I The impact of AMO (ability, motivation and opportunity) model on Knowledge sharing in family controlled businesses in Hong Kong clothing industry. LEE, Yuk Ling Angie MBA & MGFM Submitted in fulfilment of requirements for Doctorate in Business Administration, The University of Newcastle, Australia September 2016
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I
The impact of AMO (ability, motivation and opportunity) model
on Knowledge sharing in family controlled businesses in Hong
Kong clothing industry.
LEE, Yuk Ling Angie
MBA & MGFM
Submitted in fulfilment of requirements for Doctorate in Business
Administration, The University of Newcastle, Australia
September 2016
II
Statement of Originality
The thesis contains no material which has been accepted for the award of any
other degree or diploma in any university or other tertiary institution and, to the best
of my knowledge and belief, contains no material previously published or written by
another person, except where due reference has been made in the text. I give consent
to the final version of my thesis being made available worldwide when deposited in the
University’s Digital Depository**, subject to the provisions of the Copyright Act 1968.
* * U n l e s s a n E m b a r g o h a s b e e n a p p r o v e d f o r a d e t e r m i n e d p e r i o d .
S i g n a t u r e … … … … … … … … … … … … . . D a t e … … … … … … … … .
III
Acknowledgements
I would like to offer my heartfelt gratitude to Dr.Ashish Malik for the guidance and patience
that he provided me to complete this dissertation.
I would also like to express my heartiest gratitude to all my lecturers and classmates
especially, Dr Kelvin Lo, Mr Man Lai Cheung, Alfred Cheng and Sindy Yau for their
knowledge and support throughout my studies. Special thank also go to Dr Philip
Rosenberger III for providing technical advice and guidance for my data analysis.
Thank you Associate Professor Guilherme Pires and Suzanne Ryan for guiding and
motivation. I would also like to thank my ex-lecturers Professor Andrew Sia and
Dr.Wing-Sun Liu for their support and invaluable suggestions.
Last but not least, my deepest appreciation to my family for their patience and support
throughtout the period.
IV
Content
STATEMENT OF ORIGINALITY ........................................................................................................ II
ACKNOWLEDGEMENTS ................................................................................................................... III
CONTENT ............................................................................................................................................... IV
ABBREVIATIONS ................................................................................................................................ XII
ABSTRACT .......................................................................................................................................... XIII
1.3 RESEARCH OBJECTIVES ........................................................................................................................................ 5
1.4 RESEARCH PROBLEM AND QUESTIONS .............................................................................................................. 8
1.5 RESEARCH METHOD .......................................................................................................................................... 11
1.5.1 Data analysis ................................................................................................................................................... 11
1.5.2 Structure of the Thesis ................................................................................................................................ 12
2. 2. KNOWLEDGE MANAGEMENT AND ITS CORE PROCESSES ........................................................................... 17
V
2.2.1 Knowledge sharing processes and its impact on firm performance ...................................... 20
2.3 RESEARCH ON FAMILY-CONTROLLED BUSINESSES ...................................................................................... 23
2.3.1 FCBs and knowledge sharing ................................................................................................................... 26
2.4 AMO: THE PERFORMANCE RUBRIC ............................................................................................................... 28
2.5 FCBS AND AMO MODEL ................................................................................................................................... 33
2.5.1 Ability and knowledge sharing ............................................................................................................... 33
2.5.2 Motivation and knowledge sharing ...................................................................................................... 35
2.5.3 Opportunity and knowledge sharing ................................................................................................... 38
2.6 FCBS AND AMO MODEL ................................................................................................................................... 40
2.6.1 FCBs and AMO ................................................................................................................................................. 41
2.7 RESEARCH GAP, KEY QUESTIONS AND HYPOTHESES DEVELOPMENT ........................................................ 42
2.7.1 Research Gap ................................................................................................................................................... 42
2.7.2 Research Questions ....................................................................................................................................... 44
3.2 RESEARCH PROCESS: PHILOSOPHY AND PARADIGMS .................................................................................. 48
3.2.1 Positivist research approaches ............................................................................................................... 49
3.2.2 Quantitative Research ................................................................................................................................. 50
3.2.3 Justification for a positivist and quantitative methodology ...................................................... 51
3.3 RESEARCH DESIGN ............................................................................................................................................. 52
3.4 RESEARCH QUESTION AND HYPOTHESIS DEVELOPMENT ............................................................................ 53
3.4.1 Research question ......................................................................................................................................... 53
3.4.2 Hypothesis development ............................................................................................................................ 55
3.5 CONCEPTUAL FRAMEWORK OF THE RESEARCH ............................................................................................ 56
3.5.3. Moderator ........................................................................................................................................................ 62
3.5.4 Additional background data .................................................................................................................... 62
VI
3.6 QUESTIONNAIRE DESIGN AND SAMPLING ...................................................................................................... 66
3.6.1. Measurement and scales ........................................................................................................................... 66
3.6.2 Data collection and sampling .................................................................................................................. 67
3.6.3. Defining the Research population ........................................................................................................ 68
3.6.4. Selection of sample ...................................................................................................................................... 69
3.7. DATA COLLECTION METHOD ........................................................................................................................... 71
3.7.1. Administration of data collection ......................................................................................................... 71
3.7.2. Data analysis .................................................................................................................................................. 72
3.8. POWER OF TESTS OF INTERACTIONS ............................................................................................................ 72
4.1.1 Data preparation........................................................................................................................................... 83
4.1.2. Data coding and entry ............................................................................................................................... 84
4.3 CHARACTERISTICS OF DEPENDENT AND INDEPENDENT VARIABLES ......................................................... 90
4.3.1 Profile of FCBs and Non-FCBs .................................................................................................................. 90
4.3.2 Descriptive statistics of items in this study ........................................................................................ 91
4.5 SKEWNESS AND KURTOSIS ............................................................................................................................... 93
4.6 TEST OF DISTRIBUTION NORMALITY .............................................................................................................. 94
4.7. SUMMARY OF DESCRIPTIVE DATA .................................................................................................................. 98
4.8 RELIABILITY AND VALIDITY OF MEASURED DATA ........................................................................................ 98
VII
4.8.1. Validity of measured data ........................................................................................................................ 98
4.8.2. Validity of independent and dependent variables ........................................................................ 99
5.2 MAJOR FINDINGS .............................................................................................................................................. 124
5.3 RESEARCH FRAMEWORK ................................................................................................................................ 125
5.4. DISCUSSION OF FINDINGS .............................................................................................................................. 126
5.5 MODERATING EFFECT OF FCBS .................................................................................................................... 129
FIGURE 4.12: SIMPLE SLOP RESULT FOR AMP FACTOR AND FCBS ................................120
FIGURE 5.3: AMO FACTORS APPLIED TO KNOWLEDGE SHARING AND ARE INDIVIDUALLY
MODERATED BY FCBS .....................................................................................................125
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Abbreviations
• FCBs- Family control businesses
• NonFCBs – Non Family control businesses
• HKCI – Hong Kong Clothing Industry
• AMO – Ability, Motivation, Opportunity
• TW – Training for workers
• IS – Incentive systems
• T – Trust
• KS – Knowledge sharing
• FK – Formal Knowledge
• IK – Informal Knowledge
• HKTDC – Hong Kong trading department council
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Abstract ___________________________________________________________________________________________________ This study analyses the relationship between knowledge sharing, family controlled
businesses (FCBs), training for workers, incentive systems and trust in Hong Kong’s
Clothing Industry (HKCI). The study contributes by investigating the impact of the
ability, motivation and opportunity (AMO) paradigm focusing on training for
workers(A), incentive systems(M) and trust(O) and the moderating effects of Family
control businesses (FCBs) on knowledge sharing in Hong Kong’s clothing industry.
Such an investigation is timely and relevant when a number of Chinese family
businesses are facing the dilemma of succeeding their businesses through appropriate
governance structures, operations and systems so as to continue their entrepreneurial
spirit and effectively manage the generational transitions in Hong Kong (HK) (Au, K et
al. 2013).These challenges result in failure of some family control businesses from
managing succession and intergenerational leadership Issues (Chua et al., 2003; Long
& Chrisman, 2014). Thus, sharing key knowledge by people in FCBs through
appropriate people management practices is important for sustained succession in
FCBs.
The AMO paradigm has received considerable research attention in the field of Human
Resource Management (HRM) in the last two decades. The AMO model offers a useful
framework for studying how certain HRM practices can impact knowledge sharing
performance outcomes.
Based on a review of literature, a conceptual model showing the constructs of AMO was
developed and six hypotheses were then generated and tested in this research. The
findings of the research suggest that incentive systems and trust have a significant
impact on knowledge sharing but training for workers does not have any significant
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impact on knowledge sharing. The findings also revealed that variables of training for
workers, incentive systems, and trust have a significant and negative impact for FCBs.
Overall, the findings from this study have implications for theory and practice. The
results highlight the relationships among the AMO components and Knowledge
sharing performance in a new context, especially by analysing the moderating impact
of FCBs. In terms of managerial implications for practice, this research highlights that
FCBs need to focus strategically on AMO components that contribute most in
enhancing a firm’s knowledge sharing performance.
1
Chapter 1
Introduction
1.1 Introduction
In Hong Kong, many Chinese family businesses are facing the dilemma of how to manage
and sustain their family business, often considering a range of options such as appropriate
governance structures, operations, and systems to sustain their entrepreneurial spirit and
to successfully pass on their businesses to future generations (Au et al. 2013). This study
attempts to address the above challenges by focussing on how family businesses can
avoid failure and improve succession of intergenerational leadership through the vital
processes of knowledge sharing (Chua et al., 2003; Long et al., 2014). The focus on
knowledge sharing in family businesses is relevant as knowledge has been regarded as a
critical resource for firms’ sustained performance and growth (Witherspoon, Bergner,
Cockrell & Stone, 2013). Earlier studies have argued that knowledge sharing is vital for
relaying critical business information from senior leadership to employees to achieve
sustained growth and profits (Kaplan and Norton, 2001, Quigley, 1994; Witherspoon et al.,
2013). While there have been several reviews of the literature on knowledge sharing and
its antecedents, these reviews often focus on an aspect of the wider knowledge
management literature or a specific industry sector (e.g. Grossman, 2007; Yahya & Goh
2002; van Rooi & Snyman, 2006). Witherspoon et al.’s (2013) recent meta-analytic review,
classified the literature into four key areas: intentions and attitudes of employees towards
knowledge sharing, organisational culture, rewards and gender as key foci of the studies
thus far. All three groups of antecedents: intentions and attitudes, organisational culture
2
and rewards tested positive towards knowledge sharing, however, there was no support
for the impact of gender; and country of origin was as a key moderator in knowledge
sharing behaviour. Their review of 46 studies points to several gaps in the research on this
important topic. There was only one study that focused on managers in Hong Kong (Chow
& Chan, 2008), using theory of reasoned action; not focused on family controlled
businesses; and finally, their review highlighted the need to understand the barriers to
knowledge sharing. With intentions, attitudes, culture and rewards being noted as
significant factors in explaining knowledge sharing behaviour, it is logical to pursue further
research that examines the role of human resource management (HRM) practices on
knowledge sharing. Further, given the limited focus on Hong Kong, this study argues that
subsequent generations of family businesses in the Hong Kong’s clothing industry (HKCI)
can benefit from understanding the key antecedents of knowledge sharing, especially in
the context of HKCI’s family-owned businesses.
The present research uses Hong Kong’s clothing industry (HKCI) as the main research
context, and focuses on the effect of family FCBs, training and skills, incentive systems,
and trust on knowledge sharing. Insights from this research are intended to contribute to
the literature on people management factors such as ability (training for workers,
motivation (incentive systems) and opportunity (trust) in the context of FCBs that are
central for knowledge sharing in HKCI.
This research is vital for addressing managerial problems that Chinese family businesses
are currently facing, especially with the concerns regarding the effectiveness of
governance structures, operations and systems to continue the entrepreneurial spirit in
the process of generational transition in HK (Au, K et al. 2013). These challenges are
worthy of attention as there is evidence of failure to retain family succession after a shift
in intergenerational leadership. (Chua et al., 2003; Long et al., 2014).
3
The AMO (ability, motivation, opportunity) model is a widely accepted model in Human
Resource management (HRM) literature and its linkages with firm performance. As noted
above, given the importance of cultural and human intentions and behavioural factors,
focusing on the AMO paradigm seems logical. Furthermore, this is also in line with earlier
research (Chua et al., 2004; Wong & Aspinwall, 2005; Mooradian, 2006; Zahra, 2007; Yang,
2007) of the three key AMO factors: ability (training for workers), motivation (incentive
systems) and opportunity (trust). This study will adapt constructs from this dominant AMO
paradigm and based on earlier studies (e.g., Salis & William, 2008; North, 2015) apply the
model in the context of HKCI’s FCBs on knowledge sharing. A particularly helpful aspect of
the AMO model is that it assumes that all AMO factors influence knowledge sharing and
we need to explore further of any moderating effect of FCBs (Boselie, 2012; Oudkerk Pool,
2016). The presence of relevant AMO variables in FCBs within the HKCI can help improve
our understanding of knowledge sharing and its consequent impact in enhancing the
competitive advantage and business performance of FCBs.
Limited studies have thus far investigated knowledge sharing among family-owned firms
in HK (Kontinen and Ojala, 2010; Lok and Crawford, 2004), especially in the clothing
industry (HKCI). The HK clothing industry is a reputable and an important manufacturing
sector in HK. It is the third largest manufacturing employer in HK, with around 900 firms,
employing around 5,773 people in the HKCI, and with revenues exceeding HK$ 143 billion
as of December 2015 (HKTDC, 30 June 2016). The HKCI imposes a powerful influence on
the global market, especially with its major exports to the United States and European
markets. It occupies a prominent position in HK’s domestic economy. The clothing
industry’s supply chain is well developed in HK ensuring the major clothing manufacturing
sector of HK with good quality standard, quality control and products supply, and logistical
arrangement, among others (Dickerson 1999).
4
Hong Kong is the only city in China that blends Chinese tradition with a British colonial
heritage influence (Enright et al., 1997; Henderson, 2001). Most firms may simply focus
on lower agency costs and shorter production lead times with little focus on the
importance of knowledge sharing to enhance firm performance (Lin, 2007). This study
investigates how family-owned firms share their knowledge with key stakeholders in their
business and the factors that have an impact on profitability.
This research fills the research gaps by evaluating the AMO independent variables
(training for workers, incentive systems and trust that is created by organizational
leadership) as well as exploring the moderating role of (FCBs) in knowledge sharing in HK.
Although a study examined the moderating role of technological capabilities in firms with
family ownership on knowledge sharing in the context of the United States (Zahra et al.,
2007), the findings cannot be easily applied to an Asian setting especially because HK is
well-known to exhibit an aspect of a crossvergent culture, a unique fusion of Western and
Eastern cultural context (Ralston, 2008., Ralston et al., 2008; Sarala and Vaara, 2010).
Furthermore, only few studies have focused on family controlled businesses (FCBs) in the
extant literature on knowledge sharing from a HR perspective (Chrisman et al.,2006; Miller
and Breton-Miller,2006). Thus this research is timely and will contribute to the emerging
body of literature on knowledge sharing from an Asian market context. Moreover,
despite an increasing number of research focusing on FCBs (Heck & Mishra, 2008), the
review literature reveals that there is a relatively limited body of research that focuses on
examining FCBs in relation to knowledge sharing.
5
1.2 Study’s background
Knowledge sharing has been regarded as a very important determinant of success since the
seminal work of Nonaka and Takeuchi (1995). Nonaka and Toyama (2003) as well as
Jasphapara (2004), using concepts from KM literature (such as knowledge creation, sharing,
and integration), highlighted the importance of knowledge sharing. Critical for the purposes
of this study is the influence of HRM practices using the AMO paradigm (such as training for
workers, incentive system, trust) on knowledge sharing.
Zahra (2007) noted there are challenges in efficiently measuring knowledge-sharing; in the
main it has two key elements: Formal and informal knowledge sharing that need to be
observed. The willingness and attitude of employees are among the prominent factors to
motivate effective knowledge sharing in firms. A firm’s performance and growth is often
affected by conflict between and unwillingness of family members and employees to share
information with others in the organization either because of the ownership issues or due
to some of family members not willingly wanting to make any changes (Hitt, et al., 2006;
Sirmon & Hitt, 2003; Zahra et al., 2006). This research will therefore examine the
moderating effect of FCBs on knowledge sharing in the context of HKCI using the established
human resource rubric of AMO.
1.3 Research Objectives
In view of the above, this research has the following overarching objectives:
1) To address the theoretical and empirical gaps examining the relationships between AMO
model, knowledge sharing and FCBs.
2) To explain the relationship AMO model has with knowledge sharing in the context of
HKCI.
6
3) To gain insights about the benefits of knowledge sharing for workers in the HKCI for
enhancing firm’s competitive advantage.
Addressing the first research objective, this study investigates the major antecedents of
knowledge sharing using the AMO model (Salis and William, 2008). Further, little research
has focused on knowledge sharing and examining the moderating effect of FCBs. Although
research interests on the topic of knowledge sharing is on the rise, there exists no
comprehensive understanding of how the AMO model variables (such as training for
workers, incentive systems, and trust) and FCBs impact on knowledge sharing. Pursuing
this research is vital as managing individual’s ability, motivation and opportunity to apply
their knowledge and skills has been considered as the dominant approach in HRM for
understanding how individual level performance can be enhanced. It can thus be argued
that if a person’s ability, motivation and opportunity needs are not addressed, their
performance (behaviour towards an organisational activity) such as in this case, knowledge
sharing, may be adversely affected.
Addressing the second research objective, the review of literature points that a vast
majority of research on knowledge sharing is based on research from Western nations or
other Asian economies, (see for example, Mooradian et al., 2006; Wong and Aspinwall,
2005; Witherspoon et al., 2013; Zahra et al., 2007). Thus, this study is timely as it will add
to the relatively limited research on knowledge sharing in Asia, especially in Hong Kong. The
complexity of Hong Kong’s post-colonial and Chinese cultural context not only represents a
challenge to researchers, but also offers an opportunity to improve both empirical
understanding and theoretical advancement of knowledge sharing.
The above importance of knowledge sharing has been well-established in the context of
Western nations since the early 1990s and has in the last decade attracted increased
attention in Asian countries (Davison & Ou, 2007). Firms now recognize that knowledge
7
management strengthens its competitive advantages and enhances its capability to
reduce agency costs, increase productivity, and shorter the lead times for production (Lin,
2007). However, there is still limited empirical basis for understanding the impact of
family members on knowledge sharing in firms (Lai, 2010). Barring a few studies that focus
on family controlled businesses (FCB) (Williamson, 1999; Heck & Mishra, 2008; Makadok,
2003), research gaps exist in relation to FCBs’ impact on knowledge sharing outcomes and
even more so, for FCB firms in the HKCI.
Hong Kong is developing into a business networking center for global clothing sources (Jin,
2004). Many clothing manufacturing firms in Hong Kong have already developed a strategic
mechanism for improving competitiveness and reducing resource disadvantages through
knowledge sharing using internal to external sources.
The research context of Hong Kong as the only Chinese city with a unique business culture
that combines elements of both Eastern and Western cultures, a strong educational
system and political organization offers this research the opportunity to explore the
problem in context (Enright, Scott & Dowell, 1997). Historically, firms in HK have been
doing business with Western firms directly and distinguish themselves from other Chinese
communities in Asia. However, studies of crossvergence suggest there are possibilities of
convergence and divergence occurring in HK’s business environment (Ralston et al., 2008).
Such changes provide a fertile ground for conducting intensive analysis about the
correlation between family FCBs, AMO factors (workers’ training, incentive systems and
trust) and knowledge sharing in the HKCI. Internal changes brought about by such
conditions may well alter the internal day-to-day transactions between employees, posing
new demand with varying degrees of hybrid cultures in their control systems.
Further, as HKCI comprises of majority of manufacturing firms and there is an insufficient
empirical research that has tested the association between knowledge sharing, AMO
8
variables and FCBs, thus this research is expected to improve our understanding of
knowledge sharing performance and competitiveness of HKCI.
Finally, in addressing the third research objective, this research aims to capture the
potential benefits for practitioners who are employed by the HKCI including clothing related
businesses such as materials suppliers, wholesalers, and retailers. It is anticipated that the
findings of this research will inform firms and knowledge workers about how to motivate
the workers to share knowledge. Through this research implication for decision makers and
practicing managers regarding how best to design and implement AMO factors to succeed
in knowledge sharing for enhancing firms’ competitiveness in the marketplace are likely to
be addressed.
1.4 Research problem and questions
It is argued that the management and leadership styles of owners in FCBs can potentially
affect their knowledge-sharing performance and motivate staff to share knowledge (Sull &
Wang, 2005). Further, most employees working in the HKCI undertake complex knowledge
work in design, logistics, manufacturing and operating highly automated machines for the
industry. In this context, the study’s research setting is suitable for exploring how
knowledge workers share their knowledge especially in FCBs. The literature on knowledge
workers suggests that “knowledge workers predominantly do work and solve challenges
that have already been done and solved before their organizations.” (Marketwired-
viewed on December 10, 2014). Drucker (1999) stated that knowledge worker
productivity is a crucial management resource for the 21st century and that knowledge is
regarded as a key element in a firm to improve its business performance (Arthur &
Huntley, 2005). Individual knowledge sharing contributes to sustainable competitive
9
advantages and a firm’s knowledge management practices (Apshvalka and Wendorff,
2005).
To fully investigate HKCI’s context, this research employs a quantitative survey of HKCI’s
businesses and uses factor analysis to test the AMO theoretical framework and its impact
on knowledge sharing behavior. It further explores whether FCBs acts as moderator. Based
on a review of the literature (covered in detail in the next chapter- Chapter 2), this study’s
research questions aim to address the identified gaps in the literature and forms the basis
of the study’s guiding theoretical framework (See Figure 1.4 below).
Figure 1.4 Framework and Research Questions
As this research investigates the relationship between antecedents of ability (training
workers), motivation (providing incentive systems), opportunity (creating an environment
of trust) of employees, ownership (FCBs) with knowledge sharing behaviors in the HKCI,
three research questions and six hypotheses have been formulated:
10
Research Questions:
Q1 Does ability (training workers), motivation (providing incentive systems), opportunity
(creating an environment of trust) of employees have a significant effect on knowledge
sharing in the HK clothing industry (HKCI)?
Q2 what are the key relationships between FCBs, AMO factors and knowledge sharing in
the HKCI firms?
Hypotheses
Hypothesis H1.1:
In the HKCI, training for workers is positively related to knowledge sharing.
Hypothesis: H1.2
In the HKCI, incentive systems are positively related to knowledge sharing.
Hypothesis H1.3
In the HKCI, trust is positively related to knowledge sharing.
Hypothesis H2.1
In the HKCI, FCBs act as a moderating factor in the relationship between training for workers
and knowledge sharing.
Hypothesis H 2.2
In the HKCI, FCBs act as a moderating factor in the relationship between the incentive
systems and knowledge sharing.
11
Hypothesis H2.3
In the HKCI, FCBs act as a moderating factor in the relationship between trust and knowledge
sharing.
1.5 Research Method
This section provides a brief overview of the research methodology employed. Details of
this will be further elaborated in Chapter 3 of the thesis.
1.5.1 Data analysis
This research involves a survey of 900 HK clothing industry firms through an internet-based
questionnaire from geographically dispersed firms in the HKCI. The target is to obtain 100
responses from senior executives such as top management, executives, and managers. A
quantitative survey is deemed as the most effective method for data collection, especially
when a large sample of quantitative data needs to be collected and analyzed (Saunders,
Lewis and Thornhill, 2011). This study follows the design employed in previous research
(Chua et al., 2004; Mooradian, 2006; Wong & Aspinwall, 2005; Zahra, 2007) and adapts the
questions employed by earlier studies to fulfil the research objectives of this study. The
reliability and validity of each theoretical construct will be verified using established tests.
A simple convenient sampling was adopted in the HKCI in which family-owned businesses
and non-family owned businesses have not been established conclusively. Next, the
sampling frame will comprise of a list of assigned directions and significant elements drawn
through a representative sample (Malhotra 2008).
12
Using a seven-point Likert scale, various theoretical constructs were measured through
established items from the literature and administered through an anonymous self-
completion online survey. The three AMO factors (training for workers, incentive systems,
and trust) and FCBs were analyzed. Several statistical tests were used to measure the
information collected in the online questionnaire and to test whether the research results
supported the hypotheses. Analytic techniques employed include descriptive analysis,
factor analysis, Pearson’s product moment correlation, and multiple regression analysis
using Process Macro in SPSS (Hayes, 2013), SPSS software (Version 22) for reliability, validity,
and testing the study’s hypotheses (Hair, 2006).
1.5.2 Structure of the Thesis
There are five chapters for this thesis. Chapter 1 sets the introduction and background, and
includes a briefing of the study’s research questions, hypothesis and the rationale for
conducting the study. Chapter 1 concludes with a short note on ethical considerations that
have been adhered to in this study and the expected contributions this study seeks to make.
Chapter 2 presents a comprehensive review of the extant literature on knowledge sharing
with the aim of clearly delineating the gap in the literature that this study aims to address.
Chapter 3 states the research methodology and design, and introduces the research
framework, whereas Chapter 4 provides the data analysis techniques and results. Chapter
5, the final chapter, discusses the results and concludes with implications for practice and
future research.
1.5.3 Ethical considerations
Confidentiality, anonymity, and consent were key ethical issues addressed in this research.
The student researcher complied with all the ethical standards set by the University of
13
Newcastle, Australia. This study treats all information collected from respondents with
confidentiality and has assured respondents through the use of an anonymous online
survey, wherein the respondents cannot be identified. The disclosure of individual
participants’ demographics and unique characteristics are also protected by the ethics
protocol (H-2015-0383) of this study.
Participation in the research is voluntary and as such organizations in the HKCI were emailed
with an invitation to participate in this study. By forwarding the invitational email and the
link to the study’s online questionnaire in the Participant Information Sheet document (See
Appendix for details), to senior executive who is in the position of a Manager/Top
executive/business ownership or owner of a family owned business in the HKCI, the
respective organisation may provide consent and then participate in this study.
Consentingparticipants were invited to complete an online questionnaire on knowledge
sharing in the HK clothing industry by clicking on the web link provided at the end of the
Participant Information Sheet in the invitational email. The information collected was
stored securely and remains strictly confidential. The data collected were kept in an
aggregate form and no individual or identifiable information would be released to others.
All materials collected will be available to the researcher for five years. No compensation
was given for participation. Ethical standards were thus observed as per the University’s
guidelines.
1.6 Expected Contributions
The findings from this study contribute towards a better understanding of the importance
of knowledge sharing in the context of FCBs in HKCI. The findings also form the basis for
related further studies in other business sectors as well as in other countries in relation to
14
the relationships covered in this study. This could also provide a wide range of valid data for
HKCI practitioners to develop knowledge sharing strategies.
In terms of policy contributions this study highlights the importance of training for achieving
better knowledge sharing outcomes, especially in FCBs and in developing organizational
policies to support this.
From a theoretical perspective, the use of the AMO model to explain how certain HRM
practices impact knowledge sharing is a key contribution to the literature on knowledge
sharing. Although some of the AMO factors are commonly used to explain the effect of
knowledge sharing, whether this model has been fully evaluated in the knowledge-sharing
field remains unclear. Hence, this study opens this future stream of analyzing a set of HRM
practices and its impact on knowledge sharing in a range of contexts
Finally, in terms of practical contributions for managers, this research explores the effect of
management, leadership, incentive systems, trust, and FCBs on knowledge sharing in HKCI.
Knowledge sharing needs to be understood in terms of both the formal and informal modes
in relation to the moderating effect of FCBs. Insights are derived for managers to
understand the critical success factors for future strategic planning purposes and allocating
resources that will enhance knowledge sharing behaviors and create opportunities for
sustained competitive advantages.
1.7 Chapter Summary
To summarize, this research aims to explore FCBs’ moderating effect on knowledge sharing
and aims to fill a gap in the literature on knowledge management and HRM by focusing on
15
knowledge sharing in the HKCI. Contributions at theoretical and managerial levels have
been identified. The changing business environment is forcing family owned clothing
industry firms to look for suitable strategies to improve their competitive advantages. By
considering the ownership type (FCBs) in the analysis, knowledge sharing understanding in
HKCI may help firms develop their capacity for business succession, especially in the
direction of intergenerational leadership.
16
Chapter 2
Literature Review
2.1 Introduction
The chapter develops the study’s research questions following a review of the literature.
Exploring how the relationship between knowledge sharing affects the performance in
family-controlled businesses (FCBs) by employing the commonly understood performance
rubric: the ability, motivation and opportunity (AMO) framework (Blumberg & Pringle,
1982; Vroom, 1964) is specifically reviewed. This is a widely used framework in the field of
HRM for analyzing performance drivers such as providing training for workers (ability),
offering adequate incentive systems (motivation), and creating a trusting environment
(opportunity) for employees to have a positive impact on knowledge sharing behaviors of
employees.
Knowledge has been regarded as a critical resource that can be shared through both
informal and formal ways (Nonaka, 1995). People communicate information, experiences,
insights, in different ways (Liao, 2007). While there is some recent interest that considers
the impact of HRM on a range of knowledge management processes (e.g. knowledge
sharing and knowledge transfer), there is little evidence of this gap being explored in the
context of FCBs in an Asian economy such as Hong Kong (Cabrera & Cabrera, 2005;
Minbaeva, Foss & Snell, 2009; Minbaeva et al., 2003; Minbaeva, 2013). To fill this
theoretical gap, the moderating effects of FCBs on knowledge sharing is included in the
research framework.
17
The rest of the chapter is structured as follows. The first part examines the theoretical
foundations of knowledge management (KM) and, more specifically, knowledge sharing.
The second part discusses the AMO model and its relationship with knowledge sharing.
The third part examines the process of influencing knowledge sharing and the intensity of
collaborative relationships between the AMO model and leadership patterns in FCBs. The
fourth part identifies the gaps in literature, leading to the development of the study’s
questions and hypotheses, which are tested with empirical data collected through
questionnaires.
2. 2. Knowledge Management and its core processes
Jasphapara (2004, p. 63) defines knowledge management (KM) as “effective learning
processed in relation to exploration, exploitation and sharing of individual knowledge
(tacit and explicit) that use appropriate technology and cultural environment to enhance
an organization’s intellectual capital and performance.” KM describes the processes and
strategies of collecting, transferring, utilizing, and protecting knowledge that can create
and provide sustainable competitive advantage (Kululanga and McCaffer, 2001; Lin,
2007b). KM practice includes identifying and managing new and existing knowledge to
develop new opportunities (Jarrar, 2002). The critical factors of this process are creating a
learning process, disseminating knowledge, and measuring knowledge capital in relation
to the total assets of an organization (Argot, 1999; Bontis et al., 2010; Sveiby and Risling,
1986).
Every individual’s knowledge sharing contributes to the success of a firm’s KM (Apshvalka
and Wendorff, 2005). Knowledge types can be broadly classified into two: tacit (i.e.,
informal) and explicit (i.e., formal). Tacit knowledge is highly personal and implanted in an
18
individual’s daily work practices (Nonaka, 1998, 2008), trust, and face-to-face interactions.
Informal structures also expedite tacit knowledge sharing between individuals (Koskinen
et al., 2003; Dholakia, 2002). By contrast, explicit knowledge is systematically and formally
stored in databases or libraries (Polanyi, 1966 cited in Nonaka, 1994) and manuals or
computer files (Aman, 2010; Ismail and Ashmiza, 2012). Tacit knowledge is difficult to
transmit because of its inherently instinctive and subjective nature (Richey and Klein,
2010).
Haldin-Herrgard (2000) point out that the diffusion of tacit knowledge is difficult through
modes such as lectures, textbooks, or manuals. This knowledge type is best transferred
through observations (Szulanzki, 1996; Argote et al., 2003). The type of knowledge under
consideration is essential in understanding to how such knowledge is shared. For example,
sharing explicit knowledge is easier via developmental and formal training than tacit
knowledge.
Polanyi (1996) argues that tacit knowledge is not a separate from knowledge and that
such a form of knowledge is critical in knowledge integration mechanisms. Some
researchers disagree with Polanyi and suggest that knowledge can be categorized into
tacit and explicit forms (Jasphapara, 2004; Mooradian, 2005). Dholakia et al. (2002) states
that explicit knowledge is easier to codify formally than tacit knowledge. Reportedly, 90%
of people’s knowledge is tacit knowledge (Wah, 1899; Lee, 2000). Swap et al. (2001) focus
on the sharing of tacit knowledge and suggested that it is perceived as a more critical form
than explicit knowledge. Smith (2001) highlights that tacit knowledge is vital in attracting
and retaining talented, loyal, and productive workforce. Huang et al. (2011) state that
sharing tacit knowledge frequently occurs in informal situations between individuals in
close relationships. Next, the formal and informal nature of knowledge sharing methods
(Smith, 2001) is discussed in the next section.
19
Nonaka and Takeuchi (1995) proposed the socialization, externalization, combination, and
internalization (SECI) model, a framework for developing methods to convert tacit
knowledge into explicit knowledge and vice versa in a continuous and cyclical manner.
This model consists of four modes of knowledge transformation (See Figure 2.2 for
details). Socialization is about sharing experiences through informal or social interactions.
Externalization is when an individual gains knowledge through formal and codified forms
such as written manuals or through information technologies. Combination occurs when
explicit knowledge gets converted to codified or systematic sets of knowledge through a
range of sources. Internalization occurs when explicit knowledge is modified internally by
an individual, often involving interaction with aspects of the individual’s tacit knowledge
with the new explicit knowledge received.
Figure 2.2 The SECI model (Nonaka and Takeuchi, 1995, p. 80)
Managing such knowledge is crucial for developing strategic resources (Jones, 2003; Lee
and Yang, 2007b).
20
2.2.1 Knowledge sharing processes and its impact on firm performance
Although knowledge is widely collected and held through individual transmissions
in a firm, knowledge sharing is an essential process of KM, as it is the flow and
application of knowledge rather than its stock that creates opportunities for
sustained competitive advantage for a firm. Eisenhardt and Santos (2002) find
that the systematic promotion of knowledge sharing implementation is critical for
successful implementation of KM. Hsu (2008) highlights that knowledge sharing
also supports innovation strategies. Knowledge sharing occurs through formal
and informal means. For example, structured and explicit forms of knowledge can
be transferred through formal knowledge sharing (Alavi et al., 2005; Leonard-
Barton, 1995; Zahra et al., 2006). Similarly, unstructured or tacit forms of
knowledge is collectively held by individuals and is transferred through informal
knowledge sharing mechanisms (Lave and Wenger, 1991; Nonaka and Konno,
1998; Orlikowski, 2002). Both these approaches are highly relevant in attracting
and retaining talented, loyal, and productive workforce (Smith, 2000).
To enhance knowledge-sharing performance and avoid repeating the same
mistakes, firms should share their learnings, experiences, information, and
knowledge by implementing KM strategies. Successful KM strategies can
determine a firm’s and long-term sustainable competitive advantage (Leonard-
Barton, 1995; Drucker et al., 1998; Hooff and Ridder, 2004). It has been widely
noted in the extant literature that knowledge sharing requires individual
employees engaging in behaviors that are conducive to knowledge sharing
(Ardichvili et al., 2003; Ipe, 2003), as it is nearly impossible to competently record
all knowledge (Bhatt, 2001; Horwitch and Armacost, 2002; Rooke and Clark,
2005). As noted in Witherspoon et al.’s (2013) meta-analytic review, individual
21
employees’ attitudes and intentions are regarded as vital in their knowledge
sharing behaviours. Furthermore, informal approaches to knowledge sharing
relies extensively on a trust-based environment that can be collectively created
by an organisation’s employees, leaders and managers (Davison, 2013; Koskinen
et al., 2003). Knowledge as information possessed by individuals consists of
expertise, facts, judgements, and ideas relevant to the performance of
individuals, teams, and firms (Alavi and Leidner, 2001; Bartol and Srivastava,
2002). Tacit knowledge and competitive advantages can often be adversely
impacted when employees leave or retire (Reid, 2003; Sheehan et al., 2005;
Tsoukas, 1996). Knowledge sharing in organizations generally focuses on
communicating and transferring knowledge explicit forms of knowledge from
individual into tacit forms for its productive use. Individuals may also exchange
knowledge through discussions or social interactions to develop new knowledge
(Abudullah et al., 2009; Van den Hooff and De Leeuw van Weenen, 2004).
Based on the review of literature, it is apparent that knowledge sharing research
is grounded in theories of knowledge integration and creation (Alavi and Leidner,
2001; Grant, 1996; Nonaka and Toyama, 2003; Nonaka and Takeuchi, 1995;
Jasphapara, 2004). A number of studies have indicated that reasons affecting
knowledge sharing include reasons such as leadership, management, training for
workers, incentive system, and trust (Chua et al., 2004; Van den Hooff and
Hendrix, 2004; Wong and Aspinwall, 2005; Yang, 2007).
Nonaka and Takeuchi (1995) examined knowledge sharing processes and found
that knowledge creation can be enhanced by the proper attitude of people
towards knowledge sharing. Developing a knowledge sharing culture facilitates
knowledge generation, which helps firms to survive in today’s competitive
22
environment. Thus, there is a need to consider organisational practices such as its
HRM practices that may facilitate in creating a culture that is conducive to
knowledge generation, sharing and integration into an organisation’s daily
productive routines.
Knowledge sharing has several benefits that have been identified in the
literature. For example, Alavi (1999) demonstrates that knowledge sharing
enables employees to contribute to knowledge application and innovation and
ultimately to a firm’s competitive advantage. Knowledge sharing between
employees and across teams allows the capitalization of knowledge-based
resources (Cabrera and Cabrera, 2005; Damodaran and Olphert, 2000; Davenport
and Prusak, 1998). However, it is not always easy to share knowledge. Ardichvili
et al. (2003, p. 70) explored knowledge sharing processes and confirmed that it
can be curtailed by the “fear of criticism” and “fear of misleading others”. The
perception of a virtual community of knowledge sharers actively motivates
individuals to share knowledge (Ardichvili, 2003; Chiu et al., 2006; Wenger et al.,
2002). Despite evidence that knowledge sharing positively contributes to
innovation, motivating people to share has been noted as a key challenge for
reasons outlined above (Ford and Chan, 2003). Appropriately implementing
knowledge sharing is therefore important for firms in a dynamic business
environment to succeed (Kedia, Harveston, and Triandis, 2002).
Firms that can generate and manage unique knowledge tend to create
sustainable and inimitable competitive advantages (Barney, 1991; Grant, 1991;
Lank, 1997). Sharing the best practices within an organization can also influence
the ability of the organization to create these advantages (Szulanski, 1996). The
value of knowledge can be expanded through appropriate knowledge sharing, as
23
it enables improvements in work quality, problem-solving and decision-making
skills (Alavi and Leidner, 1999). By creating and sharing knowledge faster than
competitors, firms can develop competitive advantages every day (Gupta and
Govindarajan, 2000). Despite the acknowledged benefits, knowledge sharing still
remains one of the greatest challenges of KM as employees are often unwilling to
share their knowledge and expertise (Issa and Haddad, 2008). Mitchell (2003)
notes knowledge creation if often as a result of effective knowledge sharing and
that ineffective KM practices may adversely impact a firm’s competitive
advantage (Sarvay, 1999).
2.3 Research on Family-controlled businesses
In the literature on FCBs, there is a clear distinction between FCBs and non-FCBs
populations. Unlike non-FCB firms, FCBs are run and operated by its family
members. Sit and Wang (1898) found that a significant part of management
decision-making falls on families in small to medium-sized Chinese firms in Hong
Kong. In the present research, a FCBs are defined as a business in which the
majority of management stake lies in the hands of a family and its family
members are directly involved in the workings of the firm. Lansberg (1988)
highlights that by not carefully engaging in succession planning at various levels in
a FCB, the overall performance of the FCBs comprising of owners, family
members, and managers will be adversely affected. FCBs should be treated as a
system (Greenberg, 1977; Kantor and Lehr, 1975; Wertheim, 1973) that has
interdependencies and interrelationships between the key decision makers. Dyer
(1986) advocates that all families follow patterned roles as means of interacting
with the explicit and implicit rules that have been created over the years through
24
their family culture. This section reviews the literature on FCBs to identify
concepts that are relevant to studying Chinese FCBs in the context of the HKCI.
Generally, the symbolic management of the members of FCBs and the culture in
such firms is largely shaped and pursued by family members of the FCB unit. The
wealth and knowledge thus created needs to be transferred on to the next
generation for making the business potentially sustainable across generations
(Chua et al., 1999; Molly et al., 2010). The features and cultural characteristics of
FCBs are defined by paternalistic values (Chirico and Nordqvist, 2010).
Turner (1980) found that 93% of factory workers and nearly 70% of employees in
Hong Kong trust the leaders and managers of FCBs. Nearly 70% of those workers
also agreed that there exists teamwork between management and workers.
Redding (1989) concurs with Turner (1980) and notes that managing family
interest is the top priority of FCBs because of “family obligations” as the FCB is
often viewed as a “family possession.” Chinese FCBs tend to recruit less
competent relatives compared to more capable professional managers because
of the need to care for family members is embedded in part of their family’s
obligations and culture. This approach does not always effectively deliver on the
business goals and performance.
Furthermore, in traditional Chinese culture, promotions are based on seniority
(i.e., age) rather than merit. Rewarding seniority conveys loyalty and
commitment (Redding, 1979, 1984). In Hong Kong, the new generation of young
executives also view seniority as an important factor for loyalty and status in
clothing businesses (Redding, 1984; Chiu et al., 2002). Through a sustained
25
research program on the characteristics of typical Chinese-owned firms (Redding,
1979, 1984) summarized the following key characteristics:
1) centralization of power through the boss;
2) friendly relationships with suppliers and customers;
3) high flexibility;
4) minimal management control on individual performance;
5) quick decision-making;
6) limited reliance on logical analysis and rationality;
7) patronage systems; and
8) informal organization structure
Chinese FCBs in Hong Kong typically manage people using belief systems, such as
having non-rational forms of control and where feelings of senior management
are given greater priority (Redding, 1990, p. 42). Such a management style is
more autocratic than in the past (Redding & Richardson, 1986), though now it has
been gradually heading toward more of a decentralized approach. The
management system of FCBs is largely informal, loosely structured and based on
the interpretation of its managers and employers (Redding, 1979, 1984).
Carney (2005) and Sharma et al. (1997) state that Chinese FCBs focus on people,
highlighting the management of relationships. The level of organizational control
required at different stages in an organization’s life cycle varies. Successful
transitions of control are according to phases of expansion, management
succession, transitions of FCBs into public limited firms, or affected by changes in
the external environment. These factors affect control systems in Chinese FCBs.
Zuo (2002), further states that the Guanxi orientation in relation to Chinese
26
culture focuses on developing harmonious relations with each other for
maintaining a strong identity of Chinese FCBs (Dholakia, 2002).
While adopting a transactional approach is essential in achieving control-oriented
AK 119 4.4824 .09950 1.08547 -.056 .222 -.205 .440
Valid N
(listwise)
119
Next, the normality of data for each construct was examined. The distribution of data must
correspond to a normal distribution to achieve normality (Hair et al. 2006). The normality
assumption is assessed to investigate the approximate distribution of the observed variables (by
examining statistics such as histogram, stem-and leaf-plots, boxplot, detrended normal plots,
skewness and kurtosis) (Bagozzi and Baumgatner, 1994), as well as figures, such as normal
probability plots of ordinary, studentized, or Jackknife residuals. Furthermore, goodness-of-fit
tests, such as the Kolmogorov–Smirnov test (Stephens, 1974, Looney et al.1985), and, in the
case of small sample sizes (e.g., n<50), the Shapiro–Wilks (1965) test, can also be performed.
95
The results from statistical data analysis are presented in Table 4.6.1a. To examine normality
with detrended probability plots and the normal probability, the Kolmogorov–Smirnov statistic
is used with a Lilliefors significance level in this study. As all statistical data are assumed to be
greater than .05, this indicates that all data are at a significant level. Furthermore, as the
sample size is more than 100 in this research, the results of the Shapiro–Wilk statistics are also
significant.
Figure 4.6 Summary of Histograms for all Variables in the Model
96
*ATW = Average Training for workers *AIS= Average incentive systems *AT= Average Trust *AQ= Family control business (FCBs) *AK= Average knowledge sharing Descriptive data of FCBs and Non-FCBs in the HKCI
Insights on knowledge-sharing practices in the HKCI may be obtained from the distinct effects of
FCBs and Non-FCBs. The two groups of demographic data of FCBs and Non-FCBs in HKCI are
presented in Table 4.6. As shown in Table 4.6, some significant differences were found between
FCBs and Non-FCBs in relation to business performance. FCBs performed better than Non-FCBs
in terms of average sales of more than HK$10 million per year, and FCBs did relatively well in
terms of increase in sales from 10%-70%. However, other demographic data did not offer any
conclusive insights to clearly demonstrate the influence of FCBs on knowledge-sharing practices
in the HKCI-related industries. In terms of the percentage increase in labour productivity (the
contribution of on-duty workers) in the past three years, not much difference in performance
was found between FCBs and Non-FCBs.
97
Table 4.6b Descriptive Analysis of FCBs and Non-FCBs in the HKCI
` Measurement Items
Response
Percent
Response
Count
(Total
responses: 119)
Response
Percent
Response
Count
(Total
responses: 119)
1.CEO 0 0 11.5 6
2. GENERAL 22.4 15 9.6 5
3. MANAGEING
DIRECTOR 17.9 12 15.4 8
4. COO 0 0 1.5 1
5. Others 46.3 31 59.6 31
1. =or <1 19.4 13 27 14
2. >1 to 5 17.9 12 17.3 9
3. >5 to 10 10.4 7 1.9 1
4. >10 to 15 10.4 7 13.5 7
5. >15 41.8 28 40.4 21
1. =or <50 44.8 30 57.7 30
2. 51-200 13.4 9 9.6 5
3. 201-1,000 20.9 14 9.6 5
4. 1,001-3,000 9 6 1.9 1
5. > 3,000 11.9 8 19.2 10
1. Manufacturing 40.3 27 28.9 15
2. Product (owned 20.9 14 30.8 16
3. Product Trading 25.4 17 21.2 11
4. Service (material 13.4 9 19.2 10
1. = or < 1 26.9 18 36.5 19
2. >1 to 10 25.4 17 23.1 12
3. >10 to 50 13.4 9 5.8 3
4. > 50 to 100 14.9 10 13.5 7
5. > 100 19.4 13 21.2 11
1. = or < 10% 64.2 43 73.1 38
2. >10% to 40% 29.9 20 21.2 11
3. >40% to 70% 4.5 3 1.9 1
4. >70% -100% 1.5 1 3.8 2
5. > 100% 0 0 0 0
1. = or < 10% 70.2 47 76.9 40
2. >10% to 40% 23.9 16 21.2 11
3. >40% to 70% 4.5 3 0 0
4. >70% -100% 1.5 1 1.9 1
5. > 100% 0 0 0 0
The% increase of labour
productivity ( the revenue
contributed by an on-duty workers
) in the past 3 years.
Position in your enterprise
Number of year(s) your enterprise
has been operating?
Family
(52 resondents)(67 repondents)
Non-Family
Number of employees?
Business Category that your firm
belongs to the clothing industry
Average sales per year in the past
3 years (HK$ million(s))?
The % increase of sales in the past
3 years
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4.7. Summary of descriptive data
The analysis of the independent variables shows that the mean values of all measured
constructs were high (ranging between 4.89 and 5.04 on a seven-point Likert scale).
The outcomes of Knowledge-Sharing factors demonstrated that employees in the HKCI
may effectively share and gather knowledge among their peers and managers the
following section introduces the tests of correlations among the variables and checks
the validity and reliability of the constructs.
4.8 Reliability and validity of measured data
To test the theoretical constructs in the model, reliability and validity tests were
carried out. The relationship between reliability and validity can be treated as true
score model (Malhotra, 2010). Theoretical constructs can only be measured through
detectable measures or indicators that determine the full theoretical meaning of the
core construct; thus, multiple indicators of a construct are required (Steenkamp and
Baumgartner, 2000). Both validity and reliability are observed in the current study by
using SPSS, as it allows researchers to test the impacts of dormant variables on
observed variables and to determine the partial error (Baumgartner and Homburg,
1996: Bollen, 1989).
4.8.1. Validity of measured data
Before the hypothesis test, factor analysis was utilized in this study to examine the
validation of variables through key component analysis. The tests were run using SPSS
to analyse the correlations among the key variables (incentive systems, training for
workers, knowledge sharing, trust, and FCBs). This key variable is purposefully
produced by SPSS for subsequent multiple regression analyses. The criteria and
technique of measurements are clarified below.
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1. Principal component analysis was used as a technique for factor extraction.
Eigenvalues of (> 1.0) identify the amount of differences in the variables accounted by
a specific factor. A component was framed as a solitary variable, as its Eigenvalue was
higher than 1, thus meeting the accompanying two criteria.
2. Kaiser–Meyer Olkin (KMO) was used to gauge different critical relationships
among various variables (Kaiser, 1974). KMO was calculated as a measure somewhere
around 0 and 1, wherein an estimation of near 1 indicates an abnormal state of
correlation between variables. Tabachnick and Findell (2007), as referred to in
Williams et al., 2010, recommended that outcomes larger than .50 represent a
satisfactory rate of correlation.
3. Bartlett's test of sphericity was utilized to examine the significance of the
components (smaller than .05), which were distinguished in the component analysis.
4.8.2. Validity of independent and dependent variables
The validity of independent and dependent constructs was examined using KMO,
which measures the sample adequacy (check), and Barlett's test of sphericity was
adopted to examine the variables (incentive systems, training for workers, trust,
knowledge sharing, and FCBs). As demonstrated in Table 4.9.2a and 4.9.2b, KMO tests
have the estimation of equivalent to and higher than the measure (>.50 or equivalent
to .50) and the significant value of Barlett's test of Sphericity is .00 (paradigm smaller
than .05). The outcomes indicate that the gathered data of independent and
dependent variables are critical in the test and are acceptable for further factual
analysis.
Meanwhile, the results of factor analysis affirm that FCBs and KNOWLEDGE SHARING
(formal and informal) had "component loadings" larger than .50. In this way, the
individual key components for independent and dependent variables contributed to
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their respective constructs and were framed as a solitary variable separately (Hair et
al., 2006)
Table 4.8.2 Factor Analysis of Variables
Factors Items
Component
Matrix
Cronbach's
Alpha KMO
Barlett's
Test (Sig)
Ability ( Training for
workers)
TW1 .865
.939 .892 .000
TW2 .917
TW3 .923
TW4 .883
TW5 .901
Motivation ( Incentive
Systems)
IS1 .833
.945 .880 .000
IS2 .915
IS3 .909
IS4 .902
IS5 .918
Oportunity ( Trust)
T1 .910
.947 .900 .000
T2 .898
T3 .847
T4 .888
T5 .892
T6 .907
FCBs FMP .875
.690 .500 .000 FOE .875
Knowledge sharing
(Formal and Informal)
K1 .769
.950 .913 .000
K2 .819
K3 .811
K4 .779
K5 .885
K6 .849
K7 .877
K8 .840
K9 .815
K10 .861
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4.9. Reliability analysis
Reliability reflects the extent to which an indicator is free from random errors
(Diamantopoulos and Siguaw, 2000; Malhotra, 2007; Hair et al., 2009).
A typical statistical approach to test internal consistency would be the Cronbach’s
alpha test (Shin et al., 2000). Alpha values <.60 are thought to be weak, whereas
values (the correlation scores) ≥.7 are considered robust for this research (Nunnally,
1978). Results of the reliability tests to measure training for workers, trust, knowledge
sharing and incentive systems are presented below in Table 4.8.2.
4.9.1. Ability (Training for Workers)
As shown in Table 4.8.2, the alpha value of training for workers was .939, higher than
the criterion value (≥.7) suggested by Nunnally (1978). The analysis shows that the
gathered data is robust, and that this item scale (TW1-5) has a strong internal
reliability for further statistical analysis. As stated by Lubans et al. (2010), the scale has
more items than necessary or has been repeating in the scale for reliability test if the
alpha value is >.9. Accordingly, some repetitive items in this scale might be reduced in
further studies.
4.9.2. Motivation (Incentive Systems)
As shown in Table 4.8.2, the alpha value of incentive systems was .945, higher than the
criterion value (≥.70) suggested by Nunnally (1978). This outcome demonstrates that
the data collected are statistically robust, and that this item scale (IS1-5) has solid
inner dependability for further measurable examination. As per Leech et al. (2010), an
alpha value >.9 indicates that the items in the scale are monotonous for the reliability
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test, or that the scale has a larger number of items than necessary. Accordingly, some
redundant items in this scale might be excluded in further studies.
4.9.3. Opportunity (Trust)
As shown in Table 4.8.2, the alpha value of trust was .947, thus meeting the criterion
(≥0.70) suggested by Nunnally (1978). This outcome demonstrates that the data
gathered are statistically robust, and that the (T1-5) item scale has strong internal
reliability for further statistical analysis. As per Leech et al. (2010), an alpha value >.9
indicates that the items in the scale are monotonous for the reliability test, or that the
scale has a larger number of items than necessary. Accordingly, some tedious items in
this scale might be excluded in further studies.
4.9.4. Knowledge Sharing
The measurement items of knowledge sharing, including formal and informal
knowledge sharing were tested for Cronbach’s alpha reliability test. The alpha values
of formal and informal knowledge sharing were both over .95, thus meeting the
criterion of high reliability (>.70) suggested by Nunnally (1978). As indicated in Table
4.8.2, the data collected are statistically robust, and the items scale (K1-10) has a
satisfactory internal reliability for undertaking future statistical analysis.
Further analysis of the independent variables revealed a high level of correlation
among trust, incentive systems, and training for workers. The Pearson’s correlation
coefficient of .680 between knowledge sharing and trust is shown in Table 4.9.5b.
While Pearson’s correlation of .649 was found between knowledge sharing and
incentive systems at a significance level of .05 vs. .01 level in both participations in
trust and incentive systems were highly positively related to knowledge sharing and
training for workers.
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The significant correlations between the supporting AMO model may provide some
indications of the correlations among ability (training for workers), motivation
(incentive systems), opportunity(trust), and knowledge sharing as well as FCBs;
specifically, incentive systems and trust were more highly associated to knowledge
sharing. As stated in Chapter 3, the impact of AMO model on knowledge sharing will
be used for hypothesis testing in the following section.
4.9.5 Discriminant and Construct validity
Discriminant validity refers to the degree to which two variables are statistically
distinct from each other (Yau et al. 1998; Malhotra 2009). Discriminant validity may be
achieved when various latent factors via a cross-correlation between the various
indicators individually are not too high, just fairly strong (Kline 1998; Abbad, Morris
and De Nahlik 2009). The acceptable cut off level (the correlation coefficient), r of .85
is accepted generally for evaluating discriminant validity (Hultén 2007). Moreover, the
correlations between indicators must not be over their reliability estimates, i.e. the
coefficient alpha of each scale (Gaski and Nevin 1985; O'Cass and Grace 2008).
As such, the coefficients of correlation between Cronbach’s Alpha of the measured
constructs were shown in Table 4.9.5b. The correlation coefficients are shown in the
diagonal of lower matrix. Each of these coefficients were not over .85, so all
constructs were not significantly correlated. Further, the bolded values, namely
Cronbach’s Alpha, were on the diagonal, and they exceeded the correlation
coefficients shown in Table 4.9.5b. The above evidence verified construct validity.
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Table 4.9.5 Correlations of Factors in this Study
Correlations
AQ ATW AIS AT AK
AQ
Pearson Correlation 1
Sig. (2-tailed)
N 119
ATW
Pearson Correlation .133 1
Sig. (2-tailed) .148
N 119 119
AIS
Pearson Correlation .129 .766** 1
Sig. (2-tailed) .162 .000
N 119 119 119
AT
Pearson Correlation .155 .633** .734** 1
Sig. (2-tailed) .093 .000 .000
N 119 119 119 119
AK
Pearson Correlation .045 .592** .649** .680** 1
Sig. (2-tailed) .626 .000 .000 .000
N 119 119 119 119 119
** Correlation is significant at the .01 level (2-tailed).
Based on the results from this preliminary analysis, all measured constructs achieved
satisfactory validity and reliability and fulfilled regression analysis assumptions. On this
basis, they are suitable for hypotheses testing, which is discussed in the next section.
4.10. Hypothesis Testing
As indicated earlier in Chapter 3, the study’s six hypotheses were tested. After
carrying out tests for validity and reliability, the data collected were subjected
to hypothesis testing, and the results are shown in Table 4.10a.
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Table 4.10a Multicollinearity Test Results in Model 1
Coefficients
a. Dependent Variable: DV: Knowledge Sharing
The result of Model 1 (i.e., Training for Workers, Incentive Systems, and Trust)
are significant, VIF was not significant as VIF is between 2.505 to 3.268 which
is less than 10. Hence there are no multicollinearity issues and the null
2007; Zahra et al., 2007). Thus, investing in training for workers is critical for future
success of FCBs and sustaining competitive advantages in rapidly their changing market
(Zahra, 2005). Measures, such as ISO900, to guide the implementation of standards in
training programs are needed.
Training programs may also provide incentives for enhancing team spirit, which, in turn,
can improve a firm’s positive culture and boost its performance (Fox & Guyer, 1979;
Kahan, 1973: Shih et al., 2006). Training programs such as team building, cross-training,
and harnessing technological developments, can increase the levels of cognitive,
structural, and relational social capital as well as stimulate knowledge-sharing
behaviours (Cabrera & Cabrera,2005; Kang et al., 2003). Different reports can be
generated for the purposes of management and marketing analyses.
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To build relationships, team-based trainings are important for the transfer of
knowledge (Fleishman, 1980; Axelrod, 1984 Van Lange et al., 1992; Cabrera & Cabrera,
2002). Cross-training also increases the interactions and allows for a common language
to enhance such interactions (Kramer & Brewer, 1984; Schneider, 1992; Cabrera &
Cabrera, 2002; Cabrera & Cabrera, 2005). Business managers not only seek to improve
business performance, but they also maintain a useful knowledge base for securing
future growth (Singh, 2008). Training to help people use the systems more efficiently
and for further reducing costs can be helpful (Cabrera & Cabrera, 2002).
Second, the implementation of incentive systems has been identified as influential
factor of the AMO model. Rewarding and recognizing these knowledge-sharing
behaviours sends a strong signal to the employees that the organization values
knowledge-sharing in FCBs (Cabrera & Cabrera, 2005). An incentive system,
incorporating extrinsic (e.g. Money, avoidance of punishment etc.) and intrinsic (praise)
rewards, (Foss et al., 2009), can motivate people to practice reciprocal behaviours of
knowledge sharing (Fehr & Fischbacher, 2002). Reciprocal behaviour is important,
because it affects the fundamental methods in the functioning of markets, firms,
incentives, and collective actions (Fehr & Fischbacher, 2002). However, some
researchers found that incentive systems may reduce any corresponding increases in
efforts as it can create a hostile atmosphere and even induce negative reciprocity
(Bewley, 1999; Fehr & Fischbacher, 2002).
Third, trust has been identified as an influential factor in fostering knowledge sharing
behaviours. Thus, it is critical for managers to improve and develop the strategy of
team building. Long-term relationships between managers and peers are needed to
improve the knowledge-sharing performance within firms. Trust can be improved by
team-building strategies to enhance employees’ willingness to share knowledge.
Employees may, through knowledge sharing, reduce the supervisor’s expert power
through team spirit and create a knowledge-sharing atmosphere in a firm. Trust can
also improve the efficiency of knowledge exchange and mutual understanding among
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peers, managers and staff, as proven by results between trust and knowledge sharing
(Abrams et al., 2003; Moravian et al., 2006), especially in FCBs.
Furthermore, Others have argued that trust is the least costly and the most effective
method to encourage people to share their knowledge (Dyer & Singh, 1998; Sharratt
& Usoro, 2003). For this reason, trust treats as a solution to motivate employee to
share knowledge. When individual views a firm as enhancing trustworthy values, such
as honesty, reliability and
mutual reciprocity, the commitment seems to be a greater standard of motivation to
share individual knowledge within that firm (Sharratt & Usoro, 2003). Thus, high levels
of interpersonal trust relates to high levels of willingness to share knowledge
(Kalantzis & Cope, 2003). If employees work in a trusting environment, wherein a firm
recognizes and values their contributions and where they can count on reciprocity,
then they become naturally more willing to share their knowledge (Cabrera & Cabrera,
2005). Thus, for fostering knowledge sharing, organizations must create a trusting
environment.
Some researchers have demonstrated that FCBs may have too much personalized
control. For example, Hong Kong partners may not be willing to share their
management and marketing knowledge in the HKCI, which may impact the growth of
the latter (Merck & Yeung, 2003). Therefore, the management of FCBs may require
appointment of Non-FCB members into the board of directors of FCBs. Such a move
may send a signal to the employees that high abilities of the employees are highly
respected and needed in FCBs.
5.8 Contributions
The major contributions of this study can be summarized as follows. First, knowledge
sharing is driven by the AMO factors. Second, the study fills the gap in the literature
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concerning the role of FCBs as a moderating factor affecting the relationship of the AMO
model and knowledge sharing. Third, the study highlights the role of managers in FCBs
in relation to the promotion of the AMO factors and enhancement of the competitive
advantages by sustaining long-term improvements. Firms may provide training for
workers to encourage the development of knowledge sharing because it is an important
determinant of the intention to share knowledge. The development of an affective trust
can also be nurtured during such trainings, which will encourage employees to
consistently demonstrate a genuine concern for their colleagues and act in ways that is
in the best interests of their colleagues. One way to encourage managers and peers to
act in this way is to provide them with an environment that fosters trust and friendly
cooperation, and in which rewards are collective rather than individualistic. For
example, incentive systems to reward group success may motivate knowledge sharing
and foster team spirit within a firm.
Finally, the distinct characteristics of FCBs is to facilitate knowledge sharing with a
strong sense of identity (Lansberg, 1999). Knowledge sharing occurs when people who
share a common purpose, experience similar problems come together to exchange
ideas. Although knowledge is very important, FCBs may have several characteristics that
can potentially inhibit such exchanges. In addition, family members may not have the
same levels of entrepreneurial spirt (Merck & Yeung, 2003). Family rivalries may just
limit some senior members to share knowledge with the next generation. In fact, some
of next generation managers may not want to learn at all. These rivalries are common
and happen in family members or non-family members in FCBs (Grote, 2003). This
finding is consistent with the findings of past studies (Zahra, 2007; Gomez–Mejia et al.,
2001).
5.9 Limitations and future research
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The first limitation pertains to the research context, as all data were collected in Hong
Kong. Trading behaviours in Hong Kong may not be generalizable to other Chinese
business communities. Other countries, such as Singapore and Taiwan, may be further
considered in future research focused on firms within the Asia-Pacific Region.
The second limitation relates to the research context. The adopted questionnaire for
this study was distributed online, using a convenience sampling approach to collect data
from the HKCI firms, targeting participants, such as CEOs, top management, and senior
managers. With this profile, it may be difficult to obtain good response rates.
Furthermore, convenient sampling is problematic in that it may not be representative
of the entire population being examined.
Third, the quantitative survey method measures the strengths of the statistical
relationships analysed and may not provide a conclusive direction of the cause and
effects involved. In addition, external factors, such as staff turnover, benefits and salary
packages, as well as market needs are significant factors that influence training for
workers, incentive systems, and trust (Baker et al., 1988; Batt, 2002). Hence, this study
may be unable to comment on the effect of factors that were not considered.
Fourth, the design of this study uses small a sample size that may be unable to
sufficiently support the results. This also creates high multicollinearity in all three
interactions. Nevertheless, this study used the Process Macro in SPSS is a tool to
bootstrap the sample from 100 to 1000 units, and it helps solve the high
multicollinearity problem encountered in a multiple regression analysis (Preacher &
Hayes, 2008; Nimon et al., 2010).
Fifth, the data were obtained from a single source (i.e., managers or top management)
and a single method (i.e., Likert scale-based questionnaire). Therefore, common-
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method biases may be present, because respondents might have responded similarly
on all scales given the similarity of their format (Cook & Campbell, 1983).
Meanwhile, several suggestions for future research are also offered.
First, this study is the first attempt to adapt the framework of Zahra et al. (2007) to test
the knowledge sharing as moderated by FCBs in relation to AMO factors for improving
knowledge-sharing within the HKCI. This study can be adopted to further explore how
the AMO model works between formal and informal knowledge sharing outcomes
individually. Furthermore, the conceptual model should be examined using different
industries and cultural groups, because contextual factors may influence the
hypothesized relationships.
Second, qualitative research methods can also be used to investigate the antecedents
of intention to share explicit and implicit knowledge. Qualitative research methods
might be particularly valuable when examining the antecedents of sharing informal
knowledge, because articulating and measuring informal knowledge using quantitative
methods is more difficult than doing the same for formal knowledge.
Third, control variables, such as role competence, can also be used in future studies,
because sharing knowledge does not always depend on an individual’s willingness to
share.
Fourth, future research can employ a longitudinal approach to test the conceptual
model and obtain a better understanding of the hypothesized research’s causal
mechanisms.
Finally, from a methodological and analytical perspective, smart PLS can be used for
undertaking variance-based SEM and increasing the amount of information in the
original data, because such an approach reduces the effect of random sampling errors
via bootstrapping procedures (Hair, 2016; Peng & Lai, 2012).
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5.10 Summary and concluding remarks
Refer to the table 5.11 Result and Discussion of Hypotheses testing Findings, this study
explored the moderating role of FCBs in knowledge sharing and fills a gap in the
international literature by exploring its relationship with AMO factors in the context of
HKCI firms. The study has theoretical and managerial implications.
Table 5.11 Result and Discussion of Hypotheses Testing Findings
Research questions Related Hypotheses Result and Discussion
Q1 Hypothesis 1.1 (H1.1) Results: Sig (.75) Marginal supported
Does ability ( training workers), motivation ( providing incentive systems), opportunity (creating an environment of trust) of employees have a significant effect on knowledge sharing in the HK clothing industry (HKCI)?
In the HKCI, Training for Workers is positively associated with Knowledge Sharing.
The result is marginally significant for training for workers and has a moderate and prositive influence on knowledge sharing. Training in inter-personal communication skills may help employees to exchange information and knowledge effectively. (Aragón-Sánchez, 2003; Cabrera & Cabrera, 2005; Wong & Aspinwall, 2005),
Hypothesis 1.2 (H1.2) Results: Sig (.35) Supported
In the HKCI, Incentive Systems is positively associated with Knowledge Sharing.
The result supported incentive systems as a predictor of knowledge sharing performance. Therefore, in designing incentive and rewards systems it is vital firms should provide new intrinsic opportunities that allow one to learn and actualize their full pontential. ( Sharratt & Usoro, 2003; Wong & Aspinwall, 2005).
In the HKCI, Trust is positively associated with Knowledge Sharing.
The result is the strongest in relation to trust and it is the most effecitve and often the least costly method to encourage people to share their knowledge. However, building trust requires sincere efforts by a firm’s leaders (Dyer & Singh, 1998; Sharratt & Usoro, 2003). Overall the first major set of findings from H1.1 , H1.2, H1.3 answers the first research question that AMO factors positively influence knowledge sharing in HKCI.
What are the key relationships between FCBs , AMO factors and knowledge sharing in the HKCI firms?
In the HKCI, FCBs acts as a moderating factor in the relationship between Ability ( Training for Workers) and Knowledge Sharing.
The result supported the assumption that FCBs moderate the impact of kowledge-sharing behavior when training for workers is provided . Lower values of FCBs will increase the strength of the relationship between training for workers and knowledge sharing (Kotey, 2007 and Aragon-sancher,2003).
Hypothesis 2.2( H2.2) Results:Sig (.01) Supported
In the HKCI, FCBs acts as a moderating factor in the relationship between Motivation ( Incentive Systems) and Knowledge Sharing.
The result identifed that FCBs have a stronger moderating effect on the relationship. Lower values of FCBs will increase the strength of the relationship between incentive systems and knowledge sharing.
In the HKCI, FCBs acts as a moderating factor in the relationship in between Opportunity ( trust) and knowledge sharing
The result is the strongest to support FCBs moderating effect. Lower involvement of FCBs will increase the strength of the relationship between trust and knowledge sharing (Zahra, 2010; Zahra et al., 2007). The second major finding answered Q2 that paternalism and personalized culture in FCBs can create a neagtive impact o knowledge sharing.
For practical managerial implications, this research is timely study as some junior family
members of business clans may have no ambition to seek new knowledge or for growing
the business as they may simply lack interest in the family business (Le Breton-Miller et
al., 2004). Changing business environments in this major manufacturing sector in Hong
Kong are forcing family-owned clothing industry firms to look for suitable strategies to
improve their firms’ competitive advantages. Creating and managing unique knowledge
is important in sustaining a firm’s competitive advantage over others (Barney 1991;
Lank, 1997). Consequently, by considering the ownership type (FCBs) in the analysis,
acknowledging the need towards a shared understanding of the HKCI firms may help
such firms develop their capability for business success in the future, especially in view
of shifts in intergenerational leadership.
Business performance can be enhanced through knowledge sharing. A firm’s
performance in today’s dynamic environment and its sustainable competitive
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advantages relies on its ability to fully equip its knowledge-management processes to
its business needs.
The application of AMO factors is likely to foster knowledge sharing via establishing an
organizational environment that is contributory to sharing; knowledge sharing can be
encouraged by building positive attitudes against sharing and enhancing perceptions
and norms towards sharing. Current HRM literature argues that firms should have a
strategic orientation towards acquiring and sharing knowledge within and across
organisations (Wright et al., 1994) that endorse it to build firm-specific human capital
for developing a sustainable competitive advantage.
The above implies that firms can be succeed with various strategic is subject to various
types of human capital... However, in a dynamic and-changing competitive
environment, one key capability that is applied for effective regardless of a firm’s
strategy: is the ability to continuously to renew its knowledge base. HRM practices
should therefore, dedicate greater efforts to enhance the creation, acquisition and flow
of knowledge through knowledge sharing for creating an adaptive organisation.
To this end, future scholarship should focus on developing an understanding of
knowledge-sharing by AMO model and leadership execute that will facilitate the
exchange of knowledge culture in firms.
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References
Abelson, R. P. (1985). A variance explanation paradox: When a little is a lot.
Psychological Bulletin, 97(1), 129.
Adler, P. S., & Kwon, S. W. (2002). Social capital: Prospects for a new concept.
Academy of management review, 27(1), 17-40.
Aguinis, H., O'Boyle, E., Gonzalez‐Mulé, E., & Joo, H. (2016). Cumulative
Advantage: Conductors and Insulators of Heavy‐Tailed Productivity
Distributions and Productivity Stars. Personnel Psychology, 69(1), 3-66.
Aragon-Correa, J. A., & Sharma, S. (2003). A contingent resource-based view
of proactive corporate environmental strategy. Academy of management
review, 28(1), 71-88.
Aragón-Sánchez, A., Barba-Aragón, I., & Sanz-Valle, R. (2003). Effects of
training on business results, The International Journal of Human Resource
Management, 14(6), 956-980.
Ardichvili, A., Page, V., & Wentling, T. (2003). Motivation and barriers to
participation in virtual knowledge-sharing communities of practice. Journal of
knowledge management, 7(1), 64-77. Argot, L. (1999). Organizational
learning.
Argote, L., McEvily, B., & Reagans, R. (2003). Managing knowledge in
organizations: An integrative framework and review of emerging themes.
Management science, 49(4), 571-582.
LEE, Yuk Ling Angie Student Number: C3173954
144
Arnold, H. J., & Evans, M. G. (1979). Testing multiplicative models does not
require ratio scales. Organizational Behavior and Human Performance, 24(1),
41-59.
Alam, S. S., Abdullah, Z., Ishak, N. A., & Zain, Z. M. (2009). Assessing
knowledge sharing behaviour among employees in SMEs: An empirical study.
International Business Research, 2(2), 115.
Alavi, M., Kayworth, T. R., & Leidner, D. E. (2005). An empirical examination of
the influence of organizational culture on knowledge management practices.
Journal of management information systems, 22(3), 191-224.
Alavi, M., & Leidner, D. E. (2001). Review: knowledge management and
knowledge management systems: conceptual foundations and research
issues. MIS Quarterly, 25(1), pp. 107-136.
Aiken, L. S., West, S. G., & Reno, R. R. (1991). Multiple regression: Testing and
interpreting interactions. Sage.
Allen, J., James, A. D., & Gamlen, P. (2007). Formal versus informal knowledge
networks in R&D: a case study using social network analysis. R&D
Management, 37(3), 179-196.
Aman, F. (2010). Organisational factors enhancing the use of information
technology for knowledge management: a study in Malaysian listed
organisations. Curtin University of Technology.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in
practice: A review and recommended two-step approach. Psychological
bulletin, 103(3), 411.
LEE, Yuk Ling Angie Student Number: C3173954
145
Appelbaum, E. (2000). Manufacturing advantage: Why high-performance
work systems pay off. Cornell University Press.
Appelbaum, E., Bailey, T., Berg, P., & Kalleberg, A. (2000). Manufacturing
competitive advantage: The effects of high performance work systems on
plant performance and company outcomes
Appelbaum, E., Bailey, T., Berg, P., & Kalleberg, A. (2000). Manufacturing
competitive advantage: The effects of high performance work systems on
plant performance and company outcomes.
Appelbaum, S. H., & Gallagher, J. (2000). The competitive advantage of
organizational learning. Journal of Workplace Learning, 12(2), 40-56.
Apshvalka, D., & Wendorff, P. (2005, September). A Framework of Personal
Knowledge Management in the Context of Organisational Knowledge
Management. In ECKM (pp. 34-41).
Au, K., Peng, M. W., & Wang, D. (2000). Interlocking directorates, firm
strategies, and performance in Hong Kong: Towards a research agenda. Asia
Pacific, Journal of Management, 17(1), 29-47.
Au, K., Chiang, F. F., Birtch, T. A., & Ding, Z. (2013). Incubating the next
generation to venture: The case of a family business in Hong Kong. Asia Pacific
Journal of Management, 30(3), 749-767.
Augier, M., Shariq, S. Z., & Thanning Vendelø, M. (2001). Understanding
context: Its emergence, transformation and role in tacit knowledge sharing.
Journal of knowledge management, 5(2), 125-137.
LEE, Yuk Ling Angie Student Number: C3173954
146
Axelrod, R. M. (2006). The evolution of cooperation. Basic books.
Aydin, S., Ö zer, G., & Arasil, Ö . (2005). Customer loyalty and the effect of
switching costs as a moderator variable: A case in the Turkish mobile phone
Williams, B., Onsman, A., & Brown, T. (2010). Exploratory factor analysis: A
five-step guide for novices. Australasian Journal of Paramedicine, 8(3).
Winter, G. (2000). A comparative discussion of the notion of 'validity' in
qualitative and quantitative research. The qualitative report, 4(3), 1-14.
Winer, B. J., Brown, D. R., & Michels, K. M. (1971). Statistical principles in
experimental design (Vol. 2, p. 596). New York: McGraw-Hill.
Wolters, K. (2014). Narrative review on how mediating mechanisms influence
the relationship between employees’ perception of HR practices and employee
performance.
Wood, S. J., & Wall, T. D. (2007). Work enrichment and employee voice in
human resource management-performance studies. The International Journal
of Human Resource Management, 18(7), 1335-1372.
Woolcock, M. (2001). The place of social capital in understanding social and
economic outcomes. Canadian journal of policy research, 2(1), 11-17.
LEE, Yuk Ling Angie Student Number: C3173954
192
Wong, K. Y., & Aspinwall, E. (2005). “An empirical study of important factors
for knowledge-management adoption in the SME Sector”. Journal of
Knowledge Management, 9(3), pp. 64-82.
Wu, Y., Balasubramanian, S., & Mahajan, V. (2004). When is a preannounced
new? product likely to be delayed? Journal of Marketing, 68(2), 101-113.
Wu, X., Chen, Q., Zhou, W., & Guo, J. (2010). A review of Mobile Commerce
consumers' behaviour research: consumer acceptance, loyalty and
continuance (2000-2009). International Journal of Mobile Communications,
8(5), 528-560.
Yang, J. (2007). “Knowledge sharing: Investigating appropriate leadership
roles and collaborative culture”. Tourism Management, 28(2), pp. 530-543.
Yew Wong, K., & Aspinwall, E. (2005). An empirical study of the important
factors for knowledge-management adoption in the SME sector. Journal of
knowledge management, 9(3), 64-82.
Yu, B., Singh, M. P., & Sycara, K. (2004, August). Developing trust in large-scale
peer-to-peer systems. In Multi-Agent Security and Survivability, 2004 IEEE
First Symposium on (pp. 1-10). IEEE.Companies. Knowledge Mapping and
Management, 244-253.
Yuan, D., Hua, Z., & Junxi, Z. (2008). The financial and operating performance
of Chinese family owned listed firms. Management International
Review,48(3), 297-318.
Zaheer, S., & Zaheer, A. (2006). Trust across borders. Journal of International
Business Studies, 37(1), 21-29
LEE, Yuk Ling Angie Student Number: C3173954
193
Zahra, S. A. (2003). International expansion of US manufacturing family
businesses: The effect of ownership and involvement. Journal of business
venturing, 18(4), 495-512.
Zahra, S. A., Hayton, J. C., & Salvato, C. (2004). Entrepreneurship in family vs.
Non‐Family firms: A Resource‐Based analysis of the effect of organizational
culture. Entrepreneurship theory and Practice, 28(4), 363-381.
Zahra, S. A. (2005). Entrepreneurial risk taking in family firms. Family Business
Review, 18(1), 23-40.
Zahra, S. A., Sapienza, H. J., & Davidsson, P. (2006). Entrepreneurship and
dynamic capabilities: a review, model and research agenda. Journal of
Management studies, 43(4), 917-955.
Zahra, S. A., Neubaum, D. O., & Larrañeta, B. (2007). Knowledge sharing and
technological capabilities: The moderating role of family involvement. Journal
of Business research, 60(10), 1070-1079.
Zhang, P. C., Zhang, L. B., Hou, Z. R., & Zhang, K. J. (2008). “The impact of
values and leadership on knowledge integration behaviors in medical projects
teams”. 2008 International Conference on Computer Science and Software
Engineering, 5, pp.242-245.
Zahra, S. A. (2012). Organizational learning and entrepreneurship in family
firms: Exploring the moderating effect of ownership and cohesion. Small
business economics, 38(1), 51-65.
LEE, Yuk Ling Angie Student Number: C3173954
194
Zarraga, C., & Bonache, J. (2003). Assessing the team environment for
knowledge sharing: an empirical analysis.International Journal of Human
Resource Management,14(7),1227-1245.
Zellweger, T. M., Eddleston, K. A., & Kellermanns, F. W. (2010). Exploring the
concept of familiness: Introducing family firm identity. Journal of family
business strategy, 1(1), 54-63.
Zikmund, W.G. (2003) Business Research Methods. 7th Edition, Thomson
South Western, Ohio
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Appendix A
Email Invitation
Dr. Ashish Malik Faculty of Business and Law Newcastle Business School Tel: (02) 43484133 Email: [email protected]
Subject: Information Statement for the Research Project: The impact of AMO model on knowledge sharing (KS) in Family controlled businesses (FCBs) in
Hong Kong’s Clothing industry (HKCI). Dear Sir/Madam,
This study is a research project for the Doctor of Business Administration (DBA) degree at The University of Newcastle, Australia. It is being carried out by Ms. Lee Yuk Ling Angie (Email: [email protected]), under the supervision of Dr. Ashish Malik (Email: [email protected]). Faculty of Business and Law at the University of Newcastle. The research will be undertaken in Hong Kong.
You are invited to participate in this anonymous study employing an online
questionnaire-based design focusing on the impact of AMO (ability, motivation and
opportunity) model on knowledge sharing (KS) in Family controlled businesses
(FCBs) in Hong Kong clothing industry (HKCI).
I attach to this email details of the research project in the attached Organisation
Consent form(OCF), Information statement for organisation(ISO), Participant
Information Statement (PIS), which also contains a link to the web-based
questionnaire. I would suggest you to either save this OCF, ISO,PIS or print it for
your future records.
Please sign the OCF and have a scanned copy returned to the named researcher for
your approval. I would greatly appreciate if you could circulate this email with the
attachment to the following employees who are 18 years or over:
- The CEO
- General Manager
- Manager (or designate)
Although it is stated in the PIS, I would reiterate that under no circumstances
would any of the participants be identified in the study’s reporting.
For the details, please open and read the PIS document and click on the research eSurvey Creation link to start the survey since it will only take 15 minutes to complete it. Your participation in completing the survey is highly appreciated.
Yours sincerely
Supervisor: Dr. Ashish Malik
Student Researcher: Ms. Angie Lee
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Appendix B
Information Statement for Organization
INFORMATION STATEMENT FOR ORGANISATION Date: 3rd, February, 2016 Dr Ashish Malik BO 1.16 Business Office, Central Coast Campus, Ourimbah, 2258 Newcastle Business School, University of Newcastle, Australia. Ph: 02-434 84133 (Extension: 84133). To The CEO/ Vice-President (or designate e.g. General manager) Organisation Name Address Hong Kong Dear Sir/Madam
Information Statement for the Research Project: The impact of AMO model on knowledge sharing (KS) in Family controlled businesses
(FCBs) in Hong Kong’s Clothing industry (HKCI).
Your organisation is invited to participate in the above mentioned research project which is being conducted by a student, Ms. Lee Yuk Ling Angie, who is undertaking the Doctor of Business Administration degree, under the supervision of Dr. Ashish Malik from the Schools of Business and Law at the University of Newcastle. The research will be undertaken in Hong Kong. Why is the research being done?
The purpose of the research is to investigate the relative importance ability, motivation and opportunity (AMO) in sharing knowledge in Family Controlled business in the Hong Kong (HK) clothing industry. More specifically, analysing the role of incentive systems, training for workers and trust and knowledge sharing in the HK clothing industry.
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Who can participate in the research?
Your organisation is invited to participate in this study. By forwarding this email and attached link to the study’s questionnaire in the Participant Information Sheet document attached to this email message to a relevant practitioner who is in the position of a Manager/Top executive/business ownership or owner of a family owned business in the Hong Kong clothing industry your organisation provides consent to participate in this study. What choice does your organisation have? Participation in this research is entirely your organisation’s choice. By accepting our request for the distribution of the recruitment email containing the participant information statement, containing the anonymous questionnaire link, to your employees (as specified above), your organisation provides informed consent. Please note that due to the anonymous nature of the questionnaire, once you forward the survey recruitment email to participate, your organisation will not be able to withdraw from the study. How much time will it take? The questionnaire will take between 10-15 minutes. What are the risks and benefits of participating? There are no anticipated risks associated with participating in this research project. Whilst there are no anticipated benefits to you personally in participating this research project, the research aims to benefit family businesses in HK’s clothing industry by knowledge sharing and success of family business in this industry. This study also aims to provide an understanding and learning about how family factors influence knowledge sharing in the HK clothing industry. How will your privacy be protected?
As this study will use an online questionnaire, any personal details of your organisation will not be identifiable. Confidentiality of your organisation will be maintained at all times. The data collected will be used to complete statistical analysis. The collected data will be stored on a password protected computer accessible only by the student researcher and, where necessary, by the study’s Chief Investigator. Access to the data via the online questionnaire software will be through a protected password in the Student Researcher’s, and if accessed by the Chief Investigator, it will also be password protected in the Chief Investigator’s computer. For further data analysis, data inputted in the SPSS V22 software will also be password protected for additional security measures. The data will be disposed in accordance with the policy and procedures for disposing confidential materials as per the University of Newcastle’s policies. In addition, data will be retained for a minimum of 5 years as per University of Newcastle requirements. How will the information collected be used?
The collected data will be used as part of Ms Lee Yuk Ling Angie’s thesis which will be submitted to the University of Newcastle’s library. The results of this research
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project may also be presented in academic publications such as journal articles, books and conferences. Organisations are able to receive a copy of the summary report by emailing [email protected] after October 2016. What do you need to do to participate? Please read this Organisation Information Statement and be sure you understand its contents before you provide your consent to participate. Further information If you would like further information please contact me at [email protected] Thank you for considering this invitation. Yours sincerely Ashish Malik Dr Ashish Malik Lecturer-HRM Newcastle Business School University of Newcastle Ms Lee Yuk Ling Angie Student Researcher University of Newcastle Tel: +852 93637204 Email: [email protected]. Complaints about this research This project has been approved by the University’s Human Research Ethics Committee, Approval No. H-2015-0383Should you have concerns about your rights as a participant in this research, or you have a complaint about the manner in which the research is conducted, it may be given to the researcher, or, if an independent person is preferred, to the Human Research Ethics Officer, Research Office, The Chancellery, The University of Newcastle, University Drive, Callaghan NSW 2308, Australia, telephone (02) 49216333, email Human-
[email protected]. Alternatively, you can contact Ms Yan Chau, our local Hong Kong Management Association Administrator at [email protected] or, 16/F, Tower B, Southmark , 11 Yip Hing Street, Wong Chuk Hang, HONG KONG , Phone: (852) 2774 8547
Date: 3rd, February, 2016 Dr. Ashish Malik Faculty of Business and Law Newcastle Business School Tel: (02) 43484133 Email: [email protected]
Information Statement for the Research Project: The impact of AMO model on knowledge sharing (KS) in Family controlled
businesses (FCBs) in Hong Kong’s Clothing industry (HKCI).
You are invited to participate in the above mentioned research project which is being conducted by a student, Ms. Lee Yuk Ling Angie, who is undertaking the Doctor of Business Administration degree, under the supervision of Dr. Ashish Malik from the Schools of Business and Law at the University of Newcastle. The research will be undertaken in Hong Kong. Why is the research being done?
The purpose of the research is to investigate the relative importance ability, motivation and opportunity (AMO) in sharing knowledge in Family Controlled business in the Hong Kong (HK) clothing industry. More specifically, analysing the role of incentive systems, training for workers and trust and knowledge sharing in the HK clothing industry. Who can participate in the research?
You are invited to participate in this questionnaire if you are aged over 18 and a relevant practitioner in the position of a Manager/Top executive/business ownership or owner of a family owned business in the Hong Kong clothing industry.
If you agree to participate after reading this participation information sheet, you will be invited to complete in an online questionnaire on knowledge sharing in the HK clothing industry by clicking on the web link provided at the end of this participant information sheet. What choice do you have?
Participation in this research is entirely your choice. Only those people who give their informed consent will be included in the project. Whether or not you decide to participate, your decision will not disadvantage you. If you do decide to participate, you may withdraw from the project at any time prior to submitting your completed questionnaire. Please note that due to the anonymous nature of the questionnaire, you will not be able to withdraw your response after it has been submitted. Please be informed that by completing the questionnaire you and your organisation will not be identifiable as the online questionnaire is anonymous.
How much time will it take?
The questionnaire should take about 10-15 minutes to complete all the sections.
What are the risks and benefits of participating?
There are no anticipated risks associated with participating in this research project. Whilst there are no anticipated benefits to you personally in participating this research project, the research aims to benefit family businesses in HK’s clothing industry by knowledge sharing and success of family business in this industry. This study also aims to provide an understanding and learning about how family factors influence knowledge sharing in the HK clothing industry. How will your privacy be protected?
As this study will use an online questionnaire, any personal details of the participants will not be disclosed, and nobody will be identifiable. Confidentiality of all respondents will be maintained at all times. The data collected will be used to complete statistical analysis. The collected data will be stored on a password protected computer accessible only by the student researcher and, where necessary, by the study’s Chief Investigator. Access to the data via the online questionnaire software will be through a protected password in the Student Researcher’s, and if accessed by the Chief Investigator, it will also be password protected in the Chief Investigator’s computer. For further data analysis, data inputted in the SPSS V22 software will also be password protected for additional security measures. The data will be disposed in accordance with the policy and procedures for disposing confidential materials as per the University of
LEE, Yuk Ling Angie Student Number: C3173954
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Newcastle’s policies. In addition, data will be retained for a minimum of 5 years as per University of Newcastle requirements. How will the information collected be used?
The collected data will be used as part of Ms Lee Yuk Ling Angie‘s thesis which will be submitted to the University of Newcastle’s library. The results of this research project may also be presented in academic publications such as journal articles, books and conferences. Participants can request a summary of the results of this research project by sending a request to the student research by email address: [email protected].
The Participants are able to receive a copy of the summary report by emailing [email protected] after October 2016. What do you need to do to participate?
Please read this Participant Information Statement and print a copy of the same for your records so you are sure you understand its contents before you agree to participate by clicking on the link to the online questionnaire below. If there is anything you do not understand, or you have questions, please contact the student researcher or the chief investigator. After you have read and understood the participant information statement and would like to participate, please click on the link to the questionnaire. Please be informed that completion and submission of the questionnaire implies that you agree to participate. Please click on the link below if you wish to participate in the questionnaire: https://www.esurveycreator.com/s/742c3cd Further information
If you would like further information please contact Dr. Ashish Malik at the email address above to obtain further information about the project.
Thank you for considering to participate in this study. Dr Ashish Malik, Chief Investigator University of Newcastle Tel: (02) 43484133 Email: [email protected] Ms Lee Yuk Ling Angie Student Researcher University of Newcastle Tel: +852 93637204 Email: [email protected].
Complaints about this research This project has been approved by the University’s Human Research Ethics Committee, Approval No. H-2015-0383Should you have concerns about your rights as a participant in this research, or you have a complaint about the manner in which the research is conducted, it may be given to the researcher, or, if an independent person is preferred, to the Human Research Ethics Officer, Research Office, The Chancellery, The University of Newcastle, University Drive, Callaghan NSW 2308, Australia, telephone (02) 49216333, email Human-
[email protected]. Alternatively, you can contact Ms Yan Chau, our local Hong Kong Management Association Administrator at [email protected] or, 16/F, Tower B, Southmark , 11 Yip Hing Street, Wong Chuk Hang, HONG KONG , Phone: (852) 2774 8547