2012 45th Hawaii International Conference on System Sciences

The Nature of Knowledge in the Social Media Age: Implications for Knowledge Management Models Jeff Hemsley The Information School University of Washington [email protected]

Robert M. Mason The Information School University of Washington [email protected]

Abstract

a re-examination of some of the key themes in and foundational concepts about knowledge management is justified given this new environment. Social media (SM) is viewed as the essential aspect of Enterprise 2.0 [38]. In our exploration of the impact of SM on knowledge management,1 we take a critical approach to a re-examination of the bases of many knowledge management systems (KMSs). Specifically, we consider three underlying themes: 1. Knowledge as a resource for the firm [22,31,32]. 2. Epistemology and the nature of knowledge [2]. 3. The “value chain” model of knowledge management [2,15]. Our approach is conceptual but grounded in empirical studies from other fields. We use viral information events as a means to improve our understanding of how the different components of SM interact to create a new knowledge ecosystem (KE) within which organizations must operate. To accomplish this, we analyze viral information events through the theoretical lenses of networks [11,21,59,60], diffusion [47], communication [14,18,54,58], and marketing [3,7,34]. Viral events illustrate not only the impact of individual media platforms but also how these platforms interact to change the KE landscape. Viral events reveal the roles of multiple social media tools at different points in the knowledge creation-dissemination process: a viral information event may be created (e.g. on YouTube), influenced (by blogs), disseminated and spread (social networks), and stored and acknowledged as part of history (wikis).

Social media comprise the set of tools that “enable people to connect, communicate, and collaborate,” and these tools include blogs, wikis and social network sites. This paper reviews the significance of these tools and explores how together they can result in instances of virality (e.g., viral videos). Using new insights on viral processes, we provide a critical review of epistemological perspectives and the conceptual foundations underlying knowledge management models. We conclude that the widespread use of social media creates a dynamic, recursive socio-technical information and knowledge sharing system, a knowledge ecosytem (KE). This KE requires both an expansion of our understanding of knowledge creation and substantial revisions to our approaches to enterprise knowledge management.

1. Introduction Founded February 4, 2004, Facebook declares that it is about “Giving people the power to share and make the world more open and connected” [63]. Facebook claims that over 500 million people worldwide are active users, with roughly half logging on daily [64]. Facebook is just one example of a set of Internet platforms referred to as social media. Social media tools allow people to develop and maintain social connections in new ways; collaborate with friends and strangers around the world; and self-publish as a way of sharing their knowledge with anyone who has a similar interest. Social media allows people to share content like videos (e.g., YouTube) and photos (e.g., Flickr); to maintain web logs (blogs); and to collaboratively coproduce knowledge (wikis). Finally, because of the way social media networks are structured, they may facilitate viral information events, such as viral tweets, or viral videos, in ways that were not possible before. We believe that social media has changed the knowledge ecosystem that organizations face, and that

978-0-7695-4525-7/12 $26.00 © 2012 IEEE DOI 10.1109/HICSS.2012.580

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For most of our discussions and analysis in this paper, we are comfortable with Wilson’s [62] view of knowledge, in which he argues that when discussing knowledge management one can normally can substitute the word information for knowledge without loss of meaning. However, as the title implies, we do believe that many of the foundational assumptions on which knowledge management systems (KMSs) models are based need to be reexamined.

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The contribution of our work is a synthesis of concepts and findings from other fields that reveals shortcomings in popular KM models. We characterize the current environment for KM as one in which organizations face a knowledge ecosystem that is dynamic, evolving, and not subject to direct control. In the next section we review important social media tools and recent research on viral information events. In section three we look at the three knowledge management themes mentioned above and discuss how certain aspects of social media may alter these models. In section four we discuss the implications of our work for practice and identify areas for further research.

2. New Social Media and Information Flow, Learning, and Knowledge Social media comprise the set of platforms that enable “people to connect, communicate, and collaborate” [28:44]. These tools include blogs, wikis and social network sites [6,28]. Two key aspect of any kind of social software are that 1) they allow for users to self-organize into social networks; 2) they support conversational interaction and social feedback that facilitates building trust and signaling reputation within a community [6]. In the first part of this section we briefly introduce blogs, wikis and social network sites because each has implications for knowledge management that we will discuss in subsequent sections of this paper. However, we are also interested in examining what highly visible phenomena like viral videos can tell us about information flows, learning and knowledge in social networks. Thus, the second part of this section will be devoted to viral events on social network sites.

2.1 Blogs, Wikis and Social Network Sites Blogs “are frequently updated websites where content (text, pictures, sound files, etc.) is posted on a regular basis and displayed in reverse chronological order” [48:1409]. They lack editorial oversight, but have “the potential to reach a very wide readership” [23:2]. Over time, bloggers with similar informational interests and identity tend to co-link to each other, which results in clusters of “communities of blogging practices” [48]. Also of interest to us is that in some cases, blogs have been implicated as a factor in driving virality, as in the case where political blogs post links to political videos [40,56]. A wiki is an information sharing website made up of interlinked webpages, collaboratively and incrementally developed and maintained by members of a group or the public at large [6,28]. Embedded in

the architecture of wikis are the assumptions that knowledge is not static, but emergent and that the whole is greater than the sum of its parts [6]. Occasionally viral events become part of the cultural and historical landscape as when the viral video “United Breaks Guitars” [13] was documented on Wikipedia [65]. Boyd and Ellison’s definition of social network sites is that they are “web-based services that allow individuals to (1) construct a public or semi-public profile within a bounded system, (2) articulate a list of other users with whom they share a connection, and (3) view and traverse their list of connections and those made by others within the system” [9:211]. Examples of social network sites are Facebook, Twitter, LinkedIn, and YouTube. All of these social media platforms (blogs, wikis and social network sites) work together to create a rich set of tools that allows users to find information and stay continuously connected to friends and people with whom they share interests. But there are three key aspects of social network sites that we believe are important for our discussion: 1) with the rise of mobile social software, typically on smart phones, people are continuously connected to their social networks [36], increasing the speed of dissemination; 2) when users post a message on a social network site, it is generally sent to everyone in their network simultaneously in what Walther et al., refer to as masspersonal communication [58:6] and Castells calls mass selfcommunication [14:55]; 3) sites such as Facebook facilitate the maintenance of larger numbers of weak ties [18] than users might otherwise have. Numerous authors have noted that weak ties are generally responsible for allowing messages to span holes in networks [8,11,47,58]. An important implication of these 3 aspects of social network sites is that people have the ability to broadcast messages, at any time, to people with whom they are both strongly and weakly connected. Messages that are picked up and forwarded multiple times, in a viral-like spread, can flash across digital social networks achieving a speed and reach that, while not at the same magnitude as mass media, were not feasible before online social networks. Additionally, it means that anyone participating in social network sites will likely have the opportunity to participate in, and possibly be influenced by, these viral events.

2.2 Viral Information One thing that social media has given us that did not exist a decade ago are viral videos, which, over the last few years, have been studied in political science literature [55,57], communications [4,19], and 3929 3891

information science [39,40]. Unfortunately, these authors provide no definition [4,19], or one that is vague. Even in a book specifically about YouTube and participatory culture, where the index lists 12 pages that mention viral, there is no useful definition [10]. And while scholars in marketing have been writing about viral word-of-mouth (WOM) since Jurvetson [29,30] coined the term in 1997, they have focused on strategies for “viral marketing” as opposed to the actual process of viral information diffusion [7,42,43]. Drawing on these fields, as well as the study of innovation diffusion [47], and work not yet published, we define virality as a WOM diffusion process wherein a message is actively forwarded from person to person, within and between multiple weakly linked personal networks, and marked by a period of geometric growth in the number of people who are exposed to the message. As we have defined it, virality has three core aspects: a WOM process that has speed and reach. To understand the speed of viral diffusion, we will draw on the Faberge Organic Shampoo commercial of the 1970’s. The commercial showed a woman saying she would tell two friends about the shampoo, and they would tell two friends and so on. The screen split each time to show the progression. This is a geometric progression that results from each single informed individual forwarding the message to two additional people. At first the number of people in a network who have been exposed to a message (informed) grows slowly (see thin dashed line in figure 1), but then speeds up. As the number of informed people grows, the number of uninformed decreases and the growth slows and tapers off. This process is analogous to pathogen epidemic models [5] and innovation diffusion [47].

Figure 1. Comparing WOM, viral & mass media diffusion But innovation, pathogens and information spread differently [26]. This is particularly true with sites like

Facebook and Twitter where people broadcast messages out to all of their followers simultaneously. This masspersonal broadcasting, coupled with the nature of WOM and mobile computing allowing for continuous connection, is what makes viral diffusion so fast. At its most simple, WOM entails forwarding a message from one person to another [7,34]. But when a person forwards a message as a post on their Facebook wall, or by tweeting it, they haven’t told two friends, they have told a hundred (or more) friends. And each those friends could tell a hundred, potentially reaching an audience of 10,000 people in just two steps. Certainly mass-media still reaches people faster since a single broadcast is seen simultaneously by its full audience (excepting when a broadcast is recorded or re-broadcast). Figure 1 illustrates this as a cumulative views plot that instantly reaches the maximum exposure then remain constant (heavy dashed line). A WOM process that never grew geometrically, but was none the less fairly popular, might show a roughly continuous cumulative growth (solid line). Viral messages are in-between. Even though they spread quickly, they still take some time to spread. In figure 1 the gray dashed line shows the slow start, followed by a geometric progression of growth, and finally a slowing as the network is saturated. Masspersonal communication is also responsible for the reach of viral information events. As before, a person’s post can simultaneously reach all of their friends. That potential, however, is rarely realized because people are selective when they post information [26]. Also, people selectively read, click, view or otherwise engage with the content that their friends post. Followers engage with posts for any number of reasons, one of which is related to the concept of “communicator utility,” which suggests that users may seek out content that provides them with conversation material [58]. Thus, person X may engage with person’s Y’s content for communicator utility in their relationship with Y. Also, people are often unaware of what all of their friends are interested in, particularly in the case of weak ties [21]. So a post from Y may unexpectedly be of interest to X. For whatever reason, the people who engage with and forward content do so because they are interested in the content or the person who posted the content. But a viral WOM spread “happens in the context of a specific situation and occasion,” [3:402]. This implies that WOM is a temporally bound event. Christakis and Fowler note that “the tendency to have several kinds of relationships (and sometimes many kinds of relationships with the same person) is called multiplexity,” and that since we live in these multiplex networks, “how scientists draw them depends on what types of relationships we are focused on [16:92].” In

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But Kozinets et al. note that in WOM diffusion, “messages and meanings do not flow unidirectionally but rather are exchanged among members of the consumer network” [34:73]. In their Network Coproduction Model, marketers must assume that consumers who forward messages in a WOM process “can be idiosyncratic, creative, and even resistant,” which results in those consumers becoming “coproducers of value and meaning” of marketing messages [34:72]. So while a network may be seeded with a message, that message and its meaning interact with, and are coproduced with, other members in the network. This implies that the further from the source it is, the more likely a message will be altered from its original state. In terms of virality then, where messages are actively transmitted from person to person, and where a network can be saturated in terms of individuals being exposed to the message, it is reasonable to assume that message fidelity, while not absolutely necessary, certainly assists in the process. This suggests that digital networks, where copy-paste and link forwarding can result in high message fidelity, are more likely to support viral information diffusion.

our case, the network we are interested in is the network created when people forward information in a temporally bound, contextually defined WOM process. Thus, a viral information event creates a temporally bound, self-organized, interest network where membership is based on an interest in the information content or an interest in being included in the interest network of others. So the reach that we are discussing refers to everyone with an interest in the content who can be connected to the interest network. Finally, the structure of friend networks in social network sites like Facebook also contributes to both the speed and reach of viral information events. Ellison, et al., find that undergraduates use Facebook to connect to existing friends (which likely includes strong tie friendships) but also that “Facebook enables individuals to maintain a larger set of weak ties” [18:137]. This suggests that a person’s Facebook friend list contains individuals with whom they have both strong and weak ties. Facebook thus gives users simultaneous masspersonal broadcasting access to a network that likely contains a higher ratio of weak to strong ties than their off-line network. A number of authors note that messages spread easier in strong tie holomophilous networks, but need weak heterophile links to span holes and reach farther out into the wider network [8,11,47,58]. If person X posts a message that is of interest to a subset of their followers, it will quickly and easily spread to those people who select it, both those who have strong and weak ties with X. At this stage, any of those who selected the message may opt to repost the content in their own networks. In the case of those people with strong ties to X, network overlap will reduce the reach of a reposted message, but increase the likelihood of saturating the poster’s personal network. In the case of the weak ties, a follower of X who reposts the message seeds their own personal network of strong and weak ties and the process may be replicated – local saturation of personal networks and bridging across structural holes. The result is a cascading spread from personal network to personal network. For a message to be a viral spread, and not simply a WOM spread, it must be forwarded by interested persons in multiple weakly linked personal networks. The reach of viral events means that people may be somewhat randomly exposed to ideas, information and other content that otherwise might never have reached them. If, as we discussed above, people self-select viral content based on interest, there is the further potential for latent ties to be strengthened along networks of shared interest. This means that viral events may develop, shape, and maintain interest specific knowledge networks.

3. New Social Media and Knowledge Management Themes Three interrelated themes are evident in knowledge management concepts and models: 1. The nature of knowledge as a resource of the enterprise, worthy of management in the same manner as other resources such as natural resources, human resources, and financial resources, and the successful management of this resource is a key to competitiveness [22,32,33]. 2. Epistemology and the nature of knowledge. Knowledge management systems (KMSs) are based on an explicit or assumed framework about the nature of knowledge, following the logic that if you’re going to manage “X,” you need to know something about “X” [2]. 3. A "value chain" model of knowledge management, assuming a flow of information and knowledge through creation, storage/access/sharing, and application [2,15]. Each step adds value to what has been produced before, working toward the goal of a decision or the creation of new knowledge. The role of a KMS is to improve the efficiency and effectiveness of each step and the overall process. In the paragraphs below, we examine these themes. We begin with the epistemology and nature of knowledge and explore how SM may challenge the assumptions on which many KMSs are built. We then

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critically review the value chain model on which many KMSs are based. We conclude with a short critical review of the nature of knowledge as a resource for the firm. In identifying these challenges, we also identify potential threats and opportunities for KMSs based on new understandings of what is possible in today's environment, one that has a rich variety of SM technologies and services.

3.1 Epistemology and the Nature of Knowledge Knowledge management models may take one of six different perspectives on the nature of knowledge and how it is created [2]: 1. Knowledge vis-à-vis data and information (knowledge pyramid) 2. Knowledge as State of Mind (knowledge is knowing and understanding) 3. Knowledge as Object (knowledge can be manipulated like other objects) 4. Knowledge as Process (the steps in applying expertise) 5. Knowledge as Access to information (a condition of being able to acquire information) 6. Knowledge as Capability (knowledge can influence action) We agree with Alavi and Leidner that each of these perspectives has value; none should be considered “right” or “wrong.” However, we note that a KMS typically will take one of these viewpoints (tacitly, if not explicitly expressed) as a foundation for its design and operation. This foundation provides a conceptual integrity to the design and a shared model by which participants understand their roles and the role of the KMS. Below we examine each perspective and conclude that each may continue to be valuable as a basis for conceptualizing and designing KMSs. However, some of the hidden assumptions that accompany these perspectives may not be valid—or at least as useful—in the context of today’s social media and knowledge management environment. Knowledge Pyramid. A classic epistemological perspective is one that is often called the knowledge pyramid [1]. At its simplest, this perspective posits that knowledge is built up from elements that come from sensing the environment. When these sensations (or measures) of the environment are quantified and put into a syntax that can be communicated, we say that we have data. As the data are collected and put into a systematic form, we have information. A collection of information in canonical form, perhaps accompanied by experience, becomes knowledge. The appropriate application of this knowledge to complex situations

(knowing what knowledge to apply in a given situation) may be termed wisdom. Tuomi suggests an inverted pyramid in which information actually follows from knowledge and data from information [52]. The argument is that without the knowledge and information, one would be unable to distinguish data from noise—prior knowledge is necessary to help “make sense of” the changes in sensory data, to know how to interpret information (see also Choo [15], who applies the same principle to the knowing organization). Jennex [27] has pointed out that there is value to considering the pyramid model and expanding the model to include information links that address Tuomi’s critique, turning the model into a dynamic, recursive model that evolves and responds to external stimuli and decisions (figure 3). Note that Jennex’s model explicitly includes social networks as external contributors to decisions at the boundary of each level, helping organizational leaders select what inputs (e.g., data or information) are salient and worthy of attention to contribute to organizational learning.

Figure 1. Jennex's pyramid model Organizations historically may have had more control over the consistency of the social networks that exist between levels. However, the “always on” nature of social media, along with the concept of multiplexity, where people engage in different roles depending on the context [54] (or what network they are engaged in), means the people in the social networks between levels are likely influenced both from inside and outside the organization. This has always been true, but social media magnifies the effect. Also, the effects of speed and reach discussed above implies that decision makers may be influenced from farther out in the network, more quickly and possibly less predictably, than before the advent of SM. Finally, wikis and blogs make finding information relevant to decision making nearly instantaneous.

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Knowledge as State of Mind. Knowledge is sometimes viewed as being either explicit or tacit. We prefer to think of knowledge as comprising both a tacit and an explicit dimension [31,44]. Knowledge requires both dimensions to be complete. The higher levels in these pyramid models (e.g., wisdom, knowledge), when applied at the lower levels (information, data), can be characterized as predominantly tacit—i.e., the knowledge need not be expressed explicitly, for example, when used to recognize patterns in data. Synthesizing the literature on knowledge, Alavi & Leidner [2] note that “Knowledge can also be viewed as existing in the individual or the collective” (see also Nonaka [41]). Individual knowledge is created by and exists in the individual whereas social knowledge is created by and inherent in the collective actions of a group. Nonaka and others [49,50,51] rely heavily on the tacit-explicit, individual-collective knowledge distinction, and SM affordances enable this distinction to be understood in new ways. For example, wikis support individual participation in and group knowledge production, and this coproduction process can make explicit more of the social knowledge. One of the assumptions behind the architecture of wikis is that knowledge is emergent, not static. The knowledge made available through wikis thus can be expected to be more fluid than in more fixed media and may be viewed as more current. Blogging also arguably contributes to an increase in the availability of knowledge. Hsu and Lin find that knowledge sharing for reasons of altruism and reputation building are positively related to attitudes bloggers have about blogging and their intention to continue to use blogs [25]. These observations about SM suggests that it has the potential to a) enable collective sense-making [61] and b) maintain a dynamic collective knowledge base that reflects changing definitions and cultural norms.

object is not assured as it moves through a complex network of SM platforms. Knowledge as Process. This perspective views knowledge as the application of expertise (know-what, know-how). From this perspective, KM emphasizes the flow of knowledge and the value-chain model of knowledge creation, sharing, and distributing knowledge. This perspective also underscores the value in the use of knowledge (i.e., the process of its application) rather than the level or stock of knowledge. The significance of SM in this viewpoint is that knowledge applications can be observed both from inside the organization and externally. The process of learning about and applying expertise is no longer limited to the operations and procedures that occur within the firm. With SM, the doors and windows of the firm are figuratively thrown wide, allowing twoway flows of knowledge (expertise). Knowledge “ownership” is threatened. Knowledge as Access to Information. Taking this perspective means that information technology (IT) has a very clear role in the design and operation of a KMS: IT is used to provide access, and it does this by assuring that information is available to whoever needs it, when they need it, in the format they need it. A good KMS provides ready access to reliable information. Two subtexts are implicit, however: 1) there is the expectation that KMS user is looking for particular information—that the user is searching for information to exploit in concrete ways, to take action or to make a decision, to create new information, etc.; 2) the information should be actionable (usable), so there is the underlying assumption that the user has a problem that information will help solve. By looking at viral information events we note that social network sites facilitate a wide reach into an extensive network. Question and answer features available on sites like Facebook and LinkedIn allow users to post questions (or answers) to their networks as a way to search for knowledge. Generally, as soon as someone in their network comments on (or ‘likes’) a posted question, the question is then also available to that person’s network, expanding the reach of the one posing the original query. On the other hand, viral events are unpredictable, and knowledge (or information that results in new knowledge) may become available at unpredictable times and through unpredictable channels as it is forwarded from user to user throughout the network. This provides a kind of enhanced serendipity and can stimulate innovation in receptive organizations. Also, as people forward content they often include their own

Knowledge as Object. From this perspective, knowledge is viewed as a level, a “stock” that can be stored (and leaked) and replenished. In this view (at least at the extreme), a KMS moves knowledge around—the metaphor is that of a container—as though the knowledge is inert and unaffected by the technology that is instrumental in its storage, access, and distribution. Wikis and blogs are more than platforms for storage—they enable sharing (and not simply publishing) information. Social networks and their potential for masspersonal communication means that once posted knowledge is forwarded, as in a document or a video, the poster of the knowledge can quickly lose control over the item as it is copied and forwarded throughout the network. The integrity of knowledge as 3933 3895

the knowledge base. However, Vandenbosch and Higgins showed that executives using an executive knowledge management system used the system for exploration (mental model building) as well [53]. SM can accelerate the movement of knowledge through the value chain, but this first-order impact may be less important than impacts on the notion of the value chain itself. SM opens the firm’s doors to knowledge and information access in ways not envisioned by KMS designers of a decade ago. As a consequence, knowledge creation can be facilitated: information can spread quickly through a much wider network of sources; viral videos demonstrate the potential for this rapid spread. In-house storage of knowledge may become less critical. Search tools (e.g., Google) and networking platforms (LinkedIn and Facebook) enable workers to get answers in a “just in time” approach to problem solving. The entire stage of storage/access/sharing and distribution of knowledge is open for new concepts. At the same time, the same SM affordances pose challenges for firms that strive to maintain close control over in-house proprietary knowledge.

comments, which may act as a framing for the message, alter its meaning, or provoke a different response in the recipient. Thus, the path that an item takes in digital networks may alter its meaning in subtle ways [46]. Knowledge as Capability. This perspective emphasizes the potential of knowledge to influence action. From this perspective, KM’s role is to support the organization’s development of core competencies and organizational and individual learning. To some extent, this viewpoint overlaps the knowledge as process view. Knowledge is viewed as supportive of the enterprise’s efforts to create and maintain core competencies. The increased information richness made possible by SM requires a new—or enhanced--enterprise competency. The firm must effectively recognize the salience of the information available through multiple channels and efficiently sort through the torrent of possibly relevant messages and communications. We can see a parallel to this this in virality where people send out what they think is interesting and people who are interested in it select it. WOM literature has confirmed that people are more likely to be influenced by people they know and to whom they have a personal connection [3,34,59].

3.3 Enterprise viz a viz Other levels Virtually every KMS takes the enterprise level viewpoint. The foundations for this viewpoint arise from the knowledge based view (KBV) of the firm. The KBV is attributed to Kogut and Zander [32], who argue that firms exist to create, transfer, and apply knowledge and information efficiently. Others have argued that a KBV provides strategic guidance, enabling a firm in a competitive and dynamic environment to arrange their internal activities to optimize their use of knowledge for competitive advantage and for growth [17,32]. Kogut and Zander [32] and others [22] who discuss strategy and the development of core competencies (e.g., Prahalad and Hamel [45]) acknowledge that knowledge management involves more than simply making knowledge accessible—they go beyond the notion of knowledge as a “store” or level. They recognize that knowledge is embedded in the routines, processes, and organizing principles by which people cooperate and work together within the firm. Within the firm, communities of practice [35], built around shared practices and mental models and founded on social capital that accumulates over time, enable the development of core competencies. Grant [22] goes further, identifying knowledge as the most strategically significant resource of the firm. Integration of specialized knowledge, he argues, not merely access to it, is the key to core competencies that enable the firm to succeed in a dynamic, competitive environment.

3.2 Linear Value Chain The linear value chain [2,15] can most easily be viewed as an articulation and expression of three perspectives of knowledge: as object, as process, and access to information. Within this theme, KMS address three major steps or stages: 1. Knowledge creation 2. Knowledge storage, access, sharing, and distribution 3. Knowledge application In a value chain model of KM, the KMS seeks to add value at each stage. In simple terms, the KMS designer looks for opportunities to apply information technologies to improve the effectiveness by which the organization creates, makes accessible, and applies knowledge, and the efficiency with which it can accomplish each of these. Early KMSs placed an emphasis on storage and providing access and less emphasis on the social and cultural aspects [37]. In more complex models, the KMS acknowledges the more subtle relationship among all three stages and seeks to integrate the overall process. Examples of these models include the boundary spanning model of Carlyle [12]. Most early models assumed that the objective of the KMS was to enable the exploitation of knowledge in 3934 3896

SM, by changing the information environment in which firms operate, requires that we re-think the sharp focus on the enterprise level. Firms are embedded in a web of information sources and knowledge assets, not only assets that reside within the corporate boundaries. Hedlund [24] anticipated our findings, pointing out that KM should be viewed in the context of a network and the individual, group, and inter-organizational levels in addition to the organization (enterprise) level, presaging the arguments we make that KM efforts must view the enterprise as linked to knowledge sources outside the organizational boundaries.

4. Discussion Social media platforms, by providing speed, reach, and dynamic connectivity, have created a complex knowledge ecosystem (KE). With the continuing growth of mobile social software, the issues explored in this paper will become even more salient. As technology and societies continue to coevolve, the dynamic KE can be a productive focus for researchers and practitioners. Our exploratory study is only the first step toward an understanding of the enabling processes that shape our future knowledge environment.

4.1. Implications for Practice Social networking sites facilitate an enhanced WOM process, like virality, where people “can be idiosyncratic, creative, and even resistant… coproducers of value and meaning” [34:72]. This coproduction of knowledge offers challenges and rewards for organizations, and organizations that acknowledge--even embrace—this aspect of the emerging knowledge ecosystem can create a competitive advantage. Historically workers have been immersed in the organizational culture only while at work. Social media enables workers to be immersed in the organization’s culture simultaneously with the culture and norms of other networks. Companies wishing to retain control over their knowledge (a resource view) often attempt to block sites such as Facebook, Twitter and YouTube, but these attempts are likely to inhibit innovation, knowledge seeking, and serendipitous connections and to create barriers to attracting and retaining younger workers. We believe that organizations that adhere to the paradigm of controlling knowledge will be at a competitive disadvantage to those organizations that learn how to exploit the benefits, and mitigate the uncertainties, of this new environment. For example, identifying salient knowledge in an information-rich

world may require developing methods of crowdsourcing.

4.2 Implications for Research Our exploratory study has been conceptual and has drawn on empirical studies from communication, marketing, diffusion, and network theory. Further empirical work directed toward knowledge management and social sense-making in this new KE is needed. Also of importance is an understanding how influential viral events may be. Note that Christakis and Fowler discuss a number of studies that suggest that while we may all be connected on average by six degrees of separation, we influence and are influenced only out to three degrees [16]. But viral videos easily reach further than three degrees. And since a video is passed by its link, it retains high message fidelity yet can be framed and annotated by those that pass it along. SM can extend our sphere of influence while simultaneously enabling coproduction of meaning. We would like to know if the theorized pattern of virality and network saturation scales to the macro level. That is, can we observe the saturation of a local network X, which then bridges (and then saturates) network Y, etc. Gidden’s [20] structuration theory offers a rich theoretical lens for understanding the social implications of this new dynamic networked coproduction environment. Giddens sees structures and systems as evolving and mutating under a process of structuration. The dual nature of structuration constrains and enables people’s actions, and is reconstituted or altered by their actions. When people behave according to a system’s norms it recursively reconstitutes the structure. When they do not, slippages in the structure occur which feed back into the system. Generally, social change is slow, and slippages in the structure are exceedingly small. However, the speed, reach, and interconnectedness of SM—and the occurrence of viral events—may accelerate the structuration processes. If we accept the view that knowledge is a state of mind that exists in individuals or groups, the same argument may hold. Knowledge recursively created and maintained in structuration processes may now be accelerated by SM and viral events.

5. Conclusion This paper has investigated the question of how social media may change how organizations think about knowledge, knowledge management, and knowledge management systems. Our approach, a qualitative Gedankenexperiment, was conceptual, yet 3935 3897

grounded in empirical studies from other fields. Specifically, we used analyses of viral information events as a means to reveal the roles of multiple social media tools in the knowledge creation-dissemination process. Our findings illustrate how SM platforms interact to create a new knowledge ecosystem (KE) within which organizations must operate. We conclude that the concept of a dynamic, evolving KE requires that we expand our perspective on knowledge creation and make substantial revisions to our approaches to enterprise knowledge management. A key implication is that organizations adhering to the older paradigm of attempting to control knowledge will be at a competitive disadvantage to organizations that learn how to exploit the benefits and mitigate the uncertainties in this emergent environment. Our exploratory analyses of the impact of SM on KM have been based on concepts and theory grounded in empirical work from other fields. Our study suggests that further empirical research would be rewarding. Of special interest would be an investigation into whether or not the reach of viral events extends beyond the three degree limit of influence suggested by previous researchers [16]. We also suggest that structuration theory, with its focus on networked coproduction of knowledge and meaning may be an especially fruitful approach to understand the dynamic interplay among SM platforms, knowledge, and networks.

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