Advertisement

A Sensitivity Analysis on Weight Sum Method MCDM Approach for Product Recommendation

  • Gaurav Kumar
  • N. Parimala
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11319)

Abstract

The weights assigned to features, in an MCDM approach, play a crucial role in the computation of the ranking of alternatives. These weights can be varied which can result in a varied ranking of alternatives. In this paper, we present a method for conducting a sensitivity analysis of the weight assigned to decision criteria. In our earlier work, we have applied the Weighted Sum Method (WSM) multi criteria decision making approach to rank cameras. Using the results, a sensitivity analysis is performed in this paper. The weights are varied across thirty-four experiments. The result says that the minimum percentage of change required in the weight is 8.52% to alter the final ranking of alternatives.

Keywords

MCDM Weighted Sum Method Sensitivity analysis 

Notes

Acknowledgment

One of the authors G. Kumar would like to thank Human Resource Development Group, Council of Scientific & Industrial Research (CSIR), Ministry of Science and Technology, Govt. of India for funding the fellowship (09/263(1001)/2013-EMR-1) throughout his research.

References

  1. 1.
    Pomerol, J.-C., Romero, S., Barba, R.: Multi-criterion Decision in Management: Principles and Practice, 1st edn. Kluwer Academic, Boston (2000)CrossRefGoogle Scholar
  2. 2.
    Dantzig, G.B.: Linear Programming and Extensions. Princeton University Press, NJ (1963)zbMATHGoogle Scholar
  3. 3.
    Rios Insua, D.: Sensitivity Analysis in Multi-objective Decision Making. Lecture Notes in Economics and Mathematical Systems. Springer, Germany (1990).  https://doi.org/10.1007/978-3-642-51656-6CrossRefzbMATHGoogle Scholar
  4. 4.
    Barron, H., Schmidt, C.P.: Sensitivity analysis of additive multi-attribute value models. Oper. Res. 36(l), 122–127 (1988)CrossRefGoogle Scholar
  5. 5.
    Samson, D.: Managerial Decision Analysis. Irwin, Illinois (1988)Google Scholar
  6. 6.
    Winston, L.W.: Operations Research, 2nd edn. PWS-KentPublishing Co., Boston (1991)zbMATHGoogle Scholar
  7. 7.
    Triantaphyllou, E., Sánchez, A.: A sensitivity analysis approach for some deterministic multi-criteria decision-making methods. Decis. Sci. 28(1), 151–194 (1997)CrossRefGoogle Scholar
  8. 8.
    Zavadskas, E.K., Turskis, Z., Dejus, T., Viteikiene, M.: Sensitivity analysis of a simple additive weight method. Int. J. Manag. Decis. Mak. 8(5–6), 555–574 (2007)Google Scholar
  9. 9.
    Hyde, K.M., Maier, H.R., Colby, C.B.: Reliability-based approach to multi-criteria decision analysis for water resources. J. Water Resour. Plan. Manag. 130(6), 429–438 (2004)CrossRefGoogle Scholar
  10. 10.
    Gaurav, K., Parimala, N.: A weighted sum method MCDM approach for recommending product using sentiment analysis. Int. J. Bus. Inf. Syst. (2018, accepted)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Computer and Systems SciencesJNUNew DelhiIndia

Personalised recommendations