Article Tagging


Above is the tag cloud I ended up with. My approach to tagging on CiteULike was designed to be intentionally organic and sub-optimal, in an attempt to replicate natural folksonomy development. I avoided using the “view all tags” button when tagging articles in order to reflect the ways in which multiple users can create redundancies based on different perceptions of which components matter most when creating tags.

The most visible artifacts of that are the network-networks and practice-practices pairs; the circumstances under which those arose were, in review, cases where one article or group of articles dealt specifically with the singular. theoretical concept (in terms of a specific framework, often) while another dealt with more general references and direct applications in practice. Thus, they are not perfectly identical in intent, but to an outside observer that is not evident.

“Knowledge” is by far the most prominent tag. This is due to the core principle I retained throughout the semester in my tagging efforts, that I would orient everything around that single concept, branching off into more specific expressions and variations according to the focus of a given article-“information” when that was being dealt with as an explicit distinction from knowledge, for example. Predictably, “management”, “organization”, and “transfer” were three other major tags, as each represents a core expression of knowledge in the literature.

A number of infrequently-used tags also exist. These generally emerged when an article had an overwhelming focus on a specific idea to the point where it was about that in particular; the concept of knowledge “stickiness” is a good example of this type of tag.

In hindsight, this approach was too generalized and natural. My efforts reflected the natural formation of a folksonomy in form but not in depth, as a single individual is ultimately incapable of processing the same quantity of material which goes into the construction of a folksonomy. It would likely take several times this many articles and a much more comprehensive tagging effort (a minimum of 6-7 tags per article) in order to accurately reflect the patterns of such a system.

It also lacked the strong structure of a traditional organized vocabulary, or even of a culled folksonomy, being bound only by a single guiding principle rather than a set of criteria for what types of tags should be employed, which variation of a given tag should be used, &c.

For a project of similar scope and time span, in future I would use the following design, or set of requirements. First, I would develop a core set of five or six essential tags, and then limit myself to using no more than four or five for any single article. This would ensure a strong basis for comparison on key features while preventing over-generalization based on rationalizations that almost every article touches upon almost every core issue in some regard. Likely this would also contain a measure of reform in term construction, phrasing these core terms as “Knowledge_(#Area of interest#)” to eliminate the use of the plain “Knowledge” tag as a meaningless label applied to every article.

Following that, I would enforce a mandate on myself that I include at least three area-specific tags for each work dealing with the more detailed and specialized content of the piece. These tags would be bound to apply to no more than half of the total volume of articles and no fewer than two total. Additionally, I would allow for up to three article-specific tags per work, to cover important concepts not discussed anywhere else in the literature as well as authors’ unique terms and phrases.

Although this is rather more structure than would normally be seen in a folksonomy, this sort of approach is not quite a true folksonomy, as it consists of only a single contributing individual. As an aside, it might be interesting to construct an overall class folksonomy drawing from each participant’s tags to create a larger impression of tagging patterns.

Article Tagging

A Final Perspective on Organizational Knowledge

It’s already this time again, isn’t it? Over the  course of the semester we’ve discussed organizational knowledge half to death, from a multitude of angles and using a substantial array of sources. Let’s take one more stab at it.

What is organizational knowledge, and why does it matter? Tsoukas & Vladimirou (2001) ask even more fundamental questions: what is knowledge itself, and how does it relate to action? How does knowledge differ from information? How does it become organizational? They tell us that two things are required: a theory of knowledge, and a theory of organization. Moreover, knowledge is both personal-tacit-and collective. Organizational knowledge emerges when individuals work according to generalized assumptions based on collective tacit knowledge of past events (Tsoukas & Vladimirou, 2001).

We’ve seen this idea arise again and again, both in the literature and in our own discussions of it; within the past month alone some expression of the concept of collective knowledge has arisen in the majority of our blogs, including Audrey’s piece on knowledge learning and unlearning, Mary’s discussion of narrative in knowledge and learning, Abigail’s post regarding organizations and individuals, Kamryn’s work on knowledge sharing, and posts within this blog as well.

In a word, it’s pervasive. Mary was the one who clued me in on what was going on underneath, and Sean’s recent comment regarding introducing work dealing with narrative epistemology sealed things. Knowledge so often is seen and expressed as something collective, something which is intended for (or difficult to) transfer, because storytelling is the fundamental form of human knowledge transfer and we are inherently social creatures. That is the heart of what organizational knowledge is: the ability we possess in which a single individual can gain tacit awareness of some piece of knowledge and then, through their social ties, transmit that knowledge to their peers without needing to explain it, possibly without even realizing that they’re doing so.

When a technician or engineer solves a peculiar problem that doesn’t match normal troubleshooting guides, they tend to relate the knowledge of that problem and solution to others not by writing up a report and disseminating it, but by telling the story-this sort of knowledge transfer is more effective, despite its apparent inefficient nature.

Blackler’s (1995) work, although somewhat dated, underlines another important point: knowledge, particularly tacit knowledge, is not static. This is part of why the social, collective expression of tacit knowledge is so effective: it continually develops as each individual applies their collective knowledge, refines it based on their experiences, and passes those refinements on, often without being consciously aware of the exact significance of what they are doing. His suggestion that more attention should be paid to the “cultural” systems in which individuals exchange knowledge (1995) is apt, and much of the more recent work we’ve studied has reinforced that point.

That is the note I will conclude the active portion of this blog on: organizational knowledge, tacit knowledge, and organic systems of knowledge transfer are natural constructs. Efforts to replicate them as designed systems should keep that in mind-too much constraint and the underlying processes will fail.



Blackler, F. (1995). Knowledge, knowledge work and organizations: An overview and interpretation. Organization Studies, 16(6), 1021-1046.


Tsoukas, H. (2001). What is organizational knowledge. Journal of Management Studies, 38(7), 973-993.

A Final Perspective on Organizational Knowledge

Post-Paper Framework Examination

Now that we’ve all passed the point of further submissions of revisions to our papers, we can take a bit of time to examine some of the knowledge management frameworks in our reading list with the experience of selecting or developing one of our own. This is intended both as the starting point for reflection on our work and a chance for comparing what we developed to what other scholars have created for different purposes.

Trkman & Desouza’s (2012) framework for understanding the risks of knowledge transfer in and between organizations has already been discussed in this blog in the context of knowledge transfer failure; Kamryn links it to competitive advantage while also discussing the core aspect of risk, and Mary mentions it in relation to the Hemsley & Mason (2013) article’s examination of “viral” information.

Each of those three cases brought up the Trkman & Desouza framework in a different manner, using it to help illuminate another aspect of knowledge management associated with the core focus of knowledge-sharing risks. This is indicative of a strength not directly linked to the actual argument behind the framework, but to the way in which it was constructed and explained: it is readily comprehensible and flexible enough that it can be applied as an explanatory tool for situations outside its explicit purpose, even when the author, as Kamryn said, isn’t directly interested in the whole of the idea they present.

We have another example of a knowledge management framework, one which deals with risk, even, that demonstrates the opposite sort of strength. Massingham’s (2010) framework of knowledge risk management was cited in the course blogs in a context narrower than that established by Massingham himself. Mary and Abigail both discuss Massingham’s framework alongside the Kumar & Chakrabarti (2012) article on risk and the Challenger disaster, while Rachel does so in a post about other disasters and the role of organizational relationships in the same, where Massingham primarily mentions disasters as a motivating force behind the development of organizational awareness of the need for better risk management (2010).

This demonstrates, rather appropriately, that a knowledge management framework can be strong in different manners, including ones at odds with each other. That strength can be derived from the theoretical and argumentative work supporting the framework-that is, in the original context which the author laid out, as a tool for explaining a specific phenomenon-or from the clarity, flexibility, and generalizability of the framework, the extent to which it can be applied in other areas of knowledge management.

Obviously a solid theoretical framework must make clear the assumptions and scholarly support underlying it, and within the paper presenting it should remain confined to the issue with which it is concerned. From there, the first sort of strength flows naturally, so long as the assumptions and support are sound and the presentation is effective. The second sort of strength seems to contradict the purpose of a theoretical framework at first glance-this is incorrect. The framework’s focus should not be generalized, but designing it such that the argument is generalizable to a degree allows other scholars more latitude in using the framework as a tool to examine phenomena related to the one which it was original oriented around.


Hemsley, J., & Mason, R. M. (2013). Knowledge and knowledge management in the social media age. Journal of Organizatational Computing and Electronic Commerce, 23(1), 138-167.

Kumar J, A., & Chakrabarti, A. (2012). Bounded awareness and tacit knowledge: Revisiting Challenger disaster. Journal of Knowledge Management, 16(6), 934-949.

Massingham, P. (2010). Knowledge risk management: A framework. Journal of Knowledge Management, 14(3), 464-485.

Trkman, P., & Desouza, K.C. (2012). Knowledge risks in organizational networks: An exploratory framework. Journal of Strategic Information Systems, 21(1), 1-17.

Post-Paper Framework Examination

The Information Society and Tacit Knowledge as Assumptions

Recall the previous mention of Tremblay’s 1995 lecture in the context of the role of social media as a tool for knowledge sharing. That was a single element of a similar, broader theme to the lecture, which explored the state of then-current theory regarding, conceptualization of, and influences of the model of the information society.

The principal points which Tremblay (1995) raised were the tendency among communication and information professionals to view the hypothetical information society as a good thing, the issue of technological determinism-that is, the positioning of communications technology as a central focus of the information society and myriad other elements, and a general trend of optimism in the field.

Thus, relatively early in the formulation of the concept of the modern vision of the information society-indeed, before it had even truly begun to emerge in fact rather than projection, though several decades after the idea entered development-there was already questioning of several core assumptions of the model, namely that it was a positive change and that it was not only rooted in technological development, but that new information technology enjoyed one-way causality, effecting changes in society without being affected in turn.

More recent scholars discuss the rejections of the information society model, arguing that it received insufficiently critical and empirical evaluation, as well as suggesting that the notion of the information society dates back to the Enlightenment and has recurred since, rather than originating in the mid-20th century (Rule & Besen, 2008). Specifically, these authors cite Saint Simon’s suggestion that the creative and scientific disciplines were of markedly more value to society than individuals with substantial political or social status, and Comte’s notion of science as a “positivist religion” (Rule & Besen, 2008, pp. 318-19).

In other words, Rule & Besen reduce the notion of the information society down to the principle of rational thought and the role of information and knowledge as organized, relied upon, and authoritative elements of the social order, reducing arbitrariness and increasing benefits to those who use them well (pp. 220).

As Tremblay (1995) did, Rule & Besen (2008) note the utopian drift of the dialogue about the information society model in the late 20th century. They go through the critical work on the information society model, then proceed to offer their own criticism of five major theoretical points.

Ultimately, Rule & Besen (2008) conclude that in regard to the projections of the information society model there is little empirical evidence supporting it which is both meaningful and unambiguous. Like Tremblay (1995), they make mention of the natural, understandable impulse to make certain assumptions about the nature of the information society. Furthermore, they expand on that with the implication of their argument regarding the model’s roots, suggesting that even if it loses favor now it will inevitably arise again, for much the same reason that it has before (2008).

The ongoing debate over the information society model is, somewhat amusingly, a rather apt example of Polanyi’s (2009) conception of tacit knowledge in practice, which he coincidentally proposed at around the same time that this iteration of the information society model did so. What Tremblay and Rule & Besen discuss in terms of assumptions is, in fact, a form of tacit knowledge, one which demonstrates just how easily it can be overlooked.

The scholars which make these assumptions about the nature of the information society have, one would think, encountered the concept of tacit knowledge, and may even be intimately familiar with it. Yet when it exists in the form of their own emotional or intellectual attachments to a piece of external knowledge, its effects go overlooked. There is, as the authors of that paper and lecture suggested, underlying knowledge backing the information society model which requires some degree of contextual presence to possess and understand-as they note, the model is intrinsically appealing to information and communication scholars because it meshes well with their ideological predispositions.

This is why it is so vital that we consistently maintain awareness of our tacit knowledge in the context of things which are professionally or personally important to us, because such instances are both ripe for the development of such knowledge and most likely to push us towards overlooking it.



Polanyi, Michael. (2009). The Tacit Dimension. Chicago: University of Chicago Press.

Rule, J. B., & Besen, Yasemin. (2008). The once and future information society. Theory and Society, 37(4), 317-342.

Tremblay, G. (1995). The information society: From Fordism to Gatesism. Canadian Journal of Communication, 20(4), 461-482.


The Information Society and Tacit Knowledge as Assumptions

Knowledge Transfer & Bottom-Up Knowledge Management

In much of the literature, organizational knowledge management is presented as a form of knowledge management in which knowledge is closely tied to the institution in which it was generated. Organizational knowledge transfer requires the creation of a meaningful capability for transferring tacit knowledge alongside the explicit, as the former is required to properly frame the latter.

We can observe this line of thought in one of the two oldest articles on our reading list, in which the authors argue that a prescriptive, top-down approach to organizational knowledge management is doomed to fail at its intended purpose, forcing members of the organization to improvise more in response to the decreasing flexibility of officially accepted approaches to common organizational issues (Brown & Duguid, 1991).

Furthermore, Brown & Duguid propose a model of organizational learning and knowledge management which, although it is framed in different language, intrinsically demands a strong base of commonly held tacit knowledge and mutual understanding between individuals within the organization. They identify two key components of organizational knowledge, describing it as “collaborati[ve]” and rooted in “narration”, meaning that organizational knowledge is always organizational rather than individual, and is formed through actual practice and the relation of those practical experiences between members of the organization. They go on to claim that sterile organizational knowledge transfer is impossible, and that both the sender and receiver of knowledge must share an intrinsic understanding of the context in which the knowledge was created and has existed (1991).

Much of this, as seen in the rest of the literature, has come to be accepted as common practice, though not always discussed in the terms that Brown & Duguid used. An article from the late ’00s discussed a potential approach to knowledge management which initially appears to risk the exact sort of disconnect between sender and receiver which Brown & Duguid identified as fatal to knowledge transfer attempts–the authors called it “knowledge outsourcing” (Lam & Chua, 2009).

Lam & Chua describe the process of knowledge outsourcing essentially as this: a third party organization identifies client knowledge needs, locates potential knowledge providers, and facilitates negotiations between client and provider, followed by provision of quality assurance checks. They identify as primary risks low standards of information provided and under-utilization of received information (2009), both of which are closely tied to knowledge transfer without shared tacit knowledge: the provider may not understand what the receiver needs or what they already know, and the receiver might not understand how to use the knowledge they obtain and may lack awareness of the context in which it was generated.

Indeed, the authors explicitly note that the process of knowledge outsourcing is best applied to narrow problems with little complexity behind their context.

Knowledge outsourcing on the other hand takes place when knowledge is generated by providers external to the organisation, typically under some specific contractual arrangement. Such knowledge tends to be less contextual and proprietary in nature and can be produced without significant prior knowledge about the organisation’s setting or its internal workings. However, such knowledge also tends to be more narrowly focused and specific to a problem area (2009).

As we have seen in other works, deliberate shaping of organizational culture to promote the growth of the exact sort of narrative, collaborative knowledge which Brown & Duguid have discussed has proven to be exceptionally valuable for organizations which do so successfully. In particular, Lang & Wu’s study of AMTC and the ECR recall crisis provides an exceptionally well-shaped model for how an organization which relies on bottom-up knowledge management and inter-individual relation of stories about specific cases can be more flexible, more adaptable, and more effective than one which attempts to prescribe narrow, standard reactions to problems.


Brown, J. S., & Duguid, P. (1991). Organizational learning and communities-of-practice: Toward a unified view of working, learning, and innovation. Organization Science, 2(1), 40-57.

Lam, W., & Chua, A. Y. (2009). Knowledge outsourcing: An alternative strategy for knowledge management. Journal of Knowledge Management, 13(3), 28-43.

Wang, W. T., & Lu, Y. C. (2010). Knowledge transfer in response to organizational crises: An exploratory study. Expert Systems with Applications, 37(5), 3934-3942.

Knowledge Transfer & Bottom-Up Knowledge Management

Factors in Knowledge Transfer Failure

We have previously examined a number of different elements of organizational knowledge management; this time our focus will be on how the characteristics of organizations, the knowledge they value, and the circumstances in which they attempt to transfer said knowledge–both internally and with other organizations–can adversely affect knowledge transfer attempts.

This has been addressed in the literature from a number of angles, with appropriately varied emphases. Kang, Rhee, & Kang address knowledge characteristics specifically, describing tacitness, difficulty of transfer, and importance of the knowledge as the three key ones, testing each to determine their respective association (or lack thereof) with the degree of effort organizations expend on knowledge transfer (2010). Meanwhile, Szulanski not only examines a broader set of characteristics, but also differs from Kang, Rhee, & Kang in what he notes as key characteristics of organizational knowledge: causal ambiguity and unprovenness–that is, whether an organization can identify how and why a particular piece of knowledge being applied results in a certain outcome, and whether the knowledge has an established history of successful application.

In addition, Szulanski also discusses characteristics of knowledge sources and receivers, as well as the organizational context of the transfer process. Quite beyond that, Szulanski is concerned with what he terms knowledge “stickiness”, how knowledge is sometimes not transferred within a single organization even when it possesses said knowledge and the transfer is beneficial (1996), rather than willingness to expend effort on the transfer process, although the two do have some potential relation insofar as that an organizational unwillingness to expend effort on internal knowledge transfer could be a potential cause of knowledge stickiness.

A third perspective is offered by Trkman & Desouza in their attempt to create a framework for understanding the risks of inter-organizational knowledge transfer and sharing. In a certain sense they cover a broader range of noteworthy characteristics, being concerned with the circumstances in which knowledge sharing occurs, the importance of shared knowledge, and the relationship between knowledge sharing organizations (2011). However, their arguments rest more on how those characteristics aid in the creation of different behavioral patterns–and thus, different risk factors–which affect the likelihood, depth, and degree of success of knowledge transfer, rather than attempting to link specific characteristics directly to knowledge transfer failure.

Perhaps predictably, the framework developed by Trkman & Desouza describes a familiar knowledge sharing paradigm in which organizational trust and reputation are of paramount importance, serving to reduce interorganizational antagonism, opportunism, and creating inertia by allowing initial knowledge sharing efforts to be mutually beneficial (2011). They are quick to note that their framework was largely untested at the time of writing, but the preponderance of the literature which we have reviewed supports their assertions.

More importantly, Trkman & Desouza explicitly acknowledge the potential for ineffective or failed knowledge transfer, additionally noting that organizations should and do assess the costs of mitigating knowledge transfer risks, leading them to make decisions regarding which organizations to work with based on the core levels of risk (2011)–a low-risk relationship might be preferred over one which is more beneficial but which also bears a higher level of risk, necessitating additional expenditure of resources to curtail said risk.

In the research conducted by Kang, Rhee, & Kang, those authors find support for several of their hypotheses, parsing their results into a number of interesting conclusions. They identify a weak positive relationship between knowledge tacitness and effort expended on knowledge transfer, arguing that this is due to the potential strength of disseminated tacit knowledge as a competitive advantage being balanced by the difficulty and potential futility of attempting to transfer it–there is impetus to attempt to transfer it, but plentiful cause to cease efforts to do so. The authors find stronger support for relationships between the difficulty of learning knowledge and expended effort on transfer attempts and  between between the importance of knowledge and efforts to transfer it; in other words, they identify a strong positive relationship between importance and difficulty of acquisition (2011). The implication is obviously that important knowledge is also typically difficult to transfer–note that tacit knowledge is also typically difficult to transfer, but similar degrees of effort are not always expended on attempts to transfer it, as it is often merely advantageous rather than absolutely critical.

Szulanski’s research indicates that three characteristics are of particular importance among those he identified as potential barriers to knowledge transfer: the receiver’s ability to absorb information, the causal ambiguity of information, and an arduous relationship between source and transceiver.

Essentially, these authors together provide a synthesis of sources of knowledge transfer failure: lack of trust between organizations and poor or no reputation on the part of the source, as previously discussed in myriad posts; perceptions of knowledge being transferred as more difficult to transfer than its value warrants; a receiver’s inability to parse or learn knowledge, and a lack of awareness about the truth behind knowledge–an organization knowing that doing something in a particular way will achieve a particular outcome, but not why or how it happens.

Among our blogs we’ve discussed certain aspects of knowledge transfer and organizational knowledge management a great deal: trust, tacitness in the organizational context, the use of specific technological tools, responses to external crises, &c. I can’t remember, however, seeing much discussion of situations in which knowledge transfer outright breaks down and either fails to work or works in an adverse manner–the closest was Abigail’s discussion of Connelly et al.’s work on knowledge hiding, which is related but not exactly the same thing. Barring, of course, discussion of failure in the context of the Challenger disaster, as we’ve quite thoroughly covered that.

I’m curious as to what you each think might be behind this gap. Were the articles discussing downsides to and failures of knowledge transfer simply less interesting? Was it that the early forays tended more towards other topics, shaping discourse through the rest of the semester?


Kang, J., Rhee, M., & Kang, K. H. (2010). Revisiting knowledge transfer: Effects of knowledge characteristics on organizational effort for knowledge transfer. Expert Systems with Applications, 37(12), 8155–8160.


Szulanski, G. (1996). Exploring internal stickiness: Impediments to the transfer of best practices within the firm. Strategic Management Journal, 17, 27-43.

Trkman, P., & Desouza, K.C. (2012). Knowledge risks in organizational networks: An exploratory framework. Journal of Strategic Information Systems, 21(1), 1-17.

Factors in Knowledge Transfer Failure

Extra-Organizational Knowledge Sharing

The organizational context of knowledge sharing has been heavily discussed in various blog posts from different perspectives. Rachel notes that “it seems that people have always exchanged information through workplaces”; Kamryn suggests that trust is important to KM within organizations, with the implication that trust is possible because of the structure provided by those same organizations; Mary argues quite rightly that “[e]ffective knowledge management has a cornerstone of shared language and shared goals,” which is likewise easier to establish within an organizational framework. This blog has earlier noted Lucas’ emphasis on the importance of trust and reputation in intra- and inter-organizational knowledge transfer.

Indeed, this is what much of the literature on knowledge transfer centers around, the ways in which organizations can increase the efficacy and efficiency of knowledge transfer and management. It is rarely, if ever, stated that this is exclusive to KM tasks in established organizations and cannot be applied in disorganized public venues, but the nature of many of the discussed methods makes them difficult to apply without some degree top-down control.

As a review of previously discussed work, Lucas cites trust between colleagues, the reputation of knowledge providers, and the reputation of knowledge receivers as key elements of successful knowledge transfer (2005). Nonaka emphasizes the role of organizations in providing a structure in which tacit knowledge, difficult to transmit under any circumstances, might be more readily codified into explicit knowledge (1994).

Wasko & Faraj provide an intriguing departure from this close focus on organizational knowledge management, instead writing on knowledge transfer in “networks of practice”, looser and less familiar versions of communities of practice in which any given participant has no particularly strong stake in the whole and may not even know other members, which they specifically define according to these characteristics: self-organizing and composed of individuals who participate voluntarily with the intent of engaging in mutually beneficial problem-solving (2005). The authors posit that, despite the lack of organizational structure and professional relationships, these networks of practice still allow substantial meaningful knowledge transfer to occur.

Wasko & Faraj note, among other things, a lack of quality control in contributions, a free-rider problem, and low potential for the confluence of circumstances commonly cited in the literature as sources of cohesion and trust. The authors identify social capital as the principle reason for participants in networks of practice choosing to engage even with no guarantee of reciprocity, namely that, in spite of widely held beliefs that social capital cannot accumulate to a significant degree in networks of practice, individuals choose to do so anyways due to a tacit expectation of personal benefit. Wasko & Faraj frame this benefit as a belief on the part of the contributing individual that their contribution is worthwhile, and that it will enhance the overall value of the network, ultimately benefiting them in turn (2005). Those authors base their argument on social exchange theory as outlined by Blau in 1964, the idea that social interaction is promoted by the belief of participants that their reputation will be enhanced by their involvement.

That is the gist of it, and it works well enough for explaining active participation in loose professional networks. But what about social media, particularly in the context of intentionally anonymous participation? That lacks both the general familiarity of a network of practice and the bonds of traditional social interaction. I’ll leave off with a question: Why would individuals choose to participate in such interactions, when they will likely never be identified and in all likelihood will never encounter the individual they aided in any context in the future?


Blau, P. M. (1964). Exchange and power in social life. New York, NY: Wiley.

Lucas, L. M. (2005). The impact of trust and reputation on the transfer of best practices. Journal of Knowledge Management, 9(4), 87-101.

Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5(1), 14-37.

Wasko, M. M., & Faraj, S. (2005). Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. Management Information Systems Quarterly, 29(1), 35-57.

Extra-Organizational Knowledge Sharing