Skip to main content

Performance Measurement of Knowledge Resources Using Fuzzy Logic

  • Conference paper
  • First Online:
Knowledge Management in Organizations (KMO 2015)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 224))

Included in the following conference series:

  • 2649 Accesses

Abstract

Evaluating the performance of knowledge resources is not a simple task as it involves many aspects, some of which are bounded by uncertainties and indistinctness. These make it hard to judge or quantify knowledge resources numerically for measurement purposes. Furthermore, data collection for performance measurement seems to be another difficulty faced by many organizations. This paper proposed to measure the performance of knowledge resources using fuzzy logic to cope with the shortcomings of normal measurement methods. The feasibility of using fuzzy logic as an evaluation method was shown with a five-step guideline and an example computed using MATLAB version R2013a.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and 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

Purchases are for personal use only

Institutional subscriptions

References

  1. Kankanhalli, A., Bernard, T.C.Y., Wei, K.K.: Contributing knowledge to electronic knowledge repositories: an empirical investigation. MIS Q. 29(1), 113–143 (2005)

    Google Scholar 

  2. Mills, A.M., Smith, T.A.: Knowledge management and organizational performance: a decomposed view. J. Knowl. Manag. 15(1), 156–171 (2011)

    Article  Google Scholar 

  3. Sveiby, K.E.: The intangible assets monitor. J. Hum. Resour. Costing Acc. 2(1), 73–97 (1997)

    Article  Google Scholar 

  4. Jennex, M.E., Olfman, L.: Assessing knowledge management success/effectiveness models. In: Proceedings of the 37th Hawaii International Conference on System Sciences. Hawaii, pp. 1–10 (2004)

    Google Scholar 

  5. Wu, Y.L., Wang, X., Wu, H.S.: Research on the performance measurement of knowledge management based on principal component analysis. In: Proceedings of the International Workshop on Intelligent Systems and Applications. Wuhan, pp. 1–4 (2009)

    Google Scholar 

  6. Wong, K.Y., Tan, L.P., Lee, C.S., Wong, W.P.: Knowledge management performance measurement: measures, approaches, trends and future directions. Inf. Dev. (2013). doi:10.1177/0266666913513278

    Google Scholar 

  7. Edvinsson, L.: Developing intellectual capital at Skandia. Long Range Plan. 30(3), 266–373 (1997)

    Article  Google Scholar 

  8. Tobin, D.R.: The Knowledge-Enabled Organization: Moving from “Training” to “Learning” to Meet Business Goals. Amacom, New York (1998)

    Google Scholar 

  9. Ahn, J.H., Chang, S.G.: Assessing the contribution of knowledge to business performance: the KP3 Methodology. Decis. Support Syst. 36(4), 403–416 (2004)

    Article  Google Scholar 

  10. Kluge, J., Stein, W., Licht, T.: Knowledge Unplugged: The McKinsey and Company Global Survey on Knowledge Management. Palgrave, Basingstoke (2001)

    Book  Google Scholar 

  11. Herrera, F., Herrera-Viedma, E.: Linguistic decision analysis: steps for solving decision problems under linguistic information. Fuzzy Sets Syst. 115, 67–82 (2000)

    Article  Google Scholar 

  12. Zadeh, L.A.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965)

    Article  Google Scholar 

  13. Rahmani, B., Rafezi, H.: Solving fuzzy logic problems with MATLAB (2010). http://www.scribd.com/doc/33412283/Solving-Fuzzy-Logic-Problems-With-MATLAB. Accessed 5 Feb 2015

  14. Godil, S., Shamim, M., Enam, S., Qidwai, U.: Fuzzy logic: a “simple” solution for complexities in neurosciences. Surg. Neurol. Int. 2(24) (2011). doi:10.4103/2152-7806.77177

  15. MathWorks: Fuzzy logic toolbox user’s guide (2015). http://www.mathworks.com/help/pdf_doc/fuzzy/fuzzy.pdf. Accessed 5 March 2015

  16. Uit Beijerse, R.P.: Questions in knowledge management: defining and conceptualising a phenomenon. J. Knowl. Manag. 3(2), 94–110 (1999)

    Article  Google Scholar 

  17. Handzic, M.: Knowledge management in SMEs: practical guidelines. CACCI J. 1(1), 21–34 (2006)

    Google Scholar 

  18. Davenport, T.H., Prusak, L.: Working Knowledge: How Organizations Manage What They Know. Harvard Business School Press, Boston (1998)

    Google Scholar 

  19. Clarke, J., Turner, P.: Global competition and the Australian biotechnology industry: developing a model of SMEs knowledge management strategies. Knowl. Process Manag. 11(1), 38–46 (2004)

    Article  Google Scholar 

  20. Autrey, R.L., Sansing, R.: Licensing intellectual property with self-reported outcomes. J. Acc Auditing Finan. 29(3), 260–277 (2014)

    Article  Google Scholar 

  21. WIPO: WIPO Intellectual Property Handbook. World Intellectual Property Organization Publication (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Cheng Sheng Lee .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Lee, C.S., Wong, K.Y. (2015). Performance Measurement of Knowledge Resources Using Fuzzy Logic. In: Uden, L., Heričko, M., Ting, IH. (eds) Knowledge Management in Organizations. KMO 2015. Lecture Notes in Business Information Processing, vol 224. Springer, Cham. https://doi.org/10.1007/978-3-319-21009-4_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-21009-4_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21008-7

  • Online ISBN: 978-3-319-21009-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics