Brent Gallupe

Knowledge management systems: surveying the landscape

Knowledge management systems (KMS) are the tools and techniques that support knowledge-management practices in organizations. The study of these systems consists of a small but growing body of literature. In the last two years alone, at least four books, two special editions of journals and a number of academic and practitioner articles have been published related to this area. However, much of the work that has been published has been in the form of isolated survey studies, or anecdotal case studies into particular aspects of KMSs. This has made it difficult to build a cumulative body of knowledge into the development, use and management of these systems. The purpose of this paper is to ‘survey the current landscape’ of KMSs, and provide a framework for research into the development and use of these systems in organizations. The intent is to highlight areas where ‘gaps’ exist in what we know about KMSs and suggest ways to close those gaps.

A Cognitive Three-Process Model of Computer-Mediated Group Interaction

Current theories imply text-based computer networks are socially barren, but computer-mediated interaction (CMI) research contradicts this. A cognitive perspective suggests individuals in groups construct cognitions regarding the task (purpose), other people (relationships), and the group (identity), and these drive the interaction. Three core psychological process follow: resolving task information, relating to others and representing the group. This gives three types of influence: informational, personal and normative, and three group purposes: task resolution, interpersonal relationships and group unity. Group unity occurs when group members represent a common identity. The traditional communication threads of message content and sender context therefore require a third - behavioural position. Many-to-many exchange of member positions allows the group position to be transmitted to the group. A picture emerges of three parallel processes overlapping in behaviour, although CMI allows them to be isolated and investigated. This model extends most theories of computer-mediated group interaction. It implies there is no “best” type of group interaction support, because there is no best process. The groupware challenge is to offer the flexibility to support all three processes in combination.

‘I’m busy (and competitive)!’ Antecedents of knowledge sharing under pressure

This study considers the dilemma faced by employees every time a colleague requests knowledge: should they share their knowledge? We use adaptive cost theory and self-efficacy theory to examine how individual characteristics (i.e., self-efficacy and trait competitiveness) and situational perceptions (i.e., ‘busyness’ and perceived competition) affect knowledge sharing behaviours. A study was conducted with 403 students who completed a problem-solving exercise and who were permitted (but not required) to respond to requests for knowledge from people who were doing the same activity. Our results suggest that people who perceive significant time pressure are less likely to share knowledge. Trait competitiveness predicted perceived competition. This and low task self-efficacy created a sense of time pressure, which in turn led to people feeling ‘too busy’ to share their knowledge when it was requested. Perceived competition was not directly related to knowledge sharing. Implications for research and practitioners are discussed.

Generating agreement in computer-mediated groups

Agreement is an important social outcome often poorly handled by computer-mediated groups, presumably because the computer cannot transmit the necessary rich information. A recently proposed cognitive model suggests richness is not the key to social agreement and that group agreement can be generated by the exchange of anonymous, lean text information across a computer network. This experiment investigates this theory. Self-chosen groups of 5 completed three answer rounds on limited choice problems while exchanging a few characters of position information. These asynchronous, anonymous computer-mediated groups generated agreement without any rich information exchange. The key software design criteria for enacting agreement is proposed to be not richness but dynamic many-to-many linkage. The resulting “electronic voting” may be as different from traditional voting as e-mail is from traditional mail. It may also imply a new generation of groupware that recognizes social influence.

Action learning and groupware technologies: a case study in GSS facilitation research

Effective meeting facilitation is recognised as a critical factor in group support systems (GSS) use but relatively little is known about how organisations can train and develop their “electronic meeting facilitators”. This article describes an action learning (AL) approach to the training of GSS facilitators. It begins with a description of the three schools of AL. The application of the “experiential” school of AL in GSS facilitation training is then explained. Finally, the article describes some lessons learned for both practitioners and researchers.

The emergence of a theoretical framework for gss facilitation: The dualities of e‐facilitation

Electronic meeting facilitation (e‐facilitation) continues to be a critical success factor in the use of information technology to support face‐to‐face collaborative work. Yet researchers and practitioners continue to struggle to understand the subtleties and difficulties in the application of meeting facilitation techniques in the ‘electronic’ context. To clarify that understanding, this paper develops a new theoretical framework that examines how technology interacts with human facilitator behavior in an electronic group meeting. This framework, The Dualities of E‐Facilitation, is composed of two dualities: the Duality of Computer and Human Interaction, and the Duality of Routine and Intuitive Actions. The framework emerged from an analysis of the e‐facilitation behaviors of newly trained face‐to‐face electronic meeting facilitators.

Generating Data for Research on Emerging Technologies

One of the difficulties of conducting applied qualitative research on the applications of emerging technologies is finding available sources of relevant data for analysis. Because the adoption of emerging technologies is, by definition, new in many organisations, there is often a lack of experienced practitioners who have relevant background and are willing to provide useful information for the study. Therefore, it is necessary to design research approaches that can generate accessible and relevant data. This chapter begins with a description of action learning and its application to the training of e-facilitators. It will also explain the differences between action learning and action research. The chapter will then describe two case studies in which the researchers used an action learning approach to study the nature of e-facilitation for face-to-face and for distributed electronic meetings. Finally, the chapter describes some lessons learned for both practitioners and researchers.