Skip to main content

Knowledge Potential Measurement and Uncertainty

  • Book
  • © 2004

Overview

This is a preview of subscription content, log in via an institution to check access.

Access this book

eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (7 chapters)

Keywords

About this book

Whereas the measurement of tangible assets, e.g. cost of sales or raw material, used to be one of the main issues of business in the past, the focus has now shifted towards intangible assets such as the knowledge potential of a firm's knowledge workers. Against this background, the measurement of knowledge has become a challenge for the managers of knowledge based companies and they are looking for a knowledge measurement model to achieve the optimal organization well-being.

Kerstin Fink discusses the two mainstream measurement fields: the cognitive science approach and the management approach. She develops the knowledge potential view which is determined by nine key measurement variables, i.e. content, culture, networking, organizational knowledge, learning and training, customer and competitor knowledge, and knowledge management systems. The author applies the analogical reasoning process and uses Werner Heisenberg's Uncertainty Principle as a framework for the employee knowledge potential measurement process. Her aim is to assign a specific knowledge classification or value to each employee. Case studies demonstrate the model's practical use.

About the author

Univ.-Prof. Dr. Kerstin Fink lehrt Wirtschaftsinformatik an der Universität Innsbruck, wo sie sich auch habilitierte.

Bibliographic Information

  • Book Title: Knowledge Potential Measurement and Uncertainty

  • Authors: Kerstin Fink

  • DOI: https://doi.org/10.1007/978-3-322-81240-7

  • Publisher: Deutscher Universitätsverlag Wiesbaden

  • eBook Packages: Springer Book Archive

  • Copyright Information: Deutscher Universitäts-Verlag/GWV Fachverlage GmbH, Wiesbaden 2004

  • Softcover ISBN: 978-3-8244-2183-1Published: 29 July 2004

  • eBook ISBN: 978-3-322-81240-7Published: 06 December 2012

  • Edition Number: 1

  • Number of Pages: XVIII, 274

  • Number of Illustrations: 11 b/w illustrations

  • Topics: Business Mathematics, IT in Business, Computer Science, general

Publish with us