Copyright is owned by the Author of the thesis. Permission is given for a copy to be downloaded by an individual for the purpose of research and private study only. The thesis may not be reproduced elsewhere without the permission of the Author. THE INTERACTIVE EFFECT OF COMMUNICATION MEDIA CHOICE AND PERSONAL RELATIONSHIPS ON TACIT KNOWLEDGE TRANSFER SUCCESS A thesis presented in partial fulfilment of the requirements for the degree of Master in Business Studies in Business Information Systems At Massey University Manawatu Campus New Zealand Jiatao Yu 2014 I II AABSTRACT The transfer of tacit knowledge can be facilitated by personal relationship strength and by choosing appropriate communication media. However, the interactive effect of personal relationships and media choice on tacit knowledge transfer success has not been studied. Therefore, this study aims to investigate how relationship strength and media choice affect tacit knowledge transfer, and most importantly, how media choice interacts with relationship strength. Data were collected via a questionnaire survey of New Zealand university teachers in the disciplines of human health and medicine. Exploratory Factor Analysis and Structural Equation Modelling were used to analyse the survey data and to test the model. Then, follow-up interviews were carried out with six participants, to collect in-depth qualitative data focusing on the mechanisms behind the relationships to be found statistically significant in the model. Fitting the model by using partial least square structural equation modelling suggested that a higher level of closeness between individuals lead to better tacit knowledge transfer success, the relationship was stronger when individuals use both synchronous media and asynchronous media than when they use only synchronous media. Qualitative results were used to help interpret the quantitative findings by highlighting the importance of the development of common understanding, and by pointing out the fact that individuals adjusted their communication styles to be more suitable for each other. This study contributes to theory by testing Media Synchronicity Theory in the field of tacit knowledge transfer, and by exploring the mechanisms of the change of individuals’ media choice over time. III IV AACKNOWLEDGEMENT Foremost, I would like to express my sincere gratitude to my supervisors, Dr Keri Logan and Dr Alexei Tretiakov, for their patience, knowledge, and continuous support throughout my study. This thesis would not have been possible without their guidance. A special thanks to all the respondents, who spent their valuable time and efforts to complete the survey and participant in the interviews. Finally, my utmost recognition and acknowledgement goes to my family. To my mother and father, whose love, wisdom and support have helped me to find myself and become the person who I am today. To my partner Ivy, whose love, inspiration and encouragement have opened my heart and enriched my life. Thank you for giving me the best years in my life and for your support in everything. I can’t wait for our journey ahead. V VI TTABLE OF CONTENTS ABSTRACT .................................................................................................................................. II ACKNOWLEDGEMENT .............................................................................................................. IV TABLE OF CONTENTS ................................................................................................................ VI LIST OF FIGURES ...................................................................................................................... XII LIST OF TABLES ....................................................................................................................... XIII LIST OF ABBREVIATIONS .......................................................................................................... XV CHAPTER 1 INTRODUCTION ...................................................................................................... 1 1.1 Background of the study..................................................................................... 1 1.2 Problem statement ............................................................................................. 2 1.3 Research questions ............................................................................................. 2 1.4 Scope of the study .............................................................................................. 3 1.5 Significance of the study ..................................................................................... 3 1.6 Summary of research method ............................................................................ 4 1.7 Structure of the thesis ........................................................................................ 4 CHAPTER 2 LITERATURE REVIEW ............................................................................................... 6 2.1 Introduction ........................................................................................................ 6 2.2 Knowledge .......................................................................................................... 6 2.3 Tacit Knowledge ............................................................................................... 10 2.3.1 Conceptualisation of tacit knowledge ...................................................... 10 2.3.2 The tacit and explicit dichotomy ............................................................... 11 2.3.3 The tacitness of policy knowledge ............................................................ 12 2.4 Factors that influence tacit knowledge transfer .............................................. 14 2.4.1 Tacit knowledge characteristics ................................................................ 15 2.4.2 The knowledge provider/source ............................................................... 17 2.4.3 The knowledge recipient ........................................................................... 18 VII 2.4.4 Similarities between the knowledge provider and knowledge recipient . 18 2.4.5 Relationship strength between the knowledge provider and knowledge recipient 19 2.4.6 Organisational context .............................................................................. 21 2.5 The effect of communication media on tacit knowledge transfer ................... 21 2.5.1 Media Richness Theory and Related Studies ............................................ 22 2.5.2 Media Synchronicity Theory and related studies ..................................... 26 2.5.3 The effect of media use on tacit knowledge transfer ............................... 34 2.6 Interactive effect of media choice and relationship strength .......................... 39 2.7 Summary ........................................................................................................... 40 CHAPTER 3 RESEARCH MODEL AND HYPOTHESES DEVELOPMENT ........................................ 41 3.1 Introduction ...................................................................................................... 41 3.2 Conceptual foundation ..................................................................................... 41 3.3 Research model ................................................................................................ 41 3.4 Factors hypothesised to affect tacit knowledge transfer success .................... 42 3.4.1 Relationship .............................................................................................. 42 3.4.2 Interacting role of media use .................................................................... 43 3.5 Refined model .................................................................................................. 44 3.6 Summary ........................................................................................................... 46 CHAPTER 4 RESEARCH METHOD .......................................................................................... 47 4.1 Introduction ...................................................................................................... 47 4.2 Overall research approach ............................................................................... 47 4.2.1 Positivism and Interpretivism ................................................................... 47 4.2.2 Mixed research method ............................................................................ 48 4.2.3 Overview of research method .................................................................. 51 4.2.4 Overview of research procedures ............................................................. 51 4.3 Quantitative data collection ............................................................................. 53 4.3.1 Procedures of quantitative data collection............................................... 53 VIII 4.3.2 Unit of analysis and population ................................................................ 53 4.3.3 Overview of research instrument ............................................................. 54 4.3.4 Operationalization of Variables ................................................................ 55 4.3.5 Tests for readability .................................................................................. 63 4.3.6 Survey description..................................................................................... 63 4.4 Approach to quantitative data analysis ............................................................ 63 4.4.1 Data entry ................................................................................................. 64 4.4.2 Preliminary data analysis .......................................................................... 64 4.4.3 Checking for common method bias .......................................................... 65 4.4.4 Model refinement ..................................................................................... 66 4.4.5 Approach to model testing ....................................................................... 67 4.5 Qualitative data collection................................................................................ 70 4.5.1 Open-ended questions in the survey ........................................................ 70 4.5.2 Interview questions .................................................................................. 70 4.5.3 Interview description ................................................................................ 71 4.6 Approach to qualitative data analysis .............................................................. 71 4.7 Ethical considerations ....................................................................................... 72 4.7.1 Quantitative study .................................................................................... 73 4.7.2 Qualitative study ....................................................................................... 73 4.8 Summary ........................................................................................................... 73 CHAPTER 5 QUANTITATIVE DATA ANALYSIS ........................................................................ 75 5.1 Response rate ................................................................................................... 75 5.2 Preliminary analysis .......................................................................................... 75 5.2.1 Normality and outliers .............................................................................. 75 5.2.2 Missing values ........................................................................................... 76 5.2.3 Non-response bias .................................................................................... 76 5.2.4 Representativeness of the population ...................................................... 78 IX 5.3 Descriptive statistics ......................................................................................... 79 5.3.1 Media choice ............................................................................................. 79 5.3.2 Relationship strength ................................................................................ 81 5.3.3 Tacit knowledge transfer success ............................................................. 82 5.3.4 Communication patterns .......................................................................... 84 5.4 Checking for common method bias .................................................................. 87 5.5 Group separation .............................................................................................. 87 5.6 Testing the measurement model - exploratory factor analysis on the construct of relationship strength ................................................................................................... 88 5.7 Testing the measurement model - PLS ............................................................. 91 5.7.1 Convergent validity ................................................................................... 91 5.7.2 Discriminant validity ................................................................................. 95 5.8 Testing the structural model ............................................................................ 98 5.8.1 Path coefficient and model testing ........................................................... 98 5.8.2 Effect size ................................................................................................ 100 5.8.3 Group comparison .................................................................................. 100 5.9 Summary ......................................................................................................... 102 CHAPTER 6 QUALITATIVE ANALYSIS ...................................................................................... 104 6.1 Introduction .................................................................................................... 104 6.2 Knowledge about interpreting and implementing policy............................... 104 6.2.1 Difficulties of policy interpretation and implementation ....................... 104 6.2.2 Transfer of policy knowledge .................................................................. 107 6.3 The effect of personal relationships ............................................................... 108 6.4 Communication media ................................................................................... 109 6.4.1 The use of face-to-face communication ................................................. 109 6.4.2 The use of email ...................................................................................... 111 6.4.3 The use of multiple media ...................................................................... 113 6.5 Personal relationship affects communication media use .............................. 113 X 6.6 Success factors in the implementation of policy ............................................ 114 6.7 Summary ......................................................................................................... 115 CHAPTER 7 DISCUSSION AND IMPLICATIONS........................................................................ 116 7.1 Introduction .................................................................................................... 116 7.2 Discussion of the results ................................................................................. 116 7.2.1 The effect of relationship strength on tacit knowledge transfer ............ 116 7.2.2 Interaction between media use and relationship strength .................... 118 7.2.3 Further insights ....................................................................................... 119 7.3 Contributions of the study .............................................................................. 122 7.3.1 Contributions to theory .......................................................................... 122 7.3.2 Significance for practice .......................................................................... 125 7.3.3 Contributions to methodology ............................................................... 126 7.3.4 Directions for future research................................................................. 126 7.4 Limitation of this study ................................................................................... 127 7.4.1 Population ............................................................................................... 127 7.4.2 Relied on university website ................................................................... 127 7.4.3 Self-report questionnaire ........................................................................ 128 7.4.4 Small size of datasets and low response rate ......................................... 128 7.5 Conclusion ...................................................................................................... 128 REFERENCES .......................................................................................................................... 130 APPENDICES ........................................................................................................................... 145 Appendix A. Survey questionnaire ................................................................................ 145 Appendix B. Invitation Letter ......................................................................................... 164 Appendix C. Information Sheet ..................................................................................... 166 Appendix D. Reminder Letters ...................................................................................... 169 Appendix E. Interview Invitation Letter......................................................................... 171 Appendix F. Acknowledgement of the Low Risk Notification ....................................... 172 XI Appendix G. An example of interview schedule............................................................ 173 XII LLIST OF FIGURES Figure 2.1. A hierarchy consists of data, information, knowledge, and wisdom .............. 7 Figure 2.2. Knowledge creation model ............................................................................ 16 Figure 2.3. Communication media capabilities. .............................................................. 34 Figure 3.1. The initial research model ............................................................................. 42 Figure 3.2. The revised research model .......................................................................... 45 Figure 4.1. Overall research procedure ........................................................................... 52 Figure 4.2. Procedures leading to quantitative data collection ...................................... 53 Figure 4.3. Procedures of qualitative analysis ................................................................. 71 Figure 5.1. The structural model testing result for group 1 (the participants used synchronous media). ............................................................................................... 99 Figure 5.2. The structural model testing result for group 2 (the participants used both synchronous and asynchronous media). ................................................................. 99 XIII LLIST OF TABLES Table 2.1 A comparison of explicit and tacit knowledge ................................................. 11 Table 2.2 Factors that influence tacit knowledge transfer .............................................. 15 Table 2.3 A comparison of selected media and their capabilities ................................... 31 Table 4.1 A comparison of the strengths and weaknesses of quantitative and qualitative research methods .................................................................................................... 49 Table 4.2 Strengths and weaknesses of mixed research method .................................... 50 Table 4.3 Number of potential participants in New Zealand universities ....................... 54 Table 4.4 Items measuring Communication Media Chioce ............................................. 56 Table 4.5 Items measuring Relationship Strength ........................................................... 57 Table 4.6 Items measuring tacit knowledge transfer success ......................................... 59 Table 4.7 Items measuring the pattern of synchronous media use................................. 61 Table 4.8 Items measuring the pattern of asynchronous media use .............................. 62 Table 5.1 Result of non-response bias test based on items used to measure tacit knowledge transfer success ..................................................................................... 77 Table 5.2 Result of non-response bias test based on items used to measure constructs related to relationship strength ............................................................................... 78 Table 5.3 Comparison of gender and age percentage between data set and overall population ............................................................................................................... 79 Table 5.4 Participants' choice of communication media ................................................. 81 Table 5.5 Items measuring relationship strength ............................................................ 82 Table 5.6 Items measuring tacit knowledge transfer success ......................................... 83 Table 5.7 The pattern of synchronous media use ............................................................ 85 Table 5.8 The pattern of asynchronous media use .......................................................... 86 Table 5.9 Exploratory Factor Analysis result ................................................................... 87 Table 5.10 KMO and Bartlett's Test result ....................................................................... 89 Table 5.11 Factor analysis for measures of relationship strength................................... 90 Table 5.12 Item loadings and AVEs before removing items with low item loadings ....... 92 XIV Table 5.13 Item loadings and AVEs after removing items with low item loadings ......... 94 Table 5.14 AVE, Composite reliability, and Crobach’s Alpha ........................................... 95 Table 5.15 Item loadings and crossloadings in Group 1 .................................................. 96 Table 5.16 Item loadings and crossloadings in Group 2 .................................................. 97 Table 5.17 Square root of AVE and latent variable correlations for Group 1 .................. 98 Table 5.18 Square root of AVE and latent variable correlations for Group 2 .................. 98 Table 5.19 Path coefficient, standard error, and sample size ....................................... 100 Table 5.20 Measurement invariance test result ............................................................ 101 XV LLIST OF ABBREVIATIONS AVE : Average variance extracted CMV : Common method variance EFA : Exploratory factor analysis EM method : Expectation-maximisation method ICT : Information and communication technology MRT : Media richness theory MST : Media synchronicity theory PLS : Partial least squares SECI : Nonaka and Takeuchi’s (1995) of knowledge creation model which consists of four modes: socialisation, externalisation, combination, and internalisation SEM : Structural equation modelling TIP : Time, interaction, and performance theory XVI 1 CCHAPTER 1. INTRODUCTION 1.1 Background of the study Knowledge is an important resource for modern organisations as organizations successful at generating, transferring, and adopting knowledge are likely to gain competitive advantage. It is common to distinguish explicit knowledge and tacit knowledge. Explicit knowledge can be easily captured, transferred, and organised in digital form, while tacit knowledge is highly personal and context specific and cannot be easily formalised (Pearlson & Saunders, 2006). Tacit knowledge is widely believed to be a source of sustained competitive advantage, because it is difficult to transfer between different organisational contexts (Cavusgil, Calantone, & Zhao, 2003; Johannessen, Olaisen, & Olsen, 2001; SENKER, 1995). Direct interactions between individuals is necessary for transfer of tacit knowledge (Nonaka & Takeuchi, 1995). Therefore, communication between employees is one of the most important ways for creating and transferring tacit knowledge in a modern organisation. Close personal relationships between individuals could significantly influence the success of tacit knowledge transfer (Hansen, 1999; Joia & Lemos, 2010; Walther, 1992), because they allow the establishment of common understanding (Carlson & Zmud, 1999). Close personal relationships also means individuals to spend less cognitive effort on interpreting received messages (Kock, 2004), and are able to have frequent and in-depth interaction (Nonaka & Konno, 1998). In modern work environments, technologies enabling a broad range communication patterns are available (Daft & Lengel, 1986; Dennis, Fuller, & Valacich, 2008). Media Synchronicity Theory (MST) (Dennis et al., 2008) distinguishes the extent to which the communication media enables the exchange of timely and rich in content messages, as well as communications between individuals who are more or less familiar with each other and with the media they are using. Communication media and their patterns of use have been shown to affect tacit knowledge transfer success. For example, synchronous communication involving rich content and immediate 2 feedback tends to support the transfer of tacit knowledge better than asynchronous communication (Joia & Lemos, 2010; Murray & Peyrefitte, 2007). 11.2 Problem statement While both media choice and the personal relationship between individuals have been demonstrated to affect knowledge transfer success in separate studies, media choice and personal relationships have never been considered in a single model. Therefore, interaction effects between these two constructs have never been explored. In particular, depending on the media choice, the personal relationship between individuals may affect the knowledge transfer success differently. Therefore, the purpose of my study is to fill the research gap by exploring the interaction between the effects of media choice and personal relationship on tacit knowledge transfer success. 1.3 Research questions Based on the problem stated above, the research question for this study is stated as follows: Is the effect of the relationship strength between individuals on the success of tacit knowledge transfer stronger when people use asynchronous media than when people use synchronous media? What are the underlying mechanisms? In other words, the research is concerned with whether the same media and pattern of communication would work well to support tacit knowledge transfer between individuals who know each other and have a close relationship and to support tacit knowledge transfer between individuals who are strangers. It is expected that media that enables the exchange of timely and rich in content messages supports tacit knowledge exchange both between individuals who know each other and between strangers. Conversely, media that is poor in such capabilities disadvantages individuals who are not familiar with each other. 3 To address the research question stated above, a structural model was formulated, which involved the effect of personal relationship on tacit knowledge transfer success and the moderation effect of communication media choice. This study drew from two theoretical perspectives: theories of tacit knowledge transfer and Media Synchronicity Theory. Although knowledge transfer can be studied on both organisational and individual levels this study focuses on tacit knowledge transfer activities on an individual level. 11.4 Scope of the study This study followed studies in the field of tacit knowledge transfer (Cavusgil et al., 2003; Hansen, 1999; Nonaka & Takeuchi, 1995) and in the field of communication media studies (Carlson & Zmud, 1999; Daft & Lengel, 1986; Dennis et al., 2008; Kock, 2004). Tacit knowledge transfer success was conceptualised based on Argote and Ingram (2000), and the structural model was developed based on Media Synchronicity Theory (Dennis et al., 2008). This study focuses on tacit knowledge transfer activity at an individual level, in particular, the transfer of tacit knowledge between a participant and one of the participant’s colleagues. Both quantitative data and qualitative data were collected, with the quantitative data used to test the hypotheses of the study and the qualitative data used to gain a better understanding of the underlying mechanisms. The population of this study were university teachers (university employees involved in teaching students) in New Zealand; the population is described in detail in section 4.3.2. 1.5 Significance of the study The study contributes to the field of knowledge management and knowledge management systems by exploring the consequences of media choice for tacit knowledge transfer between individuals. The research model, based on the media synchronicity theory includes the success of tacit knowledge transfer, personal relationship factors, and media choice. By examining the connections between personal relationship strength, communication media selection, and tacit knowledge 4 transfer success, this study explores the implication of MST in the field of knowledge transfer. This study contributes to practice by highlighting the effect of media choice on the success of tacit knowledge transfer. The findings of this study are of relevance for top management involved in developing knowledge management systems, IS systems, or communication systems in an organisation. 11.6 Summary of research method A mixed research method was employed in this study. First, quantitative data were collected via both an online and paper based survey of university teachers in New Zealand universities to test the structural model, and then qualitative data were collected via semi-structured interviews to gain a deeper understanding of the reasons behind the relationships found to be significant. Measures of the constructs involved in the structural model were adapted from prior empirical studies. To assess personal relationship, measurements from Carlson and Zmud (1999) as well as McKnight, Choudhury, and Kacmar (2002) were adapted. Measurement of media choice was developed based on MST as well as studies related to MST such as Kock and Lynn (2012) and Ryoo and Koo (2010). Measurement of tacit knowledge transfer success was adapted from Ko, Kirsh, and King (2005) as well as Szulanski (1996). Semi-structured interviews were conducted with survey participants who indicated that they were willing to be interviewed, with interview schedules taking into account the participants’ input in the initial survey. The interview transcripts, along with answers to the open-ended questions in the survey, were treated as qualitative data and were analysed following procedures from Patton (2002). 1.7 Structure of the thesis This thesis is structured as follows. Chapter 1 presents the background of the study, the research problem, and the overall research method. Chapter 2 presents a literature review covering tacit knowledge transfer, communication media theories, and the implication of communication theories in tacit knowledge transfer studies. Chapter 3 introduces the research model and hypotheses, which is developed based 5 on the theoretical foundation of tacit knowledge transfer and MST. Chapter 4 presents the research method, including the approaches used to obtain and analyse both quantitative and qualitative data. Chapter 5 presents the findings of the quantitative data analysis and the result of the structural model testing. Chapter 6 discusses the findings of the qualitative data analysis. Chapter 7 concludes the thesis by discussing the findings and stating the contribution and implications of this study. 6 CCHAPTER 2. LITERATURE REVIEW 2.1 Introduction This chapter presents the literature review. Firstly, the conceptualisation of knowledge and tacit knowledge is discussed, followed by a summary of factors that influence tacit knowledge transfer. As the theoretical foundation for this study, two important communication media theories, Media Richness Theory and Media Synchronicity Theory, are presented along with their application to knowledge transfer. Finally, the interaction between personal relationships and communication media is discussed. 2.2 Knowledge The nature of knowledge and its relationship with justification, truth and belief is a long lasting argument in the field of epistemology. This can be traced back to the disagreement between Plato and Aristotle regarding the nature of knowledge. For Plato, the physical world is “a mere shadow of the perfect world of ‘idea’, that cannot be known through sensory perception but only through pure reasoning” (Nonaka & Takeuchi, 1995, p. 22). For rationalists following Plato’s theory, knowledge is justified true belief. It is objective, absolute, and is expressed in the forms of logic. Aristotle suggests ideas cannot be isolated from a physical object, and it depends on perceptual senses (Nonaka & Takeuchi, 1995). Philosophers who subscribe to empiricism see knowledge from a subjective view, and believe that knowledge is derived from human perception. Subsequent philosophers brought together the two streams of rationalism and empiricism. The eighteenth-century German philosopher Immanuel Kant (1965) agreed that knowledge begins with experience, but did not agree that experience is the only source of knowledge. In Kant’s view, knowledge is the outcome of the combination of logical sense and sensory experience (Nonaka & Takeuchi, 1995). Based on Hegel’s dialectical idealism, Karl Marx emphasized the interaction between the subject (the knower) and the object (the known), and proposed that both subject 7 and object are in a continual and dialectical process of mutual adaptation in the pursuit of knowledge (Nonaka & Takeuchi, 1995). The definition of knowledge is an on-going argument. In the field of information systems, the concept of knowledge can be understood by distinguishing it from data and information. Knowledge is often considered as a part of a hierarchy consisting of data, information, knowledge, and wisdom (Ackoff, 2010; Ancori, Bureth, & Cohendet, 2000; Bellinger, Castro, & Mills, 2004; Tuomi, 1999) (See figure 2.1). DataData InformationInformation WisdomWisdom KnowledgeKnowledge Understanding relations Understanding relations Understanding patterns Understanding patterns Understanding principles Understanding principles uunnddeerrssttaannddiinngggunderstanding Figure 2.1. A hierarchy consists of data, information, knowledge, and wisdom. Adapted from “From data to wisdom,” by R. Ackoff, 1989, Journal of applied systems analysis, 16, 3-9 Most sources define the concept of data in a similar way. Data are simple facts, symbols or observations with no meaning on their own; they can be captured and stored in a mechanical and computational manner (Bellinger et al., 2004; Zack, 1999). For example, numbers can be recorded on paper or in a computer system; they are not able to be understood or interpreted without knowing the context within which they were collected. Researchers agree that Information is produced by organising data with meaningful connections (Bellinger et al., 2004; Zins, 2007). For example, a histogram could present the population growth for a period of time, or, a pie chart could show the age distribution of the current population. Nonaka and Takeuchi (1995, p. 58) define knowledge as “a dynamic human process of justifying personal belief towards the truth”. However they also emphasize the 8 role of the “knower”, and suggest that knowledge is generated from information, anchored in the beliefs and commitments of the knowledge holder. Roberts (2000, p. 430) defines knowledge as the “application and productive use of information” which “involves an awareness or understanding gained through experience, familiarity or learning”. Alavi and Leidner (1999, p. 6) conceptualise knowledge as “information possessed in the mind of the individual: it is personaliszed or subjective information related to facts, procedures, concepts, interpretations, ideas, observations, and judgements (which may or may not be unique, useful, accurate, or structural).” Ryle (1949) argues that there is a distinction between intelligence or “knowing how” and having knowledge or what he calls “knowing that”. There is a difference between knowing that something is so and knowing how to do something. He believed the workings of the mind were not separate from the body. Ryle (1949, p. 16) points out “Effective possession of a piece of knowledge that involves knowing how to use that knowledge, when required, for the solution of other theoretical or practical problems”. This is similar to Michael Polanyi’s (1966) idea about tacit knowledge where he argues that a large part of knowledge can be obtained and used without being aware of it. Polanyi suggested that such knowledge is embedded in the context, which can only be known when it influences people’s articulated knowledge, and called it tacit knowledge. All the above conceptualisations state that knowledge exists in the human mind, and it is personalised and context specific. However some researchers argue that knowledge is not only stored in the mind of individuals, but also exists in organisations. Argote and Ingram (2000) suggest while individual knowledge is anchored within the human mind, organisational knowledge is embedded within the technology structure, norms, and routines. Perhaps the conceptualisation provided by Davenport and Prusak (2000, p. 4) is the most comprehensive and clear. They suggest that knowledge is “a fluid mix of framed experiences, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information. It 9 originates and is applied in the minds of the knower. In organisations, it often becomes embedded not only in documents or repositories but also in organisational routines, processes, practices and norms.” According to this, what distinguishes knowledge from information is the involvement of the human mind. The human mind is capable of transforming information into knowledge and vice versa (Alavi & Leidner, 1999). It is common to see communication media studies use the term information and knowledge interchangeably without a clear differentiation (Hasty, Massey, & Brown, 2006; Ryoo & Koo, 2010; Yoo & Alavi, 2001). Instead of studying the transfer of explicit/tacit knowledge transfer, these studies discussed the transfer of lean/rich information (further discussed in section 2.5). While wisdom is considered to be of highest value and at the top of the hierarchy, it is usually neglected because it is a complete mental concept that is difficult to define or express (Takahashi & Bordia, 2000). Ackoff (2010) suggests that the transformation of data to information involves the “understanding of relations”, the transformation of information to knowledge the “understanding of patterns”, and the transformation of knowledge to wisdom the “understanding of principles”. The value and the involvement of the human mind increases as you move from the lower to higher levels of the hierarchy. While the Data-Information-Knowledge-Wisdom hierarchy is widely accepted and studied in information management and knowledge management research (Bellinger et al., 2004; Tuomi, 1999), it has been criticised as being too simplistic. It is sometimes argued that the relationship between information and knowledge is interactive. On the one hand, knowledge is derived from the accumulation of information; on the other hand, it guides and directs the collection of such information (Ancori et al., 2000). Also, Watson (2003) argues that knowledge is context specific. With no prior knowledge of the context, one will not be able to transform data into information, and information into knowledge. He illustrated this by the following example: “the states of nature indicated by red, amber, and green traffic lights may not be seen as informative to Bushmen of the Kalahari. Yet they in 10 turn may perceive certain patterns in the soil as indicative of the presence of lions nearby.” (Watson, 2003, p. 13). The conceptualisation and the nature of knowledge remains an on-going debate due to different philosophical and psychological views. Despite this, a large number of knowledge studies in the field of information systems to date have focused on the epistemological dimension of knowledge, that is explicit knowledge and tacit knowledge (Cowan, David, & Foray, 2000; Leonard & Sensiper, 1998; Nonaka & Takeuchi, 1995). 22.3 Tacit Knowledge 2.3.1 Conceptualisation of tacit knowledge The distinction between explicit and tacit knowledge was first introduced by Polanyi (1966), then was expanded by Nonaka and Takeuchi (1995). It is generally agreed that explicit knowledge is that which can be codified, recorded, and transmitted in formal and systematic languages. Therefore it can be effectively managed using information systems (Nonaka & Takeuchi, 1995; Zack, 1999). It can be embedded in the form of data, operational manuals, documents or videos, frameworks, sets of principles, instructions, and so on (Leonard & Sensiper, 1998; Roberts, 2000). Explicit knowledge is often considered to be “the tip of the iceberg” (Haldin-Herrgard, 2000; Leonard & Sensiper, 1998; Nonaka & Takeuchi, 1995), while tacit knowledge is the large part that lies beneath the water line. Tacit knowledge is often compared to explicit knowledge in order to conceptualise the distinction (see table 2.1). While explicit knowledge is knowing-that, tacit knowledge is knowing-how (Polanyi, 1966); while explicit knowledge is objective, tacit knowledge is subjective (Nonaka & Takeuchi, 1995); while explicit knowledge involves declarative knowledge, tacit knowledge involves procedural knowledge (Anderson, 1996). Researchers characterise tacit knowledge as personal and context specific, difficult to articulate, both visible and invisible to the holder; it involves skills, beliefs, values, experience, and know-how (Cowan et al., 2000; Leonard & Sensiper, 1998; Nonaka & Takeuchi, 1995). 11 Table 2.1 A comparison of explicit and tacit knowledge Explicit knowledge Tacit knowledge Source Knowing-that Knowing-how (Polanyi, 1966; Ryle, 1949) Objective Subjective (Nonaka & Takeuchi, 1995) There and then Here and now Declarative Procedural (Anderson, 1996) 22.3.2 The tacit and explicit dichotomy Although tacit knowledge has been extensively studied, dichotomies exist in the literature. One of the main dichotomies is whether tacit and explicit knowledge are integral parts of knowledge, or whether they are two categories of knowledge. Nonaka and Takeuchi (1995) view explicit knowledge and tacit knowledge as two categories of knowledge, where the former is distinguished from the latter by its codifiability. Explicit knowledge can be transmitted into formal and systematic language. It is about past events or objects, and it can be acquired and transferred without contextual information, whereas tacit knowledge concerns experiences from a specific, practical context (Nonaka & Takeuchi, 1995). On the other hand, researchers suggest that Nonaka and Takeuchi’s theory over-simplifies the concept of tacit knowledge (Brown & Duguid, 1998; Tsoukas, 2005). According to Polanyi (1966, p. 195), there is no clear distinction between tacit and explicit knowledge: “The idea of a strictly explicit knowledge is indeed self-contradictory; deprived of tacit coefficients, all spoken words, all formulae, all maps and graphs, are strictly meaningless”; even the most objective knowledge – scientific knowledge involves tacit thoughts (Polanyi, 1966). Based on Polanyi’s theory, Tsoukas (2005) suggests that tacit knowledge cannot be separated from all knowledge. Articulated knowledge, such as documents and blueprints, can only make sense to an individual when it is combined with that individual’s tacit knowledge. This is supported by Ribeiro’s (2012) observation of tacit knowledge management practice in a Brazilian industrial plant. Ribeiro found that a standard operation manual required workers to have had previous experiences in order for the manual to be of use in a real life situation. Therefore, 12 tacit knowledge is rooted in all knowledge, tacit and explicit are two dimensions of knowledge, rather than two different categories of knowledge (Brown & Duguid, 1998; Polanyi, 1966; Tsoukas, 2005). 22.3.3 The tacitness of policy knowledge Robbins and Coulter (2007, p. 166) define policy as a “guide that established parameters for making decisions”, which usually “contains ambiguous terms that leaves interpretation to the decision makers”. In an organisation, policies are used to set direction, to place a restriction on what members may or may not do, and enable the implementation of organisational strategies (Luckett, 2003). Because documents describing the policy often contain unclear and ambiguous terms, researchers in the field of policy studies suggest that knowledge about interpreting and implementing policy is highly tacit (Spillane, Reiser, & Reimer, 2002; Yanow, 1996). 2.3.3.1 The tacit understating of policy meanings Yanow (2000) argues that the meaning of a policy is conveyed to its audiences through symbols, that can be in the form of language, objects and acts. She argues that a symbol may have different meanings for different groups of people based on their values, beliefs, and feelings; the symbol makes sense only when members in a particular group agree on the meaning it embodies. The development of the meaning of a symbol is often historically and contextually specific. She illustrated her point by an example: a dove is a symbol of peace for some people but is simply a bird or even a meal for others. She suggests that policies are written in the form of texts, which are a type of symbolic artefact. Employing literary theory, she argues that the meaning of text is “created actively in interactions among all three [the author, the text, and the reader], in the writing and in the reading” (Yanow, 2000, p. 17). Arguing that policy is the text and the people involved in and affected by the policy are the readers, Yanow suggests that policy the artefact is open to multiple interpretations (Yanow, 1996, 2000). The interpretation and implementation of policy requires tacit knowledge from individuals. Policy is ambiguous and unclear in nature; it may hold different 13 meanings for different audiences. Policy actors have to tacitly understand the meaning of the policy in order to successfully implement the policy (Yanow, 2000). 22.3.3.2 Tacit knowledge of individuals Spillane et al. (2002) argue that people interpret and implement a policy based on the interaction between their cognitive structure (which includes their knowledge, beliefs, and attitude), the situation, and the policy fit to their agendas, interests, and resources. Summarising prior studies that explored the implementation of teaching policy, Spillane et al. (2002) found that there were similar findings among these studies. When making sense of and implementing a policy, teacher’s prior knowledge, experience, values, and beliefs about subject matter, teaching, students, and learning influenced their interpretation of that policy. As a result, teachers may interpret and implement the same policy very differently. Studying public management policy and practice in Western China, Chan and Chow (2007) found that local government officials understood the norms, values, commandments and taboos of their work place based on their tacit knowledge. With this tacit knowledge, they could understand the meaning of policy, and more importantly the intent of their superiors, accurately, which enabled them to survive under the policy and even benefit from the policy. 2.3.3.3 Tacit thinking about the situation To successfully implement a policy, people sometimes have to make decisions based on their understanding of the situation. Hier and Walby (2013) studied the deployment of public camera surveillance of special events in Canada. They found that when public safety policy conflicted with privacy policy, the people who were implementing the policy made decisions that relied on their tacit understanding about the situation. The researchers concluded that the meaning of a policy was communicated in situation-specific contexts. How the policy was interpreted and further implemented was based on individuals’ tacit assumptions about security, public safety, and risk management. Agreeing with Yanow (2000), they argue that the meaning of a policy has to be understood tacitly therefore the interpretation and 14 implementation of policies are influenced by individuals’ tacit knowledge concerning the need of the moment. In summary, to interpret and implement a policy, people have to rely on their tacit knowledge which includes experiences, values, and beliefs, to understand the meaning of the policy and to make decisions in a particular situation. When people exchange ideas about a policy, what they are actually exchanging are their experiences, knowledge, values, and beliefs towards the policy, in other words, they are transferring tacit knowledge. 22.4 Factors that influence tacit knowledge transfer Knowledge transfer can be defined at both the individual level and organisational level as “the process through which one unit (e.g., group, department, or division) is affected by the experience of another” (Argote & Ingram, 2000). Because tacit knowledge is of high value and conceptually more complex than explicit knowledge, the transfer of tacit knowledge is one of the most popular topics in the field of knowledge management (Ribeiro, 2012; Tsoukas, 2005). Researchers have investigated the factors that influence tacit knowledge transfer. This study summarised these factors into five categories, namely: tacit knowledge characteristics, knowledge provider/source, knowledge recipient, similarities, relationship, and organisational context (see table 2.2). 15 Table 2.2 Factors that influence tacit knowledge transfer Factors Studies Tacit knowledge characteristics Tacitness Nonaka &Takeuchi (1995) Ambiguity and uncertainty Szulanski (1996) Perception, language, time, value, distance Haldin-Herrgard (2000) Knowledge provider/source Knowledge power Orlikowski (1992); Davenport & Pruzak (2000) Opportunity cost Orlikowski (1992) Reward Davenport & Pruzak (2000); Leonard & Sensiper (1998) Knowledge recipient Trustworthiness of knowledge Szulanski (1996) Motivation Simonin (2004); Scott & Sarker (2010) Absorptive capacity Cohen & Levinthal (1990); Lane & Lubatkin (1998) Similarities between knowledge provider and recipient Common language Madhavan (1998); Nahapiet & Ghoshal (1998) Personal relationship between knowledge provider and recipient Tie strength Hansen (1999); Reagans & McEvily (2003) Trust Davenport & pruzak (2000); Roberts (2000) Organisational context Organisational culture Ajmal and Koskinen (2008); Joia and Lemos (2010) Knowledge management strategy Hansen, Nohria, and Tierney (2000) Information and communication technology Roberts (2000); Murray & Peyrefitte (2007) 22.4.1 Tacit knowledge characteristics The degree of knowledge tacitness influences knowledge transfer. A number of researchers suggest tacit knowledge can be converted into explicit knowledge. For example, Nonaka and Takeuchi (1995) believe that knowledge is created and expanded through social interaction. In their SECI model, they propose four modes 16 of knowledge conversion; socialisation (tacit to tacit), externalisation (tacit to explicit), combination (explicit to explicit), and internalisation (explicit to tacit) (See figure 2.2). This model emphasises the importance of socialisation in the transfer of tacit knowledge and shows that not only can explicit knowledge be internalised to create tacit knowledge, tacit knowledge can be converted into explicit knowledge through a process including metaphor and model development (Nonaka, 1994; Nonaka & Takeuchi, 1995). They argue that the shifts of the four modes of knowledge conversion shape a spiral process, through which the continuous and dynamic interaction between tacit and explicit knowledge creates new knowledge for organisations (Nonaka & Takeuchi, 1995). Socialisation Internalisation Combination Externalisation Explicit knowledge Tacit knowledge Tacit knowledge Explicit knowledge Figure 2.2. Knowledge creation model consists of four modes: socialisation, externalisation, combination, and internalisation. These four modes shape a spiral interaction between tacit and explicit knowledge. Adapted from “Theory of organisational knowledge creation,” by Nonaka and Takeuchi, 1995, Knowledge Creating Company, p. 62. Copyright by Oxford University Press, Inc. Others argue that converting tacit knowledge into explicit knowledge is neither achievable, nor necessary. According to Polanyi (1966), tacit and explicit exist on a continuum, and while some knowledge is high in tacitness, other is high in explicitness. He argues that even the most explicit knowledge involves tacit thinking, and it is impossible to remove the tacit element from any knowledge. Tsoukas (2005) argues that knowledge contains an ineffable element that is based on an act of personal insight, and such an element is essentially inarticulable. Brockmann and Anthony (1998) argue that tacit knowledge can only be learnt, while Haldin-Herrgard 17 (2000) suggests that tacit knowledge can be transferred through experience and practice and through interaction with other individuals. Despite the debate over the distinction between explicit and tacit knowledge, it is generally agreed that tacitness is one of the major barriers of knowledge transfer success (Davenport & Pruzak, 2000; Nonaka & Takeuchi, 1995; Szulanski, 1996). While explicit knowledge can be transferred easily using information technology or more traditional ways such as letters and memos, tacit knowledge transfer cannot be easily achieved. Szulanski (1996) suggested that because tacit knowledge is often embedded in human skills and experiences it can be seen as being high in ambiguity and uncertainty which contributes to its “stickiness”, thus making it more difficult to transfer. Hansen (1999) suggests that knowledge differs in codifiability. He found that because it can be codified, explicit knowledge was much easier to transfer than tacit knowledge. Haldin-Herrgard (2000) summarised the difficulties of sharing tacit knowledge as follows: perception (people may not be aware of the full range of their knowledge), language (people may not able to express their tacit knowledge), time (sharing tacit knowledge requires a long time), value (some forms of tacit knowledge such as intuition may not be considered as valuable), and distance (the physical distance between individuals hinders interaction). 22.4.2 The knowledge provider/source The knowledge provider may refuse to transfer their knowledge due to the fear of losing power or due to high opportunity costs. There are some researchers that argue employees consider knowledge as a source of power within the organisation (Orlikowski, 1992), leading to a reluctance to share knowledge with others due to their fear of losing the power their knowledge gives them (Davenport & Pruzak, 2000; Gray, 2001). Because of its complexity, the transfer of tacit knowledge is time consuming for both the knowledge source and the knowledge recipient. When there is a high opportunity cost such as the amount of time that must be invested in the transfer of knowledge the knowledge provider may refuse to participate (Orlikowski, 1992). Additionally, Social Exchange Theory suggests that people are 18 more likely to engage in tacit knowledge transfer activity willingly when the benefit of the transfer is perceived to be more valuable than any negative outcome (Muthusamy & White, 2005; Sveiby, 2007). For these reasons it is suggested by some that if knowledge sources were rewarded, they would be more willing to share their knowledge (Davenport & Pruzak, 2000). For example, a performance review system that takes knowledge sharing into consideration and financially rewards and penalises employees according to their knowledge sharing behaviour may contribute to an environment where sharing knowledge is considered positive (Leonard & Sensiper, 1998). 22.4.3 The knowledge recipient The reliability of the knowledge source is also a major element that influences knowledge transfer. If the knowledge of the provider is not considered trustworthy, then the knowledge transfer activity is likely to be resisted and challenged (Szulanski, 1996). Szulanski (1996) also suggests that a recipient’s motivation to seek knowledge, and their absorptive capacity, are two significant barriers to knowledge transfer. Motivation refers to the willingness of the recipient to learn from a source, a partner, or even to participate within a collaborative environment (Simonin, 2004). A number of studies confirm that the knowledge recipient’s lack of motivation could significantly affect internalisation of new knowledge, and therefore hinder knowledge transfer (Joshi, Sarker, & Sarker, 2007; Scott & Sarker, 2010). Absorptive capacity refers to the knowledge recipient’s ability to recognise the value of knowledge. This then impacts on their desire to acquire, assimilate , transform and exploit knowledge (Cohen & Levinthal, 1990; Todorova & Durisin, 2007). Lack of absorptive capacity decreases the knowledge recipients’ ability to discover and recognise new knowledge, and reduces their ability to assimilate or transform it into new knowledge (Lane & Lubatkin, 1998; Lane, Salk, & Lyles, 2001; Scott & Sarker, 2010). 2.4.4 Similarities between the knowledge provider and knowledge recipient A major factor found to influence tacit knowledge transfer is language. First of all, because tacit knowledge is deeply embedded in human actions, the higher the 19 tacitness the greater the difficulty in converting that knowledge into language (Haldin-Herrgard, 2000). Even when tacit knowledge can be converted into language, the diversity of terminologies and jargon creates difficulties for the transfer of such knowledge among people within different occupational groups (Davenport & Pruzak, 2000; Haldin-Herrgard, 2000). Language similarities between the knowledge source and recipient facilitate tacit knowledge transfer. Having a common language means sharing a set of codes, terms, symbols and understandings that allow people to communicate effectively (Nahapiet & Ghoshal, 1998) and therefore facilitate the transfer of knowledge (Collins & Smith, 2006). Madhavan (1998) suggests a common language, along with shared prior knowledge, could result in shared mental models, which further facilitates tacit knowledge transfer. 22.4.5 Relationship strength between the knowledge provider and knowledge recipient According to Nonaka and Takeuchi (1995) tacit knowledge can only be exchanged through interaction between individuals. They consider socialisation including “joint activities - such as being together, spending time, living in the same environment” as the key to transferring tacit knowledge (Nonaka & Konno, 1998, p. 42). People develop relationships during social interaction, and the effect of relationships on tacit knowledge transfer has been extensively studied (Bouty, 2000; Hansen, 1999; Levin & Cross, 2004). Relationship is a multilevel and multidimensional concept. In the field of knowledge management, the effect of relationships on knowledge transfer success at both organisational level (Minbaeva, 2007; Smith, Collins, & Clark, 2005; Szulanski, 1996) and individual level (Bouty, 2000; Levin & Cross, 2004; Reagans & McEvily, 2003) has been explored. It has been demonstrated that a strong relationship, which consists of strong ties (Bouty, 2000; Hansen, 1999), frequent interaction (Cavusgil et al., 2003; Levin & Cross, 2004), cumulative experience (Hasty et al., 2006), and a high level of trust (Chiu, Hsu, & Wang, 2006; Levin & Cross, 2004) between individuals positively affects tacit knowledge transfer. 20 The strength of ties between the knowledge source and recipient significantly influence knowledge transfer. Hansen (1999) found that “weak ties” (infrequent communication, a distant relationship and low reciprocity of services) between the knowledge source and receiver facilitated the search for useful knowledge, and shortened a project’s completion time, when knowledge was not complex. However, when the knowledge is complex, strong ties (frequent communication, a close relationship and a high reciprocity of services) between the knowledge source and recipient facilitate the transfer (Bouty, 2000; Hansen, 1999). Similarly, Cavusgil et al. (2003) found that a close relationship aids in the transfer of tacit knowledge, and therefore improves the innovation capability of a firm. Based on Carlson and Zmud’s (1999) Channel Expansion Theory (discussed further in section 2.6), Hasty et al. (2006) found that cumulative experience in communicating with each other helps individuals to develop a mutual understanding, which improves the efficiency of communication and further enables knowledge transfer. Researchers stress the importance of trust between the knowledge source and knowledge recipient in knowledge transfer studies. Trust refers to a set of beliefs towards another party’s integrity, benevolence, and ability (Chiu et al., 2006; Mayer, Davis, & Schoorman, 1995). A high level of trust between individuals influences tacit knowledge transfer by lowering the level of risk and uncertainty (Davenport & Pruzak, 2000; Roberts, 2000). As Roberts (2000, p. 434) said, “Trust and mutual understanding developed in a social and cultural context are prerequisites for tacit knowledge transfer”. Levin and Cross (2004) found that strong personal relationships led to a high degree of trust between individuals, and a high degree of trust positively affected knowledge transfer success. When there is a high degree of trust, the knowledge source feels secure when sharing knowledge (Joia & Lemos, 2010), the knowledge recipient is more likely to rely on the knowledge received from the source (Chiu et al., 2006), and people are more willing to engage in knowledge transfer activities (Nahapiet & Ghoshal, 1998). 21 22.4.6 Organisational context Organisational context influences knowledge transfer by its structure and systems, sources of coordination and expertise, and behaviour-framing attributes (Szulanski, 1996). Ajmal and Koskinen (2008) argue that knowledge management is not only about transferring and creating knowledge, it is also about creating an organisational culture that facilitates and encourages the creation, sharing, and utilisation of knowledge. They suggest it is important to shape an organisational culture to accept, adopt, and utilise knowledge transfer activities. When organisational activities are heavily reliant on chain of command, job specification, and standard procedures, the availability of time, flexibility, and close interactions required for tacit knowledge transfer is limited (Joia & Lemos, 2010). In order to gain a competitive advantage, an organisation needs to match its knowledge management strategy with its core values. Two strategies to facilitate knowledge transfer within organisations are codification and personalisation (Hansen et al., 2000). While a codification strategy focuses on the capturing, storing, and transmitting of explicit knowledge using information systems, the personalisation strategy focuses on how an organisation facilitates tacit knowledge transfer by arranging the organisational resources (e.g., IT resources, human resources) to promote person-to-person interactions (Hansen et al., 2000). 2.5 The effect of communication media on tacit knowledge transfer While it is generally agreed that the use of information and communication technology (ICT) significantly improves the efficiency of explicit knowledge management (Hansen et al., 2000; Zack, 1999) some researchers argue that tacit knowledge transfer can also be assisted when organisations use ICT properly (Cavusgil et al., 2003; Daft & Lengel, 1986; Murray & Peyrefitte, 2007; Roberts, 2000). Several theories are developed to determine the effect of media use on communication performance, and these theories have been applied by a number of researchers to explore how organisations could benefit from ICT to promote tacit knowledge transfer. 22 A number of theories attempt to explain media use and communication performance, the most popular and the most accepted among which are Media Richness Theory and Media Synchronicity Theory. 22.5.1 Media Richness Theory and Related Studies New communications media such as video conferencing, instant messaging, and email are widely used in organisations along with traditional methods. In order to help individuals choose the most efficient media to use it is important to determine the effectiveness of the various options available on communications. Media Richness Theory (MRT) was proposed by Daft and Lengel (1986) and is one method that provides theoretical foundations for studying the use of new communications media. Subsequent extensions of MRT approach communications media use from different perspectives such as the symbolic meanings of media (Trevino, Lengel, & Daft, 1987), social influence theory (Fulk & Boyd, 1991), adoptive structuration theory (DeSanctis & Poole, 1994), and channel expansion theory (Carlson & Zmud, 1999). 2.5.1.1 Media Richness Theory According to MRT (Daft & Lengel, 1986), an organisation is an open social system, and its success is based on its ability to process information in order to reduce uncertainty. Managers within this social system exchange, interpret and process information between each other in order to make decisions, and communication performance can be improved by matching media characteristics with information processing tasks. There are two forces that influence information processing - uncertainty and equivocality. Uncertainty is the difference between the amount of information required to perform the task and the amount of information already possessed by the organisation (Daft & Lengel, 1986). The greater the uncertainty of a task, the greater the amount of information that has to be processed (Galbraith, 1977). When dealing with a task with high uncertainty, managers do not have sufficient information to make decisions to solve the task. Also, a task may have high analysability or high equivocality. Task analysability is the application of objective, 23 well understood procedures or routines for a particular situation or problem, whereas equivocality means ambiguity, or the existence of multiple interpretations and understandings of a situation (Daft & Lengel, 1986). When dealing with a task with a high level of equivocality, a decision cannot be made by following procedures or manuals. A person’s experience and judgement, based on tacit knowledge, is required. While the level of uncertainty can be reduced by obtaining a large amount of relevant information, the level of equivocality can be reduced by information richness which is “the ability of information to change understanding within a time interval” (Daft & Lengel, 1986, p. 560). Communications where a common understanding between individuals can be established within a short period of time is considered high in richness, whereas communications which require a long period of time to achieve a common understanding are considered to be lower in richness. Communications media differ in richness according to their ability to provide immediate feedback, the amount of personalisation, the number of channels and cues, and the variety of the language used (Daft & Lengel, 1986). Based on their richness, Daft and Lengel (1986) suggest that communication media can be classified in a decreasing order or richness, ranging from face-to-face communications, telephone calls, video conferences, letters, memos and other written documents, to numeric documents such as spreadsheets. Face-to-face communication is the richest because it provides immediate feedback. Therefore the interpretation of transmitted information can be immediately confirmed. Face-to-face communication also allows for a variety of different cues to be incorporated including body language and gestures as well as tone of voice. Rich communications reduce the level of equivocality by allowing people to overcome different frames of reference and providing them with the ability to process complex and subjective messages (Daft & Lengel, 1986). While the use of rich communications media leads to better performance of equivocal tasks, the use of lean communications media such as memos and letters leads to better performance of tasks with high analysability. 24 22.5.1.2 Inconsistencies among empirical studies of MRT MRT set up a theoretical foundation for communications media studies. However, studies of MRT have inconsistent results, and some researchers have questioned the reliability of MRT when explaining the effect of ICTs on communications performance. Because computer mediated communications were not available at the time when MRT was developed, they were not included in Daft and Lengel’s (1986) classification of richness. But these new media were retroactively fitted into the framework by later researchers (Dennis et al., 2008). MRT predicts media performance, and suggests that managers who use richer media for equivocal tasks have improved performance over those who use leaner media for the same tasks. However, the majority of studies involving MRT have tended to focus on the choice of the media, rather than on how the media performs (Dennis & Kinney, 1998), and these studies produced mixed and confusing results. Some studies have found that richer media is used for equivocal tasks and leaner media for simple tasks (Daft, Lengel, & Trevino, 1987; Kraut, Galegher, Fish, & Chalfonte, 1992; Walther, 1995). Where King and Xia (1997) found that students preferred using richer media such as face-to-face conversations, group meetings and telephone conversations in their learning activity, other studies suggest that the media richness is not the only influencing factor. For example, Markus (1994) found that email tended to depersonalise communications because it was asynchronous and it filtered personal and social cues such as body language and facial expressions. Thus people tended to prefer email when they did not want/need personal interaction. She concluded that social effects had a significant influence on the choice of communication media. Not only does the effect of media richness on media choice have mixed results, but the effect of media richness on communication performance is also unclear. While Rice (1992) found that using richer media for equivocal tasks led to better performance, Dennis and Kinney (1998) found such a relationship was not significant. When studying the effect of media richness on decision making, they found that 25 matching media richness and task equivocality did not lead to better task performance. As a result of this inconsistency of research results, researchers argued about whether people always chose richer media over leaner media when dealing with equivocal tasks. And secondly did the “fit” between media richness and task characteristics always lead to better communication performances? As a result of these questions and to gain a deeper understanding of media use and media performance, a number of theories were developed based on MRT. 22.5.1.3 The subsequent theories of MRT Trevino, Lengel and Daft (1987) proposed a symbolic interaction extension to MRT. They found that the factors that influence people’s media choices were message ambiguity, symbolic cues and situational determinates such as time and distance. People often chose to use written messages over face-to-face communications when they wished to convey information about formal authority, competency or legitimacy. They argued that some media carry symbolic meanings beyond the message itself, and therefore media choice may be based on the symbolic meanings of the media rather than its richness. In their Social Influence Theory, Schmitz and Fulk (1991) argued that richness was not the objective property of a media. They suggest that media richness is partly socially constructed, and therefore different individuals may have different perceptions of the richness of a particular media. This perception may then affect individuals’ media choice. For example, one individual may see email as a leaner media and only use it to deliver text messages, where another may use it as a richer media because of the layout, the type of font, capitalisation, the use of emoticons etc. Communications media that are able to support colocation, synchronicity, the exchange of speech, the use of facial expressions, and the use of body language have a high degree of “naturalness” (Kock, 2004). Less cognitive effort is necessary to interpret a message delivered through a medium with a higher degree of naturalness (e.g., video-conference), than with a lower degree of naturalness (e.g., mail). 26 However, familiarity with the media and the communication partner, as well as experience with the communication task, lead to the establishment of a mental schema (a shared mental framework) between individuals that reduces the effort of interpreting a message. Channel Expansion Theory (Carlson & Zmud, 1999) suggests that perceived richness is related not only to the characteristics of the media, but also to the users’ experience with the media, the experience between communication partners, familiarity with the communication task and the context in which the communication occurs. Personal relationships are an important factor in the communication process. The development of personal relationships requires more time when individuals are not using face-to-face interactions, but given sufficient time, strong personal relationships can be established even by using lean media (Walther, 1992). 22.5.2 Media Synchronicity Theory and related studies Media Synchronicity Theory (MST) is different to MRT and its extensions in several aspects. First of all, MRT focuses on the equivocality and the complexity, that is, the characteristics of the task, whereas MST focuses on the communication processes required to resolve a task. Secondly, in terms of media characteristics, according to MRT, media are different in terms of richness, whereas in MST media have different capabilities supporting synchronous communication. Finally, context is neglected in MRT, whereas it is considered an important aspect in MST. The following sections discuss MST and its difference to MRT in detail. 2.5.2.1 Underlying communication processes MST was developed to explain the relationship between media characteristics and communication performance. MST argues that MRT and its extensions over stressed the importance of “task”. Instead of looking at the type and characteristics of the “task”, researchers should rather focus on the underlying communication processes required when solving a task (Dennis & Valacich, 1999). It is not the “fit” between media characteristics and task type (level of uncertainty and equivocality) that influences communication performance, but the “fit” between the communication processes (required by the task), media capability (supporting information 27 transmission and information processing), and cumulative experiences (on the media, the task, and with the communication partner) that matter. Communication is not only about the transmission of information, but also about individuals making sense of the transmitted information (Miranda & Saunders, 2003).There are two fundamental processes that must be performed to accomplish a communication task, namely conveyance of information, and convergence of meaning (Dennis et al., 2008) The conveyance processes involve the transmission of information in various formats (such as text, numbers, pictures, etc), and the processing of such information so that individuals can understand it. In conveyance processes, individuals need time to process and make sense of the gathered information. The objective of convergence processes is to achieve agreement on the meaning of the information and the context, as well as the interpretation of such information in context between communication partners. Compared to conveyance processes, there is less information processing involved in convergence processes. They require the rapid exchange of short messages in both directions to reach mutual agreement. Contrary to MRT, in MST the level of uncertainty and equivocality of a task is not important. Most tasks require both conveyance and convergence processes, although the proportion of these processes may vary. Without the conveyance of information, individuals will lack understanding of the context of the task, and without convergence, individuals will lack a shared understanding. Therefore they will not be able to make decisions or produce solutions for the task. Therefore, to investigate the influence of media characteristics on communication performance, it is important to explore how the use of media facilitates or constrains the two communication processes (Dennis et al., 2008). 22.5.2.2 Media characteristics In MST convergence processes benefit from synchronicity while conveyance processes do not. Synchronicity is defined as “a state in which individuals are working together at the same time with a common focus”. The extent to which the 28 capabilities of a media enable individuals to achieve synchronicity is called media synchronicity (Dennis et al., 2008, p. 581). According to Warren Weaver (1949, p. 2) the most basic communication problem is “how accurately the symbols of communication be transmitted?”. For Weaver, information is not only the delivered message, but also the context of the communication. Weaver suggested that the capability of a channel (referred to as medium or media in different theories) is not measured by the number of symbols that can be transmitted by it, but rather by the volume of information that can be transmitted, and by what can be produced out of the transmitted information. Based on, and extending from, Shannon and Weaver’s (1949) communication theory, Dennis, Fuller and Valacich (2008) suggest there are five media capabilities that influence the level of synchronicity. They are transmission velocity, symbol sets, parallelism, rehearsability, and preprocessability. Transmission velocity is the speed at which a medium can deliver a message to intended recipients (Dennis et al., 2008). Messages that have a high transmission velocity are delivered to the recipient as soon as they are sent. In media theories developed before MST, communication benefits from high transmission velocity are often described as “immediate”, “rapid”, or “fast feedback”. High transmission velocity helps people working together by enabling the development of shared focus and behaviour coordination, therefore positively affecting the level of synchronicity. Symbol sets are the different ways in which a medium encodes information for communication (Dennis et al., 2008). In Media Richness Theory it is referred to as a cue or language variety (Daft & Lengel, 1986). People can use multiple symbol sets simultaneously to communicate with each other (e.g., body language, spoken words, and facial expressions can be used at the same time), and communications media differ in their capabilities to deliver the use of multiple symbol sets simultaneously (e.g., a variety of symbol sets can be used in face-to-face conversation, whereas only visual symbols can be used when sending emails). Symbol sets affect the level of synchronicity not by the number of symbol sets available, but by the naturalness of the symbol, and the fit between symbol set and task type. 29 Weaver (1949) suggested that messages have to be coded precisely to maximise the efficiency of information transmission. However the more precise the coding, the greater the effort individuals spend in encoding and decoding messages. Kock (2004) argues that symbol sets differ in the speed of encoding and decoding due to the different degree of “naturalness”. Because messages with natural symbol sets (physical, visual, and verbal) are easier to be decoded than messages with unnatural symbol sets (written or typed), media that is able to deliver natural symbol sets are more capable of supporting synchronicity (Dennis et al., 2008). When symbol sets match the requirements of the message, communication is more efficient because information can be more precisely encoded and decoded in one particular symbol set than another (Dennis et al., 2008). For example, when describing sales figures to a colleague, it is easier to demonstrate the data in the form of tables or charts than to describe them orally. Therefore, the “fit” between symbol sets and the message requirement leads to higher levels of synchronicity. The number of simultaneous transmissions that can effectively take place is referred to as parallelism (Dennis et al., 2008). Media with high parallelism allow several communication threads to exist in a group discussion. By enabling multi-directional, simultaneous communication it reduces the shared focus among the group, thus negatively affecting the level of synchronicity. For example, when discussing two topics at the same time (e.g. group discussion on skype, email exchanges with more than one colleague at the same time), individuals’ attention has to shift from one to another and therefore the speed of feedback is reduced. Rehearsability refers to the ability of the sender to edit a message before sending it out so that it more precisely conveys the intended meaning (Dennis et al., 2008). Because more time is spent in editing the message, a time delay between message transmissions is created. Therefore rehearsability lowers the level of synchronicity. Finally, reprocessability refers to the level of re-examination and re-processing that is possible either within the context of the communication or after the communication event has passed (Dennis et al., 2008). Similar to rehearsability there 30 is a time delay between message transmissions, which lowers the level of synchronicity. These five media capabilities influence the level of synchronicity between individuals. Media with high transmission velocity and more natural symbol sets have greater support for synchronicity, while media with high parallelism, high rehearsability, and high reprocessability have less support for synchronicity. Before publishing the 1999 version of MST, Dennis, Valacich, Speier, and Morris (1998) examined the effect of synchronicity on task performance, and provided preliminary support for MST. They found that participants using media that support low synchronicity (written communication) generated more unique ideas, whereas participants using media that support high synchronicity (face-to-face communication) were more likely to reach consensus and spend less time on the same task. They concluded that media low in synchronicity supported information conveyance, and media high in synchronicity supported convergence. Based on the observation of, and interviews with, members of eight virtual business teams, DeLuca and Valacich (2006) concluded that media with lower synchronicity such as computer mediated communication led to better conveyance performance, whereas media with higher synchronicity such as face-to-face communication led to better convergence performance. Murthy and Kerr (2003) found that using media that supported higher synchronicity led to better performance in problem solving tasks, whereas using media supporting lower synchronicity led to better performance on idea generation tasks. According to their physical characteristics, Dennis et al. (2008) compared the capabilities of some commonly available communication media to support synchronicity (see table 2.3). 31 Ta bl e 2. 3 A co m pa ris on o f s el ec te d m ed ia a nd th ei r c ap ab ili tie s M ed ia M ed ia C ap ab ili ty Co m m un ic at io n pr oc es s Sy nc hr on ic ity Ve lo ci ty Pa ra lle lis m Sy m bo l s et s Re he ar sa bi lit y Re pr oc es sa bi li ty In fo rm at io n tr an sm iss io n In fo rm at io n pr oc es sin g Fa ce -t o- Fa ce Hi gh M ed iu m Fe w -M an y Lo w Lo w Fa st Lo w Hi gh Vi de o co nf er en ce Hi gh M ed iu m Fe w -M ed iu m Lo w Lo w Fa st Lo w Hi gh Te le co nf er en ce Hi gh Lo w Fe w Lo w Lo w Fa st Lo w Hi gh In st an t m es sa gi ng M ed iu m -h ig h Lo w - M ed iu m Fe w - M ed iu m M ed iu m M ed iu m -h ig h M ed iu m Lo w - M ed iu m M ed iu m Em ai l Lo w -M ed iu m Hi gh Fe w -M ed iu m Hi gh Hi gh Sl ow Hi gh Lo w Vo ic e m ai l Lo w -M ed iu m Lo w Fe w Lo w -M ed iu m Hi gh Sl ow M ed iu m Lo w Fa x Lo w -M ed iu m Lo w Fe w -M ed iu m Hi gh Hi gh Sl ow Hi gh Lo w Do cu m en ts Lo w Hi gh Hi gh Hi gh Sl ow Hi gh Lo w 32 It is important to understand that these propositions are made under the premise that all media capabilities are fully appreciated and used by the media user. Although users can choose how to use media, the capabilities provided by the media also restrain users’ behaviour - that is, the “fit” between media capabilities and task requirement influences how individuals choose and use communication media (DeSanctis & Poole, 1994; Yoo & Alavi, 2001). Therefore, media users are more likely to select and use the media that they find is most appropriate for the task. Also, the selection and use of a particular media is influenced by the users’ training and experience on the particular media, and their attitude towards the media (DeSanctis & Poole, 1994; King & Xia, 1997). Moreover, modern communication media may provide multiple capabilities (for example, a mobile phone can offer text, voice, and video communication functions on a single platform). In such a situation the level of synchronicity is not determined by the capabilities available, but rather by how the users use the media. In conclusion, when studying the effect of media capabilities on synchronicity, it is “necessary to examine the underlying media capabilities provided and used, rather than considering the device itself as a single entity”(Dennis et al., 2008, p. 588). 22.5.2.3 The effect of communication context According to MST, communication performance is not only affected by the “fit” between media characteristics and the underlying communication process, but is also influenced by the context in which the communication occurs (Carlson & Zmud, 1999; Kock, 2004; Zack, 1994). Based on the Time, Interaction and Performance Theory developed by Joseph McGrath in 1991, Dennis et al. (2008) propose that the accomplishment of a communication task requires individuals to work as a group. Such a group has two functions: the production function (activities that need to be accomplished), and the social function (relationships and the support of individuals). Within these two functions there are four modes of activity. The inception (understanding task goals 33 and developing a strategy), technical problem solving (the resolution of issues about how the task will be accomplished), conflict resolution (policy choice), and finally execution (goal attainment). While the inception mode and the execution mode are involved in all group activities, the conflict resolution mode and the technical problem solving mode may or may not be involved (McGrath, 1991). In the most straight forward situations, the group will move directly from inception to execution because this direct path is the most time and resource efficient. When there is a significant change on the task context (for example: new group members, change of task specifications), the group may move through each step, or when there is a power conflict within the group, the group may move from inception mode to conflict resolution mode before moving to execution mode (McGrath, 1991). Based on TIP theory, Dennis et al. (2008) suggest that the amount of convergence and conveyance required in the different modes varies according to the task context. When group members are familiar with each other, the task, and the media, they will develop shared mental models including rules, routines, and mutual understandings very quickly. These shared mental models reduce the amount of convergence of meanings between group members required in the inception and execution modes. Even when the group moves to technical problem solving or conflict solving modes due to unexpected events, less convergence will be needed because these modes often involve the development of mutual understanding. When group members are not familiar with each other, the task and the media, shared mental models will more difficult to develop. Conveyance and convergence are both involved but convergence will play a more important role because negotiation on values, interests, power, and strategy choice will need to take place in each of the group modes (Dennis et al., 2008). 34 Media Capacity VelocityVelocity Symbol SetsSymbol Sets ParallelismParallelism RehearsabilityRehearsability Reprocessabilit y Reprocessabilit y SynchronicitySynchronicity FitFit Task Requirement Task Requirement Communication context Communication context Communication performence Communication performence Figure 2.3. Communication media have different capabilities that supporting synchronicity. The “fit” between synchronicity, communication processes, and communication context determines communication performance. Adapted from: “Media, tasks, and communication processes: A theory of media synchronicity,” by Dennis et al., 2008, MIS quarterly, 32(3), p. 582. In conclusion, different degrees of conveyance and convergence processes are required when dealing with a task. Therefore individuals who are familiar with each other, the task and the media have less of a need to use media that supports synchronicity, whereas individuals who are unfamiliar with each other, the task or the media have a greater need to use media that supports synchronicity. Thus, communication performance improves when there is a fit between task requirements, the media capabilities, and the communication context (Dennis et al., 2008). 22.5.3 The effect of media use on tacit knowledge transfer 2.5.3.1 The application of MRT on tacit knowledge transfer According to Nonaka and Konno (1998), joint activities are needed for tacit knowledge transfer between individuals. Therefore, person-to-person interaction is the key to promote tacit knowledge transfer (Hansen et al., 2000). Rich communication media such as video-conferencing allows people to provide immediate feedback and transmit a variety of communication cues to each other, 35 which allows people to “co-presence” without “co-location” (Boisot, 1998), therefore enabling tacit knowledge transfer between people in different locations. Because tacit knowledge is personal and contextual, it is highly ambiguous and open to different interpretations and views (Joia & Lemos, 2010). The ambiguity of tacit knowledge creates “stickiness”, which hinders its transfer. MRT suggests that rich communication allows people to overcome ambiguity and helps them to process complex information (Daft & Lengel, 1986). Therefore the use of rich media facilitates tacit knowledge transfer. In a survey of health care employees in 2007, it was concluded that people use richer communications media such as face-to-face and video conferencing to transfer tacit knowledge, and leaner media such as email and organisational database to transfer explicit knowledge (Murray & Peyrefitte, 2007). A number of studies concluded that the use of rich media leads to better tacit knowledge transfer (Casal & Fontela, 2007; Hasty et al., 2006; Joia & Lemos, 2010; Sheng, Chang, Teo, & Lin, 2013). The relationship between media richness and knowledge transfer was investigated in a number of studies. Pedersen, Petersen, and Sharma (2003) surveyed multinational companies in Denmark, and found that the performance of knowledge transfer was maximised when tacit knowledge was transferred through rich communication media and explicit knowledge transferred through lean communication media. 22.5.3.2 The application of MST on tacit knowledge transfer While MST has been used to examine the effect of communication media on the efficiency of negotiations (Scheck, Allmendinger, & Hamann, 2008) and group performance (Rahman, Cheng, & Bayerl, 2013; Shim, Suh, & Im, 2010), few studies have investigated the application of MST to the transfer of knowledge, and even less on the transfer of tacit knowledge. However, several studies explored the effects of media capabilities (as part of media synchronicity). Scott and Sarker (2010) found that symbol sets and reprocessability 36 positively affected knowledge receivers’ ability to internalise knowledge. In their experiment, symbol sets were manipulated so that some participating groups used text only online tutorials and other groups used text and graphic online tutorials. Reprocessability occurred by enabling and disabling participants to revisit previous tutorials when they were working on a task. Because the task was drawing an activity diagram solely by following an online tutorial, the knowledge received by the participants can be considered as explicit knowledge. Therefore, in this situation low synchronicity (written and graphical messages, high reprocessability) between the knowledge source and knowledge recipient positively influenced the transfer of explicit knowledge. Arguing that remote site health care delivery involves tacit knowledge transfer, Paul (2005) found that a telemedicine system capable of delivering synchronous communication, (voice and video messages) significantly improved the performance of remote site health care delivery. Jasimuddin (2007), who studied knowledge transfer mechanisms in UK based high tech groups, found that while the information technology infrastructure was capable of managing explicit knowledge efficiently, the most effective way to transfer tacit knowledge was still face-to-face communication. The possibility of using virtual worlds as platforms of knowledge management was studied by Mueller, Hutter, Fueller, and Matzler (2011) . They found that individuals benefited from the functionalities of virtual worlds. The synchronous interaction, variety of communication channels, social presence, and so on, which allowed them to interact with each other in a shared context, facilitated the transfer of tacit knowledge (Mueller et al., 2011). 22.5.3.3 Prior measurements of tacit knowledge Because the concept of “tacit knowledge” itself remains tacit, it is difficult to explain to the participants what exactly tacit knowledge is, and it is even more difficult to assess the degree of tacitness. There is no generic measurement for tacitness in the literature; all measurements are designed to fit the respective settings. 37 One popular measurement for tacitness is the Tacit Knowledge Inventory for Managers (TKIM) developed by Wagner and Sternberg (1991). This measurement is based on the idea that tacit knowledge is acquired through experience and influences the knowledge holders’ performance in the working environment. The approach suggested by TKIM is to develop a series of questions simulating workplace-related problems through