาใหวสยทศนธนาคารบรรล5 เปาหมายของสาขาเปนเรองนาเบอหนาย เพมขนทกป6 ทสาขาเรา มการทบทวนและแกปญหา ตดตามประเมนผลตามเปาหมายอยางตอเนอง

7 เมอมการเรยนรส งใหม ๆ ทกคนจะบอกเพอนรวมงานใหรบร 8 การแบงปนทกษะ ความร ขอมล ทาใหงานทซาซอนลดลง9 การแบงปนทกษะ ความร ขอมลทาใหการทางานบรรลเปาหมายงายขน

10 เปนเรองเสยเวลา และยงยากทตองอธบายเทคนคการทางานใหคนอนร

แบบสอบถามการวจย เรอง ทนทางสงคม การแลกเปลยนความร กบผลสาเรจในการทางาน

เรยน ผตอบแบบสอบถาม แบบสอบถามน เปนสวนหนงของการทาวทยานพนธ หลกสตร Doctor of Philosophy in Development Administration

(International Program) คณะรฐประศาสนศาสตร สถาบนบณฑตพฒนบรหารศาสตร เพอศกษาสมการโครงสรางทมผลตอความสาเรจในการทางาน ผวจยใครขอความรวมมอจากทานในการตอบแบบสอบถามทกขอ และโปรดระบขอเสนอแนะเพอความสมบรณของขอมลโดยขอมลทไดจากทานจะถกเกบเปนความลบ เพอผลทางการศกษาวจยเทานน จงเรยนมาเพอโปรดใหความรวมมอตอบแบบสอบถาม และขอขอบพระคณในความรวมมอมา ณ โอกาสน

กฤษณา ฟองธนกจผวจย

สวนท 1: ขอมลสวนบคคล

ระยะเวลาในการทางานในธนาคาร ....................ป

1 2 3 4 5

11 เวลาทหวหนาอารมณไมด พวกเราจะกระซบบอกกน12 ฉนเหนวา งานทกงาน มความสาคญเทากนหมด13 ฉนตดตามงานตามแผน เพอใหภาพรวมในงานของสาขาบรรลเปาหมาย14 ฉนมความเชอมนในความมนคงขององคกร15 ธนาคารทฉนทางานอย เชอถอได เปดเผย โปรงใส พรอมใหการตรวจสอบ16 ฉนเปนคนทผอ นพงพา หรอไววางใจได 17 ฉนสนบสนนเพอนรวมงานใหเจรญกาวหนาในหนาทการงาน18 ฉนสนทสนม ใกลชด กบเพอนรวมงาน รสกเหมอนเปนคนในครอบครว19 เวลาทประสบปญหาในชวตทางาน ฉนไมเคยแพรงพรายใหใครร 20 ฉนมจตอาสา ชอบบรการ ชวยเหลอเพอนรวมงาน

1 2 3 4 5

21 ฉนเขาใจและยอมรบในความสามารถของเพอน22 ฉนใชเวลาวาง ใหความชวยเหลอ สนบสนน และรวมมอในการทางาน23 ฉนรวมมอกบกจกรรมของธนาคาร แมจะเปนวนหยด24 ฉนใหเวลาทกคน เพออานวยความสะดวก และสรางคณคาใหกบลกคา25 ฉนใชเวลาพดคย ถกเถยงกบเพอนรวมงานในสาขาเกยวกบการทางาน เพอใหงานดขน

26 ฉนสามารถเสนอผลตภณฑและบรการทเหมาะสมกบลกคา27 ฉนศกษาเปรยบเทยบผลตภณฑและบรการของธนาคารอน ๆ ตลอดเวลา 28 ฉนทางานเฉพาะตามทไดรบมอบหมายเทานน 29 ปญหาธนาคารคอปญหาทฉนตองขบคด แกไขใหดข น30 ฉนจะตองอธบาย หากไดยนใครพดถงธนาคารในทางทไมด หรอเขาใจธนาคารผด ๆ

สวนท 2: ขอคาถาม (ตอเนอง)

โปรดทาเครองหมาย √ ในชองทใกลเคยงความรสกทานมากทสด1 = ไมเหนดวยทสด 5 = เหนดวยมากทสด

ประเดน 1 2 3 4 5

31 ฉนภมใจทจะบอกใคร ๆ วาฉนทางานทธนาคารออมสน32 ฉนแบงปนขอมลกบเพอนรวมงาน เมอมการรองขอ33 ฉนจะไมบอกเรองงานใครหมด ทเหลอกไปเรยนรกนเอง 34 เมอฉนกลบจากฝกอบรม ฉนจะเลา และสอนเพอนรวมงาน35 ฉนชอบใชเวทแลกเปลยนเรยนรงานระหวางกน36 ฉนจะบอกเพอนรวมงานใหทราบวา ใครเปนลกคารายสาคญของสาขา37 เมอเพอนไมสบาย ฉนตองไปเยยมเยยน หรอถามไถอาการ38 ฉนไปรวมงานแสดงความเสยใจ เมอคนสาคญในครอบครวของเพอนพนกงานจากไป

39 ฉนไมชอบไปงานแตงงานของเพอนรวมงาน หรอ ของลกๆ เพอนรวมงาน40 ฉนไมชอบไปงานบวชของลกเพอนรวมงาน

1 2 3 4 5

41 เพอนรวมงานอยากทางานรวมกบฉน 42 เพอนรวมงานฉน ซอสตยสจรต ไวใจได 43 เพอนรวมงานจะใหความชวยเหลอฉนได ถาฉนขอรอง44 เพอนรวมงานมกจะสรางความยงยากในการทางาน 45 เพอนรวมงานฉน เชอถอได มจรรยาบรรณและจรยธรรม ประพฤตตนเปนพนกงานทด

46 เพอนรวมงานจะแบงปนขอมลแกคณ47 คนอน ๆ ใหขอมลทไมคอยเทยงตรง ตองตรวจสอบเพม 48 เพอนจะเลา และสอนงานเมอกลบมาจากการฝกอบรม49 เพอน ๆ ชอบพดคย แลกเปลยนความคด ปรบปรงกระบวนการใหบรการ50 เพอนรวมงานจะใหขอมลทสาคญของพนทใหคนอน ๆ ทราบ51 เมอเพอนรวมงานทางานผดพลาด ฉนใหอภยได

สวนท 3 : ความคดเหนเพมเตม

APPENDIX B

ABBREVIATIONS AND SYMBOLS

 

 

ABBREVIATIONS AND SYMBOLS

Abbreviations Equivalence

AVE The Average Variance Extracted

CFI Comparative Fit index

CMIN/DF Relative chi-square

CR. The construct reliability

C.R. The Critical Ratio

df Degree of freedom

e Error

GIF Goodness of Fit index

GSB The Government Savings Bank

IC Inter-construct correlation

NNFI Nonnormed fir index

n Number of sample size

(R) Reverse item

res Residual

RMSEA Root Mean Square error of approximation

SIC Squared inter-construct correlation estimates

SEM Structural Equation Model

S.E. Standard Effort

TLI Tucker Lewis Index

146

 

SYMBOLS Equivalence

α The Alpha

β The Beta

Mean

λ The Standardized factor loading

i The number of items

δi Sum of the error variance terms for a construct

Chi-square fit index

BIOGRAPHY

NAME Krishna Fongtanakit

ACADEMIC BACKGROUND

Political Sciences,

Chulalongkorn University, 1978

Law, Sukhothai Thammathirat

University, 2004

Accounting, Sukhothai Thammathirat

University, 2007

Management, Sasin Graduate Institute of

Business Administration of

Chulalongkorn University, 1995

Public Administration, National Institute

of Development Administration, 1996

PRESENT POSITION

Senior Vice President

EXPERIENCES

Personnel, Bank for Agriculture and

Agricultural Cooperatives

Secretary to the President, the

Government Savings Bank

Executive in various departments-

Electronics Card, Life Insurance, Foreign

Exchange, and Strategy and Planning.