Tacit Knowledge Transfer in Virtual Teams: Exploring the Role of Organizational Mobile Social Networking
Introduction
As the modern organization establishes operations and alliances across the globe, virtual teamwork has become critical to its success (Friedman, 2005). Corporations and governmental institutions increasingly rely on teams consisting of well-qualified members who are distributed not only across a given country but around the world, as they outsource, expand, and seek ways to cut costs. However, the management of virtual teams introduces significant challenges not seen in the management of traditional, collocated teams.
Among the suggestions provided by scholars to practitioners who manage virtual teams are: finding new ways to focus the attention of virtual team members on the nature of their task; providing for face-to-face meetings; designing activities that allow virtual team members to get to know one another; emphasizing teamwork skills; agreeing on the standards and terminology that will be used by virtual team members; embedding collaboration technology into the practices and systems already in use by virtual teams (Nunamaker et al., 2009; Siebdrat et al., 2009).
According to the resource-based view of the firm, the assets of an organization that are valuable, rare, difficult to imitate by other firms, and difficult to substitute with other resources provide the organization with a competitive advantage. Knowledge is one such asset, as valuable as brand identity, customer information, and corporate reputation (Pascarella, 1997). Tacit knowledge, knowledge that cannot be found in manuals or files, but which is so ingrained that it is taken for granted (Sternberg, 1997), is, in turn, one such type of knowledge.
However, the more virtual the team, the less time, if any, it will spend together on tasks, and the more it will rely on the use of traditional tools such as e-mail and video-conferencing when communication between members is required. And such teams will be more likely to transfer explicit knowledge than tacit knowledge because these tools support the declarative nature of explicit knowledge (Griffith et al., 2003).
As social networking, smart phones, and apps that facilitate social networking via mobile devices continue to proliferate, this paper examines the potential role that mobile social networking may play in the transfer of tacit knowledge among virtual team members. While much of the prior work on virtual teams and tacit knowledge has focused on the definition of these terms, we propose the placement of all teams along a continuum of “virtualness” and the conceptualization of tacit knowledge transfer as a function of the level of conflict experienced between team members. By doing so, we provide a framework by which academicians may advance the study of virtual teams, and by which practitioners may improve the effectiveness of such teams.
Overview of Virtual Teams and Tacit Knowledge
Virtual Teams
Organizations form teams because a combination of individuals whose experience and expertise inform the various facets of a particular decision is more effective than any manager acting alone (Deeter-Schmelz & Ramsey, 2003; Dennis, 1996, Stasser and Titus, 1985). Such teams may consist of individuals who work within a single organization in a given location or of those who belong to multiple organizations distributed throughout the world. However, researchers have shown that the integration of such disparate knowledge may be ineffectual and lead to poor decision-making (Dennis, 1996; Stasser & Stewart, 1992; Hollingshead, 1996; Straus, 1996). One particular conclusion is that a given team’s performance may be affected not only by its members’ individual performance but also by the team’s inability or failure to integrate its members’ knowledge (Reus & Liu, 2004).
Virtual, or digitally-enabled, or distributed, teams have been the focus of much research in recent years. The vast majority of teams in organizations today supplement traditional, face-to-face communication with a wide variety of communication media to support their work. Virtual teams have thus been conceptualized as those in which members are physically or temporally dispersed. Such teams range from collocated but telecommuting individuals within a single organization, to employees of a single organization who are geographically-dispersed, to employees of multiple organizations who are assembled, based on skill, for the sole purpose of working on a particular project. According to Watson-Manheim et al. (2002), the common thread of these teams is the notion of discontinuity, gaps or lack of coherence in certain aspects of team work, such as work setting, task, and relations with other employees. Such discontinuities may be temporal, geographic, organizational, cultural, or related to group membership. However, a common definition of “virtual team” has yet to emerge among practitioners and researchers.
While the widespread study of virtual teams is still relatively new, what most researchers nevertheless seem to agree on is that the key feature of virtual teams is the relative lack of face-to-face contact, whether that lack of contact is due to work place mobility, team distribution, or specific organizational practices. Our definition and proposed measures for “virtualness” are based on this relative lack of face-to-face contact.
Tacit Knowledge
Distinctions between explicit and tacit knowledge tend to be more the result of convenience than that of a theoretical requirement (Griffith et al., 2003). In general, explicit knowledge is regarded as knowledge that can be articulated and is accessible to others (Leonard & Sensiper, 1998). This is in line with references to explicit knowledge as objective (Schultze, 2000) and declarative or fact-based (Berry, 1987). Tacit knowledge, on the other hand, has been characterized either as knowledge that cannot be articulated (Polyani, 1966) or as including both knowledge that cannot be articulated and knowledge that could be articulated but has yet to be so (Spender, 1996). It has been further defined as knowledge that is not articulated but which is tied to the senses, movement skills, physical experiences, intuition, or implicit rules of thumb (Nonaka & von Krogh, 2009).
Griffith et al. (2003) proposed a continuum of individual knowledge, with explicit and tacit knowledge at the two ends and implicit knowledge falling in the mid-range of the continuum. They further define explicit knowledge as the most objective or declarative type of knowledge; implicit knowledge as knowledge that is not currently declarative but could be made so; and tacit knowledge as that which has never been and could not likely be made declarative.
In his review of work done on or involving tacit knowledge, Castillo (2002) highlights the disparity that exists in the ideas that have been advanced by psychologists and management theorists, suggesting that researchers have stretched the boundaries of what can be considered tacit knowledge. Among his proposals to bring unity and clarity to the concept of tacit knowledge is a fourfold typology of tacit knowledge, in which such knowledge is classified as nonepistle, sociocultural, semantic, or sagacious. We adopt this typology in studying tacit knowledge acquisition from communities-of-practice and tacit knowledge transfer between virtual team members.
Theoretical Foundations and Research Model
Among Griffith et al.’s (2003) propositions are 1) More virtual teams will have greater access to communities-of-practice than will less virtual teams; and 2) Tacit knowledge from members’ links to communities-of-practice is less likely to be disseminated within more virtual teams than they are within less virtual teams. We slightly modify the first proposition by suggesting that members of more virtual teams will actually be involved to a greater extent with communities-of-practice than will members of less virtual teams. Furthermore, we include organizational mobile social networking between virtual team members as a moderating factor in the negative relationship between the extent of members’ involvement with communities-of-practice and the transfer of tacit knowledge between them (Figure 1).
Virtualness
Tacit Knowledge Transfer
Organizational Mobile Social Networking
Involvement with Communities-of-Practice
Figure 1. Conceptual Framework
Virtualness and Communities-of-Practice
While “virtualness” has been defined solely in terms of the extent of face-to-face contact among team members (Fiol & O’Connor, 2005), and while technological support and dispersion may not necessarily define virtual teams (Griffith & Neale, 2001), it is difficult to ignore the tendency of virtual teams to be geographically dispersed and dependent on technology. In fact, Griffith et al. (2003) define “virtualness” in part by geographic distance and technological support.
In an effort to avoid the extremes of “never” versus “always” meeting face-to-face, hybrid teams have been defined as those that combine face-to-face meetings with work done apart and supported by technology. These teams may consist of collocated members who rely on both face-to-face meetings and communication technologies, or of geographically-dispersed members who meet occasionally (Cousins et al., 2007). However, unless specific ratios of face-to-face work to work-done-apart are offered, one can argue that all teams are “hybrid.”
Given the pervasiveness of communications technologies, we suggest the avoidance of labelling teams as either “virtual,” “traditional,” or “hybrid.” Instead, we propose a conceptualization of all teams as falling somewhere along the continuum of “virtualness.” For the purposes of this study, we define a team as a group of individuals employed either by a single organization or by multiple organizations and who work together on a given set of tasks and towards a common goal, regardless of whether they are traditionally considered “collocated,” “virtual,” or “hybrid.”
We further define “virtualness” as a function of two variables: 1) the percentage of team contact using communications technologies; and 2) the percentage of team tasks performed in the absence of team members. (It is interesting to note that the greater the geographic and/or temporal dispersion amongst team members, the more likely the team is to score high on both measures. However, a team consisting of collocated members who rarely meet may also score high on “virtualness.”)
Communities-of-practice are those that develop when groups of practitioners have many opportunities for informal contact (Griffith et al., 2003). These communities focus on the sharing of relevant experiences which, once a level of personal intimacy develops (Leonard & Sensiper 1998) in an environment of frequent and intensive interaction (Nonaka & Takeuchi 1995), enables the transfer of tacit knowledge (Nambisan et al. 1999). In essence, a community-of-practice functions as a pseudo-team that acts as a substitute for the actual team.
Teams that score higher on “virtualness,” due of their lack of face-to-face communications and greater time spent apart on team tasks, can thus be expected to have greater involvement with local communities-of-practice, which we operationalized as the frequency of contact.
Hypothesis 1: The greater the percentage of contact between team members via communications technologies, the greater its members’ frequency of contact with communities-of-practice.
Hypothesis 2: The greater the percentage of time spent on team tasks in the absence of team members, the greater its members’ frequency of contact with communities-of-practice.
Communities-of-Practice and Tacit Knowledge Acquisition/Transfer
Explicit knowledge transfer is part of the function of communities-of-practice. However, tacit knowledge may well be transferred as members meet and discuss solutions to problems (Griffith & Sawyer, 2006). In fact, participation in communities-of-practice has been shown to have a positive effect on knowledge attainment, whether explicit or tacit (Griffith & Sawyer, 2006).
While tacit knowledge has become increasingly important to managerial and organizational studies (Polyani, 1966; Hennart, 1992; Kim & Hwang, 1992; Nonaka & Takeuchi, 1995; Folger & Truillo, 1999; Nonanka & von Krogh, 2009), there seems to be little consensus on the definition of tacit knowledge and whether or not it is measurable. Castillo (2002) offers a useful typology of tacit knowledge, classifying such knowledge into four categories: nonepistle tacit knowledge, sociocultural tacit knowledge, semantic tacit knowledge, and sagacious tacit knowledge. Of these, semantic and sociocultural tacit knowledge are of greatest relevance to this study.
Semantic tacit knowledge refers to knowledge that, “either because of special symbolism and/or possible distinctive behavior peculiar to the job, makes it unnecessary to mention such knowledge” (Castillo, 2002). In other words, this type of tacit knowledge consists of the specialized, but non-codified, communication of those in a particular field who understand the implicit meaning of each other’s abstract expressions, but who may not be members of a formal team.
Sociocultural tacit knowledge is knowledge that is not attributable to any individual but which belongs to the social/cultural systems that use this type of knowledge (Castillo, 2002). It is similar to Spender’s (1992; 1994) “collective tacit knowledge,” Cook and Brown’s (1999) “group tacit knowledge,” and Leonard and Sensiper’s (1998) idea of tacit knowledge that is developed, over time, in interactions among individuals who have been socialized into the group.
We suggest that semantic and sociocultural tacit knowledge is acquired by team members from their involvement with communities-of-practice. If increased contact with these communities-of-practice is coupled with decreased levels of face-to-face interaction with team members, we can expect that the tacit knowledge acquired from the communities-of-practice will be less likely to be transferred to other team members. Teams that spend less time together on task and make greater use of traditional technological tools will be more likely to transfer explicit knowledge than tacit knowledge because the technological tools support the declarative nature of explicit knowledge (Griffith et al., 2003).
If the tacit knowledge acquired by team members in their respective communities-of-practice differs from one community to another, we can also expect more conflict between team members in their interactions. This study thus conceptualizes the level of tacit knowledge transfer as a function of the level of conflict between team members: the higher the level of tacit knowledge transfer, the lower the level of conflict between team members; the lower the level of tacit knowledge transfer, the higher the level of conflict between team members. We operationalize team conflict as the individual team members’ perceived level of conflict between members.
Hypothesis 3: The greater the frequency of contact with communities-of-practice, the greater the members’ perceived level of conflict between team members.
Organizational Mobile Social Networking
Hundreds of millions of people today use social network sites (SNS) to meet, reconnect, and share content with others. Facebook alone boasts a half-billion users. Much of the research thus far on these sites has focused on privacy issues (Acquisti & Gross, 2006; Krasnova et al., 2010), social capital (Ellison et.al., 2006; Ellison et al., 2007), education (Mazer, et.al., 2007; Wankel, 2009), and uses and gratifications (Raacke & Bonds-Raacke, 2009; Joinson, 2008). The body of this research suggests that the primary reasons individuals use SNSs are to maintain pre-existing relationships. However, relatively little work has been done on the use of social networking within the organization, whether through a public SNS, such as Facebook, or through a private, organizational SNS.
In a series of studies on the use of Beehive, an SNS developed for use by IBM employees, the researchers found that among the most popular uses of the site were to get a better sense of co-workers (DiMicco et al., 2009) and to connect on a personal level with co-workers (DiMicco et al., 2008). In fact, the number one reason employees gave for using Beehive was that they enjoyed connecting socially with colleagues (DiMicco et al., 2008).
For members of teams that do not meet face-to-face on a regular basis, an SNS, such as Beehive, can serve as a medium through which the communication of those in a particular field who understand the implicit meaning of each other’s abstract expressions (semantic tacit knowledge) may flow. As the members connect with each other socially, they may also share knowledge that is developed, over time, in interactions among individuals who have been socialized into the group (sociocultural tacit knowledge). It is not unreasonable, then, to think that tacit knowledge acquired by team members from their respective communities-of-practice may be transferred to other team members through the use of an SNS. Additionally, with the proliferation of SNSs have come apps that allow members to leverage such sites through their mobile devices. The ability to connect with one’s team members on-the-go, anytime, anywhere, through status updates may serve to further facilitate the transfer of tacit knowledge.
We define organizational mobile social networking as the combined use of mobile devices (e.g. smartphones, tablet PCs) and an SNS (whether public or private) by organizational members to connect with each other. We anticipate that the frequency of mobile social networking between members of teams will lead to the transfer of tacit knowledge acquired from each member’s communities-of-practice to other members and thus moderate the relationship between the frequency of contact with such communities and the perceived level of conflict amongst team members.
Hypothesis 4: The frequency of mobile social networking between team members moderates the relationship between members’ frequency of contact with communities-of-practice and members’ perceived level of conflict amongst team members.
The above hypotheses form a model (Figure 2) that seeks to provide an understanding of how the “virtualness” of teams affects members’ acquisition of tacit knowledge from communities-of-practice, the transfer of such tacit knowledge to other team members, and effect of mobile social networking on this transfer.
Frequency of mobile social networking between members
Organizational Mobile Social Networking
Percentage of team contact using communications technologies
Perceived level of conflict amongst team members
(Tacit Knowledge Transfer)
Virtualness
Percentage of team tasks performed in absence of team members
Acquisti, A. & Gross, R. (2006). Imagined communities: awareness, information sharing and privacy on the Facebook. Paper presented at the 6th workshop on Privacy Enhancing Technology, Cambridge, England.
Berry, D.C. The problem of implicit knowledge. Expert Systems, 4(3), 1987, 144-150.
Castillo, J. A note on the concept of tacit knowledge. Journal of Management Inquiry, 11(1) 2002, 46-57.
Cook, S.D.N. & Brown, J.S. Bridging epistemologies: The generative dance between organizational knowledge and organizational knowing. Organization Science, 10(4), 1999, 381-400.
Cousins, K.C., Robey, D. & Zigurs, I. Managing strategic contradictions in hybrid teams. European Journal of Information System, 16, 2007, 460-478.
Deeter-Schmelz, D.R. & Ramsey, R.P. An investigation of team information processing in service teams: Exploring the link between teams and customers. Journal of the Academy of Marketing Science, 31(4), 2003, 409-424.
Dennis, A.R. Information exchange and use in group decision making: You can lead a group to information but you can’t make it think. MIS Quarterly, 20(4), 1996, 433-455.
DiMicco, J., Geyer, W., Millen, D.R., Dugan, C., and Brownholtz, B. (2009). People Sensemaking and Relationship Building on an Enterprise Social Networking Site. Proc. HICSS.
DiMicco, J., Millen, D.R., Geyer, W., Dugan, C., Brownholtz, B., and Muller, M. (2008). Motivations for Social Networking at Work. Proc CSCW.
Ellison, N., Heino, R., & Gibbs, J. (2006). Managing impressions online: self-presentation processes in the online dating environment. Journal of Computer-Mediated Communication, 11(2).
Ellison, N., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends”: social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication, 12(4).
Fiol, C.M. & O’Connor, E.J. Identification in face-to-face, hybrid, and pure virtual teams: Untangling the contradictions. Organization Science, 16(1), 2005, 19-32.
Folger, R. & Truillo, C.J. Theorizing as the thickness of thin abstraction. Academy of Management Review, 24(4), 1999, 742-758.
Friedman, T.L. The World is Flat: A Brief History of the 21st Century, Farrar, Straus and Giroux, NY, 2005.
Griffith, T.L. & Neale, M.A. Information processing in traditional, hybrid, and virtual teams: From nascent knowledge to transactive memory, in Research in Organizational Behavior (Volume 23), B.M. Staw and R.I. Sutton (eds.), JAI Press, Stamford, CT, 2001, 379-421.
Griffith, T.L., Sawyer, J.E. & Neale, M.A. Virtualness and knowledge in teams: Managing the love triangle of organizations, individuals, and information technology. MIS Quarterly, 27(2), 2003, 265-287.
Griffith, T.L. & Sawyer, J.E. Supporting technologies and organizational practices for the transfer of knowledge in virtual environments. Group Decision and Negotiation, 15, 2006, 407-423.
Hennart, J.F. The transaction costs theory of joint ventures: An empirical study of Japanese subsidiaries in the United States. Management Science, 37(4), 1992, 483-497.
Hollingshead, A.B. The rank-order effect in group decision making. Organizational Behavior Human Decision Processes, 68(3), 1996, 181-193.
Joinson, A.N. (2008). ‘Looking at’, ‘looking up’ or ‘keeping up with’ people? Motives and uses of Facebook. Computer Human Interactions Proceedings, Florence, Italy.
Kim, W.C. & Hwang, P. Global strategy and multinationals’ entry mode choice. Journal of International Business Studies, 23(1), 1992, 29-53.
Krasnova, H., Spiekermann, S., Koroleva, K., & Thomas Hildebrand, T. (2010). Online social networks: why we disclose. Journal of Information Technology, 25(2).
Leonard, D. & Sensiper, S. The role of tacit knowledge in group innovation. California Management Review, 40(3), 1998, 112-132.
Mazer, J., Murphy, R., & Simonds, C. (2007). I'll see you on Facebook: the effects of computer mediated communication on teacher-student communication. Communication Education, 56(1).
Nambisan, S., Agarwal, R. & Tanniru, M. Organizational mechanisms for enhancing user innovativeness in information technology. MIS Quarterly, 23(3), 1999, 365-395.
Nonaka, I. & Takeuchi, H. The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press, Oxford, UK, 1995.
Nonaka, I. & von Krogh, G. Tacit knowledge and knowledge conversion: Controversy and advancement in organizational knowledge creation theory. Organization Science, 20(3), 2009, 635-652.
Nunamaker, J.F., Reinig, B.A., & Briggs, R.O. Principle for effective virtual teamwork. Communications of the ACM, 52(4), 2009, 113-117.
Pascarella, P. Harnessing knowledge. Management Review, October, 1997, 37-40.
Polyani, M. The Tacit Dimension. Doubleday, New York, 1966.
Raacke, J. & Bonds-Raacke, J. (2008). MySpace and Facebook: applying the uses and gratifications theory to exploring friend-networking sites. CyberPsychology and Behavior, 11(2).
Reus, T. & Liu, Y. Rhyme and reason: Emotional capability and the performance of knowledge-intensive work groups. Human Performance, 17(2), 2004, 245-266.
Schultze, U. A confessional account of an ethnography about knowledge work. MIS Quarterly, 24(1), 2000, 3-41.
Siebdrat, F., Hoegl, M. & Ernst, H. How to manage virtual teams. Sloan Management Review, 50(4), 2009, 62-68.
Spender, J.C. Organizational knowledge, collective practice and Penrose rents. International Business Review, 3(4), 1994, 353-367.
Spender, J.C. Making knowledge the basis of a dynamic theory of the firm. Strategic Management Journal, 17(Winter), 1996, 45-62.
Stasser, G. & Stewart, D.D. The discovery of hidden profiles by decision making groups: Solving a problem versus making a judgment. Journal of Personality and Social Psychology, 63, 1992, 426-434.
Stasser, G. & Titus, W. Pooling of unshared information in group decision making: Biased information sampling during discussion. Journal of Personality and Social Psychology, 48(6), 1985, 1467-1478.
Sternberg, R.J. Managerial intelligence: Why IQ isn’t enough. Journal of Management, 23(3), 1997, 475-493.
Strauss, S.G. Getting a clue: The effects of communication media and information distribution on participation and performance in computer-mediated and face-to-face groups. Small Group Research, 27(1), 1996, 115-142.
Wankel, C. (2009). Management education using social media. Organization Management Journal, 6(4).
Watson-Manheim, M.B., Chudoba, K.M. & Crowston, K. Discontinuities and continuities: a new way to understand virtual work. Information Technology & People, 15(3), 2002, 191-209.
Exploring the Role of Organizational Mobile Social Networking
Introduction
As the modern organization establishes operations and alliances across the globe, virtual teamwork has become critical to its success (Friedman, 2005). Corporations and governmental institutions increasingly rely on teams consisting of well-qualified members who are distributed not only across a given country but around the world, as they outsource, expand, and seek ways to cut costs. However, the management of virtual teams introduces significant challenges not seen in the management of traditional, collocated teams.
Among the suggestions provided by scholars to practitioners who manage virtual teams are: finding new ways to focus the attention of virtual team members on the nature of their task; providing for face-to-face meetings; designing activities that allow virtual team members to get to know one another; emphasizing teamwork skills; agreeing on the standards and terminology that will be used by virtual team members; embedding collaboration technology into the practices and systems already in use by virtual teams (Nunamaker et al., 2009; Siebdrat et al., 2009).
According to the resource-based view of the firm, the assets of an organization that are valuable, rare, difficult to imitate by other firms, and difficult to substitute with other resources provide the organization with a competitive advantage. Knowledge is one such asset, as valuable as brand identity, customer information, and corporate reputation (Pascarella, 1997). Tacit knowledge, knowledge that cannot be found in manuals or files, but which is so ingrained that it is taken for granted (Sternberg, 1997), is, in turn, one such type of knowledge.
However, the more virtual the team, the less time, if any, it will spend together on tasks, and the more it will rely on the use of traditional tools such as e-mail and video-conferencing when communication between members is required. And such teams will be more likely to transfer explicit knowledge than tacit knowledge because these tools support the declarative nature of explicit knowledge (Griffith et al., 2003).
As social networking, smart phones, and apps that facilitate social networking via mobile devices continue to proliferate, this paper examines the potential role that mobile social networking may play in the transfer of tacit knowledge among virtual team members. While much of the prior work on virtual teams and tacit knowledge has focused on the definition of these terms, we propose the placement of all teams along a continuum of “virtualness” and the conceptualization of tacit knowledge transfer as a function of the level of conflict experienced between team members. By doing so, we provide a framework by which academicians may advance the study of virtual teams, and by which practitioners may improve the effectiveness of such teams.
Overview of Virtual Teams and Tacit Knowledge
Virtual Teams
Organizations form teams because a combination of individuals whose experience and expertise inform the various facets of a particular decision is more effective than any manager acting alone (Deeter-Schmelz & Ramsey, 2003; Dennis, 1996, Stasser and Titus, 1985). Such teams may consist of individuals who work within a single organization in a given location or of those who belong to multiple organizations distributed throughout the world. However, researchers have shown that the integration of such disparate knowledge may be ineffectual and lead to poor decision-making (Dennis, 1996; Stasser & Stewart, 1992; Hollingshead, 1996; Straus, 1996). One particular conclusion is that a given team’s performance may be affected not only by its members’ individual performance but also by the team’s inability or failure to integrate its members’ knowledge (Reus & Liu, 2004).
Virtual, or digitally-enabled, or distributed, teams have been the focus of much research in recent years. The vast majority of teams in organizations today supplement traditional, face-to-face communication with a wide variety of communication media to support their work. Virtual teams have thus been conceptualized as those in which members are physically or temporally dispersed. Such teams range from collocated but telecommuting individuals within a single organization, to employees of a single organization who are geographically-dispersed, to employees of multiple organizations who are assembled, based on skill, for the sole purpose of working on a particular project. According to Watson-Manheim et al. (2002), the common thread of these teams is the notion of discontinuity, gaps or lack of coherence in certain aspects of team work, such as work setting, task, and relations with other employees. Such discontinuities may be temporal, geographic, organizational, cultural, or related to group membership. However, a common definition of “virtual team” has yet to emerge among practitioners and researchers.
While the widespread study of virtual teams is still relatively new, what most researchers nevertheless seem to agree on is that the key feature of virtual teams is the relative lack of face-to-face contact, whether that lack of contact is due to work place mobility, team distribution, or specific organizational practices. Our definition and proposed measures for “virtualness” are based on this relative lack of face-to-face contact.
Tacit Knowledge
Distinctions between explicit and tacit knowledge tend to be more the result of convenience than that of a theoretical requirement (Griffith et al., 2003). In general, explicit knowledge is regarded as knowledge that can be articulated and is accessible to others (Leonard & Sensiper, 1998). This is in line with references to explicit knowledge as objective (Schultze, 2000) and declarative or fact-based (Berry, 1987). Tacit knowledge, on the other hand, has been characterized either as knowledge that cannot be articulated (Polyani, 1966) or as including both knowledge that cannot be articulated and knowledge that could be articulated but has yet to be so (Spender, 1996). It has been further defined as knowledge that is not articulated but which is tied to the senses, movement skills, physical experiences, intuition, or implicit rules of thumb (Nonaka & von Krogh, 2009).
Griffith et al. (2003) proposed a continuum of individual knowledge, with explicit and tacit knowledge at the two ends and implicit knowledge falling in the mid-range of the continuum. They further define explicit knowledge as the most objective or declarative type of knowledge; implicit knowledge as knowledge that is not currently declarative but could be made so; and tacit knowledge as that which has never been and could not likely be made declarative.
In his review of work done on or involving tacit knowledge, Castillo (2002) highlights the disparity that exists in the ideas that have been advanced by psychologists and management theorists, suggesting that researchers have stretched the boundaries of what can be considered tacit knowledge. Among his proposals to bring unity and clarity to the concept of tacit knowledge is a fourfold typology of tacit knowledge, in which such knowledge is classified as nonepistle, sociocultural, semantic, or sagacious. We adopt this typology in studying tacit knowledge acquisition from communities-of-practice and tacit knowledge transfer between virtual team members.
Theoretical Foundations and Research Model
Among Griffith et al.’s (2003) propositions are 1) More virtual teams will have greater access to communities-of-practice than will less virtual teams; and 2) Tacit knowledge from members’ links to communities-of-practice is less likely to be disseminated within more virtual teams than they are within less virtual teams. We slightly modify the first proposition by suggesting that members of more virtual teams will actually be involved to a greater extent with communities-of-practice than will members of less virtual teams. Furthermore, we include organizational mobile social networking between virtual team members as a moderating factor in the negative relationship between the extent of members’ involvement with communities-of-practice and the transfer of tacit knowledge between them (Figure 1).
Virtualness and Communities-of-Practice
While “virtualness” has been defined solely in terms of the extent of face-to-face contact among team members (Fiol & O’Connor, 2005), and while technological support and dispersion may not necessarily define virtual teams (Griffith & Neale, 2001), it is difficult to ignore the tendency of virtual teams to be geographically dispersed and dependent on technology. In fact, Griffith et al. (2003) define “virtualness” in part by geographic distance and technological support.
In an effort to avoid the extremes of “never” versus “always” meeting face-to-face, hybrid teams have been defined as those that combine face-to-face meetings with work done apart and supported by technology. These teams may consist of collocated members who rely on both face-to-face meetings and communication technologies, or of geographically-dispersed members who meet occasionally (Cousins et al., 2007). However, unless specific ratios of face-to-face work to work-done-apart are offered, one can argue that all teams are “hybrid.”
Given the pervasiveness of communications technologies, we suggest the avoidance of labelling teams as either “virtual,” “traditional,” or “hybrid.” Instead, we propose a conceptualization of all teams as falling somewhere along the continuum of “virtualness.” For the purposes of this study, we define a team as a group of individuals employed either by a single organization or by multiple organizations and who work together on a given set of tasks and towards a common goal, regardless of whether they are traditionally considered “collocated,” “virtual,” or “hybrid.”
We further define “virtualness” as a function of two variables: 1) the percentage of team contact using communications technologies; and 2) the percentage of team tasks performed in the absence of team members. (It is interesting to note that the greater the geographic and/or temporal dispersion amongst team members, the more likely the team is to score high on both measures. However, a team consisting of collocated members who rarely meet may also score high on “virtualness.”)
Communities-of-practice are those that develop when groups of practitioners have many opportunities for informal contact (Griffith et al., 2003). These communities focus on the sharing of relevant experiences which, once a level of personal intimacy develops (Leonard & Sensiper 1998) in an environment of frequent and intensive interaction (Nonaka & Takeuchi 1995), enables the transfer of tacit knowledge (Nambisan et al. 1999). In essence, a community-of-practice functions as a pseudo-team that acts as a substitute for the actual team.
Teams that score higher on “virtualness,” due of their lack of face-to-face communications and greater time spent apart on team tasks, can thus be expected to have greater involvement with local communities-of-practice, which we operationalized as the frequency of contact.
Hypothesis 1: The greater the percentage of contact between team members via communications technologies, the greater its members’ frequency of contact with communities-of-practice.
Hypothesis 2: The greater the percentage of time spent on team tasks in the absence of team members, the greater its members’ frequency of contact with communities-of-practice.
Communities-of-Practice and Tacit Knowledge Acquisition/Transfer
Explicit knowledge transfer is part of the function of communities-of-practice. However, tacit knowledge may well be transferred as members meet and discuss solutions to problems (Griffith & Sawyer, 2006). In fact, participation in communities-of-practice has been shown to have a positive effect on knowledge attainment, whether explicit or tacit (Griffith & Sawyer, 2006).
While tacit knowledge has become increasingly important to managerial and organizational studies (Polyani, 1966; Hennart, 1992; Kim & Hwang, 1992; Nonaka & Takeuchi, 1995; Folger & Truillo, 1999; Nonanka & von Krogh, 2009), there seems to be little consensus on the definition of tacit knowledge and whether or not it is measurable. Castillo (2002) offers a useful typology of tacit knowledge, classifying such knowledge into four categories: nonepistle tacit knowledge, sociocultural tacit knowledge, semantic tacit knowledge, and sagacious tacit knowledge. Of these, semantic and sociocultural tacit knowledge are of greatest relevance to this study.
Semantic tacit knowledge refers to knowledge that, “either because of special symbolism and/or possible distinctive behavior peculiar to the job, makes it unnecessary to mention such knowledge” (Castillo, 2002). In other words, this type of tacit knowledge consists of the specialized, but non-codified, communication of those in a particular field who understand the implicit meaning of each other’s abstract expressions, but who may not be members of a formal team.
Sociocultural tacit knowledge is knowledge that is not attributable to any individual but which belongs to the social/cultural systems that use this type of knowledge (Castillo, 2002). It is similar to Spender’s (1992; 1994) “collective tacit knowledge,” Cook and Brown’s (1999) “group tacit knowledge,” and Leonard and Sensiper’s (1998) idea of tacit knowledge that is developed, over time, in interactions among individuals who have been socialized into the group.
We suggest that semantic and sociocultural tacit knowledge is acquired by team members from their involvement with communities-of-practice. If increased contact with these communities-of-practice is coupled with decreased levels of face-to-face interaction with team members, we can expect that the tacit knowledge acquired from the communities-of-practice will be less likely to be transferred to other team members. Teams that spend less time together on task and make greater use of traditional technological tools will be more likely to transfer explicit knowledge than tacit knowledge because the technological tools support the declarative nature of explicit knowledge (Griffith et al., 2003).
If the tacit knowledge acquired by team members in their respective communities-of-practice differs from one community to another, we can also expect more conflict between team members in their interactions. This study thus conceptualizes the level of tacit knowledge transfer as a function of the level of conflict between team members: the higher the level of tacit knowledge transfer, the lower the level of conflict between team members; the lower the level of tacit knowledge transfer, the higher the level of conflict between team members. We operationalize team conflict as the individual team members’ perceived level of conflict between members.
Hypothesis 3: The greater the frequency of contact with communities-of-practice, the greater the members’ perceived level of conflict between team members.
Organizational Mobile Social Networking
Hundreds of millions of people today use social network sites (SNS) to meet, reconnect, and share content with others. Facebook alone boasts a half-billion users. Much of the research thus far on these sites has focused on privacy issues (Acquisti & Gross, 2006; Krasnova et al., 2010), social capital (Ellison et.al., 2006; Ellison et al., 2007), education (Mazer, et.al., 2007; Wankel, 2009), and uses and gratifications (Raacke & Bonds-Raacke, 2009; Joinson, 2008). The body of this research suggests that the primary reasons individuals use SNSs are to maintain pre-existing relationships. However, relatively little work has been done on the use of social networking within the organization, whether through a public SNS, such as Facebook, or through a private, organizational SNS.
In a series of studies on the use of Beehive, an SNS developed for use by IBM employees, the researchers found that among the most popular uses of the site were to get a better sense of co-workers (DiMicco et al., 2009) and to connect on a personal level with co-workers (DiMicco et al., 2008). In fact, the number one reason employees gave for using Beehive was that they enjoyed connecting socially with colleagues (DiMicco et al., 2008).
For members of teams that do not meet face-to-face on a regular basis, an SNS, such as Beehive, can serve as a medium through which the communication of those in a particular field who understand the implicit meaning of each other’s abstract expressions (semantic tacit knowledge) may flow. As the members connect with each other socially, they may also share knowledge that is developed, over time, in interactions among individuals who have been socialized into the group (sociocultural tacit knowledge). It is not unreasonable, then, to think that tacit knowledge acquired by team members from their respective communities-of-practice may be transferred to other team members through the use of an SNS. Additionally, with the proliferation of SNSs have come apps that allow members to leverage such sites through their mobile devices. The ability to connect with one’s team members on-the-go, anytime, anywhere, through status updates may serve to further facilitate the transfer of tacit knowledge.
We define organizational mobile social networking as the combined use of mobile devices (e.g. smartphones, tablet PCs) and an SNS (whether public or private) by organizational members to connect with each other. We anticipate that the frequency of mobile social networking between members of teams will lead to the transfer of tacit knowledge acquired from each member’s communities-of-practice to other members and thus moderate the relationship between the frequency of contact with such communities and the perceived level of conflict amongst team members.
Hypothesis 4: The frequency of mobile social networking between team members moderates the relationship between members’ frequency of contact with communities-of-practice and members’ perceived level of conflict amongst team members.
The above hypotheses form a model (Figure 2) that seeks to provide an understanding of how the “virtualness” of teams affects members’ acquisition of tacit knowledge from communities-of-practice, the transfer of such tacit knowledge to other team members, and effect of mobile social networking on this transfer.
References
Acquisti, A. & Gross, R. (2006). Imagined communities: awareness, information sharing and privacy on the Facebook. Paper presented at the 6th workshop on Privacy Enhancing Technology, Cambridge, England.
Berry, D.C. The problem of implicit knowledge. Expert Systems, 4(3), 1987, 144-150.
Castillo, J. A note on the concept of tacit knowledge. Journal of Management Inquiry, 11(1) 2002, 46-57.
Cook, S.D.N. & Brown, J.S. Bridging epistemologies: The generative dance between organizational knowledge and organizational knowing. Organization Science, 10(4), 1999, 381-400.
Cousins, K.C., Robey, D. & Zigurs, I. Managing strategic contradictions in hybrid teams. European Journal of Information System, 16, 2007, 460-478.
Deeter-Schmelz, D.R. & Ramsey, R.P. An investigation of team information processing in service teams: Exploring the link between teams and customers. Journal of the Academy of Marketing Science, 31(4), 2003, 409-424.
Dennis, A.R. Information exchange and use in group decision making: You can lead a group to information but you can’t make it think. MIS Quarterly, 20(4), 1996, 433-455.
DiMicco, J., Geyer, W., Millen, D.R., Dugan, C., and Brownholtz, B. (2009). People Sensemaking and Relationship Building on an Enterprise Social Networking Site. Proc. HICSS.
DiMicco, J., Millen, D.R., Geyer, W., Dugan, C., Brownholtz, B., and Muller, M. (2008). Motivations for Social Networking at Work. Proc CSCW.
Ellison, N., Heino, R., & Gibbs, J. (2006). Managing impressions online: self-presentation processes in the online dating environment. Journal of Computer-Mediated Communication, 11(2).
Ellison, N., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends”: social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication, 12(4).
Fiol, C.M. & O’Connor, E.J. Identification in face-to-face, hybrid, and pure virtual teams: Untangling the contradictions. Organization Science, 16(1), 2005, 19-32.
Folger, R. & Truillo, C.J. Theorizing as the thickness of thin abstraction. Academy of Management Review, 24(4), 1999, 742-758.
Friedman, T.L. The World is Flat: A Brief History of the 21st Century, Farrar, Straus and Giroux, NY, 2005.
Griffith, T.L. & Neale, M.A. Information processing in traditional, hybrid, and virtual teams: From nascent knowledge to transactive memory, in Research in Organizational Behavior (Volume 23), B.M. Staw and R.I. Sutton (eds.), JAI Press, Stamford, CT, 2001, 379-421.
Griffith, T.L., Sawyer, J.E. & Neale, M.A. Virtualness and knowledge in teams: Managing the love triangle of organizations, individuals, and information technology. MIS Quarterly, 27(2), 2003, 265-287.
Griffith, T.L. & Sawyer, J.E. Supporting technologies and organizational practices for the transfer of knowledge in virtual environments. Group Decision and Negotiation, 15, 2006, 407-423.
Hennart, J.F. The transaction costs theory of joint ventures: An empirical study of Japanese subsidiaries in the United States. Management Science, 37(4), 1992, 483-497.
Hollingshead, A.B. The rank-order effect in group decision making. Organizational Behavior Human Decision Processes, 68(3), 1996, 181-193.
Joinson, A.N. (2008). ‘Looking at’, ‘looking up’ or ‘keeping up with’ people? Motives and uses of Facebook. Computer Human Interactions Proceedings, Florence, Italy.
Kim, W.C. & Hwang, P. Global strategy and multinationals’ entry mode choice. Journal of International Business Studies, 23(1), 1992, 29-53.
Krasnova, H., Spiekermann, S., Koroleva, K., & Thomas Hildebrand, T. (2010). Online social networks: why we disclose. Journal of Information Technology, 25(2).
Leonard, D. & Sensiper, S. The role of tacit knowledge in group innovation. California Management Review, 40(3), 1998, 112-132.
Mazer, J., Murphy, R., & Simonds, C. (2007). I'll see you on Facebook: the effects of computer mediated communication on teacher-student communication. Communication Education, 56(1).
Nambisan, S., Agarwal, R. & Tanniru, M. Organizational mechanisms for enhancing user innovativeness in information technology. MIS Quarterly, 23(3), 1999, 365-395.
Nonaka, I. & Takeuchi, H. The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press, Oxford, UK, 1995.
Nonaka, I. & von Krogh, G. Tacit knowledge and knowledge conversion: Controversy and advancement in organizational knowledge creation theory. Organization Science, 20(3), 2009, 635-652.
Nunamaker, J.F., Reinig, B.A., & Briggs, R.O. Principle for effective virtual teamwork. Communications of the ACM, 52(4), 2009, 113-117.
Pascarella, P. Harnessing knowledge. Management Review, October, 1997, 37-40.
Polyani, M. The Tacit Dimension. Doubleday, New York, 1966.
Raacke, J. & Bonds-Raacke, J. (2008). MySpace and Facebook: applying the uses and gratifications theory to exploring friend-networking sites. CyberPsychology and Behavior, 11(2).
Reus, T. & Liu, Y. Rhyme and reason: Emotional capability and the performance of knowledge-intensive work groups. Human Performance, 17(2), 2004, 245-266.
Schultze, U. A confessional account of an ethnography about knowledge work. MIS Quarterly, 24(1), 2000, 3-41.
Siebdrat, F., Hoegl, M. & Ernst, H. How to manage virtual teams. Sloan Management Review, 50(4), 2009, 62-68.
Spender, J.C. Knowing, managing, and learning. Management Learning, 25(3), 1992, 387-412.
Spender, J.C. Organizational knowledge, collective practice and Penrose rents. International Business Review, 3(4), 1994, 353-367.
Spender, J.C. Making knowledge the basis of a dynamic theory of the firm. Strategic Management Journal, 17(Winter), 1996, 45-62.
Stasser, G. & Stewart, D.D. The discovery of hidden profiles by decision making groups: Solving a problem versus making a judgment. Journal of Personality and Social Psychology, 63, 1992, 426-434.
Stasser, G. & Titus, W. Pooling of unshared information in group decision making: Biased information sampling during discussion. Journal of Personality and Social Psychology, 48(6), 1985, 1467-1478.
Sternberg, R.J. Managerial intelligence: Why IQ isn’t enough. Journal of Management, 23(3), 1997, 475-493.
Strauss, S.G. Getting a clue: The effects of communication media and information distribution on participation and performance in computer-mediated and face-to-face groups. Small Group Research, 27(1), 1996, 115-142.
Wankel, C. (2009). Management education using social media. Organization Management Journal, 6(4).
Watson-Manheim, M.B., Chudoba, K.M. & Crowston, K. Discontinuities and continuities: a new way to understand virtual work. Information Technology & People, 15(3), 2002, 191-209.