Advertisement

A Case-Based Reasoning Approach for Evaluating and Selecting Human Resource Management Information Systems Projects

  • Santoso Wibowo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7030)

Abstract

This paper presents a case-based reasoning (CBR) approach for evaluating and selecting human resource management information systems (IS) projects in an organization. The concept on case-based distance is introduced for measuring the degree of similarity between each case in the case base and the new case. To avoid the inconsistency of the decision maker’s subjective assessment, an induction technique is applied to help assign the importance of the criteria in the similarity measure. A human resource management IS project evaluation and selection problem is presented to demonstrate the effectiveness of the approach.

Keywords

Case-Based Reasoning Evaluation and Selection Multicriteria Human Resource Management IS Project 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Stone, D.L., Stone-Romero, E.F., Lukaszewski, K.: Factors affecting the acceptance and effectiveness of electronic human resource systems. Hum. Resour. Manage. Rev. 16, 229–244 (2006)CrossRefGoogle Scholar
  2. 2.
    Hussain, Z., Wallace, J., Cornelius, N.E.: The use and impact of human resource information systems on human resource management professionals. Inform. Manage. 44, 74–89 (2007)CrossRefGoogle Scholar
  3. 3.
    Deng, H., Wibowo, S.: Fuzzy Approach to Selecting Information Systems Projects. In: 5th ACIS International Conference on Software Engineering, Artificial Intelligence, Networks and Parallel/Distributed Computing, Beijing, China, June 30-July 2 (2004)Google Scholar
  4. 4.
    Hsu, C., Chiu, C., Hsu, P.L.: Predicting information systems outsourcing success using a hierarchical design of case-based reasoning. Exp. Syst. Appl. 26, 435–441 (2004)CrossRefGoogle Scholar
  5. 5.
    Tung, Y.H., Tseng, S.S., Weng, J.F., Lee, T.P., Liao, Y.H., Tsai, W.N.: A rule-based CBR approach for expert finding and problem diagnosis. Exp. Syst. Appl. 37, 2427–2438 (2010)CrossRefGoogle Scholar
  6. 6.
    Du, Y., Wen, W., Cao, F., Ji, M.: A case-based reasoning approach for land use change prediction. Exp. Syst. Appl. 37, 5745–5750 (2010)CrossRefGoogle Scholar
  7. 7.
    Zhang, G., Keil, M., Rai, A., Mann, J.: Predicting information technology project escalation: A neural network approach. Eur. J. Oper. Res. 146, 115–129 (2003)CrossRefzbMATHGoogle Scholar
  8. 8.
    Lim, S.H., Nam, K.: Artificial Neural Network Modeling in Forecasting Successful Implementation of ERP Systems. Int. J. Comput. Intell. Res. 2, 115–119 (2006)CrossRefGoogle Scholar
  9. 9.
    Tian, L., Noore, A.: Evolutionary neural network modeling for software cumulative failure time prediction. Reliab. Eng. Syst. Saf. 87, 45–51 (2005)CrossRefGoogle Scholar
  10. 10.
    Narayana Naik, G., Gopalakrishnan, S., Ganguli, R.: Design optimization of composites using genetic algorithms and failure mechanism based failure criterion. Compos. Struct. 83, 354–367 (2008)CrossRefGoogle Scholar
  11. 11.
    Chen, Y., Kilgour, M., Hipel, K.: Case-based distance method for screening in multiple-criteria decision aid. Omega 36, 373–383 (2008)CrossRefGoogle Scholar
  12. 12.
    Zhao, K., Yu, X.: A case based reasoning approach on supplier selection in petroleum enterprises. Exp. Syst. Appl. 38, 6839–6847 (2011)CrossRefGoogle Scholar
  13. 13.
    Quinlan, J.R.: Induction of Decision Trees. Mach. Learn. 1, 81–106 (1986)Google Scholar
  14. 14.
    Wettschereck, D., Aha, D.W., Mohri, T.: A review and empirical comparison of feature weighting methods for a class of lazy learning algorithms. Artif. Intell. Rev. 11, 273–314 (1997)CrossRefGoogle Scholar
  15. 15.
    Chou, T.Y., Chou, S.T., Tzeng, G.H.: Evaluating IT/IS investments: A fuzzy multi-criteria decision model approach. Eur. J. Oper. Res. 173, 1026–1046 (2006)CrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Santoso Wibowo
    • 1
  1. 1.Faculty of Business InformaticsCQUniversityMelbourneAustralia

Personalised recommendations