The remainder of this chapter examines the role a community plays in explaining why people share knowledge in organizations. A brief review is provided of some of the key literature on communities within and outside the organizational context, followed by a discussion on how diverse and distributed interests may influence knowledge sharing in communities. Assuming that organizations are populated by people with dynamic rather than static interests, the chapter ends with an examination of how opportunity structures and the social norms of care and authenticity could have a positive impact on knowledge sharing.
The term ‘community’ is derived from a classical sociological premise that people form social bonds through shared norms, traditions, identity, and solidarity. Historically, the concept of community stands in contrast to society, where competition, individualism, and self-interest rule (Toennies, 1887; Durkheim, 1893; Weber, 1978). Communities have their own languages, rituals, norms, and values that can only be developed and refined over a long period of time. Members of a community develop a shared and deep sense of identity through intense and sustained communication. Interestingly, this deep sense of identity, and the traditions, solidarity, and long-standing norms that come with it, can create a binding commitment among community members to mobilize large-scale societal changes. Sociologists have noted that when people experience grievances, or entrepreneurs see opportunities for action, feelings of solidarity can bind them together in collective action (Calhoun, 1986, 1994; Cohen, 1985; Fantasia, 1988).
Building on a long tradition in sociology, anthropology, and economics, a growing number of authors have focused on the role of communities in knowledge sharing. For example, the literature on rural and peasant communities emphasizes how farmers and village inhabitants acquire the skills of productive farming without depleting natural resources. Through processes of socialization, the very subtle rules and skills of farming are transferred from one generation to the next (see Foster, 1965). Related to this, a very important stream of work on occupational communities has shown how people who practice similar work develop a shared identity related to their occupations. Shared identity and work practice enable mutual learning, as well as solidarity (e.g. Van Maanen and Barley, 1984; Orr, 1996).
The Internet has become increasingly important for communication within and between organizations. Another literature stream reports on the characteristics of virtual communities, where protecting the anonymity of individuals often takes precedence over membership selection on the basis of social categories such as occupation. Anonymity is not a trivial issue. It enables a free flow of information between community members; for example, individual sharing is not inhibited by the fear of possible future retaliation due to the contents of messages (Myers, 1994). Virtual communities typically exist because people share an interest in exchanging information and explicit knowledge on particular topics at low cost (e.g. Rheingold, 1993; Castells, 1996; see also Wasko and Faraj, 2005). Research on communities of interest has focused on groups that are topic as well as relationship based. However, in these communities, anonymity might be less pronounced than for virtual communities. Learning and exchange of information are central activities in communities of interest, and interactions are mostly limited to the personal needs of members to obtain explicit knowledge and information at low cost and high speed. Common engagement in work, such as joint projects and tasks, is rare (e.g. Amstrong and Hagel, 1995). Virtual and interest communities do not necessarily bind people together by occupation or socialization into a village, rural district, or peasant group.
In contrast, there is an interesting stream of work relating to ‘imagined communities.’ Here, people ‘imagine oneness’ with others whom they have neither met nor seen. The foundation of this solidarity is a set of simple, effective socially transmitted constructs, such as an area of expertise or nationality. Imagined communities can be powerful forces for large-scale social change (Anderson, 1983; Calhoun, 1991). Case studies of communities for knowledge-sharing have observed that people tend to identify with similar groups of experts throughout the organization, even though they have never met face to face. This identification, in turn, seems to impact positively helping behavior across organizational boundaries (von Krogh, Nonaka, and Ichijo, 1997). Work on micro-communities of knowledge has argued that collective identity is formed as people jointly engage and commit to processes of knowledge creation.
The most systematic exploration of communities in organizations can be found in the practice-based perspective on organizational learning (Wenger, 1998; Brown and Duguid, 1991; Lave and Wenger, 1991; Lave, 1988; Orr, 1996). These studies provide insight into the social fabric of communities, how they work, and the conditions that enable or constrain them. A community of practice is characterized by members who share work activities and engagement, work together over a certain period of time, and develop a shared identity, language, artifacts, norms, and values. Learning through imitation, observation, narration, and storytelling gives rise to shared knowledge.
Returning to our initial problem, although communities are interesting for understanding how individuals behave apolitically and altruistically (Wolin, 1961) and how knowledge and learning happen in social practices (Tsoukas, 1996), systematic attention must also be paid to the collective action problem of knowledge sharing that results from the distributed and diverse interests of the individuals who comprise these communities (For a critique of the practice-based view of organizational learning, see Yakhlef, 2010.) A community acts collectively without outside intervention from an agency. In this sense, it exists outside the organization (see Bennis et al., 1958), and is not regulated by formal structure and incentive mechanisms, control, and sanctions (Wenger, 1998). A community attracts people around common tasks, work, knowledge, and experience, as well as emotions such as liking and empathy. Also, a community has a certain stability of affiliation over time;13 it has multiple and direct relations between the actors (Taylor and Singleton, 1993), and there is some level of common information (cues) about other members’ knowledge. The negative returns to size apply; not all needs can be satisfied immediately in knowledge sharing. However, the community could be a resource for knowledge sharing because the satisfaction of needs is suspended and the natural sequence of activities well preserved. This point will be scrutinized more closely later.
A community is different than the production team (Alchian and Demsetz, 1972). The community is established, developed, and maintained by its affiliates in a manner of self-production. The production team to some extent relies on the agency that allocates a complex production task and external inputs, performs external monitoring of production output, and sanctions the team. Empirical evidence has shown that communities produce less collective action when outside agencies monitor community activities and appropriate resources (Schmitt, Swope, and Walker, 2000). Yet, communities and production teams face the same challenge of self-monitoring. Within the production team, members can observe each other and sanction internal processes. If interests and effort diverge strongly in the production team and the community, members and affiliates can sanction others; but in the production team, members can appeal to an outside agency and rely on it to take corrective and punishing action. However, as Osterloh and Frey argue, the problem is one of motivation and interests rather than agency function (2000). If knowledge to be shared is tacit, even self-monitoring can fail to produce the expected results. Also, tacit knowledge is shared if people are intrinsically motivated, but, as mentioned earlier, this in turn requires immediate need satisfaction related to tasks.
Because communities can be conducive to sharing knowledge, they can appropriately be termed resources (von Krogh, 2002; Spaeth et al., 2008).14 Taylor and Singleton (1993), basing their argument on Coase (1960), suggest that where the community displays a high degree of collective interests, it can lower social (transaction) costs (Coase, 1960; Taylor and Singleton, 1993). First, affiliates of a community have access to information (cues) about others’ knowledge. This is a resource because it reduces the affiliate’s costs of searching for knowledgeable people in the organization. This is particularly relevant for communities where people share work practices or some set of common tasks and problems (Wenger, 1998). Second, bargaining costs are lower in a community because beliefs, preferences, and interests are shared. Stable affiliations in a community make it easier to conclude agreements between individuals, and relations on many fronts make it easier for individuals to make trade-offs that compensate for differences in cooperative gains between the parties in question. Third, the level of shared interests, expectations of continued interaction, and direct and manifold relations among individuals all reduce the monitoring costs involved in enforcing compliance in knowledge-sharing. Here it is important to note the multiplex character of relationships. In a community where interests are shared, relationships are enduring, and affiliates have options for seeking out who they will share knowledge with, affiliates are likely to attempt to share their best knowledge, even when tacit. In the types of communities described by Taylor and Singleton, recurring interactions give precedence to collective interests over self-interest (e.g. group utility). This has been described as a process where the community gains its own collective identity (Stoecker, 1995).15
For the organization in question, reduced monitoring costs and no need for an agency could potentially make the community a valuable resource. As an example, for a functioning community, management does not have to design a formal system for knowledge-sharing, monitoring members’ behavior, and enforcing compliance with system procedures and rules. Knowledge-sharing happens due to the internal dynamics of the community and the gradual establishment of a collective identity (Kogut and Zander, 1996). The community also allows individuals to specialize and apply their knowledge to complex tasks within the firm (Grant, 1996). The community is also a resource because for many reasons—liking and emotion, deprivation, experience, etc.—it attracts individuals to identifiable social and virtual gatherings where people share interests, tasks, and knowledge.
Yet, the problem of knowledge-sharing is only partly resolved. As mentioned earlier, a common thread in the literature on communities within organizations seems to be that organizational members have a collective interest in sharing knowledge. In general, interests in organizations are very difficult to make meaningful, stable, and valid; and they are subject to constant bargaining and drift (March, 1962; Devine, 1999). Because communities comprise affiliates who are subject to changing work demands and conditions, an interesting dilemma arises. An organizational member may be accused of not being a responsible affiliate on the one hand, and of not being self-interested on the other (Hardin, 1968). In organizations that comprise communities, people are rewarded not only for sharing knowledge within the community, but also for being self-interested, rational, and free riding, in order to advance their career and improve their financial position (for related discussions, see Fife, 1977; McCay and Jentoft, 1998). In organizations where knowledge-sharing communities are explicitly fostered, supported by top management, and endowed with slack resources, this dilemma could potentially be powerful. A community consists of people with diverse and distributed interests, and it would be overly simplistic to assume that their individual interests would stabilize over time.
It follows from the discussion so far that the ‘community’ should not be defined by its level of shared interests, but rather by what we may call its evolutionary stability. In other words, the community is not a communal resource per se. Even if collective interests cannot be assumed, there is no reason to exclude the possibility of stable, multiplex, and direct relations between affiliates. Depending on the context of community interactions, an individual’s interests, namely motivational focus, definition of a situation, personal objectives, and guidelines for conduct, evolve over time. As Massey (1994) points out in her criticism of Taylor and Singleton (1993), some communities are more inauspicious for collective action because of these possible changes in people’s interests. Think of a community within the organization based on physical proximity, shared grievances, hobbies, or friendship, without much systematic knowledge sharing. For example, construction engineers might have strong friendships built around playing a game of cards at night, but might have very varied levels of interest in others’ technical know-how beyond this hobby, as well as rules of conduct, such as ‘no shop talk.’ Moreover, in some communities it might be difficult to start knowledge sharing, because of a wish to conform and avoid later retaliation and punishment for breaking the rules. Conversely, think of a vibrant and creative community, where affiliates’ diverse and distributed interests threaten the social fabric. The point of departure for defining a community should be to what extent it is able to maintain its community characteristics over time despite this diversity. For defining a communal resource, the start point is whether the community shares knowledge without the prerequisite of an agency to monitor and enforce cooperation.
So communities can be resources, or perhaps even liabilities, and there is a need to examine the conditions under which knowledge sharing can take place without the agency.16 There are at least three factors associated with knowledge sharing in the community: opportunity structures, care, and authenticity.
Opportunity structures
Opportunity structures refer to the benefits of sharing knowledge in the community and occasions for doing so. Since interest and knowledge are intimately connected, and since it takes more effort to identify sharing possibilities if affiliates have diverse interests (irrespective of community size), the opportunity structure of a community is a particularly important factor in the problem of knowledge sharing. The way opportunities present themselves to affiliates helps create structures for sharing relationships within the community. These structures hinge on factors such as individual and collective benefits of knowledge sharing; the cost of knowledge sharing; the sequence of knowledge-sharing activity; the history of sharing activities in the community; the search for sharing opportunities; affiliates’ diverse and distributed interests, knowledge, and experience; bargaining; and helping behavior. The community is an arena or, as Nonaka and Konno (1998) understand it, a number of ‘places,’ (Japanese: Ba) where affiliates can realize diverse interests over time as they see fit. Narrow opportunity structures imply that knowledge-sharing benefits can only be realized through a limited number of relationships with affiliates, sharing very specific knowledge at very specific times and places. In contrast, broad opportunity structures involve more relationships that share broader knowledge, in a continuous manner, and in several virtual and physical places (see Diemers, 2001). In other words, an opportunity structure can be within each affiliate’s immediate reach, both cognitively and manipulatively. Cognitively, individuals within the community can imagine their interests being realized through cooperation with others, and how this realization could happen. Manipulatively, individuals can take concrete action to meet physically or virtually with other community affiliates in order to realize these opportunities.
The concept of opportunity structures does not rely on affiliates having full knowledge of others’ knowledge; by our definition of knowledge this would be impossible. If this were the case, the social cost of monitoring compliance with knowledge sharing would not have been a problem. However, in his studies of the transfer of tacit knowledge involved in the design and manufacture of highly complex technologies, MacKenzie (1998) found that evoking an interest in sharing at a particular time and place needed only a cue about other affiliates’ capabilities. The cue is both a stimulus to perception and a hint about how to behave in certain circumstances. Typically, in a work community, people will observe someone who performs tasks with originality, high precision, speed, and diligence. This individual’s performance might be based on long-standing experience with the task. Other affiliates take cues from how the task is performed and how that performance differs from their own way of solving tasks (Dreyfus and Dreyfus, 1986).
Although cues about knowledge can elucidate opportunities for sharing, a lot of sharing is likely to be improvised in the community. It is this system of cues that Tilly (1999) referred to when he described a situation of collective action as ‘deep improvisation,’ where people do not necessarily follow predefined behavioral scripts (like in a wedding ceremony), but where strong social ties and a shared interpretation of cues allow people to improvise collectively (e.g. a jazz orchestra). A history of interaction among affiliates allows deeply improvised knowledge sharing within the community (see also Vendelo, 2009). People will send and interpret cues about when, where, and how knowledge sharing is appropriate. A wink, the wave of a hand, or a cough invites the apprentice into the master’s workspace. A shake of the head and a sigh urge affiliates to approach the master and learn what has gone wrong. A system of cues allows sharing in a community to proceed without unnecessary interruption. Individuals can coordinate the realizations of their interests at a particular time and place, for example, avoiding everyone intruding on each other’s activities all the time. In this sense there is a relationship between the system of cues in a community and social cost, both in terms of searching for knowledge and of bargaining about suitable times for sharing it. A system of cues is particularly useful for guiding the level, time, and type of interaction needed for sharing tacit knowledge, which must be shared on the fly. However, as Tilly (1999) underscores, collectively meaningful cues take a long time to evolve and learn, and easily mutate under conditions of discontinued interactions, for example, where turnover of group members is high.
In order to sustain collective knowledge sharing under adverse conditions, opportunity structures could rely less on a system of cues and deep improvisation, and more on behavioral rituals. In this case, the community will attempt to create a routine for its own knowledge sharing and expect everyone to engage in it. Such rituals could encompass the introduction of newcomers into the community, discussion platforms, weekly debriefs of tasks and activities, morning speeches and breakfast meetings, coffee breaks, trading posts, poster sessions, a ‘speaker’s corner’ where people can state what’s on their mind regarding the work of the community, and so on. However, rituals like these do not foster the spontaneous and impromptu realization of interests, and therefore might work better for sharing explicit rather than tacit knowledge.
Opportunity structures may be costly to identify and realize as the community grows in size. A large community will have an abundance of cues, more attempts at spontaneous sharing, and many rituals that serve the interests of powerful individuals. The community’s efforts to monitor free-riding can also be important for its ability to sustain knowledge sharing. Several solutions to the free-rider problem have been suggested, such as convincing participants that they are engaging in long-term cooperative relationships (Axelrod, 1984); convincing participants to contribute using their particular resources, skills, and interests at various points in the unfolding collective action, where a match is found with a particular task (Granovetter, 1978; Oliver, et. al, 1985); convincing individual contributors that the importance of ‘group fate’ outweighs the cost of contributing (Schwartz and Paul, 1992); and convincing participants with diverse interests that they can trade control and participation over a range of ends (Coleman, 1973). However, most contributions to the concept of collective action note that the free-rider problem can be overcome in the creation and deployment of selective incentives (Friedman and McAdam, 1992; Oliver, 1980).
Selective incentives can be both monetary (for example, a non-participation fine) and non-monetary and, all else being equal, free riding is better dealt with when the community is small enough for selective incentives to be used effectively. Selective incentives are either positive (reinforcing behavior) or negative (changing behavior) and they are directed not at the group as a whole, but to each individual within it (Olson, 1967: 43–52; Fireman and Gamson, 1979; Taylor and Singleton, 1993). Selective monitoring of individual efforts is easier in a small group where people meet and communicate face to face (Ostrom, 1998). It is important to consider how this plays out in the realization of opportunity structures through cues and rituals. First, common knowledge of cues takes time and might involve considerable investment on the part of the individual newcomer to the community. The community determines affiliation on the basis of how well the newcomer has learned to interpret the cues necessary for knowledge sharing (Tilly, 1999). It is unlikely that a potential free rider would make this investment to engage in knowledge sharing with such uncertain outcomes.17 Hence, there may be self-selection among extrinsically- and intrinsically-motivated people. Second, rituals give easier access to the community and formalize opportunity structures; the community could be expected to attempt to restrict its access to newcomers and deploy non-monetary selective incentives more strictly.
A typical immaterial selective incentive to mobilize people for collective action is membership of social categories (Friedman and McAdam, 1992; Tajfel, 1982). Empirical studies in sociology show that people tend to classify themselves and others in terms of cognitive categories (Turner, Brown, and Tajfel, 1979; Tajfel, 1982). Collective identity can be defined as
people’s sense of who they are in terms of some meaningful social category (e.g. occupational, gender, status, age, Community of Practice member, presence on the intranet, tech-clubs, etc.) that distinguishes how they interact with those inside from those outside the category
(Roy and Parker-Gwin, 1999).18
Larger ritual-based communities benefit by bestowing credentials on affiliates, based on their observed efforts and/or skills. Individuals derive utility from these credentials if they give privileged access to resources, knowledge, social relations, status reputation, and so on. Hence, a value can be assigned to the social category that will be affected by past and current community affiliation. The higher the category’s value in the mind of the affiliates, the more effective the non-monetary selective incentive.
In the larger community, opportunity structures tend to be less robust, since social relationships become increasingly scattered and ephemeral, and interests become more diverse. Therefore, the value of credentials might decrease with increasing community size (more people have access to scarce resources). Also, when the community increases in size, the impact of any individual’s participation in knowledge sharing is negligible, and a self-interested, rational individual will choose to free ride under those conditions (Hardin, 1968). The cost of an individual’s decision to free ride is spread over a greater number of people and the cost of organizing and using selective immaterial incentives to induce individual cooperation increases as well (Marwell and Oliver, 1988). It becomes even more costly for each group member to monitor and sanction others’ free-riding behavior. Eventually, as the group grows, monitoring costs outgrow sharing costs, and could jointly outweigh the rewards from knowledge sharing itself. In addition, the value of the social category could become depleted, making it less attractive for newcomers to join the community. The expected outcome is that the opportunity structure will be underprovided and the value of the communal resource will decrease.
Affiliates’ limited attention and cognition, and the cost of realizing knowledge sharing, make opportunity structures a constraint on the communal resource. As far as the practice of knowledge management is concerned, a popular way of facilitating knowledge sharing in many organizations is through so-called ‘technical share fairs’ or ‘knowledge fairs’ (e.g. Davenport and Prusak, 1998). These are large exhibitions held over several days where research and engineering teams, technical groups, and so on, can exhibit information about their projects, areas of expertise, and technical pursuits. Some will already belong to a community of technical specialists at a research site. Others will not be affiliated with any particular community, but will discover new opportunities for establishing a community and sharing knowledge. Through these fairs, organizations enlarge the opportunity structure for knowledge sharing. The fair might also contribute to the evolutionary stability of the community, whereby social relations are reinforced and new ones are created. However, in spite of the abundant opportunities such fairs offer, it is not at all clear whether individuals will coordinate knowledge sharing. A fair might simply be a pleasant break in a somewhat dull and repetitive workday. For sharing to be enabled in an evolutionary stable manner, the right social norms have to be in place.
Care
A non-monetary selective incentive would result from members creating and enforcing social norms (‘Thou shalt . . . Thou shalt not . . .’) that compel affiliates to knowledge sharing in a customary fashion (e.g. Heckatorn, 1993). When the number of believers in the social norm increases, affiliates derive utility from the conformity of behavior to the norm, both due to reputation in the community as well as the individual’s taste towards conformity (Hess, 1998). In effect, strong socialization and loyalty to the social norm could moderate free riding in the group (Ferre, 1982; Hirschman, 1970; Ostrom, 1999).
Care is a social norm in human relationships, and implies trust, active empathy, access to help, lenience in judgment, and the extent to which all of these are shared in the community (von Krogh, 1998).19 Care can entail concrete action in helping others but does not necessarily do so. Depending on the needs of the recipient, care can mean merely presence and intimacy, without action. Moreover, care is sufficient to induce helping in others (Egan, 1986). In caring for another, a care provider may give information and support for task execution, integrate an individual socially, give guidance, and enhance social bonds, as well as help to choose what output of task performance is to be presented to a larger audience. However, assisting is not necessary for care to be relationship quality (Mayeroff, 1971). As stressed throughout this chapter, organizations are populated with individuals who have different interests and personalities. The only requirement for care to be a social norm is for more than one individual, even the self-interested, to derive utility from complying with it.
Let us look more carefully at these four dimensions of care and how they relate to knowledge sharing. First, the more affiliates trust each other to share knowledge, the lower the social costs, as Taylor and Singleton (1994) mentioned (see also Nonaka and Takeuchi, 1995; Szulanski, 1996).20 Second, the more leniently people judge others’ knowledge, experience, and behavior, the more likely it is that diverse and distributed interests persist among affiliates in the community. Interaction can happen in spite of diverse interests; opportunities for knowledge sharing might emerge at a later point in time, when affiliates suspend their immediate realization of their own interests for the benefit of the community. Lenience also means that affiliates accept diverse rates of learning in the community. As we saw, learning rates may differ immensely among individuals, particularly for tacit knowledge, and a great deal of time can elapse before the giver realizes returns, if at all. In addition, newcomers into the community have to learn cues, especially where rituals are vague or absent. Lenience could be particularly important for integrating newcomers with different learning rates.
Active empathy, the third component of care, means that affiliates assess and understand others’ interests and needs. Empathy is the attempt to put one’s self in others’ shoes, understanding their particular situation, interests, skills levels, successes, failures, opportunities, and problems (von Krogh, Ichijo, and Nonaka, 2000). Active empathy is the proactive attempt by community affiliates to understand the interests of others observed in ongoing conversations in the community. It allows many different interests to co-exist over time, and should impact positively the learning and the use of subtle cues needed for the sharing of tacit knowledge.
Fourth, while active empathy prepares the ground for helping behavior, care in the community also has to develop into real and tangible help when necessary. In the relationship between master and apprentice, for instance, the master teaches the design of a tool, how to use it, how to maintain it, where to acquire it, and so on. The master shows by example what to do to reach good task performance, listens to the apprentice’s concerns and questions, and also extends a helping hand by being actively involved in the apprentice’s task performance. But this interest in helping can be accompanied by various levels of access to the helper. Help might be offered based on an affiliate’s own experience, by knowledge sharing, or simply by sharing the burden of the task, and learning together. As a social norm, care, through helping behavior, should moderate the free-rider problem in larger communities where knowledge sharing plays out as a deep improvisation rather than a ritual. Levels of trust and active empathy, as important as they are for knowledge sharing, may provide very vague information about people’s compliance with the social norm, their inclusion or exclusion from the community. However, levels of access to help and levels of help given can be directly observed. Hence, where opportunity structures are narrow due to individual affiliates’ lack of interest in helping, their future community status might be endangered; yet if helping matters to them, they are likely to change their behavior.
It was observed earlier that, in the communal resource, the natural sequence of the collective activities of (tacit) knowledge sharing must be preserved. When affiliates exhibit strong trust, active empathy toward each other, a strong inclination to help, as well as lenient judgment, this should have a positive impact on the suspended satisfaction of individual needs and the realization of interests. Imagine a community of engineers who have worked together for several years, all of whom know each other, and where there has been some stability in relations. Enter a young engineering school graduate. Some affiliates exhibit a high level of help toward the newcomer, trying to integrate this person into the community. The newcomer will have to learn cues, rituals, and behavior according to social norms. Some experienced engineers might also recollect some long-gone feelings from their own inauguration process, where an experienced person took the time to introduce the ‘subtle stuff’ of the community. Because of the engineers’ empathy with the newcomer, he or she is treated leniently. The newcomer gives no immediate learning feedback, so there is no immediate need satisfaction for the others from giving this help. Furthermore, without cues about the newcomer’s capabilities, there is no guarantee that he or she will be a valuable affiliate of the community in the future. Learning the secrets of engineering in this way, where the opportunities of sharing are found, based on cues about what experienced engineers are capable of doing, the newcomer will eventually contribute new methods and theories from his or her education. It is care that allows for evolutionary stability—that is, for the community to persist as a resource for knowledge sharing.
Authenticity
When interests are shared in the community, we can assume that the ‘best’ knowledge will be spread among affiliates. In the absence of self-interested people or free riders, there is no reason why people should hide important details about task performance, pass on false information, sub-optimal procedures, unwarranted lessons, etc. However, where interests are diverse and distributed, it is possible that the social norm ‘authenticity’ could have an impact on the community as a resource for knowledge sharing. Authenticity means that legitimate knowledge in the community is shared directly with the source in a way that ensures its genuineness, accuracy, validity, and reliability. The master–apprentice dynamic illustrates what this means. An apprentice observes the genuine know-how of the master first-hand. The accuracy of their shared knowledge depends on the apprentice’s ability to observe a certain level of detail in the master’s work. Validity, in turn, refers to the master’s and the apprentice’s mutual ability to appraise observations, interpretations, and understanding of task performance. Validity also refers to the extent to which knowledge shared with the apprentice can also be extended to similar or different tasks the apprentice has to perform. Reliable knowledge enables the apprentice to resolve repeated tasks. Reliability, in turn, depends on affiliates’ interests in applying shared knowledge in the collective action process. Hence, we have to revisit the system of social norms outlined thus far.
Care is a social norm from which people derive utility by giving. However, if care is the only norm in social relationships, the community might end up with more knowledge giving and limited collective knowledge sharing, or in other words, little learning and using. In the case of authenticity, people derive utility from searching out valid and genuine knowledge, but since sharing is a matter of collective action, people also derive utility from making this knowledge reliable by using it.
The best way to understand valuable authentic knowledge in the context of this chapter is to view it as cues about what others are capable of in terms of above-average performance in the community at large, in particular in a master–apprentice relationship. However, as mentioned, at one extreme communities can be self-preserving, conforming, retaliatory, and punitive, penalizing people who try to branch out and be inventive. Massey (1994) found that collective action is highly unlikely in groups with strong social norms and diverse interests, due to the social costs faced by individuals pursuing their own courses of action. Standing out in the crowd by proposing new ideas or criticizing the work of others could invite retaliation and exclusion from the social category (see also Hirschman, 1970).21 Further, a community might have affiliates who detest any new knowledge, even if the benefits are immediate and collective. Rejection could be warranted by the costs of bargaining about what is really ‘valuable’ knowledge, or the unlearning of previous lessons learned. Individual interests in rejecting new knowledge could quickly transform into a collective protest against any new idea that someone tries to introduce into the community. The well-known not-invented-here (NIH) syndrome is a good example of such behavior; people who have worked hard and long to achieve a certain level of task performance might find it extremely difficult to change routines that have proved successful in the past (Kluge, Stein, and Licht, 2001). Even though new knowledge can have a potentially significant impact on people’s task performance, those who would be in favor of trying the new way will withdraw their engagement in the process.
Perhaps NIH syndrome indeed results from a lack of authenticity. If authenticity is a social norm, the closeness of observation matters for the acceptance of new knowledge, and hence, new knowledge is best introduced by affiliates of the community. However, willingness to be taught by others is key to recognizing individual differences and accepting the new lessons as well. Furthermore, sharing depends on care among those with superior knowledge, and not necessarily collective interests associated with their knowledge, as in ‘If I learn from you, you might not want to learn much from me, except for the way I apply that knowledge.’
For example, the newcomer to the engineering community might find that in some areas of practice, it is worthwhile learning lessons from experienced engineers. However, there are new methods that are more productive and will enhance the performance of the whole community, such as the use of a computer aided design (CAD) system. The experienced engineer might take cues about the newcomer’s extraordinary and repeated ability to finish technical designs in a fraction of the time that it used to take. The newcomer may supply the other engineers with documents and manuals on the use of these systems. If care is strong, he might even personally teach the use of these systems to other engineers. In turn, some may take great interest in learning and using the newly shared knowledge. This sharing requires cues about capable behavior, and assumes that most community affiliates would be content to receive genuine, accurate, valid, and reliable solutions from those who have experience and insight. These experienced individuals in turn must be willing to share their experience with the new systems. This example underlines that interest in both teaching and learning is diffused widely in the community (among old timers as well as newcomers).
To summarize, communal resources are impacted by a community’s characteristics, including the degree to which affiliates’ interests are diverse and distributed. In particular, three factors taken together—opportunity structure, care, and authenticity—should impact knowledge sharing where interests are diverse and distributed. Opportunity structures here work as a constraint on knowledge sharing. As a social norm, care positively impacts affiliates’ ability to suspend the immediate satisfaction of needs and to search for opportunities, in spite of diverse interests. As a social norm, authenticity positively impacts affiliates’ ability to realize ‘better’ knowledge within opportunity structures, to learn, and to improve. For example, in a community where there are ample opportunities for knowledge sharing, affiliates trying to determine with whom they want to interact will search out cues about others who demonstrate superior knowledge related to their interests and tasks at hand. Care in relationships makes affiliates patient with respect to returns on the knowledge they share, and allows them to realize varied interests, learning speeds, and behavior. It is important to note that even if interests are shared, the community can be characterized by opportunity structures, care, and authenticity. However, the argument does not assume a priori collective interests in sharing knowledge among affiliates, although the more collective the interests, the more powerful the communal resource for solving the problem of the social costs involved in the sequential collective action of knowledge sharing.