Effective use of knowledge management systems: a process model of content ratings and credibility indicators (1).(SPECIAL ISSUE)

Abstract

Knowledge management systems (KMSs) facilitate the efficient and effective sharing of a firm's intellectual resources. However, sifting through the myriad of content available through KMSs can be challenging, and knowledge workers may be over-whelmed when trying to find the content most relevant for completing a new task. To address this problem, KMS designers often include content rating schemes (i.e., users of the KMS submit ratings to indicate the quality of specific content used) and credibility indicators (indicators describing the validity of the content and/or the ratings) to improve users' search and evaluation of KMS content. This study examines how content ratings and credibility indicators affect KMS users' search and evaluation processes and decision performance (how well and how quickly users selected alternatives offered by the KMS). Four interrelated laboratory experiments provide evidence that ratings have a strong influence on KMS search and evaluation processes, which in turn affects decision performance. Finally, this study demonstrates that certain credibility indicators can moderate the relationship between rating validity and KMS content search and evaluation processes.

Keywords: Knowledge management systems, knowledge usage, decision making, content ratings, credibility indicators

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Introduction

Knowledge management systems (KMSs) are becoming ubiquitous in today's corporations (Davenport and Prusak 1998). KMSs store vast amounts of information, and knowledge workers often have difficulty locating the best content for their task, resulting in suboptimal decision performance (poor selection of content from the KMS) (Davenport and Hansen 1999; Nevo et al. 2003; Teece 1995). The problem is particularly significant in light of the fact that corporate KMS investment is forecast to grow to $13 billion annually by 2007 (Anonymous 2004). To address this problem, this study focuses on KMS design features that are intended to enable knowledge workers to search and evaluate KMS content more effectively, resulting in improved decision performance.

To ensure effective usage, a KMS must be designed such that knowledge workers can readily find high-quality content without feeling over-whelmed (Alavi and Leidner 2001; Roussinov and Zhao 2003; Thomas et al. 2001). Identifying high-quality content is difficult given its abundance (Davenport and Beck 2001; Farhoomand and Drury 2002) and the variability of its quality (Constant et al. 1994; Hansen and Haas 2001).