3.1 INTRODUCTION

This chapter continues the investigation of some of the key issues and debates in knowledge management (KM), which, it is claimed, have an absolute impact on what is managed and measured, what is researched, and what is theorized. Key points drawn in the previous chapter suggest that how an organization defines itself, or conceptualizes itself to use a broader term of reference, influences how it approaches the management of its knowledge. It is also concluded that, while many continue to emphasize the role of technology, now cast as a defining marker, too much emphasis in these directions is implicated in KM failure. This is an issue that is particularly highlighted in the following discussions. On a positive note, there is a pragmatic case to be made for KM being more than just a passing management fad.

The chapter begins with a consideration of the “commodification and reification” issue. This leads into issues around KM’s reported high rates of failure. As it turns out, the difficulty in the measurement of KM failure or success is itself identified as a failure factor. With a brief pause to consider the role of culture themed around the question of whether “one size fits all,” the discussions move onto a discussion of two of the most significant debates in KM, namely, creating and sharing knowledge. Again, as we have already seen elsewhere, what we find is a multiplicity of perspective and approach. The subject of “knowledge sharing” (KS) is of particular interest given that it represents a more practical focus of study as opposed to, for instance, new knowledge creating. Consequently, we highlight some of the key factors reported in the literature as influencing, in some way, KS practices. These factors collectively establish some early and novel directions for the research which forms the central topic of Part Two.

3.2 THE COMMODIFICATION AND REIFICATION OF KNOWLEDGE

A significant feature of the traditional perspectives on KM is the commodification and reification of knowledge. The field is largely split on its views on this issue with some claiming that it leads to poor practice, while others see it as a business opportunity. For instance, Professor Linda Smith of the University of Auckland, in her paper on researching ethnic minorities, concludes somewhat pessimistically that far from being inspired by the pursuit of knowledge, the knowledge economy has the goal of turning knowledge into a commodity, which is perhaps inappropriately referred to as “knowledge creating.” As if to evidence her point, Kazuo Ichijo of Hitotsubashi University, a colleague of Nonaka’s, defines KM as the process of sharing, creating, protecting, and discarding knowledge: this arguably constructs it as an object of value to be traded and leveraged. But where does this notion come from?

An early clue is found in writer, professor, and management consultant Peter Drucker’s visionary paper on the nature of future organizations. He predicts that an organization of 20 years hence would have fewer tiers of management, relying instead on “knowledge workers” who would be seen as specialists. It is difficult to work out which year Drucker had in mind, as while the paper was originally published in 1988, this version is taken from a 1998 publication, and there is no evidence to support any variation, or not, between versions. He was either, then, referring to 2008 or 2018. The reader may be the judge of whether his prediction finds an echo in the modern organization’s environment. On this note, from a modern perspective, Drucker rather quaintly draws positive synergies between this future organization and the workings of the Indian Raj and UK’s National Health Service. The latter is frequently painted by the UK media as being on the verge of total collapse.¹ As well as being among the first to introduce the notion of the “knowledge worker,” Drucker also gives a radical definition of knowledge:

Information is data endowed with relevance and purpose. Converting data into information thus requires knowledge. And knowledge, by definition, is specialized.

(1998a: 5)

It is the latter statement coupled with the notion of specialist knowledge workers that perhaps unintentionally set the commodification of knowledge in motion. In Drucker’s vision, workers are the ones who will do the majority of work, and they will do this because they are specialist. Moreover, specialists are needed by the transformation that technology—principally IT—is bringing to the workplace. One interpretation of Drucker’s vision suggests that it is the knowledge specialists who are the “commodity” rather than the knowledge that they possess. A “devil’s advocate” might argue, however, that it was Sir Francis Bacon (1561–1626) who laid the foundation stone for the commodification of knowledge when he allegedly described it as “power.”

By the mid-1990s, the commodification of knowledge had become deeply entrenched, which is consistent with the chronology of development referenced in Chapter 1. Knowledge had become labeled as the essential feature of the successful company, linked to innovation abilities and capabilities, competitive edge, and indeed just about any other positive attribute of an organization that one can think of. As Spender and Grant summarize, knowledge had become acknowledged as the main source of “economic rent,” and its management had become a major force in business thinking.

If a product can be a commodity with a value, does it necessarily follow that it must be seen as an object? Not necessarily: it is more tied to how the product is treated. In their study of the role and importance of context to knowledge, Mark Thompson and his colleague are particularly critical of Nonaka’s approach to knowledge, which, in their opinion, reifies it as an object. This is arguably a point of interpretation as Nonaka does not make a direct reference to the reification of knowledge. The implication of “reification” mainly emerges because of the knowledge conversion process that lies at the heart of his SECI model. This is explored in greater detail in Chapter 4.

Another way in which knowledge has been commodified and reified is through the emphasis on technology. There are countless critics of the brand of KM which lays too much before the altar of ICT and IT. As noted elsewhere, there has been a recent shift of emphasis toward a “softer” view of KM, mainly stemming from the turn to knowledge as social action. But it would be redundant to insist that technology plays no part in KM. Indeed not only do many credit technologies as major drivers behind KM (as seen in Chapter 2), but technology is today a ubiquitous, vital, and embedded part of most organizations.

Ironically, alongside these ideas and arguments over the commodification and reification of knowledge, against a backdrop of general agreement over its importance to organizational success, there are ongoing questions over KM’s future. Have Grover and Davenport been proven correct when they predicted that KM, if it realizes its full potential, should eventually become so embedded in the organization that it is all but invisible. Invisible or simply not there? This leads to a review of successes and failures.

3.3 DETERMINING SUCCESS OR FAILURE

In their review of the historical and contemporary developments in KM, Laurence Prusak and his colleague conclude that around 50% of the initial KM implementations in organizations failed for a variety of reasons: too much emphasis on technology, a failure to link KM initiatives to organizational strategy, a one-size-fits-all approach, and, of particular interest here, a lack of focus on the social aspects of trust and relationships. This finding, while drawing on no more than anecdotes and references to other literature, is consistent with the period in which knowledge is predominantly seen as a commodity. Their final point will also be shown to have some gravitas based on the research reported in Part Two. Incidentally, Prusak and Weiss do not specify how they define “failure.” Building on Prusak and his colleague’s initial point, researcher Rosina Weber notes 15 failure factors in her literature review focusing on repository-based KM approaches: she concludes that attempts to build a “monolithic organizational memory” are doomed. Based on her analysis, she cautions against approaching technology as the “silver bullet.”

A particularly fascinating case study of “KM failure” is reported by Ashley Braganza of the UK’s Cranfield School of Management and his colleague, featuring US pharmaceutical giant PharmaCorp. This case study was touched on in the previous chapter in the discussions around technology as a “defining push factor.” In the mid-1990s, the company’s top executives took the decision to implement a KM initiative in the face of what were seen as growing problems with order handling operations. The initiative was given the highest priority, full funding, direct reporting access to the board, and a high profile within the organization. Yet within a couple of years, the project was deemed to have failed, and the KM team shut down. Why?

Braganza and his coworker draw out a number of lessons (which should be mandatory reading for any KM initiative leader), but perhaps the most interesting center around a failure to link the initiative to the everyday jobs that people do, the poor and unmaintained nature of “knowledge” stored in IT repositories, the transition from an “informal” KM project team to a formal “business line,” as well as the “turf wars” that broke out between the KM team and the IT teams. But perhaps most significant of all is that this KM initiative was entirely dependent on the introduction of new seamless IT throughout the business: this was never delivered. From a simplistic perspective, that is the responsibility of the IT department. Without its plank, the KM initiative, as strategically envisioned, could not work. Yet it was the KM team that took the “wrap.”

The lesson learned here is that when KM failure is reportedly blamed on an overreliance on IT, it is worth reflecting on whether that is because it was strategically misdirected or whether its tactical foundation failed to materialize. This conclusion finds support in other studies, particularly where KM initiatives are solely focused on ICT projects. Another example is a research project that investigated the use of a custom-built “Wiki” as a KS environment for academic researchers. Despite the academics’ involvement in its design, and stated intentions to use it, the Wiki failed over time through lack of use. The researchers unpick the reasons, finding that lack of time and inertia are key factors resulting in low contributor rates and visit duration. Elsewhere, researchers investigate how Chinese culture affects KM practices, finding that a company website established as a formal KS platform attracted little use. In fact, most of the contributors to their study were not even aware of its existence. Note, though, that both of these studies use participant interviews as part of their research data and these, as noted in Chapter 1, are potentially susceptible to researcher bias.

Harvard Business School Professor David Garvin, in his critical focus on learning and knowledge-creating organizations, offers a rather unique perspective on failure. Claiming that there have been more failed programs than successes, which is largely consistent with other findings, Garvin suggests that it is the scholars with their “near mystical terminology” who are largely to blame for this failure. They have been too quick to jump on “…the bandwagon, beating the drum for ‘learning organizations’ and knowledge-creating companies” (1998 : 49). (Interestingly, in the same collection of edited papers, another contributor pins the blame on consultants who, the authors imply, will sell your secrets to other firms!) Too much emphasis has been placed on knowledge creation, Garvin claims, and not enough on its application. More recently, research has shown a KM failure rate of up to 70%. Ilkka Virtanen of the University of Tampere in Finland bluntly ascribes KM failure as due to popular theories of KM being simply wrong. This suggests that in the near two decades since Garvin pinned the blame on scholars, little has changed.

A further explanation for KM failure is arguably due to traditional thinking. In their review of the field, Angela Burford and colleagues find that organizations ingrained in traditional thinking (or as Vincent Barabba and his coworkers describe it, industrial-age thinking) have a tendency to objectify knowledge (in one organization, the “knowledge repository” became known as the “information junkyard”) and to force the establishment of communities of practice rather than allowing these to emerge ecologically. Interestingly, Nonaka refers to the informal community as the location of emergent knowledge and new ideas, but then proposes that, because these are so important, they should be related to the formal hierarchical structure of an organization. This should surely lead to a formalization of these communities, which is precisely what Burford and her colleagues suggest leads to failure.

To round off the catalogue of failure factors, other studies have concluded that the lack of a KM culture, limited top management commitment and lack of supportive leadership, resistance to change, lack of worker involvement, and poor usability of KM systems are all implicated. With direct reference to the popular Theory of the Knowledge-Creating Firm, a report by Kenneth Grant and his coworker concludes that initiatives designed to convert tacit to explicit knowledge are equally likely to fail.

All of this paints a fairly depressing picture of KM and the jobs of KM practitioners. However, there is an important mitigating factor. This evidence is drawn from a wide range of studies, many of which can be criticized in, for instance, their use of secondhand data (e.g., case studies drawn from the literature). This raises the implication of interpreting someone else’s interpretation, with who knows how many layers of interpretation underlying the latter. Additionally, case studies are often presented without dates raising the possibility that the researchers’ conclusions are based on old data. The upshot is that for each reported failure, one could probably produce a success story. It is also worth raising the issue of motivation to report success or failure: typically one would expect scholars in particular to be more likely to report success rather than failure, but there is a suggestion here that the opposite is the case. The field could consequently be skewed.

Despite these points, a broad conclusion that can be drawn is that early KM initiatives were not entirely successful perhaps largely because organizations latched onto the tangible, digestible, measurable features of KM such as the introduction of new ICT. But what of measurement: the apparent inability to show measurable benefits is itself indicated as a failure factor, something that I picked up in a previous study of a KM managers’ discussion forum in which practitioners’ concerns are contrasted with key questions in the KM academic field.

3.4 MEASURING KNOWLEDGE MANAGEMENT OUTCOMES

Very little exists, certainly in the academic literature, in terms of robust and tested methods for measuring the success or failure of KM initiatives. This is not surprising given the difficulties over definition: if the subject of measurement is not well specified, how can it be measured?

This is further compounded when one considers the multiplicity of perspective on what exactly constitutes KM. An intriguing exception is offered by Jenny Darroch of the University of Otago in New Zealand: she claims to be the first to develop a scale for measuring KM behaviors and practices. This, she suggests, will help in the development of a theory of KM. The scale is specifically developed to measure behaviors in knowledge acquisition, dissemination, and responsiveness (use), and has allegedly been subject to rigorous development and validity testing. In the apparent absence of any other similar scale, this particular work stands out uniquely as a scientifically based, psychologically orientated empirical work. A point to note though is that while she makes much of the definition of KM, she does not discuss or define its product.

Taking a different approach, another exception involves measuring five organizational factors—strategy, people/HRM, IT, quality, and marketing—deemed to be critical to effective KM. In a review of the literature, the report finds that motivation and reward have notable impacts on KM and that an environment that facilitates trust is essential. This study by Pieris Chourides and colleagues at the University of Derby, England, uses surveys and interviews limited to private sector firms, finding little hard evidence to back the perception that KM leads to improved performance, claiming that performance measures are not well developed. Additionally, they emphasize the need to be able to demonstrate unambiguous links between KM and the “bottom line.” The idea of KM leading to improved performance as being little more than a perception finds support in a more recent study by Ragab and his colleague. Their review of work in the field concludes that while a causal link between KM and performance is widely proposed, there is little research that would evidence this. Secondly, they speculate that the impetus for KM measurement emanates from the “billions” spent on its activities, and thirdly, based on their analysis of some 350 published works, they conclude that there is as yet no convincing method of measuring performance, echoing the conclusion of Chourides and his colleagues.

This difficulty in measuring KM impacts and outcomes is a point of ongoing debate, arguably underlined by the problems with knowledge and KM definition, but is also suggestive of an apparently enormous amount of belief in a business practice with limited evidence of its ability to deliver.

3.5 KNOWLEDGE MANAGEMENT AND CULTURE

The theme of culture is discussed in more detail in subsequent chapters, so here the sides of the debate are positioned in overview. The principal question concerns whether “one size can fit all.” Can a framework or theory and its associated practice that is allegedly shown to work in, for instance, a Japanese culture, transmit, translate, and operate effectively in other cultures? However, the question is further complicated in that it is not just concerned with national culture but also organizational culture, even culture at the level of group. Thus, the notion of “culture” can be understood to refer to societal culture in its wider meaning of “context” (see also Section 1.4). A number of research studies provide some interesting and illuminating findings relevant to the “one size” question.

A recent empirical study that focuses on how Chinese national cultural factors influence KM practice in high-tech firms concludes that factors such as fear of losing face, hierarchy consciousness, and preference for face-to-face communications result in a general tendency to keep knowledge implicit but with a willingness to share informally. Arguably, one would find the same outcomes in Western firms but for different reasons. A study of Korean organizations similarly finds that cultural factors influence KM outcomes—in this case, intentions to share knowledge.

Others have investigated organizational factors on KM practice and outcomes. A study of 111 Spanish firms finds that organizational culture, leadership, and human resource practices affect KM practices on innovation outcomes. In his theoretical piece, Rajnish Kumar Rai of the Indian Institute of Management argues that organizational culture is critical in building and reinforcing new knowledge but admits that little is known about how this works. In their fascinating and revealing comparison of the effects of US and Korean culture on a single multinational, Yoo and Torrey perhaps unsurprisingly find major differences in KS behaviors between the two: Koreans tend to share knowledge in informal settings, while their American counterparts perceive their (formal) KM IT system as their primary vehicle for KS.

The results of these and other studies suggest that a one-size-fits-all approach will simply not work. Organizations vary considerably in structure, scope, culture—not forgetting language—and many other aspects such that a standardized approach will not deliver the desired KM outcomes. William Starbuck of Stern School of Business, New York University, makes a very good point when he reasons that organizations are not going to achieve the outstanding success and competitive edge that they seek by adopting a “one size” approach in attempting to copy the “properties” of others. Developing this perspective, innovative organizations are, by default, unique systems that emerge, evolve, and metamorphose as a consequence of their people, their products, their suppliers and partners, their markets, their temporal and geographic qualities, and so forth.

Culture understood in the wider sense of “context” influences KM and its outcomes on at least three interrelated levels: group, organizational, and national. From a psychological perspective, there is a fourth even more complex layer to this based on the theory of individual differences and social relationships, an idea touched on in a previous chapter (Section 1.3). In social psychology, mainstream research in the study of personality places considerable emphasis on measuring individual differences (e.g., variation in anxiety levels in response to tests) and the relationships between these. JC Spender hints at such differences when, drawing on Kant, he claims that knowledge is formed from individual sensory impression, implying its uniqueness to the individual rather than constituting some universally shared truth about the world out there. It is the subject of creating new knowledge that is turned to next.

3.6 CREATING NEW KNOWLEDGE

According to Peter Drucker, new knowledge is the superstar of entrepreneurship, a concept that would be difficult to challenge. In fact, the importance of new knowledge and its role in achieving and maintaining organizational competitive edge and in leveraging innovation—even allowing for the debates over its definition and substance—are generally accepted. The ongoing debate in the KM literature concerns the “how” based on an interpretation of the “what.” Chapter 1 has already discussed issues around knowledge from a definitional standpoint and will, in subsequent chapters, go on to consider it from a theoretical one. Here, the concept of new knowledge creation is considered from a learning perspective.

Two assumptions can be drawn out from the KM literature (albeit themselves the subjects of debate). First, that new knowledge is generally created in social interaction between people with “social interaction” understood in the broadest sense. Second, the creation of new knowledge involves a learning process although the learning aspect of new knowledge in particular is underrated in the field of KM according to Max Boisot and others. For instance, John Seely Brown and his colleague, while emphasizing the role and importance of organizational communities of practice and the social nature of knowledge, make no reference to the learning process. It is also on these grounds that some scholars criticize Nonaka’s theory of the knowledge-creating firm. More specifically, Frank Blackler draws attention to Nonaka’s distinction between knowledge and learning that he considers a mistake. Similarly, by implication, David Garvin distinguishes between learning organizations and knowledge-creating companies, claiming that too much emphasis is placed on knowledge creating at the expense of knowledge application (with the inference that this application refers to learning). By contrast, one of the few empirical studies to focus specifically on organizational learning culture, involving 120 firms, finds that a learning culture positively affects knowledge process capabilities (defined as the capability to acquire knowledge, convert it, apply, and protect it).

Harvard scholar Dorothy Leonard, in her discussion on knowledge transfer, emphasizes the role of active learning through guided practice, observation, and problem solving. Her fundamental argument is that when knowledge is transferred from one person to another, it rarely remains identical to its original as the knowledge becomes mapped to the recipient’s preexisting internal store of knowledge, experience, categories, and concepts. Thus, transferred knowledge effectively becomes new—and unique—knowledge to the recipient. It also implies that any transferred knowledge is in effect new knowledge to the recipient—even if the recipient “thinks he/she already knows it.” People interpret data in different ways (data also being understood as “stimulus” and again invoking the notion of “individual differences”), according to Max Boisot. From this perspective, he claims that knowledge creation can be likened to problem solving through hypothesis testing and that this is fundamentally a learning process.

As a comparison, the learning process can be considered from the psychological perspective. Learning is structured as a subset of human memory that has been the subject of scientific study for more than a century. According to the psychologist Endel Tulving, memory is the ability to acquire, store, and use knowledge or information. Although memory is closely related to learning, Tulving differentiates between the two cognitive functions on the assumption that learning deals only with the first stage of memory—acquisition. One could argue that the differentiation is more complex than this: learning could be associated with retention and use of knowledge. Tulving, however, is referring to the cognitive process of learning as the stage of acquisition in what is otherwise formulated as a highly complex mental mechanism and process. As it stands, the process by which new knowledge (concepts) is learned is poorly understood. Nonetheless, considerable research in this field suggests that it is an individual’s personal store of knowledge about the world, coupled with the predictability of language that is essential to making sense of the environment, that fuels the process of generating new knowledge. This is an important conjunction of concepts, which is returned to in Chapters 5 and 6.

Further insight can be drawn from a consideration of Bloom’s Taxonomy first published in 1956 and subsequently revised by David Krathwohl, one of its originators, in 2001. Its original purpose was to create a kind of universal, hierarchical psychologically based matrix against which all learning objectives could be mapped and measured. It consisted of six elements, listed in terms of their relative and incremental complexity: evaluation, synthesis, analysis, application, comprehension, and knowledge. The revised version comprises two dimensions—knowledge and cognitive process. The knowledge dimension’s substructures are “factual,” “conceptual,” “procedural,” and “metacognitive.” Those of the cognitive process comprise “remember,” “understand,” “apply,” “analyze,” “evaluate,” and “create.” This is a widely adopted framework within education and beyond (for instance, anecdotal evidence suggests the Taxonomy is often referred to in organizational learning strategy and design implementations) yet receives little attention in the KM field. What this framework represents is a description of the goals of education and their interrelationships.

A comparison of Bloom’s Taxonomy (revised) with ideas about knowledge creation within the traditional approaches to KM suggests that the latter are overly simplistic. According to Bloom’s Taxonomy, the creation of new knowledge is the pinnacle of a hierarchical, multitiered, corelational, and incremental cognitive process that recognizes four types of knowledge. Furthermore, these knowledge types are defined clearly within the Taxonomy—no mention of the tacit–explicit construct here. From the Bloom’s Taxonomy perspective, knowledge is a part of the learning process, and new knowledge creation is one outcome of the process. Importantly, the significant implication of Bloom’s Taxonomy is that knowledge can be managed, but from the learning process perspective. This turns us in the direction of KS, another major area of debate in KM.

3.7 SHARING KNOWLEDGE

One of the strongest organizational imperatives associated with KM is that of KS. Many scholars consider KS as key to improving organizational performance. From a commonsense perspective, the prospect of an organization in which its members do not share their knowledge either in conversation or in text would seem inconceivable. More specifically, KS is connected to competitive advantage, increased productivity; it is key to creating value, critical to innovation; KS supports response to change and quality improvements and contributes to new knowledge creation. The organizational practice of sharing knowledge is also linked to cost reduction. Based on all of these attributes, it would seem reasonable to propose that KM’s success is reliant on KS as a focal and fundamental organizational activity.

One critic of this conventional view of the underpinning importance of KS is Max Boisot who claims that it is not knowledge that is shared but rather it is information. From a pragmatic perspective, his argument is somewhat weakened by the title of his work—The Creating and Sharing of Knowledge—and the impression that he uses the terms “knowledge” and “information” interchangeably. For instance, having argued that “…it is never knowledge as such that flows between agents, but rather data from which information has to be extracted and internalized” (2002 : 72), he subsequently reasons that in order to share knowledge, there needs to be at least some degree of articulation of that knowledge. Setting this confusion to one side, he does offer an interesting and entirely plausible explanation for KS as signifying a “degree of resonance” between the “repertoires”—the expectations and behaviors—of two or more people. Boisot is one of the few who describe KS in terms of a process that is arguably indicative of the myriad issues associated with the definition of knowledge itself (see Chapter 1).

Evidence in support of KS as an advantageous organizational practice can perhaps more readily be seen in the battery of barriers, critical factors, and enablers thrown in its direction. Before taking up some of these issues, it is worth noting a compelling perspective offered by Thomas Suddendorf who we encountered in both of the previous chapters. Suddendorf claims that the instinct in humans to share knowledge is innate, irrepressible, and a significant underpinning feature and factor in human evolution—“…by linking our minds to those of others we have enormously increased our predictive capacities and powers of control” (2013: 158)—and that humans by their nature give preference to situations more likely to result in new information and understanding. From these perspectives, humans are born with the motivation to share their knowledge with others. Contrary to this view, a study of Korean organizations finds that extensive KS in organizations is the exception. What is going on? Youngjin Yoo of Case Western Reserve University and Ben Torrey of Accenture Inc. astutely identify the key question: “(I)if knowledge sharing is so universal an aspect of the human experience and critical to relationships, then why is there an issue when it comes to the organizational context?” (424)

One explanation is offered by M. Max Evans of McGill University in Canada, whose study focuses on the human social and cognitive factors affecting KS practices in a Canadian law firm. He reasons that because KS involves highly complex social interactions, influenced by trust and other sociocognitive factors, it is by its nature difficult. The point that he makes is that knowledge is not a commodity, and as such it cannot be “shared out” in the normal understanding of the action to share—in the sense of, say, a book or a DVD. He particularly focuses on the factors of trust, homophily (the tendency to associate and connect to others perceived as similar to oneself), shared language and vision, tie strength, and relationship length: the findings show that trust is the single most important influencing factor, followed by a “willingness to share” and shared vision. Interestingly, length of relationship is shown to have no effect, while tie strength and homophily have a minimal impact on KS. Signaling a word of caution, however, note that these findings are based on a study of a single Canadian firm, using self-reporting survey questionnaires, methods that we have elsewhere called into question. Despite any potential reservations regarding research methodology, this study offers some interesting and relevant insights. In particular, the importance of trust in KS activities is supported elsewhere in the KM literature, along with a mixed bag of other factors and features.

Any glance at the KM literature on the topic of KS reveals innumerable barriers and issues including what is described as the natural desire to store and hoard one’s knowledge, costs associated with KS, and the threat of reputational damage. Some point to the lack of incentives to share, but contrastingly other scholars find that extrinsic rewards can work as a hindrance to KS. A study of Wiki use by Alexeis Garcia-Perez and Robert Ayres of Cranfield University in the United Kingdom finds that issues concerning time and a lack of critical mass are implicated in online community contexts. Others warn that low values placed on mentoring can particularly impede the sharing of tacit knowledge. In fact, there are so many barriers reported that one wonders if knowledge can ever be shared. Fortunately, a review of the critical and enabling factors reveals a more discernible pattern.

Technology is frequently connected to KS, distinguished by two contrasting perspectives. Garcia-Perez and his colleague, for instance, study KS behavior in the context of a research group’s (failed) Wikipedia. They conclude that technology does not constitute the “silver bullet,” a perspective shared by many others. In contrast, Michael Earl, professor of information management at the London Business School, claims that strategic KM success relies on recognizing the importance of communications networks implying the mediating effects of technology. Web 2.0/Enterprise tools are also claimed to be key enabling factors, although one proponent, perhaps controversially, suggests that their use must be controlled. Clearly, technology in some form has a role in KS—as it does in almost every aspect of the modern organization’s operations. But technology is a tool of which the perceptive value is dependent on many factors. Consequently, the present discussions will not pursue this topic beyond these few points drawn from the literature, principally noting the debate’s focus on the extent or otherwise of technology’s role in delivering and mediating KS activities.

Culture (understood as “context”: see Section 3.5) is also a frequently visited theme in debates specifically around KS. Earl’s communications networks, mentioned earlier, imply a culture of mutual support as a critical factor to successful KS. Mutual support also suggests trust (a topic that starts to take on increasing importance as the ideas develop throughout this book). Others more explicitly implicate a culture based on trust: in their literature review and case study examining the effects of culture in KM practices in general, Yoo and Torrey draw an explicit relationship between KS, trust, integrity, and status. The importance of a trusting and mutually supportive culture can be seen as the explaining factor in some of the barriers noted earlier. For instance, without a trusting culture, one might very well be disposed to “protect” one’s knowledge and guard against reputational damage.

Extending from there, we find a strong theme of the social world in accounts of what enables KS. Person-to-person communications in the form of regular meetings, physical proximity, and shared narratives are promoted as key—and commonsense—enablers. These have synergies with an emphasis on the social group, networking, and the idea of “density.” A study of Spanish firms’ sharing of best practices finds that coaching and leadership are important. There are of course many other factors mentioned in the KM literature: knowledge “stickiness,” for instance, and “knowledge gaps,” with the former relating to difficulties in sharing knowledge as a result of problems in separating it from its source (host) and the latter referring to differences in the knowledge of transmitter and receiver. What can be drawn from all of these perspectives is that barriers and enablers (collectively referred to hereafter as “KS factors”) are rooted in fundamental organizational practices, suggesting both the contextual (see Section 1.4 for a discussion around the importance of context) and foundational nature of KS behavior.

A closer analysis of these factors suggests that these can be related to one or more of four thematic categories: trust, risk, context, and identity. The first two, as we have seen in the previous discussions, are explicitly referred to in the KM literature on KS. The third, context, can be applied to those factors that refer to the action environment and its associated social norms such as those relating to “culture.” The final category, identity, while not specifically referenced in the accounts of KS, is embedded to factors such as leadership, the urge to store and hoard personal knowledge, and the threat of reputational damage, for instance. Table 1 makes this mapping explicit.

These mapping categories are positioned as psychological phenomena. All that has been done here is to organize this lengthy list of claimed influencing factors in KS into a pattern of subjective psychological phenomena. This mapping is itself admittedly subjective and interpretive in that the factors are drawn from multiple different authors, each of which has their own aims and agenda. The general heuristic adopted has been to regard each factor as emanating from perceptual experience and to ask, in the case of “shared narratives,” for instance, given that it is one’s perception that leads one to understand this as an experience of shared narratives, what are the psychological phenomena that might give rise to this. In the case of shared narratives, context, identity, and trust are conjectured to be the phenomena that are intrinsic to an understanding of the activity of “shared narratives.”

3.8 SUMMARY AND CONCLUSIONS

The discussions over the “commodification and reification” issue unsurprisingly reveal polarized views. This raises an interesting question: if how the organization is conceptualized influences how it approaches the practice of KM, as suggested in the previous chapter, is a reified account of knowledge the variable outcome of “conceptualization–influence”? That is, how an organization views itself as a determinant of how it approaches the management of its knowledge will also determine what it manages. Or is a reified perspective of knowledge the starting point? Which comes first, the chicken or the egg? In other words, if the starting point is a view of knowledge as object, with KM strategy sensibly organized around this concept, is there any point at which this is mapped to the conceptualization of the organization itself? Could it be that misalignments in this particular organizational narrative are an underlying cause of KM failure? That can only be considered as speculation.

Leading on from this speculation, the debates and questions around KM success or failure are interesting if for no other reason than that little account is given for what such success or failure actually looks like. There is also the potential that “blame” for failure is apportioned in the wrong direction. Nonetheless, according to the various case studies and reviews featured here, there is a theme of high rates of failure with reasons variously ascribed to organizational strategy (e.g., too much emphasis on technology, lack of supportive leadership and disassociation from central organizational strategy, a reliance on “traditional thinking”), economic impact (e.g., lack of measureable benefits and an impact on working time), and sociopsychological factors (e.g., a lack of focus on the social aspects of knowledge work such as trust and relationships and resistance to change). We have however raised a question over where this evidence comes from and how it has been interpreted: is there a tendency to prioritize the reporting of “bad news” rather than success stories?

The issue over difficulty in the application of a robust measurement to KM activities is not only categorized as a failure factor in its own right, but also results in a lack of supporting evidence for KM as an advantageous organizational practice. The assumption of the connections between KM and increased performance is, for instance, claimed to be based on no more than a perception. That is arguably a theme that could be applied to all of the foregoing. Also indicated as a failure factor, the “one size fits all,” seen from the cultural perspective, is claimed to be ineffective due to the complexities and variation in national cultures. It is further suggested that this variation persists at the organizational, group, and individual levels, as understood from the wider viewpoint of “context.” On a more positive note, what can be inferred from these claims and debates is that “context” influences KM. That being the case, then it stands to reason that a “check box approach” lacks credibility. KM as a practice, in this sense, cannot be treated as an “off-the-peg, ready-to-wear” suit.

The discussions around new knowledge creation and sharing knowledge generally reprise similar issues to those raised elsewhere. It is interesting to note that while the literature considered here spans a period from the late 1980s to the present, the same issues are shown to recur. With reference to knowledge creation, an important conjunction of four human factors is identified: the idea that a person’s individual store of knowledge, mediated by the predictability of language, is what enables sensemaking in the social world, and this results in the generation of new knowledge (to the individual).

This has some synergy, albeit loosely, with the factors shown to be implicated in KS, which are themselves mapped to the four thematic categories of trust, risk, context, and identity. In most cases, each factor maps to more than one KS category, and this suggests a potential for corelation. For instance, “leadership,” “shared narratives,” and “trusting climate” map to the same categories, which open a question of whether these categories are corelational in KS actions. Arguably, the same set of categories could be applied to factors claimed to be implicated in KM failure. From a pragmatic perspective and for the purposes of the research presented in Part Two, the practice of KS—rather than KM failure, for instance—represents a more viable and accessible focus. Thus, these thematic categories become a focal point of investigation.

This chapter has critically reviewed and discussed some of the most significant and influencing debates and questions in KM and in particular has identified a set of thematic categories of particular interest. The following chapter engages with the KM theory. To bring some constructive order to what is found to be a substantial field, theories are organized onto two bisecting continua relating to “knowledge as object versus knowledge as social action” and “personal knowledge versus organizational knowledge.” Support is found for some of the social themes already uncovered in this and the preceding two chapters. The discussions around theory particularly look for indications of the KS thematic categories.

FURTHER READING