Knowledge Sharing Model of 24-Hour Knowledge Factory

Knowledge Sharing Model of 24-Hour Knowledge Factory

Huosong Xia (Wuhan University of Science & Engineering, China) and Amar Gupta (University of Arizona, USA)
DOI: 10.4018/978-1-60960-783-8.ch209

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1. Introduction

In today’s rapidly changing business environment, we have entered a new era of knowledge management; humans must now live and work in a knowledge-based society as knowledge workers (Drucker, 1993). Various streams of knowledge management (KM) research have emerged. Early research focused on understanding the differences among data, information, knowledge and classifications, such as tacit versus explicit knowledge (Polanyi, 1962; Nonaka, 1995), and individual versus collective knowledge (Spender, 1996). Other research has viewed knowledge as a source of competence and as a competitive resource (Hung et al., 2001). A goal of many KM initiatives is to develop a global knowledge community where knowledge is shared and utilized within the community. However, knowledge sharing is inherently a difficult process, and only partial knowledge fragments can be created and shared. Information technology (IT) has been long thought of as a way to facilitate sharing of knowledge; indeed, the use of IT to supplement knowledge sharing amongst communities of practice has been explored (Pan & Leidner, 2003), and the notion of ‘virtual teams’ has been proposed as a basic construct for this activity. Within virtual team environments, four key challenges exist: constraints on transaction memory; insufficient degree of mutual understanding; failure in sharing and retaining contextual knowledge; and inflexibility of organizational ties. Various knowledge management system approaches have been posited as potential solutions to meet these challenges (Alavi & Tiwana, 2002). Overall, the advent of knowledge management has transformed the way decisions are made and how companies manage common knowledge.

We are interested in knowledge management for decision support applications, especially as it pertains to enterprise knowledge shared in global, virtual teams. Decision makers are faced with a challenge: accurate and quick knowledge sharing is especially difficult when dealing with distributed, heterogeneous, and asynchronous knowledge assets that exist when dealing with geographically dispersed virtual teams. The skills and technologies utilized by virtual teams are a blend of both old and new concepts, each useful for a variety of different tasks and each with its own advantages and disadvantages (Gillam & Oppenheim, 2006). In order to address the problem of knowledge sharing in geographically dispersed environments, an integrated knowledge sharing framework is proposed; this incorporates concepts of the 24-Hour Knowledge Factory, grid computing, and case-based reasoning (CBR).

The 24-Hour Knowledge Factory (Gupta, 2009) is a paradigm that decision makers can employ for distributed, team-based work. For this paradigm to be employed in an effective manner, one needs to consider the following types of research questions:

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