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Assessing the Effect of Knowledge Management Initiatives on Stakeholder Objectives Using Fuzzy TOPSIS

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

Abstract

Comprehensive assessment tools to prioritize KM initiatives are critical for KM adoption. This paper aims to develop a hierarchical fuzzy TOPSIS model to rank KM initiatives in terms of their effect on often contradictory stakeholder objectives. The empirical case study of a medical supplier company demonstrates that this group multi-criteria decision making tool can effectively address both the uncertainty in KM assessment and the different effects of KM processes on individual stakeholder objectives. Thus, it may contribute to the successful KM implementation process.

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References

  1. Gold, A.H., Arvind Malhotra, A.H.S.: Knowledge management: an organizational capabilities perspective. J. Manage. Inf. Syst. 18(1), 185–214 (2001)

    Google Scholar 

  2. Zack, M., McKeen, J., Singh, S.: Knowledge management and organizational performance: an exploratory analysis. J. Knowl. Manage. 13(6), 392–409 (2009)

    Article  Google Scholar 

  3. Hajkova, V., Hajek, P.: Efficiency of knowledge bases in urban population and economic growth - evidence from European cities. Cities 40, 11–22 (2014)

    Article  Google Scholar 

  4. Dyer, J.H., Hatch, N.: Using supplier networks to learn faster. Sloan Manage. Rev. 45(3), 57–66 (2006)

    Google Scholar 

  5. Patil, S.K., Kant, R.: A fuzzy AHP-TOPSIS framework for ranking the solutions of knowledge management adoption in supply chain to overcome its barriers. Expert Syst. Appl. 41(2), 679–693 (2014)

    Article  Google Scholar 

  6. Ruoning, X., Xiaoyan, Z.: Extensions of the analytic hierarchy process in fuzzy environment. Fuzzy Sets Syst. 52(3), 251–257 (1992)

    Article  Google Scholar 

  7. Chen, C.T.: Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst. 114(1), 1–9 (2000)

    Article  Google Scholar 

  8. Chen, T.Y., Tsao, C.Y.: The interval-valued fuzzy TOPSIS method and experimental analysis. Fuzzy Sets Syst. 159(11), 1410–1428 (2008)

    Article  Google Scholar 

  9. Wang, Y.M., Elhag, T.: Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment. Expert Syst. Appl. 31(2), 309–319 (2006)

    Article  Google Scholar 

  10. Zolfani, S.H., Sedaghat, M., Zavadskas, E.K.: Performance evaluating of rural ICT centers (telecenters), applying fuzzy AHP, SAW-G and TOPSIS grey, a case study in Iran. Technol. Econ. Dev. Econ. 18(2), 364–387 (2012)

    Article  Google Scholar 

  11. Lee, H., Choi, B.: Knowledge management enablers, processes, and organizational performance: an integrative view and empirical examination. J. Manage. Inf. Syst. 20(1), 179–228 (2003)

    Google Scholar 

  12. Hackman, J.R., Morris, C.G.: Group tasks, group interaction process, and group performance effectiveness: a review and proposed integration. In: Berkowitz, L. (ed.) Advances in Experimental Social Psychology, vol. 8, pp. 45–99. Academic Press, New York (1975)

    Google Scholar 

  13. Andreeva, T., Kianto, A.: Knowledge processes, knowledge-intensity and innovation: a moderated mediation analysis. J. Knowl. Manage. 15(6), 1016–1034 (2011)

    Article  Google Scholar 

  14. Darroch, J.: Knowledge management, innovation and firm performance. J. Knowl. Manage. 9(3), 101–115 (2005)

    Article  Google Scholar 

  15. Wang, Z., Wang, N.: Knowledge sharing, innovation and firm performance. Expert Syst. Appl. 39(10), 8899–8908 (2012)

    Article  Google Scholar 

  16. Tiwana, A.: The Knowledge Management Toolkit: Practical Techniques for Building a Knowledge Management System. Prentice Hall PTR, Upper Saddle River (2000)

    Google Scholar 

  17. Bornemann, M., Sammer, M.: Assessment methodology to prioritize knowledge management related activities to support organizational excellence. Meas. Bus. Excell. 7(2), 21–28 (2003)

    Article  Google Scholar 

  18. Wu, W.W., Lee, Y.T.: Selecting knowledge management strategies by using the analytic network process. Expert Syst. Appl. 32(3), 841–847 (2007)

    Article  Google Scholar 

  19. Tseng, M.L., Wu, W.W., Lee, C.F.: Knowledge management strategies in linguistic preferences. J. Asia Pac. Bus. Innov. Technol. Manage. 1, 60–73 (2011)

    Google Scholar 

  20. Wu, W.W.: Choosing knowledge management strategies by using a combined ANP and DEMATEL approach. Expert Syst. Appl. 35(3), 828–835 (2008)

    Article  Google Scholar 

  21. Wu, W.W.: Segmenting critical factors for successful knowledge management implementation using the fuzzy DEMATEL method. Appl. Soft Comput. 12(1), 527–535 (2012)

    Article  Google Scholar 

  22. Büyüközkan, G., Feyzioglu, O., Cifçi, G.: Fuzzy multi-criteria evaluation of knowledge management tools. Int. J. Comput. Intell. Syst. 4(2), 184–195 (2011)

    Article  Google Scholar 

  23. Jenab, K., Sarfaraz, A.R.: A fuzzy graph-based model for selecting knowledge management tools in innovation processes. Int. J. Enterp. Inf. Syst. 8(1), 1–16 (2012)

    Article  Google Scholar 

  24. Hung, Y.H., Chou, S.C.T., Tzeng, G.H.: Knowledge management adoption and assessment for SMEs by a novel MCDM approach. Decis. Support Syst. 51(2), 270–291 (2011)

    Article  Google Scholar 

  25. Zandi, F., Tavana, M.: A hybrid fuzzy real option analysis and group ordinal approach for knowledge management strategy assessment. Knowl. Manage. Res. Pract. 8(3), 216–228 (2010)

    Article  Google Scholar 

  26. Luukka, P.: Fuzzy similarity in multicriteria decision-making problem applied to supplier evaluation and selection in supply chain management. Adv. Artif. Intell. 2011(6), 1–9 (2011)

    Article  Google Scholar 

  27. Collan, M., Luukka, P.: Evaluating R&D projects as investments by using an overall ranking from four new fuzzy similarity measure based TOPSIS variants. IEEE Trans. Fuzzy Syst. 22(3), 505–515 (2013)

    Article  Google Scholar 

  28. Turskis, Z., Zavadskas, E.K.: Multiple criteria decision making (MCDM) methods in economics: an overview. Technol. Econ. Dev. Econ. 2, 397–427 (2011)

    Google Scholar 

  29. Chen, C.T., Lin, C.T., Huang, S.F.: A fuzzy approach for supplier evaluation and selection in supply hhain management. Int. J. Prod. Econ. 102(2), 289–301 (2006)

    Article  Google Scholar 

  30. Wang, J.W., Cheng, C.H., Huang, K.C.: Fuzzy hierarchical TOPSIS for supplier selection. Appl. Soft Comput. 9(1), 377–386 (2009)

    Article  Google Scholar 

  31. Hussi, T.: Reconfiguring knowledge management-combining intellectual capital, intangible assets and knowledge creation. J. Knowl. Manage. 8(2), 36–52 (2004)

    Article  Google Scholar 

  32. Alavi, M., Leidner, D.E.: Review: knowledge management and knowledge management systems: conceptual foundations and research issues. MIS Q. 25(1), 107–136 (2001)

    Article  Google Scholar 

  33. Bao, Q., Ruan, D., Shen, Y., Hermans, E., Janssens, D.: Improved hierarchical fuzzy TOPSIS for road safety performance evaluation. Knowl. Based Syst. 32, 84–90 (2012)

    Article  Google Scholar 

  34. Kahraman, C., Ates, N.Y., Çevik, S., Gülbay, M., Erdogan, S.A.: Hierarchical fuzzy TOPSIS model for selection among logistics information technologies. J. Enterp. Inf. Manage. 20(2), 143–168 (2007)

    Article  Google Scholar 

  35. Paksoy, T., Pehlivan, N.Y., Kahraman, C.: Organizational strategy development in distribution channel management using fuzzy AHP and hierarchical fuzzy TOPSIS. Expert Syst. Appl. 39(3), 2822–2841 (2012)

    Article  Google Scholar 

  36. Hajek, P., Henriques, R., Hajkova, V.: Visualising components of regional innovation systems using self-organizing maps - evidence from European regions. Technol. Forecast. Soc. Change 84, 197–214 (2014)

    Article  Google Scholar 

  37. Matatkova, K., Stejskal, J.: Descriptive analysis of the regional innovation system-novel method for public administration authorities. Transylvanian Rev. Adm. Sci. 39, 91–107 (2013)

    Google Scholar 

  38. Büyüközkan, G., Çifçi, G.: A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers. Expert Syst. Appl. 39(3), 3000–3011 (2012)

    Article  Google Scholar 

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Acknowledgments

This article was created as a part of the solution of the research task No. 14-02836S, financially supported by the Grant Agency of the Czech Republic.

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Correspondence to Petr Hajek .

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Hajek, P., Mansfeldova, L. (2015). Assessing the Effect of Knowledge Management Initiatives on Stakeholder Objectives Using Fuzzy TOPSIS. 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_6

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  • DOI: https://doi.org/10.1007/978-3-319-21009-4_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21008-7

  • Online ISBN: 978-3-319-21009-4

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