UNIVERSITY OF VAASA 
FACULTY OF BUSINESS STUDIES 
DEPARTMENT OF MANAGEMENT 

 
 
 
 
 
 
 
 
 

Miikkael Koistinen 
 

Knowledge sharing in the context of mentoring 
 
 
 
 
 
 
 

 
 
 
 

Master’s Thesis in 
International Management 

 
 
 

 
 
 
 
 

VAASA 2015  



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TABLE OF CONTENTS         page 

LIST OF TABLES AND FIGURES             5       	
  

ABSTRACT 7 

1. INTRODUCTION 9 
1.1 Background of the research 9 
1.2 Research questions and objective 12 
1.3 Scope of the study 13 
1.4 Structure of the thesis 13 

2. LITERATURE REVIEW 14 
2.1 Knowledge-based view and the MNC 14 
2.2 Perspectives on knowledge 17 
2.3 Knowledge transfer as part of knowledge management 22 
2.4 MNC knowledge sharing 25 

2.4.1 Knowledge sharing and its barriers 27 
2.4.2 The Knowledge governance approach and AMO framework 30 

2.5 Factors affecting knowledge sharing 33 
2.5.1 Motivation 33 
2.5.2 Opportunity 39 
2.5.3 Ability 42 

2.6 Knowledge sharing in the context of mentoring 45 
2.6.1 Mentoring defined 45 
2.6.2 Mentoring and knowledge sharing 49 
2.6.3 Mentoring and motivation to share knowledge 51 
2.6.4 Mentoring and opportunity to share knowledge 54 
2.6.5 Mentoring and ability to share knowledge 58 

2.7 Theoretical framework 60 

3. RESEARCH METHODS 64 
3.1 Research approach and strategy 64 
3.2 Background information of case study company 65 
3.3 Data collection and analysis 67 
3.4 Validity and reliability 70 

4. FINDINGS 73 
4.1 State of knowledge sharing in the case-company 73 

4.1.1 ABU -level knowledge sharing –silo thinking 75 



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4.1.2 Cross-border knowledge sharing –an articulated ambition 80 
4.1.3 Antecedents of individual level knowledge sharing 82 

4.2 Knowledge sharing in the context of mentoring 91 
4.2.1 Background information about the mentoring program and participants 91 
4.2.2 Mentoring and motivation to share knowledge 93 
4.2.3 Mentoring and opportunity to share knowledge 96 
4.2.4 Mentoring and ability to share knowledge 103 

4.3 Effects of mentoring on the antecedent of individual level knowledge sharing 106 

5. CONCLUSIONS 109 
5.1 Discussion and summary of the findings 109 
5.2 Limitations of the research 115 
5.3 Implications for research 116 
5.4 Implications for practice 117 

REFERENCES 120 

APPENDIX 129 
Appendix A. Participant information sheet. 129 
Appendix B. Interview questions. 130 

 
  



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LIST OF TABLES AND FIGURES        page 
 
 
TABLES 
 
Table 1. Knowledge classifications. 22 
Table 2. Factors affecting knowledge sharing motivation.         38 
Table 3. Factors affecting knowledge sharing opportunity.         42 
Table 4. Factors affecting knowledge sharing ability.         45 
Table 5. Factors expected to have an influence on the knowledge sharing       61 
    behavior of mentoring participants and how mentoring could address             
               these issues.               
Table 6. Present state of knowledge sharing.           90 
Table 7. Facts about the mentoring program and background information       92 
    about   interviewees.          
Table 8. Effects of mentoring on the antecedents of individual level knowledge    106 
    sharing. 
 
 
FIGURES 
 
Figure 1. Knowledge types and dimensions (Bhagat et al. 2002).        20 
Figure 2. Km-cycle based on (Gupta & Govindarajan 2000 b).        23 
Figure 3. MNC knowledge flows            26 
Figure 4. Knowledge sharing models (based on Harvey 2012).        29 
Figure 5. Different levels of analysis (Modifies from Foss et al. 2010).       31 
Figure 6. Mentoring and knowledge sharing.          50 
Figure 7. Overview of the Infranet Industry.           65 
Figure 8. Power Distribution business unit.           67 
  



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UNIVERSITY OF VAASA 
Faculty of Business Studies 
Author:     Miikkael Koistinen 
Topic of the Thesis:    Knowledge sharing in the context of  
      mentoring 
Name of Supervisor:    Dr. Adam Smale 
Degree:     Master of Science in Economics and  
      Business Administration 
Department:     Department of Management 
Major Subject:    International Business 
Line:      Master’s Programme in International 
      Business 
Year of Entering the University:  2009 
Year of Completing the Thesis:  2015        Pages: 133 
 
ABSTRACT 
 
The research examines individual level horizontal knowledge sharing across MNC subsidiaries 
taking place in the context of mentoring. The aim is to look beyond traditional career related 
outcomes associated with mentoring and explore how it affects ability, motivation and 
opportunity to share knowledge. The theoretical review is guided by the knowledge governance 
approach and factors affecting knowledge sharing are discussed with the help of the AMO-
framework. 
 
The research is a qualitative case study of a MNC’s international business unit. Data was 
collected by conducting structured theme interviews. The empirical part of the research is based 
on the integrative framework derived from existing scientific literature on the research topic. 
The data was first analyzed to form a comprehensive picture about the current state of 
knowledge sharing in the business unit. Then, knowledge sharing in the context of mentoring 
was taken under closer examination. In the end, factors affecting an individual’s motivation, 
opportunity and ability to share knowledge within and outside the mentoring relationship were 
compared with each other for conclusions to be drawn. 
 
The findings suggest that knowledge sharing at the local level is mostly affected by a siloing 
effect arising from internal competition and an entrepreneurial organizational culture, whereas 
cross-border sharing is still in its infancy and is characterized by lack of structures. Mentoring 
can be considered as a commitment-based knowledge governance mechanism, which improves 
individuals’ motivation, opportunity and ability to share knowledge by transcending barriers 
otherwise present in the business unit. Nevertheless, perceived organizational commitment, 
prior mentoring experience and a wide work related experience gap were shown to have a 
negative effect on knowledge sharing, even in the context of mentoring. 
 
 KEYWORDS: Knowledge sharing, Mentoring, AMO, MNC 



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1. INTRODUCTION 
 
 
1.1 Background of the research 
 
 
 “If the doctrinal history of management research in the 1990s and the beginning 
of the new millennium ever comes to be written, a central – and perhaps the central – 
chapter will concern how ‘knowledge’ became a dominant construct in a number of 
management fields.” 
       –Foss et al. (2010: 455) 
 
Knowledge and its management have received a lot of attention in the last two decades. 
It has been widely agreed upon that those companies, which create, identify, transfer 
and use knowledge reach better performance (Davenport & Prusak 1998). For example 
O’Dell and Grayson (1998:157) highlight in their article the additional capacity gained 
by Texas Instruments equal to building a new production facility worth several hundred 
of millions by identifying and transferring knowledge within the company.  According 
to OECD (1996) we live in a knowledge economy characterized by the production, 
distribution and use of knowledge instead of tangible resources. As a corollary to the 
resource-based view (RBV), the knowledge-based view (KBV) regards knowledge as 
the most important source of sustainable competitive advantage because of its intangible, 
hard to imitate nature (Davenport & Prusak 1998). The KBV is a result of companies 
trying to succeed in an ever more competitive and rapidly changing global economy. 
This view applies especially to large multinational corporations (MNCs), which 
existence has been validated through their superior capabilities to leverage and integrate 
world wide knowledge repositories to the use of the entire company (e.g. Kogut & 
Zander 1993; Grant 1996; Gupta & Govindarajan 2000 a; Yang et al. 2008). 
 
Even though its importance and potential payoffs, transferring knowledge does not 
happen easily. Knowledge transfer is a delicate process with many determinants such as 
motivational factors of the source and the recipient and different knowledge 
characteristics affecting the very occurrence of the process. Szulanski (1996) uses the 
term “sticky” in describing impediments and barriers hindering knowledge transfer. In 
cross-boarder spanning MNCs additional hardship is encountered do to colliding 
national and organizational cultures and institutions of the parent company and its 
subsidiaries. The stickiness of intra-firm knowledge transfer and its effects on MNCs is 



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well crystalized in the words of former Chairman, President and CEO of Hewlett- 
Packard Lewis E. Platt: “I wish we knew what we know at HP.” (O’Dell & Grayson 
1998: 154). 
 
Knowledge resides in several levels within the organization and is transferred across 
functions, departments and organizational boundaries. However, all levels of knowledge 
transferring originate from knowledge sharing taking place at the individual level. 
Individuals are the ones in possession of knowledge, which can be shared to the 
organizational level where it is transformed into economic value for the company (Ipe 
2003). As such, it is in the interest of MNCs to affect individual-level conditions of 
action in order to promote and secure required levels of knowledge sharing between for 
example their foreign subsidiaries. Despite the identified importance of individual level 
knowledge sharing, extant literature has been criticized to neglect micro level analysis 
and leap straight to explaining causal links between macro (i.e. organizational, 
collective) variables (see e.g. Minbaeva, Mäkelä & Rabbiosi 2012; Foss, Husted & 
Michaiova 2010). 
 
The emerged knowledge governance approach or KGA encompass the management of 
organizational structures and mechanisms that influence the creating, sharing, 
integrating and using of knowledge and the guiding of these processes in preferred 
directions (Foss, Husted & Michailova 2010: 456). The KGA differentiates between 
macro and micro level analysis and brings forward the importance of understanding 
how companies can manage organizational outcomes through influencing individual-
level conditions of action (Foss 2007). According to Foss et al. (2010), by concentrating 
on micro level constructs existing gaps, problems, unresolved issues and untested 
claims characterizing literature on knowledge and organizations could be addressed. 
 
Following the KGA, a number of recent publications have addressed the link between 
HRM practices and knowledge management efforts (Prieto Pastor et al. 2010; Minbaeva 
et al. 2012), employee behavior (Kehoe & Wright 2013) as well as knowledge-based 
performance of the company (Minbaeva 2013). For example Minbaeva et al. (2013) 
view HRM as a mechanism to influence individual conditions determining individual 
action. Indeed, different HRM practices can be regarded as mechanisms to govern the 
antecedents of knowledge sharing behavior. Nevertheless, Minbaeva (2013) states that 
the relevant underlying mechanisms characterizing the causal relation between HRM 
and knowledge processes are only partially understood and deserve further examination. 
 



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Based on the well-established AMO framework knowledge sharing is essentially 
determined by an individual’s ability, motivation and opportunity to share knowledge 
(Argote et al. 2003). Thus it is in the interest of organizations to implement HRM 
practices, which promote these antecedents in order to increase their organizational 
knowledge sharing. Literature on knowledge sharing has identified several factors 
affecting these antecedents, however, only few studies have made the effort to explore 
how a given HRM practice could affect the ability, motivation and opportunity to share 
knowledge.  
 
In the past couple of decades, mentoring has increasingly been recognized as a 
mechanism for the transferring of knowledge within organizations (Swap, Leonard, 
Shields & Abrams 2001). However, despite the obvious notions of growth and 
development associated with mentoring, only little research has studied how knowledge 
is shared in mentoring relationships (Haggard, Dougherty, Turban & Wilbanks 2011). 
Indeed, as a channel and governance mechanism bringing individuals closer together, 
mentoring should have mostly a positive effect on knowledge sharing because it creates 
a context for the purpose of developing employees. Nevertheless, only few studies have 
looked into this channel to actually prove or disapprove mentoring as a channel for 
knowledge sharing. More precisely, mentoring has been shown to result in career 
related outcomes through for example challenging assignments, raised self-esteem and 
visibility but findings on mentoring as an effective channel for the sharing of firm 
specific best practice is scarce. In their review of the evolution of mentoring, Kram and 
Ragins (2007) argue that scholars have focused on a relatively narrow area of research. 
Ragins and Verbos (2007 as cited by Kram & Ragins 2007: 8) state that research has 
overly emphasized mentoring as a one-sided relationship resulting in career related 
outcomes. Also Bearman, Blake-Beard, Hunt an Crosby (2007: 380) criticize the depth 
of existing mentoring research by stating that practitioners will not be able to leverage 
the full potential of mentoring before researchers shift their focus from demonstrating 
that mentoring works to explaining why it does so.  
 
The traditional hierarchical view of the headquarters (HQ) providing knowledge to its 
production intensive subsidiaries has changed to a more heterarchical network-based 
perspective regarding subsidiaries as sources of valuable knowledge (Ambos, Ambos & 
Schlegelmilch 2006; Michailova & Mustaffa 2011). MNCs are perceived as social 
communities, where power is decentralized and subsidiaries are granted with 
strategically important roles providing competitive advantage by contributing to the 
overall knowledge base of the company. As a result, successful horizontal knowledge 



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transfers taking place across borders between different MNC units have become an 
important determinant whether or not the company succeeds in being more than the sum 
of its parts. This research approaches these sticky horizontal knowledge flows through 
studying individual level knowledge sharing taking place in the context of mentoring 
between a mentor and a protégé from different country organizations. More precisely, 
mentoring is perceived as a mechanism to govern and ultimately secure horizontal 
cross-border knowledge transfers through affecting individual-level conditions of action 
dictating the knowledge sharing behavior of mentors and protégés. 
 
 
1.2 Research questions and objective 
 
 
Due to the identified research gap in existing literature the aim of this study is to look 
beyond traditional career and psychosocial outcomes associated with mentoring and 
explore how mentoring affects the ability, motivation and opportunity of mentors and 
protégés to share knowledge, and as such, helps to facilitate horizontal knowledge flows 
between MNC subsidiaries. The adopted individual level analysis together with the 
AMO framework is expected to shed light on the functioning of mentoring as a channel 
and governance mechanism for cross-border horizontal knowledge sharing. Furthermore, 
instead of following extant literature and proving that mentoring works, the knowledge 
sharing perspective could be considered as a step closer in answering the question of 
why it does so. 
 
The research questions are defined as follows: 
 

1. What affects individuals’ motivation, opportunity and ability to share knowledge 
within and across MNC subsidiaries? 
 

2. How does mentoring affect the antecedents of knowledge sharing behavior? 
 
The first research question is a preliminary question and needs to be answered first for 
the effects of mentoring on individual’s motivation, opportunity and ability to share 
knowledge to be discovered. 
 
 



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1.3 Scope of the study 
 
 
This study is limited to the context of knowledge sharing taking place in the case MNC. 
More precisely, to the context of formal mentoring relationships in the Power 
Distribution business unit. This study assumes that knowledge already exists in 
individuals and therefore the organizational challenge is to encourage and support it’s 
sharing so that the entire company can benefit from it. Following the work of Ipe (2003), 
while acknowledging that knowledge is present at many levels in the organization, the 
focus is on knowledge that exists within individuals and factors that affect its sharing in 
a formal workplace mentoring program between a mentor and a protégé. The scope of 
this study is limited to individual level knowledge sharing behavior and therefore 
knowledge sharing outcomes on the organizational level are not covered. 
 
 
1.4 Structure of the thesis 
 
 
The thesis is structured into five sections. The first section is an introduction to the 
study. It provides background information, identifies the research gap in existing 
literature and presents the research problem, objectives and questions. Furthermore, the 
introduction outlines the scope of the study and presents an overview on the structure of 
the thesis. The second section comprises theoretical perspectives of the study. It is 
written in the form of a literature review on conducted research on the topic. First 
knowledge sharing and factors affecting it are taken under examination after which the 
concept of mentoring will be covered. The second section formulates a conceptual 
framework on which the empirical part of the study is based. The third section presents 
the methodology of the research followed by the forth section, in which obtained results 
of the study are presented. This section follows the structure of the literature review and 
presents results on the current state of knowledge sharing before integrating mentoring 
and its effects into the contemplation. In the end of the fourth section factors affecting 
knowledge sharing within and outside of the mentoring relationship are contrasted with 
each other and a summary of the findings is presented. The fifth and final section of the 
research summarizes the research and discusses the findings for conclusions to be 
drawn. After having answered the research questions limitations of the research are 
identified and both implications for practice and areas for future research are suggested. 
  



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2. LITERATURE REVIEW 
 
 
2.1 Knowledge-based view and the MNC 
 
 
The multinational corporation, or the MNC, is regarded as a complex multidimensional 
organizational entity, which has been identified by extant literature as a powerful 
economic and political player in the global economy (Geppert, Becker-Ritterspach & 
Mudambi 2013). For example the OECD (2013) acknowledges the role played by 
MNCs in shaping the international business environment through job creation, human 
capital development, the distribution of capital, and the transferring of technology, skills 
and knowledge. MNCs have had and continue to have significant effects on the 
economic growth and development of their home and host countries and the global 
economy. 
 
The explanation for the existence of the MNC as an economic institution has its roots in 
the internalization theory. According to the theory, the MNC serves as a superior 
internal market through which it can exploit internally created company specific 
advantages without the fear of negative externalities present in external market 
transactions (Buckley & Casson 1976 as cited by Johanson & Mattson 1988: 307). 
According to Bouquet and Birkinshaw (2008 a), early conceptualizations of the MNC 
were mainly concentrated on transaction cost economics before the 1980s when 
different theoretical lenses through which the MNC could be interpreted started to 
emerge. One of these lenses was the resource-based view of the firm (RBV). According 
to the RBV, a company needs to build its competitive advantage through resources, 
capabilities and distinctive competences superior to its competitors (Wills-Johnson 
2008: 215–217). In line with this view Grant (1996: 375) argues that under dynamic 
competition and unstable market conditions caused by innovation organizational 
capabilities rather than positioning are the basis on which to build long-term strategies. 
Grant’s argument illustrates the shift from industry-based view and Porter’s Five Forces 
–model to the RBV emphasizing the importance of key resources in building 
sustainable competitive advantage. 
 
The ever more complex and demanding nature of customers, the urge in meeting 
shortened development times and constantly changing environments in the more and 
more competitive global economy have brought up the value of firm specific, intangible 



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and hard to imitate resources for MNCs (Davenport & Prusak 1998). It is challenging 
for companies to establish an edge over competitors. Technologies are imitated and best 
practices benchmarked: Competitors are short to tag along. As a result focus has shifted 
to knowledge and the knowledge-based view (KBV) of the firm. Knowledge has always 
been understood as an integral part of growth and development. However its relative 
importance has grown over the last three decades because economies have become 
increasingly dependent on the production, distribution and use of knowledge (OECD 
1996: 9). According to OECD (1996) the share of high-technology industries in total 
manufacturing more than doubled from 1970 to 1994 while the knowledge intensive 
service sector grew even faster. Over 50 percent of OECD major economies’ Gross 
Domestic Product (GDP) is estimated to be knowledge-based. Indeed a “knowledge –
based economy” has emerged. Knowledge, just like technology, offsets the basic 
assumption behind the neo-classical production function according to which added 
capital to the economy diminishes returns. According to the new knowledge-based 
growth theory knowledge raises returns on investment by enhancing production 
methods and stimulating new and better products and services. Consequently a constant 
flow of investments has the possibility to continuously accelerate a country’s growth 
rate (OECD 1996: 11). 
 
 As a corollary to the RBV, the KBV considers knowledge as the most important source 
in achieving sustainable competitive advantage (Davenport & Prusak 1998; Gupta & 
Govidarajan 2000 a; Yang, Mudambi & Meyer 2008). People and organizations have 
always, at least subconsciously, searched and valued knowledge. It is not new for 
organizations to try to recruit the most skillful individuals and then try to keep them on 
the payroll of the company. Knowledge has always been there, it is not new. What is 
new is the recognition of knowledge as a corporate asset. Just like the more tangible, 
easy to grasp resources knowledge should also receive the same amount of attention, 
investments and management. Knowledge should be regarded as any other asset in the 
company (Davenport & Prusak 1998: 12). However, the mere existence or possession of 
knowledge does not guarantee competitive advantage: A company must be able to 
create new knowledge as well as build on existing one. Unlike more material resources, 
knowledge assets grow when used. Davenport and Prusak (1998: 17) state that ideas 
serve as a foundation for new ones and shared knowledge is not lost by the sender and 
benefits the receiver. However, if not managed properly and leveraged or transferred to 
the use of the company, this intangible asset stays un-valuable. In large MNCs 
knowledge is widely dispersed among subsidiaries in different levels around the world 



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making knowledge integration a crucial component regarding the competitiveness of 
MNCs (Gupta & Govidarajan 2000 a: 473; Kogut and Zander 1993: 625). 
 
Ghoshal and Bartlett (1990) observe the MNC as an entity consisting of a group of 
geographically dispersed organizations including the headquarters and national 
subsidiaries. Adopting a network perspective, they conceptualize the MNC as an 
interorganizational network embedded in an external network composed of actors with 
which different MNC units interact. In other words, MNCs are cross-border spanning 
internal networks that are present in a combination of external markets meaning the 
external networks in which subsidiaries are embedded (Nell, Ambos and Schlegelmilch 
2011). According to Bouquet and Birkinshaw (2008 a), the concept of 
interorganizational network drawing mainly from the social network theory brings forth 
the importance of semiautonomous subsidiaries with their specific environments and 
resources capable of making their own strategic choices. In line with this view, 
Michailova and Mustaffa (2012: 383) state that the traditional hierarchical perspective 
of the MNC regarding the HQ as the provider of knowledge to geographically dispersed 
subsidiaries has changed to a more heterarchical, network-based view, which recognizes 
the subsidiary as a valuable source of knowledge. Subsidiaries are no longer seen as 
only production intensive implementers and are granted with strategic independence. 
Indeed, MNCs are perceived as social communities, where power is decentralized and 
subsidiaries are granted with strategically important roles providing competitive 
advantage by contributing to the overall knowledge base of the company. Conducted 
research regard subsidiaries, for example, as knowledge intensive innovators, 
competence creators and centers of excellence playing an essential role in the 
knowledge network of the entire MNC (Gupta & Govindarajan 1991; Yang, et al. 2008; 
Frost, Birkinshaw & Ensigne 2002). 
 
Emanating from internalization theory, transaction cost economics, social network 
theory and the KBV, Gupta & Govindarajan (2000 a: 473) state, that the MNC is a 
“bundle of knowledge”, which existence is based on its superior abilities in transferring 
and exploiting knowledge compared to external market mechanisms. Kogut and Zander 
(1993: 625) argue accordingly that all firms can be regarded as social communities 
specialized in the internal transfer and creation of knowledge but particularly the MNC 
stands out as an efficient “organizational vehicle” transferring knowledge across 
boarders. Thus the MNC as an organizational form has a significant benefit in tapping 
into the different knowledge repositories of its geographically dispersed subsidiaries. 
According to Grant (1996: 375–384), knowledge being the most important resource of 



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the company, the primary task of the organization in pursuing sustainable competitive 
advantage is the integration of multiple knowledge bases. In other words, to maximize 
value attainable through sharing, transferring and combining MNC specific resources 
created and situated in every part of the company. Thus transforming subsidiary and HQ 
specific advantages into MNC-specific assets making the global company more than the 
sum of its parts (Bouquet & Birkinshaw 2008 b). 
 
 
2.2 Perspectives on knowledge 
 
 
To be able to understand the concept of knowledge transfer in MNCs one must first 
understand the different approaches regarding knowledge. The literature presents 
differentiating definitions, categorizations and terms of knowledge depending on 
adopted perspective of conducted research. One tendency is to separate between types, 
dimensions and characteristics of knowledge. However, this separation is far from 
consistent, and hence distinction between types, dimensions and characteristics of 
knowledge is blurred and different terms are often used in the same context 
(Michailowa & Mustaffa 2011: 4–5). For example Gupta and Govidarajan (2000 a) 
regard knowledge as all-inclusive by addressing it as organizational, whereas other 
researchers talk about customer, marketing and product knowledge or concentrate solely 
on technological knowledge (Davenport & Prusak; Håkanson & Nobel 2000). In 
addition to characteristics and types of knowledge scholars also use different terms for 
instance capabilities, best practices, know-how etc. when describing knowledge 
(Michailova & Mustaffa 2011). 
 
Knowledge originates from individuals and is situated in every part of the organization. 
According to De Long and Fahey (2000: 114) knowledge can be located in individuals, 
collectives or embedded in routines or processes depending on the context. The type, 
dimension and location of knowledge define its characteristics, which again, proven by 
the literature (e.g. Bhagat, Harveston & Triandis 2002; Michailova & Mustaffa 2011), 
affect its transferability. Therefore, it is crucial to understand different aspects of 
knowledge. 
 
Davenport and Prusak (1998: 1–2) suggest that a good starting point is to understand 
differences between data, information and knowledge. These three terms are often used 
interchangeably as synonyms despite they have a hierarchical relationship. Knowledge 



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derives from information, which is data with meaning and purpose. Without proper 
distinction between data, information and knowledge the organization will be likely to 
face problems along its knowledge management efforts (Davenport & Prusak 1998:1–6). 
 
Data is best described as a compilation of discrete, tangible and objective facts. Unlike 
information, data does not create an impact. It constitutes of signs without a meaning 
ready to be used as raw material. In organizations data is usually stored with the help of 
information technology and is valued through its accessibility. The importance of data 
is its function as raw material for creating information. (Davenport & Prusak 1998: 2–3; 
Bhagat et al. 2002: 205–206.) 
 
Information is data with relevance and purpose. It can be seen as a message, with a 
sender and a receiver, which brings human action to the focus (Davenport & Prusak 
1998: 3; Nonaka & Takeuchi 1995: 58–59). Unlike data, information is organized, 
contextualized and corrected. It has a shape and is given importance only if the receiver 
regards it as useful or more than data. As a message, information can flow in 
organizations whereas data stays stored in records. (Davenport & Prusak 1998: 1–4.) 
 
Knowledge is a complex mix of information with beliefs, commitment, experience and 
values with an expert insight. Knowledge is deeper than information and gives a 
platform for assimilating more information, experiences and expertize. It is embedded 
in every part of the organization from employees to processes and is thus both fluid and 
structured not to mention complex making it very hard to define. Unlike information, 
knowledge is constantly changing. An essential point is that information cannot evolve 
to knowledge without human action. Knowledge is considered valuable because it is 
complex and always about some end. For example knowledge can lead to better 
decision-making. (Ipe 2003; Bhagat et al. 2002: 205; Davenport & Prusak 1998: 5–6; 
Nonaka & Takeuchi 1995: 58–59.) 
 
Conducted research on characteristics of knowledge often defines knowledge through 
the distinction between tacit and explicit knowledge (Michailowa & Mustaffa 2011: 4; 
Chini 2005: 8). Michael Polyani first introduced this classification in 1966 (Szulanski 
1996). According to Nonaka and Takeuchi (1995) explicit knowledge is publicly 
expressed knowledge, which is easily articulated with words and numbers through 
social interaction and written documents. It is ”codified” therefor revealed by its 
communication, easy to store and transmit (Grant 1996: 111; Viitala 2006: 131; Nonaka 
& Takeuchi 1995: 59). Tacit knowledge is more cognitive and subjective, thus harder to 



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access or communicate. It is located in the minds of individuals and has been developed 
and internalized over time, which makes it very difficult to articulate or capture 
(Davenport & Prusak 1998: 70). Like explicit knowledge is revealed by its 
communication tacit knowledge comes visible through its application (Grant 1996: 111). 
Viitala (2006) states that individuals may not even be aware of the tacit knowledge they 
possess. Nonaka and Takeuchi (1995: 60) continue by describing explicit knowledge as 
“the tip of the iceberg” tacit knowledge being hidden under water. 
 
Another way to understand knowledge is to conceive it through which questions it helps 
to answer. OECD (1996) presents four different types of knowledge: know-what, know- 
why, know-how and know-who. Know-what is closest to data or explicit knowledge that 
can be seen as facts supporting basic functions and processes. Know-why is scientific 
knowledge retrieved from universities or external networks. This kind of knowledge is 
more tacit than know-what and is related to product and process development. Know- 
how can be described as firm specific capabilities and skills. Know-how equals to 
complex and valuable knowledge that can differentiate a company from its competitors. 
It constitutes mostly of tacit components. Know-who constitutes of the awareness of the 
location of knowledge and the way the knowledgeable uses his or her knowledge. This 
means that know-who includes parts of know-how, which enables the company to use 
effectively its overall knowledge, thus possessing this type of knowledge is the key in 
achieving competitive advantage. Because of their differing tacitness and explicitness 
all of the above-mentioned knowledge types are obtained from different sources: Know- 
what and –why can be retrieved from databases or reading a book, whereas know-how 
and –who need to be learned through practical experience including social interaction. 
(OECD 1996.) 
 
De Long and Fahey (2000) state that confusion revolving around the definition of 
knowledge would cease if the three types of individual, social and structured knowledge 
would be recognized. Building on this typology Bhagat et al. (2002) combined the 
aforementioned types with three dimensions of knowledge proposed by Garud and 
Nayyar (1994) to create a comprehensive view on knowledge. The types and 
dimensions of knowledge are presented in Figure 1. 
 



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Figure 1. Knowledge types and dimensions (Bhagat et al. 2002). 
 
 
Human knowledge is what individuals know. This type of knowledge can be tacit as 
well as explicit or both. According to De Long and Fahey (2000) human knowledge 
comprise skills like how to ride a bike or interview a customer. Social knowledge is 
created and shared within groups and teams as a result of working together, thus it is 
mostly tacit. Social or collective knowledge reflects cultural norms of the group, which 
can make it hard to transfer to an outsider (De Long & Fahey 2000; Bhagat et al. 2002). 
The third type of knowledge is Structured knowledge. This kind of knowledge is largely 
explicit and can therefore exist also independently in the routines, processes and 
systems of the organization (De Long and Fahey 2000). 
 
Garud and Nayyar (1994) argue that knowledge can be situated along three dimensions 
of knowledge: explicit versus tacit, simple versus complex and independent versus 
systemic. The position of knowledge on these dimensions affects the amount of 
information or additional knowledge needed to articulate it, which again influences the 
level of hardship encountered when transferring this knowledge (Garud & Nayyar 1994). 
For example complex knowledge requires naturally more effort to be understood than 
simple knowledge. Accordingly, systemic knowledge is embedded in the organizational 
context and can therefore be understood properly only through the wisdom (i.e. existing 
body of knowledge) of the transferring organization, whereas independent knowledge is 
more separable and thus easier to transfer. The concepts of explicit and tacit knowledge 



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were presented earlier but as a reminder this dimension follows same kind of rules tacit 
knowledge being harder to transfer than the more easily articulated explicit knowledge. 
(Bhagat et al. 2002.) 
 
In the model presented in Figure 1. the types and dimensions of knowledge are 
combined. Bhagat et al. (2002) argue that different types of knowledge tend to position 
differently on the three dimensions of knowledge. For example the type of social 
knowledge tends to be more tacit and systemic whereas structured knowledge is more 
likely explicit than tacit. In all, the more the type of knowledge is tacit, complex and 
systemic the more difficult it will be to transfer (Garud & Nayyar 1994: 370; Bhagat et 
al. 2002: 207). Nevertheless, the more tacit and complex the knowledge, the more it 
tends to provide competitive advantage and is thus perceived as valuable. 
 
Indeed, the classifications of knowledge help in explaining different knowledge 
characteristics, which again influence its transferability. The model presented in Figure 
1. adapted from Bhagat et al. (2002) was originally created to shed light on how 
different characteristics of knowledge in addition to cultural differences affect the 
effectiveness of cross-border knowledge transfers in MNCs. According to Bhagat et al. 
(2002) among cultural differences and the cognitive styles of individuals the type of 
knowledge is the most important factor affecting the effectiveness of cross-border 
knowledge transfers. Similarly to the model of Bhagat et al. (2002) Kogut & Zander 
(1993) present the three constructs of knowledge codifiability, teachability and 
complexity embodying different amounts of tacit and explicit elements determining the 
easiness or difficulty of knowledge transfers. Riusala and Suutari (2004) used these 
constructs in their study on international knowledge transfers through expatriates. 
 
Considering the scope of this study and for the sake of simplicity, this thesis follows the 
well-established view of knowledge as a combination of tacit and explicit components 
presented by Polyani. The more tacit the knowledge, the more complex and hard it is to 
transfer. However, this type of knowledge is most valuable to the company because it is 
hard to imitate and constitutes of a combination of accrued experiences, values and 
beliefs molded in the context of the organization. Knowledge resides in every part of the 
organization but originates from individuals and their interaction. The different 
classifications of knowledge are summarized in Table 1. 
 
 



 22 

Author Perspective on knowledge 
Polyani (1996) Tacit & Explicit 
Kogut & Zander (1993) Codifiability-Teachability-Complexity 
Garrud & Nayyar (1994) Three dimensions of knowledge: 

• Explicit vs. Tacit  
• Simple vs. Complex  
• Independent vs. Systemic  

OECD (1996) Know-what, -why, -how and who 
Davenport & Prusak (1998) Data-Information-Knowledge 
De Long & Fahey (2000) Three types of knowledge: 

• Individual 
• Social 
• Structured 

Bhagat, Harveston & Triandis (2002) The types of individual, social and 
structured knowledge position differently 
on explicit vs. tacit, simple vs. complex 
and independent vs. systemic dimensions 
of knowledge. 

Table 1. Knowledge classifications. 
 
 
2.3 Knowledge transfer as part of knowledge management 
 
 
With the rise of the KBV of the firm, knowledge is considered as the most important 
asset of the company and needs to be managed like any other tangible resource. 
According to Davenport, De Long and Beers (1998: 43) organizational processes 
aiming at more effective creation, transfer and utilization of knowledge are all part of 
knowledge management. The literature presents a variety of definitions of knowledge 
management including various numbers of different terms but in general they all 
embody the three objectives of creating, retaining and transferring of knowledge. 
 
Gupta and Govindarajan (2000 b) argue that the objective of knowledge management is 
to mold the organization into a “knowledge machine” with a “social ecology” composed 
of culture, structure, information systems, reward systems, processes, people and 
leadership. This machine needs to effectively create, acquire, share and mobilize 
knowledge to stay competitive. As it is visible in the forgoing words of Gupta and 



 23 

Govindarajan (2000 b) the sphere of influence of knowledge management is deep 
involving the whole organization from employees to top managers, people to structures, 
systems and processes. Hansen, Nohria and Tierney (1999: 116) argue that knowledge 
management requires the attention of the CEO and general managers and needs to be 
coordinated with functional departments of IT and HR and the competitive strategy of 
the company. If not, both the company and its customers suffer. Davenport et al. (1998) 
state accordingly that knowledge management and its processes are seen as the modern 
company’s strategic tools in achieving competitive advantage. 
 
Knowledge transfer is an important part of the knowledge management cycle. See 
Figure 2. Gupta and Govindarajan (2000 b) regard knowledge management consisting 
of two main tasks of accumulating and mobilizing (i.e. transferring) knowledge. These 
main tasks can be subdivided into the elements of knowledge creation, acquisition, 
retention, identification, outflow, transmission and inflow. Knowledge creation equals 
learning or could be considered as innovating whereas acquisition is the process of 
internalizing knowledge gained outside the company. Retention consists of efforts to 
retain created and acquired knowledge. These three elements are all part of knowledge 
accumulation in a company. Mobilizing knowledge starts with the identification of 
opportunities to share knowledge. Next, the company must encourage knowledge 
outflow by motivating knowledgeable people to share their knowing keeping in mind 
that knowledge, to be transmitted, needs effective and efficient channels. For the 
mobilizing of knowledge to succeed knowledge receivers must also be encouraged to 
accept and utilize the inflowing knowledge. (Gupta & Govindarajan 2000 b: 73.) 
 

Figure 2. Km-cycle based on (Gupta & Govindarajan 2000 b). 



 24 

According to Argote, McEvily and Reagans (2003) research conducted on 
organizational learning and knowledge management is highly differentiated combining 
several disciplinary perspectives. The researchers argue that the heterogeneity of 
knowledge management research cuts across the disciplines of economics, information 
systems, organizational behavior and theory, psychology, strategic management and 
sociology. This observation is very much in line with the arguments of the sphere of 
influence of knowledge management in the organization presented earlier (e.g. Gupta 
and Govindarajan 2000 b; Hansen et al. 1999; Davenport et al. 1998). In their attempt to 
organize the literature on knowledge management and bring forward existing 
interconnections between the different disciplinary perspectives Argote et al. (2003) 
created a framework structured around the two dimensions of knowledge management 
outcomes and knowledge management context. 
 
 Emanating from the literature Argote et al. (2003) divide knowledge management 
outcomes to the three factors of creating, retaining and transferring of knowledge. In 
line with the knowledge management cycle presented by Gupta and Govindarajan (2000 
b), Argote et al. (2003) perceive the creation, retention and transferring of knowledge as 
interrelated. In other words, if one of these outcomes is missing or not implemented 
effectively the cycle breaks and knowledge is neither created, nor transferred properly. 
For example, if a company wishes to gain competitive advantage it is not enough to 
accumulate knowledge, but also to transfer it. On the other hand, mobilizing knowledge 
is not possible if it is not accumulated, or like Gupta and Govindarajan (2000 b) put it: 
created, acquired and held on to. Furthermore, the transferring and combining of 
knowledge can create new knowledge to be shared (Argote et al. 2003; Davenport & 
Prusak 1998). 
 
Literature tends to explain the context in which knowledge management takes place 
through the properties of units, properties of the relationships between units and 
properties of the knowledge itself depending on adopted theories and perspectives. In 
other words, “different theories of knowledge management give causal priority to 
different contextual properties” (Argote et al. 2003: 572). According to Argote et al. 
(2003) these properties illustrate how researchers have addressed the issue of what 
affects the creation, retention and transferring of knowledge (i.e. knowledge 
management outcomes).  However, the contextual properties of knowledge management 
do not explain the reason behind the very occurrence of the outcomes. Thus fail to 
answer the question why a given property of the context affects a chosen outcome. To 
answer this question, for example why the relationship between two individuals affects 



 25 

knowledge transfer, researchers must adopt a more micro-level approach and 
concentrate on mechanisms affecting individual level behavior. This is especially true 
when studying individual level knowledge sharing instead of organizational knowledge 
transfer between for example two subsidiaries. After all, understanding individual level 
knowledge sharing forms the basis for understanding MNC wide knowledge integration 
(Ipe 2007). MNC knowledge flows and knowledge sharing will be covered next under 
the following section. 
 
 
2.4 MNC knowledge sharing 
 
 
Conducted research on MNC knowledge transfers has identified different kinds of 
knowledge flows present in the global company (e.g. Michailova & Mustaffa 2012; 
Gupta & Govindarajan 2000 a). Due to the multidimensional nature of the MNC, 
knowledge flows in several directions and across multiple organizational levels (Gupta 
& Govindarajan 2000 a). On a general level MNC participates in two kinds of 
knowledge exchange: internal and external knowledge transfers. The former 
encompasses knowledge flows within the borderlines of the company the latter 
comprising knowledge transfers with external third parties. The focus of this study is 
limited to internal transfers which can further be broken down into inter unit or intra 
unit flows. According to Michailova and Mustaffa (2012) inter unit knowledge flows 
can be divided into knowledge in- and outflows depending on if the focal unit of 
analysis is receiving or dispatching knowledge. When knowledge flows between two 
subsidiaries it is referred as being horizontal whereas if the knowledge is transferred 
between the HQ and a sister unit it is called vertical knowledge flow. When the 
subsidiary transfers knowledge to the HQ, or engages in vertical outflow, it can also be 
referred as reverse knowledge transfer (Ambos et al. 2006). Intra unit knowledge 
transfers flow along the same directions as inter unit transfers with the exception that 
they do so within a MNC unit not between them. For example intra unit knowledge 
flows occur between different divisions and business functions and the hierarchical 
structures of a given subsidiary. However, when the MNC is considered as the unit of 
analysis, researchers can utilize the term intra unit instead of inter unit in describing a 
knowledge transfer between two MNC units. The different MNC knowledge flows are 
summarized in Figure 3. 



 26 

 

Figure 3. MNC knowledge flows 
 
 
The discussion so far has been on the organizational level of knowledge transferring: 
between units, functions and divisions. However, the most fundamental form of 
knowledge transferring happens at the individual level between two or more employees 
either from the same or between different MNC units. According to Minbaeva, Mäkelä 
and Rabbiosi (2012: 389), there exists a shared understanding in knowledge transfer 
research that organizational level knowledge transfer emanates from individuals.  In line 
with this view Mäkelä and Brewster (2009) identify an increase in the recognition of 
interpersonal interaction as an important channel for inter unit knowledge flows. For 
example Cabrera and Cabrera (2005) state that knowledge sharing is a key enabler of 
knowledge transfer within organizations. Also Shotter and Bontis (2009) argue that 
direct linkages and communication enabling person-to-person interaction are needed for 
all kinds of knowledge flows to happen. One of the most cited arguments is the one 
presented by Foss (2007) according to which an understanding of intra organizational 
knowledge transfers cannot be reached by excluding the individual level of knowledge 
sharing from the examination (see e.g. Husted et al. 2012; Minbaeva et al. 2012; 
Michailova & Minbaeva 2012). 
 
The so-called “people perspective” of knowledge management stresses the importance 
of individuals who possess knowledge that needs to be disseminated to the level of 
groups and eventually up to the organizational level where it can be transformed into 
competitive and economic value for the company (Ipe 2003). For example, Foss, Husted 
and Michailova (2010) argue that individual level knowledge sharing results in 

Vert
ica

l (
fo

rw
ard

) Vertical (reverse) 



 27 

organizational knowledge. Research assuming this perspective adopt individual level of 
knowledge sharing as their focal point of analysis compared to studies concentrating on 
the more organizational level of knowledge transferring. Like mentioned earlier, 
knowledge assets grow when used and existing knowledge serves as a foundation on 
top of which new knowledge can be created. Thus the effective leveraging of 
knowledge is dependent on the capabilities of employees to share their knowledge while 
building on the knowledge received from others. According to Ipe (2003: 341) 
knowledge sharing is studied at the most basic level between individuals as “an act of 
making knowledge available to others”. The focus of this study is to take a closer look 
on mentoring as a context and/or channel for individual level knowledge sharing 
between employees from different MNC subsidiaries. 
 
2.4.1 Knowledge sharing and its barriers 
 
Knowledge transfer and thus sharing is a complex and intricate process because of its 
many determinants (Szulanski 2003; Minbaeva 2007: 568; Ipe 2003). Conducted 
research traditionally approaches this process through a communication model or 
signaling metaphor by specifying the five elements of the source, recipient, channel, 
message and context (Szulanski 2000: 11). In other words, the sharing process takes 
place in a given environment including at least two individuals, one acting as the source 
or sender of a message (i.e. knowledge) the other adopting the role of a recipient to 
whom, the message is sent through a chosen channel. Szulanski (2003) argues that the 
transfer of best practices within an organization is the recreation of a superior practice 
in another setting. Thus the act of sharing knowledge can be considered successful not 
until the shared knowledge is received, understood and utilized by the recipient. 
 
Szulanski (1996, 2003) divides the transferring of knowledge into four stages: initiation, 
implementation, ramp-up and integration. Initiation stage starts when there exists a gap 
between someone’s knowing and what is known in the organization. The discovering of 
a need to fill this gap triggers a search for superior knowledge. On the other hand, 
coming across knowledge, which renders an existing situation unsatisfactory might 
reveal a need to acquire new knowledge. In short, the initiation stage includes actions 
and situations that ultimately lead to the decision to share knowledge (Szulanski 1996). 
The implementation stage comprises the actual sharing of knowledge. Social ties are 
established and the shared knowledge is refined to the needs of he recipient and shaped 
into an easily understandable form. The implementation stage comes to an end when the 
receiver starts to use the shared knowledge. During the ramp-up stage the source 



 28 

receives support in the utilization of the newly acquired knowledge. Occurring 
problems are solved and the ineffective use of knowledge is “ramped up” to satisfactory 
levels. The integration stage is about making the shared knowledge routinized. 
Established shared meanings and behaviors are reflected in knowledge related actions. 
As a consequence behavior becomes understandable, predictable and stable. In the end 
of the process knowledge becomes institutionalized. 
 
The process view of exchanging knowledge has been criticized due to its simplistic 
approach on a complex phenomenon. According to Harvey (2012) conducted research 
has suggested that knowledge transfer is better understood through mutual exchanges 
compared to the generic source-recipient model. As the former entails a one-way 
process where knowledge is modified by the sender to be easily recreated in another 
setting, the latter model considers a deeper level of sharing know-how through a back 
and forth movement, socialization and shared experiences resulting in new skills and a 
mutual understanding of issues (Harvey 2012). The mutual exchange model stresses the 
importance of interaction through discussion and the reciprocity of the relationship 
between the sender and the receiver of knowledge. For example Harvey (2012) found 
mentoring and storytelling groups to enhance knowledge transfer through interaction 
and learning taking place in discussions. The knowledge being sent was constantly 
adapted to meet the needs of the recipient and refined with the input of both the sender 
and the receiver. However, one could argue that the model of mutual exchange relies 
heavily on the basics of the source-recipient model. The back and forth exchanges can 
be understood as a mix of individual acts of sharing knowledge explained by the source-
recipient model. The two models are summarized in Figure 4. 



 29 

Figure 4. Knowledge sharing models (based on Harvey 2012). 
 
 
Emanating from both, the sender-receiver and the mutual exchange model, Michailova 
and Minbaeva (2012) view knowledge sharing as a relational act based on a sender-
receiver relationship composed of multiple concurrent exchanges between the 
participants. During this ongoing act (or process) none of the participants relinquish 
ownership of their knowledge. On the contrary, the outcome is joint ownership of the 
shared knowledge, which might even be a refined version of the original due to the 
input of the receiver (Ipe 2003 as cited by Michailova & Minbaeva 2012: 60). This 
thesis adopts the definition of knowledge sharing presented by Michailova and 
Minbaeva (2012). 
 
In an ideal situation knowledge would circulate around the organization from 
knowledgeable to knowledge seekers regenerating the knowledge bases of the company 
and enabling full leveraging of individual’s know-how. However, contrary to popular 
belief and despite of its axiomatic benefits, research has shown that knowledge sharing 
does not happen by itself and has even been referred as being “sticky” (Szulanski 1996). 
Knowledge sharing, its occurrence and stickiness have been explained through the 
variables of the source-recipient model. That is, research has identified several aspects 



 30 

of the source, recipient (and the relationship between them), knowledge and the context 
to have an effect on knowledge sharing. A good example of such research is the work 
conducted by Szulanski (1996; 2000; 2003) on different knowledge barriers or 
“stickiness factors”.  
 
Szulanski (1996) argues that both the source and knowledge being transferred might 
lack credibility or there exists uncertainty how a given practice can be recreated in a 
new context, thus it suffers from “causal ambiguity”. It is also possible that the source 
lacks credibility or is not motivated to engage in knowledge transfer because of a fear of 
loosing a favorable role or not getting a fair compensation from the valuable asset he or 
she has created. Gupta and Govindarajan (2000 b: 73–74) refer to this unwillingness to 
share as the “Knowledge is power –syndrome”. Likewise, the recipient could lack 
motivation to search or even accept knowledge outside its boundaries. This is referred 
as the “Not Invented Here” or NIH –syndrome (Szulanski 1996: 31). In addition, the 
recipient might suffer from low absorptive and retentive capacities to even receive, 
utilize and keep transferred knowledge. Szulanski (1996) also brings forth the negative 
effects of a barren organizational culture and arduous relationship hindering the process 
of transferring knowledge. The presented stickiness factors have different effects during 
the stages of the transfer process: in the beginning source related factors dominate but 
as the transfer process unfolds their importance decreases while the recipient’s 
characteristics stand out (Szulanski 2003). Furthermore, given the context of the MNC, 
the presented barriers for effective knowledge transfer are raised higher by the 
international dimension of cross border knowledge transfers. More precisely, colliding 
organizational and national cultures, institutions, norms and values not to mention 
relationships and power balances between the different MNC units can cause extra 
hardship regarding the effective transferring of knowledge. 
 
Indeed, the process or act of sharing knowledge, which starts from the identification of 
a need and ends with the internalization of know-how encompass many determinants, 
which together or in isolation can act as barriers for the effective sharing of knowledge. 
Even though discussed at the level of organizational knowledge transfer, the above-
mentioned barriers and their effects on knowledge transfer are equally valid at the 
individual level of knowledge sharing. 
 
2.4.2 The Knowledge governance approach and AMO framework 
 



 31 

Even though acknowledged as a fundamental building block of organizational 
knowledge sharing, conducted research has been claimed to pay insufficient attention to 
individual level constructs and mechanisms of knowledge sharing (Foss et al. 2010). 
For knowledge sharing to occur conscious action is needed on behalf of the individual 
in possession of the knowledge and/or the individual receiving the shared knowledge 
(Ipe 2003). Therefore, like mentioned earlier under the section of knowledge 
management, there exists a need to explain individual level behavior regarding 
knowledge sharing. More precisely, adopting a micro level approach to complement the 
well-established macro level research is warranted. As a response to this need a new 
approach on knowledge sharing has emerged: the knowledge governance approach or 
KGA. 
 
The knowledge governance approach (KGA) makes a distinction between micro and 
macro levels. According to Foss (2007) extant literature on the “knowledge movement” 
is confined to studying macro level phenomenon or the correlation between macro 
phenomena. For example how organizational antecedent, like control mechanisms affect 
knowledge sharing outcomes. However, by concentrating solely on macro variables or 
the links between them and neglecting mediating micro variables and 
interconnectedness researchers end up with a shorthand explanation of a complicated 
multilevel phenomenon (Foss et al. (2010). See Figure 5 for different macro and macro 
links underlying the KGA approach. 
 
 

Figure 5. Different levels of analysis (Modified from Foss et al. 2010). 
 
 

C 



 32 

Based on the work of Coleman 1990, Foss et al. (2010) argue that and ideal level of 
analysis considers a macro level outcome (upper-right corner), for example 
organizational knowledge sharing as a result of individual level behavior and action 
(lower-right corner), which in turn is affected by surrounded conditions (lower-left 
corner) determined by organizational antecedents (upper-left corner). According to 
Gooderham, Minbaeva and Pedersen (2011) this causal process from organizational to 
individual level and back brings forward important individual level factors such as 
beliefs, perceptions, expectations, decision-making and abilities, which all occupy an 
essential role in explaining knowledge sharing. Bock et al. (2005) stress the importance 
of the willingness of individuals to make their knowledge available. Thus effective 
knowledge sharing is dependent on the understanding and proper management of 
factors inducing such behavior. The underlying assumption presented by the KGA is 
that organizations have the possibility to impact conditions in which knowledge sharing 
takes place through for example HRM practices and thus affect individual knowledge 
sharing behavior that aggregates to the organizational level (Foss 2007; Foss et al 2010; 
Gooderham et al. 2011).  
 
One widely utilized approach in explaining knowledge sharing behavior, its antecedents 
and the relationship between them is the AMO framework. According to Hughes (2007) 
the Ability–Motivation–Opportunity framework spawns formal, meta and midrange 
theories, which serve as a basis for understanding human behavior. For example, 
applying the framework in the context of knowledge management Argote et al. (2003) 
argue that the causal mechanisms of ability, motivation and opportunity answer the 
questions of how and why properties of the context affect the creation, retention and 
transferring of knowledge. The three mechanisms are often considered as 
complementary and interconnected, having a combined effect on knowledge sharing. 
However, like suggested by Siemsen, Roth and Balasubramanian (2008) it is also 
possible to consider which one of the AMO variables present itself as the constraining 
factor ultimately impeding desired behavior. 
 
Regarding the topic of this thesis, knowledge sharing behavior can be understood by 
analyzing an individual’s ability, motivation and opportunity to engage in knowledge 
sharing. Siemsen, Roth and Balasubramanian (2008) condense that ability refers to an 
individual’s skills and existing knowledge regarding the action to be initiated. 
Motivation encompasses the individual’s willingness to act whereas opportunity 
embodies exogenous factors such as environmental and contextual mechanisms 
enabling or restricting action. Indeed, the AMO framework guides analysis towards the 



 33 

conditions of individual behavior and helps to synthesize literature on factors affecting 
knowledge sharing. Next, different factors affecting MNC knowledge sharing will be 
taken under closer examination utilizing ability, motivation and opportunity as the three 
mechanisms constructing the conditions for knowledge sharing behavior. 
 
 
2.5 Factors affecting knowledge sharing 
 
 
Factors affecting knowledge sharing presented in this section are accumulated from 
several academic sources covering the topics of knowledge sharing and transferring. 
The following division of the identified factors under the constructs of the AMO 
framework should not be considered as all-encompassing or definite but rather as a 
generalization offering insight and clarity in understanding knowledge sharing and its 
antecedents. 
 
2.5.1 Motivation 
 
Huang et al. (2013) argue that motivation serves as the core proposition behind various 
theories such as social exchange theory, agency theory, expectancy-value frameworks 
and social capital theory all used to explain knowledge sharing behavior. The focal role 
of motivation in explaining knowledge sharing behavior is also visible in the work of 
Bock et al. (2005) in which motivation serves as the underlying driver for an 
individual’s intention to share knowledge. Conducted research on motivation tends to 
make a division between internal an external motivational factors or discuss about 
intrinsic and extrinsic motivations (See e.g. Ipe 2003; Minbaeva et al. 2012; Bock et al. 
2005). According to Minbaeva et al. (2012) extrinsic motivation is affected by 
exogenous factors originating from the surrounding context. It is a result of indirectly 
satisfied needs, through for example financial compensation or gaining recognition 
(Osterloh, Frost & Frey 2002 as cited by Minbaeva et al. 2013: 391). Thus extrinsic 
motivation to do something is fundamentally composed from expectations of external 
rewards. The concept of extrinsic motivation has been widely used for example in 
research on compensation and reward systems to incentivize knowledge sharing. In 
contrast to extrinsic motivation, intrinsic motivation to share knowledge comes form 
within the individual the only reward from engaging in the behavior being the activity 
itself. In other words, an intrinsically motivated individual engages in knowledge 
sharing because it satisfies internal needs (Minbaeva et al 2012). Nevertheless, extant 



 34 

literature is not unambiguous about the terminology. For example, extrinsic motivation 
is often linked solely to monetary compensation. 
 
A similar division is also visible in the theory of reasoned action or TRA presented first 
by Fishbein and Ajzen in 1975. According to the theory a certain behavior is preceded 
by an intention to perform that behavior, which again is dependent on an individual’s 
attitudes as well as subjective norms towards and concerning the behavior to be 
conducted (Fishbein & Ajzen 1975). Attitudes are composed of personal beliefs about 
the consequences of the behavior, for example the individual might consider attainable 
benefits if engaging in the behavior. Subjective norms on the other hand are a result of 
normative beliefs about the behavior, for example an individual’s intention might be 
affected by the general acceptability of the intended behavior. Bock et al. (2005) view 
the TRA as an integrative framework, which brings together forces, both internal and 
external, constituting an individual’s willingness to share knowledge. In short, 
motivational factors are embedded in intentions, which ultimately affect behavior as 
proposed by Ajzen (1991 as cited by Gagné 2009: 572). If motivation is the core 
proposition behind theories explaining knowledge sharing behavior then TRA and the 
notions of extrinsic and intrinsic motivations can be argued to serve as the underlying 
ideas behind motivation itself. According to Cabrera and Cabrera (2005: 721–722), the 
theories of social exchange, social dilemma and social capital shed light on factors 
affecting knowledge sharing attitudes and what constitutes an environment conducive to 
sharing knowledge (i.e. subjective norms). Next motivation will be taken under closer 
examination with the help of these theories. 
 
From the perspective of extrinsic motivation an individual’s decision-making process 
about whether or not to share knowledge is comparable to a cost-benefit analysis 
(Cabrera & Cabrera 2002 as cited by Minbaeva et al. 2012: 391). Based on conducted 
research, Bock et al. (2005) state that knowledge-sharing participants have to endure 
costs in the form of lost time and effort. Therefor, perceived benefits must outweigh 
costs for an individual to engage in knowledge sharing. According to Bock et al. (2005), 
an individual’s personal belief structures regarding the sharing of knowledge are 
composed of the consideration between individual, group and organizational level gains 
from monetary rewards to gaining reputation and loosing power.  This self-interested 
analysis of cost and benefits is usually placed under the theory of social exchange 
according to which expected benefits can also manifest themselves in an intangible 
form for example as an expectation of reciprocity in the future (Cabrera & Cabrera 
2005). 



 35 

 
According to Cabrera and Cabrera (2005) an individual’s expectations of reciprocity are 
regulated by trust that sharing of knowledge will, at some point, be reciprocated. 
Without trust of getting compensated, it is not rational to engage in knowledge sharing. 
Indeed, the cost-benefit -ratio can be altered in two ways. First, the organization can 
rely in commitment-based “communal governance” aimed and leveraging individuals’ 
volunteerism and intrinsic motivation driven by the psychological mechanisms of trust, 
loyalty and commitment. Second, tangible and explicit incentives can be implement to 
more or less force desired behavior. Nevertheless, research has shown little or negative 
effects of transaction-based governance on knowledge sharing behavior. For example, 
Husted et al. (2012) found transaction –based governance to strengthen individuals’ 
reasons for hoarding and rejecting knowledge and argue that knowledge sharing cannot 
be ruled or paid but rather stimulated by affecting intrinsic motivation. Monetary and 
other tangible incentivizing of knowledge sharing behavior have a negative effect on 
volunteer exchanging of know-how and accentuate the “politics of information” in the 
company (Davenport, Eccles & Prusal 1992 as cited by Ipe 2003: 346). 
 
Closely related to the idea of expected benefits and the social exchange theory is the 
earlier mentioned “Knowledge is power –syndrome” (Gupta & Govindarajan 2000 b) 
with the exception that instead of engaging in knowledge sharing based on 
considerations about attainable benefits one might withdraw from the behavior in fear 
of loosing a benefit linked to the possession of specific knowledge. When knowledge is 
valued as the most important resource of the company, its possession can serve as a 
noticeable advantage when trying to exert influence in the power circuits of the 
company (Bouquet & Birkinshaw 2008 a). When knowledge is attributed with power 
and considered as a source of individual competitive advantage voluntary sharing of 
knowledge is discouraged (Ipe 2003; Husted et al. 2012). Attached value to knowledge 
might in addition create a need among employees to create and utilize their own 
knowledge instead of receiving it from someone else due to professional pride (Husted 
et al. 2012). Related to the notion of professional pride, Michailova and Minbaeva 
(2012) state that managers in a higher hierarchical position might be reluctant to receive 
knowledge from employees at lower hierarchical levels. Likewise, subordinates could 
withhold knowledge in order to appear less knowledgeable than their manager. The 
rejection of knowledge might also be a result of missing trust in the source or the 
knowledge being shared. A strong group affiliation might even cause a “them versus us” 
differentiation. According to Husted et al. (2012), all of the above-mentioned issues 
related to receiving knowledge can be grouped under the not-invented-here syndrome. 



 36 

 
According to Bock et al. (2005), in addition to an unfavorable cost and benefit –ratio, 
missing trust or value attached to knowledge, a lack of motivation to engage in 
knowledge sharing might originate from a public good dilemma. Cabrera and Cabrera 
(2005) argue accordingly that knowledge contribution to the repositories of the 
company is comparable to the same social dilemma identified to exist with public goods. 
In short, once shared in the organization, knowledge is available for everyone, even for 
those who have not made any contribution in return (Bock et al. 2005). Thus the fear of 
free-riding has a negative effect on motivation to share knowledge resulting in a 
suboptimal outcome from the standpoint of the organization. In line with this view 
Kramer (1999 as cited by Ipe 2003: 347) identify perceptions of others not contributing 
equally or exploiting cooperative efforts produce barriers to trust resulting in decreased 
motivation to share. As such, social dilemma is closely related to expectations of 
reciprocity. Nevertheless, Cabrera and Cabrera (2005) state that by lowering perceived 
costs of contributing and increasing perceived rewards when sharing knowledge, the 
public good dilemma can be overcome. In addition to relying solely on extrinsic 
motivation, the public good dilemma can be fought with the help of individual needs, 
the components of intrinsic motivation. For example, knowledge sharing is more likely 
to take place when an individual regards his or her knowledge as helpful and valuable to 
others and shares it out of personal joy and satisfaction. Thus the contribution of sharing 
possessed knowledge is expected to have a positive impact on the receiver’s life. This 
kind of behavior results from other-oriented empathy and helpfulness (Allen 2003). 
Furthermore, an individual’s willingness to share and receive knowledge is influenced 
by his or her level of “self-efficacy”, that is, the person’s beliefs about the achievability 
of the task at hand (Cabrera & Cabrera 2005: 723). A final option to fight the public 
good dilemma is to increase group identification among individuals, which is also 
touched upon the relational dimension of social capital. 
 
Nahapiet and Ghosal (1998: 243) define social capital as: “...the sum of the actual and 
the potential resources embedded within, available through, and derived from the 
network of relationships possessed by an individual or social unit.” In other words, 
social capital reflects the quality of relationships: a dense social capital enhances the 
creation and sharing of intellectual capital (i.e. knowledge) (Nahapiet and Ghosal 1998). 
Researchers usually distinguish between three dimensions of social capital: structural, 
relational and cognitive (e.g. Nahapiet & Ghosal 1998; Cabrera & Cabrera 2005). The 
structural dimension constitutes of the ties and bonds or linkages between actors. It 
describes the density of network ties and refers to the pattern of social interactions 



 37 

among individuals. The cognitive dimension embodies factors increasing mutual 
understanding and enabling effective communication such as shared language, codes 
and the way actors impress themselves. The relational dimension comprises emotional 
attachments including shared trust, identity, norms and obligations affecting individual 
behavior. The shared trust that forms in socialization processes and originates from the 
relational social capital is a prerequisite for the beliefs of reciprocity affecting 
knowledge sharing motivation to exist (Cabrera & Cabrera 2005). The relational 
dimension of social capital resembles closely the constructs of intention presented by 
the theory of reasoned action. Indeed, attitudes and subjective norms are composed of 
beliefs about the consequences of and beliefs about an intended behavior. In line with 
this view, Cabrera and Cabrera (2005) argue that it is the relational dimension of social 
capital, which determines the willingness to share knowledge the other two dimensions 
mainly affecting the opportunity to engage in knowledge sharing. 
 
As presented earlier under the topic of knowledge barriers, the organizational culture 
plays an essential role in the success or failure of the knowledge sharing process. 
Szulanksi (1996) argues that an organizational culture may either be barren or fertile 
towards the sharing of knowledge. Organizational culture constitutes of values, norms 
and practices, which affect the behavior of the company including the way it creates, 
uses and shares knowledge (De Long & Fahey 2000). Kostova (1999) argues 
accordingly that organizational culture affects at both the general level on how learning, 
innovation and change are perceived and at the practice level on how the values of a 
given practice match with the ones of the receiving party. Michailova and Minbaeva 
(2012: 60) argue that organizational values that operate both on behavioral and 
cognitive levels are the most important elements forming organizational culture. 
According to the researchers organizational values affect established patterns of 
behavior, thus affect knowledge sharing. By studying the espousing, enacting and 
internalizing of the value of dialogue Michailova and Minbaeva (2012) found out that 
knowledge sharing behavior of individuals is not influenced by organizational values 
per se but by the degree of their internalization among organizational members within 
and across departments. 
 
If the value of sharing knowledge occupies an integral part in the organization 
employees are more likely to be motivated to share and receive knowledge because the 
behavior is valued in the company and among colleagues. Thus, attitudes and subjective 
norms forming the intention to share knowledge are more likely to be positive and 
supportive than negative. For example, the internalization of the value of sharing 



 38 

knowledge can be decisive whether sharing knowledge is considered as a laborious 
extra-role behavior or daily in-role behavior (Wang & Noe 2010). Also Cabrera and 
Cabrera (2005) identify organizational culture as a normative guideline for supporting 
knowledge sharing. However, in addition to creating a hospitable environment for 
sharing to take place through social norms depicting the importance of knowledge 
sharing, organizational culture should be utilized to construct an environment of 
fairness and trust. Among others Ipe (2003) and Bock et al. (2005) stress the role of an 
open, trusting and fair culture whereas Husted et al. (2012) discuss about tolerance 
towards making mistakes. Cabrera and Cabrera (2005: 729) state that extant literature 
on knowledge sharing seems to unanimously agree that willingness to share is increased 
in an open and trusting environment. 
 
The linkage between organizational culture and knowledge sharing is emphasized in the 
case of MNCs, which might comprise of multiple subcultures (Michailova & Minbaeva 
2012). Individuals from different MNC units may not always share the same norms and 
values. Differences in values can originate from the operating environment, such as the 
national culture, as well as differing appointed unit roles in the corporation. As a result 
even though the corporate headquarters would promote and foster a culture of sharing 
knowledge some units may decide not to adhere to the parent company mandate, which 
will be reflected at the individual level. Researchers have identified this situation as a 
principal-agent dilemma (e.g. Björkman, Wilhelm, Barner-Rasmussen & Li 2004). 
According to the agency theory, or agency dilemma, due to differing interests and 
information asymmetries, the agent (e.g. subsidiary) might not act as the principal (e.g. 
HQ) whishes. Even though the principal would value knowledge sharing the agent 
might not. Because of differing values the agent might consider knowledge sharing 
initiatives as costly or in vein. In this kind of situation the role of organizational culture 
as an enabler of a conducive environment bringing individuals closer together both 
physically and mentally is emphasized. Factors affecting motivation to share knowledge 
are presented in Table 2. 
 
 

Factors affecting knowledge sharing motivation 
Source Expected costs & rewards 
 Expectations of reciprocity 
 Prosocial behavior 
 
Recipient Professional pride 



 39 

 Them vs. us 
  
General Trust 
 Self-efficacy 
 Hierarchies 
 Value related to knowledge 
 Open, trusting & fair culture 
Table 2. Factors affecting knowledge sharing motivation. 
 
 
2.5.2 Opportunity 
 
Siemsen et al. (2008) view the opportunity to share as a vague concept compared to 
motivation and ability and argue that the construct of opportunity captures the 
remaining exogenous factors affecting knowledge sharing. Nevertheless, without the 
existence of sharing channels, enabling structures and facilitating technology 
knowledge sharing is impeded. 
 
Opportunity to share knowledge is highly dependent on the existence, availability and 
quality of proper sharing channels. In other words, knowledge sharing opportunity and 
the success or failure of the sharing process is conditional on the relationships between 
individuals and the surrounding context. Argote et al. (2003) argue that organizational 
relationships physically and psychologically reduce the amount of distance between 
individuals and provide employees the opportunity to learn from each other. From a 
theoretical perspective, a dense social capital and especially its structural dimension 
facilitate the sharing of knowledge. Indeed, strong ties and bonds between individuals 
increase the opportunity of knowledge sharing (Nahapiet & Ghosal 1998). 
 
Depending on the formulation of the relationship Ipe (2003) makes a distinction 
between formal and informal opportunities to share knowledge. Formal opportunities to 
share knowledge or “purposive learning channels” are specifically designed by the 
organization to enable and support the acquisition and dissemination of knowledge. The 
organization can create such opportunities for example through establishing 
communities of practice, work teams and training programs all of which provide 
necessary tools and create a structured environment for knowledge sharing to take place 
(Cabrera & Cabrera 2005; Ipe 2003). Furthermore, the existence of such channels can 
be seen to reflect top management’s support toward knowledge initiatives. On the 



 40 

contrary, informal opportunities or “relational learning channels” arise from 
interpersonal relationships and social networks. Unlike opportunities created through 
formal interventions of management, informal opportunities can only be supported by 
the organization for example through creating a fertile environment for employees to 
interact and build relational channels (Ipe 2003). The utilization of these channels is 
optional, thus occurring opportunities to engage in knowledge sharing are informal in 
nature. Nevertheless, informal learning channels can be blocked by hierarchical or 
organizational structures dictating strict information reporting procedures and building 
silos around functions and departments (Al-Alawi, Al-Marzooqi & Mohammed 2007). 
As a consequence knowledge sharing becomes laborious and takes place on a restricted 
level mostly between top management from which it is assimilated downwards. Another 
barrier for informal knowledge sharing to take place is the absence of suitable places. 
According to Swap et al. (2001) knowledge is shared unconsciously and incidentally 
while at work. Therefor, closed offices and small coffee rooms inhibit knowledge 
sharing (Al-Alawi et al. 2007). 
 
According to Ipe (2003: 349) the advantage of formal opportunities is their 
effectiveness. The company has the possibility to control the amount and experience of 
employees it whishes to bring closer together. Even though the dissemination of 
knowledge taking place, for example in training, is fast and reaches a large number of 
individuals, the knowledge being shared has been shown to be mostly explicit in nature 
(Ipe 2003). Research has shown that the majority of knowledge being shared takes place 
in informal settings through relational channels due to the fact that individuals prefer 
informal opportunities to formal ones (Stevenson and Gilly 1991 as cited by Ipe 2003: 
350). Relational channels support face-to-face interaction, which again results in closer 
relationships between individuals. Employees learn to trust and respect each other, 
which increases their motivation to share knowledge. However, one could argue that 
regardless of the explicitness of the knowledge being shared, purposive learning 
channels such as training and cross-functional teams create space and time for 
employees to socialize and form relationships both formal and informal. Cabrera and 
Cabrera (2005: 722) concur that when employees spend more time together the 
resulting increased interaction breathes continual communication, which again builds a 
foundation for a shared language to form. Thus formal opportunities may spawn 
informal ones and reflect the organization’s positive attitudes toward knowledge sharing. 
In line with this view Argote et al. (2003) stress the importance of proximity enabling 
individuals to learn who knows what and where in the company lowering the bar to 
search for knowledge in the organization. Thus employees are more likely to seek 



 41 

knowledge further than the next office down the hall. Accordingly Boschma (2005 as 
cited by Harvey 2012: 403) states that proximity is geographical but also cognitive, 
organizational, institutional and social and therefor plays an important part in the 
process of sharing knowledge. 
 
While identifying the importance of proximity and the organization’s role in facilitating 
the occurrence of knowledge sharing, Siemsen et al. (2008) argue that opportunity is 
essentially dependent on available time. If employees do not have enough slack time 
between their regular work routines and tasks, informal knowledge sharing will not 
occur. In fact, Siemsen et al. (2008) found opportunity, operationalized as time 
availability, to have an indirect effect on knowledge sharing behavior through 
motivation and ability. More precisely, lack of time presents itself as a barrier for 
motivation and ability thus no matter how willing or able an individual might be, 
without time no knowledge will be shared. 
 
A final, important factor affecting opportunity to share knowledge is the availability of 
technology. Indeed, instant messaging enabling software such as office communicator 
and videoconference technology help to overcome physical distance and time related 
problems (Siemsen et al. 2008). IT -based systems can also be deployed to help store 
and disseminate knowledge. However, the creation of databases risks excessive 
focusing on the collection instead of sharing of knowledge. Furthermore, the possibility 
of storing experience and real know-how (i.e. codification of tacit knowledge) into 
databases and the active retrieving of the stored knowledge has been widely criticized 
(Davenport & Prusak 1998). In addition to the availability of technology and proximity, 
a related enabler of knowledge sharing opportunities is the company’s policies 
regarding travelling expenses. Indeed, Argote et al. (2003) argue that personnel 
movement across organizational and unit borders increase knowledge sharing 
opportunity. 
 
In the end, opportunity to share knowledge originates from interpersonal relationships. 
Organizations can rely on building formal or support the formation of informal face-to-
face opportunities to share knowledge. These learning channels should cut across 
organizational and hierarchical boundaries creating a time and space for individuals to 
interact and share knowledge. Factors affecting knowledge sharing opportunity are 
summarized in Table 3. 
 
 



 42 

Factors affecting knowledge sharing opportunity 
General                                  Existence of formal learning channels 

Existence of informal learning channels 
Proximity 
Available time & place 
Technology 
Hierarchical & organizational structures 

Table 3. Factors affecting knowledge sharing opportunity. 
 
 
2.5.3 Ability 
 
Siemsen et al. (2008) understand ability as the level of skills and competencies needed 
to engage in knowledge sharing. Thus: “…is a construct that reflects an individual’s 
general capacity to perform in specific types of situations.” (Cummings & Schwab 
1973; Rothschild 1999 as cited by Siemsen et al. 2008: 432). Abilities are innate but can 
be a result of training as well. For example Argote et al. (2003) argue that training in 
analogical reasoning makes it easier for an employee to utilize accumulated knowledge 
in other tasks. Drawing from the social capital theory, individuals on the same cognitive 
levels are better suited to share knowledge with each other because they share the same 
language, codes and way to express themselves. 
 
One of the most established reasons having a negative effect on knowledge sharing 
ability is the tacitness of and complexities surrounding the knowledge being shared. For 
example, Szulanski (1996) found causal ambiguity and the lack of absorptive capacity 
of the recipient in addition to an arduous relationship being the most important factors 
affecting internal knowledge transferring. Szulanski (1996: 30–31) defines causal 
ambiguity as the uncertainty surrounding the process of recreating a practice in a new, 
different setting: The reasons for the knowledge transfer to succeed or to fail are 
unknown. This “irreducible uncertainty” could be a result of tacitness, the source’s 
week capabilities to articulate the knowledge being transferred or the recipient’s 
difficulties in clarifying the environment where the knowledge will be applied 
(Szulanski 1996: 30; 2000: 14). Absorptive capacity is related to the recipient’s ability 
to exploit sources of knowledge other than its own and is linked to the prior, related 
knowledge of the recipient. According to Szulanksi (1996) both absorptive capacity and 
causal ambiguity are knowledge related factors. In line with the work of Szulanski 
(1996), Argote et al. (2003) argue that individuals understand, learn and absorb new 



 43 

knowledge by associating it with what they already know. Hence, the ability to share 
and receive knowledge is greatly affected by the characteristics of the knowledge being 
shared and the existing knowledge bases of the source and the recipient. 
 
Adopting the perspective of the sender, Hinds and Pfeiffer (2003) argue that the sharing 
of expertise is affected by cognitive limitations of the source. More precisely, how a 
knowledgeable individual stores, process and articulates knowledge may present itself 
as a barrier for effective knowledge sharing. According to Hinds and Pfeiffer (2003) the 
way experts mentally represent a task is distinct because as expertise develops mental 
representations become more abstract and simplified. This simplification process helps 
experts to adopt a holistic view on a task, process information rapidly and avoid getting 
stuck on details. Abstract and simplified representations make knowledge sharing 
between experts rich and effective. However, when there exists an expertise gap 
between the sender and receiver or when tacit knowledge is being articulated 
knowledge sharing is impeded. 
 
According to Hinds and Pfeiffer (2003), experts suffer from cognitive limitations, 
which inhibit them from establishing a common ground with recipients of their 
knowledge. Research has shown that experts fail to provide concrete and detailed 
enough background information and use an understandable language when sharing their 
knowledge with less knowledgeable individuals (Hinds & Pfeffer 2003). As a result, 
even though experts would be willing to share their knowledge they might not be able 
to do so because of the existing gap in expertise between the source and recipient. In 
line with the work of Szulanski (1996), Hinds and Pfeiffer (2003) identify knowledge 
related factors to have an effect on knowledge sharing. Experts’ knowledge is a 
combination of tacit and explicit components from which the former might be 
challenging to share no matter the level of expertise. Unlike explicit knowledge, tacit 
knowledge resides at the unconscious level and is therefor hard to articulate and share. 
Another knowledge related cognitive problem is its embeddedness. Indeed, Hinds and 
Pfeiffer (2003) argue that knowledge created and utilized in one environment may not 
serve its owner in a new and different setting. Closely related to the concept of causal 
ambiguity, knowledge embeddedness may present itself as a cause for the recipient to 
refuse the shared knowledge. Hence, the not-invented-here syndrome might be caused 
by other than motivational factors alone (Hinds & Pfeiffer 2003). 
 
One could argue that factors such as tenure, position and spoken language also play an 
important role regarding one’s ability to share and receive knowledge. A longer tenure 



 44 

is often related to experience and a good understanding of the business (Pacharapha & 
Ractham 2012). Likewise, a senior position in the company denotes a strong track 
record but also a better view on the overall business of the company due to for example 
a wider range of responsibilities compared to employees on the shop floor. Hence, these 
employees are better suited to share and understand knowledge. Nevertheless, 
regardless of the tenure or position, knowledge sharing and receiving can still be 
hindered because of knowledge related factors and cognitive limitations presented 
earlier. For example, Kang and Hau (2014) found, contrary to expectations, employees 
with longer company tenure to demonstrate lower levels of acceptability toward new 
knowledge. Finally, even in the situation of a perfect cognitive alignment between the 
source and the recipient language skills might present itself as an insurmountable barrier 
for knowledge sharing. Barner-Rasmussen and Björkman (2005) found language skills 
to play a crucial role in the success of inter unit knowledge transfers. Indeed, no matter 
the motivation or opportunity if the parties do not speak each other’s language no 
knowledge will be shared. 
 
In parallel with language skills, cultural differences can affect individuals’ ability to 
engage in knowledge sharing. As an open, trusting and faire organizational culture can 
have a positive effect on individuals’ motivation to share knowledge, colliding national 
cultures and institutions have the potential to decrease employees’ ability to engage in 
knowledge sharing. The concept of national culture has been defined in various ways 
Hofstede’s dimensions of national culture along which societies differ being one of the 
most seminal and used (Hofstede-Geert 2012). The four dimensions of power distance, 
individualism vs. collectivism, masculinity vs. femininity and uncertainty avoidance 
were later on complemented with the dimensions of long-term vs. short-term orientation 
and indulgence vs. restraint. Hofstede and Bond (1988: 6) regard culture as “the 
collective programming of the mind that distinguishes the members of one category of 
people from those of another.” Instead of interpreting national cultures and their 
differences by placing them on various continuums, Kostova (1999) distinguishes 
national cultures based on their regulative, normative and cognitive institutions forming 
specific country institutional profiles or CIPs. The regulatory component of the CIP 
embody formal institutions like laws and rules whereas the cognitive and normative 
components refer to more informal institutions like “the way people notice, categorize 
and interpret stimuli from their environment” and the norms and values of a given 
country (Kostova 1999: 317–318). Nevertheless, understood whether in dimensions or 
CIPs, colliding national cultures have a negative impact on individual level knowledge 
sharing. For example Bhagat et al. (2002) argue that among the type of knowledge 



 45 

being transferred and the cognitive styles of the source and the recipient such as 
preferred problem solving styles (signature skills), way of thinking (holistic vs. 
analytical) and tolerance for ambiguity the cultural variations have an impact on the 
effectiveness of cross-border knowledge sharing. Factors affecting the ability to share 
and receive knowledge are summarized in Table 4. 
 
 

Factors affecting knowledge sharing ability 
Source Cognitive limitations 
 
Recipient Absorptive capacity 
 Experience gap 
  
General Causal ambiguity 
 Tacitness of knowledge 
 Language skills, cultural differences & tenure 
Table 4. Factors affecting knowledge sharing ability. 
 
 
2.6 Knowledge sharing in the context of mentoring 
 
 
Having presented general factors identified by literature to have an effect on the ability, 
motivation and opportunity to engage in knowledge sharing behavior, the aim of this 
section is to contemplate how the aforementioned antecedents of knowledge sharing are 
shaped within the context of mentoring. First the concept of mentoring is defined to lay 
the ground for following contemplation on the context of mentoring and its effects on 
individual level knowledge sharing. 
 
2.6.1 Mentoring defined 
 
According to Ragins and Kram (2007), mentoring and mentoring relationships have 
their roots in ancient mythology and have been present in both social and working life 
for thousands of years. Finkelstein and Poteet (2007: 346) state that both academic and 
practical articles give away that many companies have or have had mentoring programs 
in place. In their review of literature on workplace mentoring dating from 1980 Haggard, 
Dougherty, Turban and Wilbanks (2011) found 40 different definitions of mentoring 



 46 

ranging from very detailed to more vague conceptualizations. Nevertheless, the 
researchers acknowledge that scholars share a general view on mentoring, which 
follows the theoretical foundations laid by Kram in 1985 on the developmental 
relationships at work. According to Kram (1985 as cited by Ragins & Kram 2007: 4) 
mentoring is defined as a relationship between an older and more experienced 
individual referred as the mentor and a younger less experienced individual usually 
titled as a protégé or mentee with the aim of helping and developing the protégé’s career. 
 
Haggard et al. (2011), identify the three “core attributes” of reciprocity, developmental 
benefits and consistent interaction distinguishing mentoring relationships from other 
work-related ties. Mentoring is composed of mutual social exchanges requiring 
reciprocity. Unlike teaching, coaching and supervising mentoring promotes two-way 
discussion between the mentor and protégé. Developmental benefits resulting from 
mentoring exceed skills obtained from training or required by the organization. 
Traditionally these benefits are linked with the protégé’s work and career development 
but research has shown that also mentors benefit from the relationship. For example, 
Kram and Isabella (1985) state that both parties are expected to benefit from a 
mentoring relationship. Furthermore, Kram and Ragins (2007) argue that research on 
mentoring has found mentored employees to enjoy higher incomes, receive more 
promotions and are more committed and satisfied with their work and career compared 
to non-mentored colleagues. Likewise, mentors have been shown to benefit from 
improved job performance, career success and revitalization, recognition and a sense of 
personal fulfillment and satisfaction. These individual level benefits are aggregated on 
the organizational level for example as improved job satisfaction and organizational 
socialization as well as reduced employee turnover intentions (Ragins & Cotton 1999). 
Lastly, mentoring relationships are characterized by a level of commitment, which is 
manifested in the consistent communication between the mentor and the protégé during 
a longer period of time compared to for example other working relationships (Haggard 
et al. 2011). 
 
Traditionally mentors are seen to provide their protégés’ with two sets of functions. 
Career enhancing functions are dependent on the mentor’s position and influence in the 
organization. The mentor can for example offer exposure and visibility, coaching, 
sponsorship and challenging assignments to prepare the protégé for a higher position in 
the organization. In addition to career enhancing functions, mentors can concentrate on 
the