The Concept of Knowledge Communication and Its Relevance to Management

The Concept of Knowledge Communication and Its Relevance to Management

USI Research Note July 2006, Version 2.2

Martin J. Eppler, School of Communication Sciences, University of Lugano (USI), Switzerland, Martin.Eppler@lu.unisi.ch, www.knowledge-communication.org

Abstract:

In this research note we illustrate the relevance of the notion of knowledge communication for management. We outline where and how the communication of expertise from specialists to decision makers is crucial. We introduce key elements of the concept of knowledge communication and review influential theoretical constructs that explain why knowledge communication among experts and decision makers frequently fails.

1. INTRODUCTION: THE IMPORTANCE OF KNOWLEDGE COMMUNICATION IN MANAGEMENT

Communicating professional knowledge is a key activity for today’s specialized workforce. The efficient and effective transfer of experiences, insights, and know-how among different experts and decision makers is a prerequisite for high-quality decision making and co-ordinated, organizational action (Straub & Karahanna, 1998; Rosenthal & ‘t Hart, 1991). Situations of such deliberate (interfunctional) knowledge transfer through interpersonal communication or group conversations (Gratton & Goshal, 2002, Tsoukas 1996) can be found in many business constellations, as the following typical examples illustrate: Technology experts present their evaluation of a new technology to management in order to jointly devise a new production strategy (McDermott, 1999). Engineers who have discovered how to master a difficult manufacturing process need to convey their methods to engineers in other business units (Szulanski, 1996, 1999). Legal experts brief a management team on the implications of new regulations on their business model (Wilmotte & Morgan, 1984). Experts from various domains need to share their views and insights regarding a common goal in order to agree on a common rating of risks, requirements (Browne & Ramesh, 2002), industries or clients. Project leaders need to present their results to the upper management and share their experiences of past projects in order to assess the potential of new project candidates

1

(Schindler & Eppler, 2003). Scientists who work as drug developers present new avenues for future products that business unit managers must assess. Market researchers present their statistical analyses of recent consumer surveys to the head of marketing (Boland et al., 2001). Strategy consultants present the findings of their strategic company assessment to the board of directors in order to devise adequate measures (Creplet et al., 2001).

What these diverse situations all have in common is the problem of knowledge asymmetry (Sharma, 1997) that has to be resolved through interpersonal communication. While the manager typically has the authority to make strategic or tactical decisions, he or she often lacks the specialized expertise required to make an informed decision on a complex issue (Watson, 2004). Because of the wide scope of decisions that need to be made, a manager frequently has to delegate the decision preparation to experts who – based on their professional training and previous experience – can analyze complex situations or technological options in a more reliable manner. The results of such analyses then need to be communicated back to the manager, often under considerable time constraints. The knowledge communication challenge, however, begins long before that, at the time when the manager has to convey his or her knowledge needs and decision constraints to the experts in order to delegate the analysis task effectively.

2. BACKGROUND: THE CONCEPT OF KNOWLEDGE COMMUNICATION Based on the reasoning described in the previous section, we define knowledge communication as the (deliberate) activity of interactively conveying and co-constructing insights, assessments, experiences, or skills through verbal and non-verbal means. Knowledge communication has taken place when an insight, experience or skill has been successfully reconstructed by an individual because of the communicative actions of another. Knowledge communication thus designates the successful transfer of know-how (e.g., how to accomplish a task), know-why (e.g., the cause-effect relationships of a complex phenomenon), know-what (e.g., the results of a test), and know-who (e.g., the experiences with others) through face-to-face (co-located) or media-based (virtual) interactions. This type of knowledge communication can take place synchronously or asynchronously1. The first mode of communication refers to (often face to face) real-time interactions, while the latter designates delayed (usually media-based) interactions.

We use the term knowledge dialogues for the first type of (synchronous) knowledge communication, stressing the interactive and collaborative style of knowledge exchange in this communication mode (see Isaacs, 1997, Nonaka et al., 2000). Depending on the knowledge-focused goal of such dialogues, we distinguish among Crealogues (that focus on in the creation of new insights), Sharealogues (facilitating knowledge transfer), Assessalogues

1

Both modes can be used in one-to-one or one-to-many contexts. Both modes can rely on speech, text, graphics, and other means of communication (i.e., verbal and non-verbal).

2

(focusing on the evaluation of new insights) and Doalogues (e.g., turning understanding into committed action, i.e., ‘talk the walk’). Each type of knowledge dialogue requires different behavior and interaction patterns and support measures (e.g., whereas Assessalogues require critical, convergent evaluation tools, Crealogues require an open atmosphere for divergent thinking and rapid idea generation without judgment).

With regard to asynchronous knowledge communication, we refer to the concept of knowledge media (see Eppler et al., 1999) that enable knowledge transfer through technology-based communication, collaboration, e-learning, aggregation, retrieval and archiving services. Knowledge media can be differentiated in terms of their target community, e.g., scientific knowledge media, public knowledge media, professional knowledge media, etc. The concept of knowledge media in general stresses the importance of a community that collaborates regularly using a common platform that consists not only of IT-functionalities, but also of common communication norms and (usage) rules.

In this understanding, knowledge communication is more than communicating information (e.g., facts, figures, events, situations, developments, etc.) or emotions (e.g., fears, hopes, reservations, commitment) because it requires conveying context, background, and basic assumptions. It requires the communication of personal insights and experiences. Communicating insights requires the elicitation of one’s rationale and reasoning (i.e., one’s argumentation structure), of one’s perspective, ratings and priorities, and of one’s hunches and intuition. At times it may even be necessary to present an overview of the expert’s relevant skills along with his/her previous professional experiences and credentials (Lunce et al., 1993) in order to build trust and enable an adequate atmosphere for effective knowledge transfer. Thus, in addition to pure information (and at times emotion), a myriad of other indicators need to be provided in order to transfer knowledge. These indicators help the person who requires insights from another to understand the other’s perspective, to re-construct the other’s insights correctly, and to connect them to one’s own prior knowledge.

Still, knowledge communication does not only differ in terms of what is communicated (knowledge in context rather than isolated data or information2), but also how one communicates. The transfer of information can often be successful without additional effort beyond an ordinary, every day communication style. Communicating expertise-based, complex insights, by contrast, calls for didactic tricks and at times sophisticated indirect speech acts and visualization means that help the other side to become actively involved in the 2

Our distinction between data, information, and knowledge follows the main stream conception found in current literature (see for example Davenport & Prusak, 1998). We view data as isolated recordings that are often generated automatically and cannot be directly used to answer questions. Information is connected, condensed or generally processed data that allows an individual to answer questions. Knowledge is what enables an individual to ask relevant questions (Newman and Newman, 1985, p. 499). It refers to the capability of an individual to solve problems (Probst et al., 1999). Information only becomes knowledge, if a person interprets that information correctly, connects that piece of information with his or her prior knowledge, and can apply it to problems or decisions (see also Alavi & Leidner, 2001)

3

communication and engage in a collaborative, goal-directed sense making process – a prerequisite for the construction of new knowledge (see Weick, 1995). The process of knowledge communication hence requires more reciprocal interaction between decision makers and experts because both sides only have a fragmented understanding of an issue and consequently can only gain a complete comprehension by iteratively aligning their mental models. All of this means that when we communicate knowledge, we are still communicating information and emotions, but we also create a specific type of context so that this information can be used to re-construct insights, create new perspectives, or acquire new skills.

This (interpersonal) communication perspective on knowledge transfer has already been emphasized by other researchers – who explicitly label this view as ‘knowledge communication’ – (Scarbrough, 1995, p. 997; Antonelli, 2000; Harada, 2003; Reiserer et al., 2002) and by several practitioners (e.g., Watson, 2004). Nevertheless, these authors have often treated knowledge communication as a kind of black box that is described only in broad terms and general traits, such as the major communication goals or steps. By examining the communication problems which often impede knowledge transfer in detail, we can look into this black box and propose pragmatic ways of improving knowledge communication, especially among experts and managers where the chasm between in-depth knowledge and decision authority is particularly apparent.

3. PROBLEMS IN COMMUNICATING KNOWLEDGE AMONG EXPERTS AND DECISION MAKERS

In order to better understand the problems that can impede the effective transfer of decision-relevant knowledge from experts to managers and from managers to experts, we will review relevant constructs and prior findings from social and engineering sciences, as there are in fact numerous concepts that describe issues related to sub-optimal knowledge transfer. These concepts regard topics such as interdepartmental knowledge transfer, professional communication, decision making, communication technology, or the nature of expert knowledge. By screening these disciplines and topic areas, we can establish a first overview of possible knowledge communication problems and we can create a systematic terminology to speak more explicitly (and consistently) about knowledge communication barriers.

Previously identified barriers of knowledge communication are summarized in Table 1. There are three main criteria for including concepts in this table: first, the concept has to be closely related to problems of interpersonal, professional knowledge transfer3. Second, the concept

3

The concept does not have to originate in the context of interpersonal communication research, but its application to it must be obvious and fruitful, as in the example of the ASK problem. The ASK problem was

4

has to describe a problem of major impact on the quality of knowledge transfer (rare or very specific issues are not included). Third, the concept has to be influential, i.e., it has to be cited with the same construct label by several authors (other than the creator of the concept). The resulting list in Table 1 first includes ‘umbrella’ concepts that designate a group of closely related problems, such as cognitive biases, decision making problems, argumentation fallacies, communication biases, or defensive routines, and then concepts that label individual problems, such as the not-invented here syndrome or the ASK problem. The ‘Impact on’ column designates whether the particular concept is mostly a weakness of decision makers or of experts, or for both professional groups.

Table 1: Key research concepts that illustrate knowledge communication barriers

Key Concept / Knowledge Communication Barrier

Absorptive capacity

Description

Limited ability of decision makers to grasp the knowledge of the expert based on lack of prior knowledge.

Impact on

Decision makers

References

Bower and Hilgard, 1981; Cohen & Levinthal, 1990

In demonstrating one’s ideas and insights, people Experts and decision Van Argumentation fallacies (begging the question, fall into argumentative traps, such as begging the makers Eemeren et overgeneralizing, personal question (circular reasoning), over-generalizing, al., 1992 attacks, defective testimony, appealing to false majorities or false expertise, problematic premise, slippery reasoning ad consequentiam (what shouldn’t be slope, red herring, etc.) true, can’t be true) or reacting with direct attacks

at a person (at hominem) rather than at a knowledge claim.

Anomalous State of Knowledge: when a decision Decision makers Belkin, ASK problem

maker does not have the knowledge base to really 1980 ; Chen know what to ask for. People need to know quite et al., 1992 a bit about a topic to be able to ask or search for relevant information.

The decision makers do not give sufficient weight Decision makers Mikalachki, Cassandra syndrome

or attention to an expert’s warning because they 1983 face many other important problems. Only when the situation has deteriorated dramatically do they start taking the expert’s advice.

Knowledge may not be correctly interpreted or Experts and decision Tversky & Cognitive biases (confirmation, availability, used due to biases in one’s reasoning, such as maker Kahnemann, recency, dichotomized listening only to those insights that confirm one’s 1974 reasoning, framing, anchoring, prior opinion. representativeness, etc.)

The tendency of a group to focus merely on Experts and decision Gigone & Common knowledge effect

commonly shared (rather than unique) pieces of makers Hastie, 1993information.

The knowledge is inadvertently manipulated Experts and decision Higgins, Communication biases

(audience tuning, through communication itself: makers 1999 misattribution bias, saying-is-- Audience Tuning: Communicators believing, shared reality) spontaneously tune their messages to:

–the personal characteristics of the audience –the situational factors

–Misattribution Bias: Communicators tend to consider their audience-tuned messages to be about the topic of the message rather than about the audience

- Saying-Is-Believing Effect: Auto-persuasion has

first discussed in the information retrieval community, but it has ramifications for interpersonal knowledge

communication as well.

5

stronger effects because one does not activate regular mechanisms of critical reflection. - Shared Reality: You consider your audience-tuned message to provide objective, accurate information on the message topic because it was shared with others.

Decision problems such as The decision maker may for example believe that plunging in, shooting from the he/she can make a complex decision right away hip, poor feedback, taking without looking further at the provided analysis. shortcuts, frame blindness etc. Defensive routines (skilled New knowledge is sometimes not accepted (or incompetence, learned provided) due to mechanisms or habits that helplessness, easing-in, etc.) prevent the identification and acceptance of one’s

own ignorance. This may lead to a reduced effort to understand complex issues (learned helplessness).

Sometimes experts indicate other rules than they Expert inconsistency

actually apply in their problem solving.

We assume others see situations as we do, and fail False consensus effect

to revise our framing.

Decision makers

Russo & Shoemaker, 1989 Argyris, 1986, 1990

Decision makers

Experts Johnson, 1983

Decision makers Manzoni &

Barsoux, 2002

A (management) team may not truly listen to the Decision makers Janis, 1982 Groupthink

input of an expert because of the team’s group coherence and group dynamics sometimes block outside advice and feel omniscient. One often doesn’t know other people's Decision makers Stasser Hidden profile problem

background (profile), i.e., what they know and 1992; could contribute to a problem’s solution. The Stasser & knowledge that is thus frequently shared in a Stewart, discussion is what is expected by everyone. 1992 The knowledge that the decision maker has Decision makers Whitehead, Inert knowledge

acquired from the expert does not come to mind 1929 when it is needed or useful for decision making or actions. The transferred knowledge is stuck in the situation where it has been acquired.

An individual is sometimes not able to integrate Decision makers O’Reilly, Information overload

new information into the decision making process 1980, Eppler because too much complex information has to be & Mengis, interpreted too quickly. 2004

Decision makers Blau, 1977 Ingroup outgroup behavior We tend to interact more with likewise groups

than with others thus reducing our changes to acquire radically new knowledge.

Knowledge can sometimes not be transferred Decision makers Szulanski, Internal knowledge because of arduous relationships or casual 1996, 1999 stickiness

ambiguities regarding the knowledge or because of the lack of absorptive capacity of the knowledge receivers.

Pfeffer & Knowing-Doing gap / Smart Sometimes organizations know where a problem Decision makers

resides and how to tackle it, but do not move from Sutton, 2000talk trap

knowledge to action (due to unhealthy internal competition or lacking follow-up).

A number of factors have been found which limit Decision makers Zaltman, Knowledge disavowal

information use in organizations, such as not 1983;

Deshpande spending enough time collecting advice, refusal to

& Kohli, share, fear of exposure, etc. Knowledge disavowal

occurs when reliable and relevant information is 1989 not shared among decision makers.

& Knowledge sharing hostility Knowledge communication fails because the Experts Husted ‘knowledge giver’s are reluctant to share their Michailova, insights due to micropolitics, strenuous 2002 relationships, or due to fear.

Common ground refers to the manager’s and Experts and decision Clark & Lack of common ground

expert’s assumptions about their shared makers Schaefer, background beliefs about the world. If those 1989, Olson assumptions are wrong or inconsistent & Olson, communication becomes more difficult. 2000 The ‘knowledge claims’ of an expert are Decision makers Lazega, Micropolitics of knowledge

discredited by the decision makers due to their 1992

6

differing (hidden) agenda, because of a coalition of people with an alternative view, or due to the expert’s lack of formal authority.

Because of an inadequate understanding of the Decision makers Cantoni & Mutism

role and capabilities of an expert, the decision Piccini, maker does not articulate his suggestions, but 2004 remains quiet when asked about his expectations or needs.

Negative transfer occurs when knowledge from Expert Van Lehn Negative Transfer

one area of expertise is incorrectly applied in a 1998 different problem solving domain

Katz & Not-Invented here syndrome Knowledge from others is sometimes rejected Decision makers

because it originated elsewhere. Allen, 1982

Experts Hinds 1999; Paradox of expertise / Curse Experts sometimes find it difficult to articulate

their knowledge or rephrase their insights in a Johnson, of Knowledge

way that non-experts can relate to. An insight 1983 seems to them self-evident whereas for others it is in fact difficult to grasp.

This is the opposite of the NIH syndrome and Decision makers Menon & Preference for outsiders

describes the tendency of managers to value Pfeffer, outside knowledge higher than internal 2003 knowledge because it has a higher status, it is scarcer (because of difficult access) and because it is less scrutinized for errors than internal knowledge.

In the communication of his or her analysis Experts Cantoni & Projectionism

results, the expert does not tailor his insights to Piccini, the knowledge of the decision maker, as he 2004 assumes that the target group already has a similar understanding of an issue.

Individuals tend to discount advice and favor their Decision makers Yaniv & Self/Other effect

own opinion. Kleinberger,

2000

Managers are projecting their initial expectation Experts and decision Manzoni & Set-up to fail syndrome

of an expert’s likely performance unto him/her, makers Barsoux, leading to the self-fulfilling prophecy of (at times) 2002 lower performance. This is aggravated by de-motivating feedback to the expert.

In our communication, we may choose to use a Decision makers Straub & Task closure

one way communication medium because it Karahanna, permits us to close an open task without having to 1998; have a conversation. Thus leaner communication Meyer, 1962channels are used than may be necessary. In other words: We tend to want to close a communication process in order to complete an open task. Experts tend to overestimate the notoriety of Experts Rambow Terminology Illusion

terms at the limits of every day language and 2000 specialized language. In consequence they overestimate the level of understanding of non-experts of what they communicate.

The problems listed in Table 1 are neither mutually exclusive nor collectively exhaustive. Nevertheless, Table 1 summarizes many of the key pitfalls in communicating knowledge. It is in the nature of the phenomenon that these problems are not isolated, but that they rather interact in many, sometimes unpredictable ways.

Based on the concepts from Table 1, and based on ten focus groups4 and ten personal interviews with engineers that frequently collaborate with managers in their companies, as 4

Each focus group lasted for approximately one hour and consisted of 12-20 participants. The focus groups were conducted in 2002 and 2003 in Switzerland and Germany with engineers and IT specialists from eight

7

well as interviews with 20 IT managers5 who regularly interact with experts for their decision making, we distinguish among five types of knowledge communication problems. These are briefly summarized below, followed by examples of each type of problem, cited from both experts and managers.

The first type of knowledge communication problems is expert-caused difficulties. These mistakes make it cumbersome for the decision maker to grasp the insights of a specialist. This type of problem also includes issues that make it difficult for the manager to explain his or her own constraints and priorities. Examples of this kind of problem are the use of overly technical jargon, not relating the insights to the manager’s situation, starting with details before an overview is given or lacking interest of the expert in related (but relevant) issues. From the list provided in Table 1, knowledge-sharing hostility and the paradox of expertise clearly belong to this category.

The second type of knowledge communication challenges is manager-caused problems that leave it unclear to the expert what the manager actually expects from him/her (briefing). This makes it difficult for the expert to convey what he or she knows. Management mistakes make it harder for the manager to fully profit from the offered expertise. For example, a manager’s reluctance to discuss detailed problems may have major effects on an issue, such as lack of concentration and attention or lack of technical know-how. From the list in Table 1 the decision problems, the ASK problem, the Cassandra syndrome or the inert knowledge problem are typical examples of this group.

The third type of knowledge communication problems are caused by the mutual behavior of experts and managers, including their experiences or attitudes (e.g., reciprocal stereotypes and role misunderstandings). Examples from the list of concepts that belong to this group are lacking feedback on both sides, the set-up to fail syndrome, groupthink, and ingroup outgroup behavior on both sides.

Fourth, we see problems caused by the interaction situation of the expert-manager interaction, such as time constraints, communication infrastructure, distractions, interventions from others, etc. The problem of information overload in Table 1 can arise due to the time constraints in a communication situation. But the hidden profile problem can also be due to the communicative situation, where the background of the participants is not fully revealed or discussed at the beginning of a manager-expert interaction.

companies (each employing more than 1000 people). Focus group facilitation and documentation was

provided by the research team. The topic of the focus group discussion was “communication problems among engineers/specialists and managers”. 5

Each interview lasted between 30 minutes to two hours. Interviewees were mostly senior IT managers or chief information officers of medium-sized and large Swiss companies, as well as select line managers with

8

The fifth and final type of knowledge communication problems includes issues that are caused indirectly by the overall organizational context of managers and experts, such as their organizational constraints and their differing tasks, priorities and interests. The ‘micropolitics of knowledge’ concept listed in Table 1 would be an example of the (negative) impact of the organizational context on the transfer of knowledge.

CONCLUSION AND FUTURE TRENDS

Many studies in knowledge management examine the structural, macro aspects of knowledge transfer on an organizational level (Szulanski, 1999). There are also studies that examine the general motivational barriers to such transfers (Husted & Michailova, 2002). The field of knowledge communication, by contrast, examines the micro perspectives of knowledge transfer, thus highlighting the role of adequate or inadequate communication behavior patterns for knowledge transfer. These examined patterns go beyond the question of motivation and encompass issues such as the use of adequate language, timing, group interventions, or media use for knowledge transfer. This article has defined this approach as knowledge communication. It has outlined the various problems that exist when individuals (particularly experts) communicate their knowledge to others (e.g., managers). This problem jostle can lead to improved communication knowledge for knowledge communication (Hägglund et al, 1992). Future knowledge management research should build on these insights and examine ways of facilitating and thus improving knowledge communication. This can be achieved through such tools as knowledge visualization suites, dialogue techniques, or knowledge elicitation methods. In doing so, future research should pay particular attention to the influence of (expert and manager) behavior and to situational and organizational factors that affect the quality of knowledge communication.

REFERENCES

Alavi, M., Leidner, D. (2001). Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues. MIS Quarterly. 25(1), 107-136.

Alvesson, M. (1993). Organizations As Rhetoric: Knowledge-Intensive Firms And The Struggle Of Ambiguity. Journal of Management Studies. 30(6), 997-1020.

Antonelli, C. (2000). Collective Knowledge Communication and Innovation: The Evidence of Technological Districts. Regional Studies. 34(6), 535-547.

Argyris, C. (1990). Overcoming Organizational Defenses, Prentice-Hall, New York, NY.

Argyris, C. (1986). Skilled Incompetence. Harvard Business Review. 64(5), 74-79.

Belkin, N.J. (1980). Anomalous states of knowledge as a basis for information retrieval. Canadian Journal of Information Science. 5, 133-143.

considerable experience. The main topic of the interviews was “problems in the knowledge communication

with specialists.”

9

Blackler, F. (1995). Knowledge, Knowledge Work and Organizations. Organization Studies. 16(6), 1021-1046.

Blau, P.M. (1977). Inequality and heterogeneity: A primitive theory of social structure, New York: Free Press.

Boland, R.J., Singh, J., Salipante, R., Aram, J.D., Fay, S.Y., Kanawattanachai, P. (2001). Knowledge Representations and Knowledge Transfer. Academy of Management Journal. 44(2), 393-417.

Bower, G.H., Hilgard, E.R. (1981). Theories of Learning, Englewood Cliffs, New Jersey: Prentice-Hall.

Bouty, I. (2000). Interpersonal and Interaction Influences on Informal Resource Exchanges between R&D Researchers across Organizational Boundaries. Academy of Management Journal. 43(1), 50-65.

Bromme, R., Rambow, R., Nückles, M. (2001). Expertise and Estimating what other People Know: The Influence of Professional Experience and Type of Knowledge. Journal of Experimental Psychology. 7(4), 317-330.

Browne, G.J., Ramesh, V. (2002). Improving information requirements determination: a cognitive perspective. Information & Management, 39, 625-645.

Cantoni, L., Piccini, C. (2004) Il sito del vicino è sempre più verde. Milan: Franco Angeli.

Chen, H. (1994). Collaborative systems: Solving the vocabulary problem. IEEE Computer. May, 58-69.

Clark, H. H., & Schaefer, F. S. (1989). Contributing to discourse. Cognitive Science. 13, 259–294.

Creplet, F., Duouet, O., Kern, F., Mehmanzapir, B., Munier, F. (2001). Consultants and experts in management consulting firms. Research Policy. 30, 1517-1535.

Davenport, T., Prusak, L. (1998). Working Knowledge: How Organizations Manage What They Know, Boston: Harvard Business School Press.

Deshpande, R., A. K. Kohli (1989). Knowledge disavowal: Structural determinants of information processing breakdown in organizations. Knowledge. 11(2), 155-169.

Eemeren, van H., Grootendorst, R. (1992). Argumentation, Communication, and Fallacies: A Pragma-Dialectical Perspective, Lawrence Erlbaum.

Eppler, M., Röpnack A., Seifried P. (1999). Improving Knowledge Intensive Processes through an Enterprise Knowledge Medium. Prasad, J. (Ed.): Proceedings of the 1999 ACM SIGCPR Conference ‘Managing Organizational Knowledge for Strategic Advantage: The Key Role of Information Technology and Personnel’, 222-230.

Eppler, M., Mengis, J. (2004). The Concept of Information Overload. The Information Society – an International Journal. 20(5), 1-20.

Gigone, D., Hastie, R. (1993). The common knowledge effect: Information sharing and group judgment. Journal of Personality and Social Psychology. 65, 959-974.

Goldhaber, G.M., Yates, M.P., Porter, D.T., & Lesniak, R. (1978). Organizational communication, Human Communication Research, 5, 76-96.

Gratton L, Ghoshal S (2002). Improving the quality of conversations. Organizational Dynamics. 31, 209-223.

Gülich, E. (2003). Conversational techniques used in transferring knowledge between medical experts and non-experts. Discourse Studies. 5(2), 235-263.

Hagglund, S., Löwgren, J., Rankin, I., Sokolnicki. T. (1992) Communication knowledge for knowledge communication. Man-Machine Studies, 37, 215-239.

Harada, T. (2003). Three Steps in Knowledge Communication: the Emergence of Knowledge Transformers. Research Policy. 32, 1737-1751.

Higgins, T. (1999). Saying is Believing Effects: When Sharing Reality About Something Biases Knowledge and Evaluations, in: Thompson, L; Levine J.; Messick D. (Eds.) (1999) Shared Cognition in Organization: The Management of Knowledge, Mahwah: Erlbaum.

Hinds, P. J. (1999). The Curse of Expertise: The Effects of Expertise and Debiasing Methods on Predictions of Novice Performance. Journal of Experimental Psychology: Applied, 5(2), 205-221

Husted, K., Michailova, S. (2002). Diagnosing and Fighting Knowledge-Sharing Hostility. Organizational Dynamics. 31(1), 60-73.

10

Isaacs, W. (1997). Dialogue and the art of thinking together: A pioneering approach to communicating in business and in life, New York: Doubleday.

Janis, I. (1982). Groupthink: Psychological Studies of Policy Decisions and Fiascoes, Boston: Houghton Mifflin.

Johnson, P. E. (1983). What kind of expert should a system be? Journal of Medicine and Philosophy. 8, 77-97.

Katz, R., Allen, T. J. (1982). Investigating the Not Invented Here (NIH) Syndrome: A Look at the Performance, Tenure, and Communication Patterns of 50 R&D Project Groups. R&D Management ,12(1), 7-19.

Kirmeyer, S.L., Lin, T. (1987). Social Support: Its Relationship to Observed Communication with Peers and Superiors. Academy of Management Journal. 30(1), 151-162.

Lazega, E. (1992). Micropolitics of Knowledge. Communication and Indirect Control in Workgroups, New York: deGruyter.

Lunce, S.E., Iyer, R.K., Courtney, L.M., Schkade, L.L. (1993). Experts and Expertise: An Identification Paradox. Industrial Management and Data Systems. 93(9), 3-9.

Manzoni, J.-F., Barsoux, J.-L. (2002). The Set-up-to-fail Syndrome, How Good Managers Cause Great People to Fail, Cambridge: Harvard Business School Press.

McDermott, R. (1999). Learning across Teams. Knowledge Management Review. 8, 32-36.

McLeod, J.M., Chaffee, S.H. (1973). Interpersonal Approaches to Communication Research. American Behavorial Scientist. 16(4), 469-499.

Menon,T., Pfeffer, J. (2003). Valuing Internal vs. External Knowledge: Explaining the Preference for Outsiders. Management Science. 49(4), 497-513.

Meyer, R.L. (1962). A Communications Theory of Urban Growth, Boston: MIT Press .

Mikalachki, A. (1983). Does anyone listen to the boss? Business Horizons. January-February, 18-24.

Newman, J., Newman, R. (1985). Information work: the new divorce? British Journal of Sociology. 24, 497-515.

Nonaka, I., Toyama, R., Konno, N. (2000). SECI, ba and leadership: a unified model of dynamic knowledge creation. Long Range Planning. 33, 5-34.

Olson, G., Olson, J. (2000). Distance Matters. Human-Computer Interaction. 15(2-3), 107-137.

O’Reilly, C. A. (1980). Individuals and information overload in organizations: Is more necessarily better? Academy of Management Journal. 23, 684-696.

Pfeffer, J., Sutton, R.I. (2000). The Knowing-Doing Gap: How Smart Companies Turn Knowledge into Action, Boston: Harvard Business School Press.

Probst, G., Romhardt, K., Raub, S. (1999). Managing Knowledge: Building Blocks for Success, London: Wiley.

Rambow, R.: (2000). Experten-Laien-Kommunikation in der Architektur. Münster, Waxmann

Reiserer, M., Ertl, B., & Mandl, H. (2002). Fostering collaborative knowledge construction in desktop videoconferencing. Effects of content schemes and cooperation scripts in peer teaching settings. Paper presented at the International Workshop on Barriers and Biases in computer-mediated knowledge communication - and how they may be overcome, Münster, Germany.

Rosenthal, U., ‘t Hart (1991) Experts and Decision Makers in Crisis Situation, in Knowledge: Creation, Diffusion, Utilization, 12(4,) June 1991, 350-372.

Russo, J. E., Shoemaker, P.J.H. (1989). Decision Traps, New York: Simon and Schuster.

Scarbrough, H. (1995). Blackboxes, Hostages and Prisoners. Organization Studies. 16(6), 991-1019.

Schindler, M., Eppler, M. (2003). Harvesting Project Knowledge: A Review of Project Learning Methods and Success Factors. International Journal of Project Management. 21, 219-228.

Sharma, A. (1997). Professional as Agent: Knowledge Asymmetry in Agency Exchange. Academy of Management Review. 22(3), 758-798.

11

Starbuck, W.H. (1992). Learning by Knowledge-Intensive Firms. Journal of Management Studies. 29, 147-175.

Stasser, G., & Stewart, D. (1992). Discovery of hidden profiles by decision-making groups: Solving a problem versus making a judgement. Journal of Personality and Social Psychology. 63, 426–434.

Stasser, G., Stewart, D. D., Wittenbaum, G. M. (1995). Expert roles and information exchange during discussion: The importance of knowing who knows what. Journal of Experimental Social Psychology, 31, 244–265.

Straub, D., Karahanna, E. (1998). Knowledge Worker Communications and Recipient Availability: Toward a Task Closure Explanation of Media Choice. Organization Science. 9(2), 160-175.

Szulanski, G. (1996). Exploring Internal Stickiness: Impediments to the Transfer of Best Practices within the Firm. Strategic Management Journal. 17, Winter Issue: 27-43.

Szulanski, G. (1999). The process of knowledge transfer: a diachronic analysis of stickiness. Organizational Behavior and Human Decision Processes. 82(1), 9-27.

Tversky, A., Kahnemann, D. (1974). Judgement under uncertainty: Heuristics and biases, Science, 1.185, 1124-1131.

Tsoukas, H. (1996). The Firm as a Distributed Knowledge System: A Constructionist Approach. Strategic Management Journal. 17, 11-25.

Van Lehn, K. 1989, Problem Solving and cognitive skill acquisition, in Posner, M. Foundations of cognitive science, 572-580: Cambridge: Bradford Books, MIT Press.

Vaughan, D. (1997). The Challenger Launch Decision, Chicago and London: The University of Chicago Press.

von Krogh, G., Roos, J. (1995). Organizational Epistemology, New York, NY: St. Martin's Press.

Watson, C.M. (2004). Don‘t blame the engineer. Sloan Management Review. Winter, 26-29.

Weick, K.E. (1995) Sensemaking in Organizations. Thousand Oaks: Sage Publications.

Whitehead, A. N. (1929). The Aims of education and other essays. New York: McMillan.

Wilmotte, R.M., Morgan, P.I. (1984). The Discipline Gap in Decision Making. Management Review. September, 21-24.

Yaniv, I., Kleinberger, E. (2000). Advice taking in decision making: Egocentric discounting and reputation formation. Organizational Behavior and Human Decision Processes, 83, 260-281.

Zaltman, G. (1983). Knowledge Disavowal in organizations. In: Kilmann, R.H., Thomas, K.W., Slevin, D.P., Nath, R., Jesell, S.L. (Eds.): Producing useful knowledge for organizations, New York: Praeger, 173-187.

12