Knowledge management and information technology: can they work in perfect harmony?

Author:

Mohamed Mirghani,Stankosky Michael,Murray Arthur

Abstract

PurposeAims to impart new insights into the role of information technology (IT) in knowledge extraction, capture, distribution and personalization. The paper seeks to pin‐point the strengths and weaknesses of IT in the domain of knowledge management (KM) and to explain why the technology promise remains unfulfilled, as seen by many KM practitioners.Design/methodology/approachThe discussion in this paper is fundamentally based on Stankosky's four KM pillars conceptual framework. Within this framework the authors attempted to shed some light on the IT role and the hidden reasons that make knowledge prominently unreachable via IT.FindingsIT assimilation and representation of knowledge intangibility, dynamism, experience and other humanistic cognitive dimensions remain debatable. The current technology is immature to resolve such problems. For IT to be effective for KM it must shred its bivalent logic and instead learn to operate within an authentic continuum.Originality/valueKnowledge managers need to understand that a KM initiative that considers IT as a Utopian panacea will fail. Equally, the KM initiative that undervalues IT will follow suit. Owing to IT immaturity in the area of cognitive behavior, the situation is still perplexing. This elusiveness imposes some obstacles to sufficiently represent the context of tacit knowledge. Hence, codifying knowledge with the poser of the existing IT and without the support from socio‐cultural inputs, will result in de‐contextualization, i.e. “knowledge dilution.” Hence, special considerations should be given to applications that offer some behavioral context and human cognitive dimensions.

Publisher

Emerald

Subject

Management of Technology and Innovation,Strategy and Management

Reference46 articles.

1. Adams, K.C. (2001), “The web as a database: new extraction technologies and content management”, Online, Vol. 25 No. 2, pp. 27‐32.

2. Argyris, C. (1990), Overcoming Organisational Differences: Facilitating Organisational Learning, Allyn & Bacon, Boston, MA.

3. Austin, R.D. (1998), On the Feasibility of Monitoring Complex Work: The Case of Software Metrics, Harvard Business School, Boston, MA.

4. Bair, J. (1998), “Case‐based reasoning in knowledge management: when?”, Gartner research note: Technology, T‐04‐9557, available at: www.gartner.com.

5. Baker, M., Barker, M., Thorne, J. and Dutnell, M. (1997), “Leveraging human capital”, Journal of Knowledge Management, Vol. 1 No. 1, pp. 63‐74.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3