Knowledge manipulation activities: results of a Delphi study
Introduction
A hallmark of the emerging knowledge economy is the rise of knowledge-based organizations [14]. In these, knowledge is regarded as a crucial resource processed by a joint human–computer system in changing the organization’ state of knowledge and of producing outputs. Individually, each human or automated processor is a knowledge worker that has a particular set of skills for manipulating knowledge. Collectively, an organization’ knowledge processors are arranged into a system that amplifies the knowledge work to be accomplished.
Knowledge management (KM) involves attempts to get the right knowledge to the right processor at the right time in the right representation and at the right cost. The task of recognizing and satisfying the needs of a modern organization is both important and challenging. These can be modest or voluminous, simple or complex, routine or novel, well specified or vague, stable or volatile, of low priority or urgent. We shall term what occurs from the time of recognizing a knowledge need through its satisfaction (or abandonment) as a KM episode which may be independent or interdependent with other episodes and active at any given time in an organization. Each involves one or more knowledge processors operating on some knowledge resources and constrained or guided by various influences.
Fig. 1 illustrates a KM episode. But what knowledge manipulation activities are allowed in a KM episode? The answer to this question is important. Indeed, a recent survey found that a majority of respondents preferred an activity-oriented KM [20]. However, there has been little agreement among researchers or practitioners on what they are [29].
This paper presents a descriptive framework of basic knowledge manipulation activities that can occur in an episode. The framework was developed through a Delphi process involving an international panel of over 30 KM researchers and practitioners. The result is a relatively comprehensive, unified perspective on the kinds of knowledge manipulation activities that can occur in a KM episode. This offers several benefits. It can serve as a common language for discussion about an organization’s KM episodes. It gives a foundation for suggesting how each of the knowledge manipulation activities should be accomplished and how they should be configured within episodes. Its characterization of each manipulation activity is suggestive of functionalities that would be helpful to include in the design of computer-based processors for performing or supporting the activity. It could be applied to highlight and investigate KM issues, such as a means for measuring, controlling, and coordinating manipulation activities, etc.
Section snippets
Background
A comparative analysis of KM frameworks in the literature indicates that they identify various KM activities [11]. These are summarized in Table 1. Some frameworks treat these activities at an elemental level, while others deal with higher-level knowledge activities. For instance, the activities identified by Arthur and APQC [2], Wiig [31], van der Spek and Spijkervet [30], Alavi [1], and Szulanski [28] appear to be more elemental than those identified by Leonard-Barton [17], and Choo [6]. The
Methodology
Through a synthesis of concepts, best practices, and issues in the literature, an initial descriptive framework of knowledge manipulation activities was developed. This evolved through a Delphi process, involving two rounds of critique and evaluation by a panel of KM practitioners and academicians.
A descriptive framework of knowledge manipulation activities
The conduct of KM in an organization results in learning and projection, thereby adding value. The conduct of KM is guided and shaped by managerial influences; enabled and constrained by environmental influences and organizational resources. In a KM episode, processors use their knowledge handling skills to perform manipulation on knowledge resources. That is, the mechanisms and results of knowledge manipulation activities are expressions of processors’ knowledge manipulation skills. Skill is
Analysis of Delphi responses
In examining panelist reactions to the framework, no major or crippling reservations were detected. However, several concerns related primarily to pushing beyond framework boundaries were expressed.
- 1.
Three of the 17 respondents had reservations about referring to generation (or some aspect of generation) as a kind of use activity. Some were unclear about the interplay of generation and externalization.
Comment: This is largely a presentational issue. The use activity can be further explained to
Implications
This paper presents a generic framework of basic knowledge manipulation activities that operate on an organization’s knowledge resources with KM episodes. Identification and explanation of knowledge manipulation activities and their inter-relationships allows for better understanding of the nature and the dynamics of activities that manipulate an organization’ knowledge resources.
Each of the four knowledge manipulation activities and any of their sub-activities can be further characterized an
Acknowledgements
Funding for this research was provided by Kentucky Initiative for Knowledge Management. We are indebted to the following persons for their participation as Delphi panelists. Those who participated in every round are indicated by an asterisk (∗).∗Debra Amidon ENTOVATION International, Ltd., USA Sulin Ba University of Southern California, USA ∗Thomas J. Beckman George Washington University & IRS, USA Kesper Deboer Andersen Consulting, USA Marc Demarest The Sales Consultancy, USA ∗Alain Godbout Godbout
Clyde W. Holsapple has held the Rosenthal Endowed Chair in MIS and directed the Kentucky Initiative for Knowledge Management for more than a decade. He has served as editor of the Journal of Organizational Computing and Electronic Commerce, area editor of Decision Support Systems and the ORSA Journal on Computing, and associate editor of Management Science. He is editor of Springer’s new Handbook on Knowledge Management. His earlier books include Decision Support Systems: A Knowledge-Based
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Clyde W. Holsapple has held the Rosenthal Endowed Chair in MIS and directed the Kentucky Initiative for Knowledge Management for more than a decade. He has served as editor of the Journal of Organizational Computing and Electronic Commerce, area editor of Decision Support Systems and the ORSA Journal on Computing, and associate editor of Management Science. He is editor of Springer’s new Handbook on Knowledge Management. His earlier books include Decision Support Systems: A Knowledge-Based Approach, The Information Jungle: A Quasi-Novel Approach to Managing Corporate Knowledge, Business Expert Systems, and Foundations of Decision Support Systems. Dr. Holsapple has published over 100 scholarly articles.
Kshiti D. Joshi is an Assistant Professor in the School of Accounting, Information Systems, and Business Law at Washington State University. She holds a BA in Mathematical Statistics and an MA in Operational Research from the University of Delhi. She also earned an MS degree in Industrial and Operations Engineering from the University of Michigan. Dr. Joshi holds a PhD in Decision Science and Information Systems from University of Kentucky. Her research articles have been accepted for publication in Decision Support Systems, Information Systems Journal, The Information Society, Knowledge Management Handbook, and Handbook of Electronic Commerce, Journal of Strategic Information Systems. She has been awarded an NSF grant to study gender differences in information systems career choice.