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UAL Research Online

The Next Generation of Knowledge Management: Mapping-Based Assessment Models

Carlucci, Daniela and Schiuma, Giovanni (2015) The Next Generation of Knowledge Management: Mapping-Based Assessment Models. In: Advances in Knowledge Management - Celebrating Twenty Years of Research and Practice. Knowledge Management and Organizational Learning, 1 . Springer. ISBN 9783319095004

Type of Research: Book Section
Creators: Carlucci, Daniela and Schiuma, Giovanni
Description:

Understanding how to capture value from KM is relevant, today more than ever. The current dynamic and unpredictable social and economic scenario struggles organisations to know how optimising the use and the development of their resources, included knowledge resources, to create value. Managers and decision makers need approaches and models able to drive them in the complex decisions regarding how actively managing knowledge resources and assessing the achieved outcomes.

This chapter provides a contribution to the emerging discussion concerning the definition of new KM models specifically aimed to a better understanding of KM outcomes and value. Based on some previous works of the authors, the chapter analyses how to elicit the mechanisms of conversion of knowledge resources into value through the use of visual techniques and presents an AHP based mapping model that allows to identify the knowledge asset value drivers on which management attention should be focused as well as to highlight and assess the network of relationships between and among knowledge assets, and between knowledge assets and organisational performance.

Official Website: http://www.springer.com/business+%26+management/business+information+systems/book/978-3-319-09500-4
Keywords/subjects not otherwise listed: knowledge resources, value, mapping, AHP, strategic assessment model
Publisher/Broadcaster/Company: Springer
Your affiliations with UAL: Colleges > Central Saint Martins
Date: November 2015
Date Deposited: 08 Jul 2014 15:18
Last Modified: 03 Oct 2019 14:38
Item ID: 7051
URI: https://ualresearchonline.arts.ac.uk/id/eprint/7051

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