Dynamic Stochastic Multi-Criteria Decision Making Method Based on Prospect Theory and Conjoint Analysis

Junhua HU, Peng CHEN, Liu YANG

Abstract


A method based on prospect theory and conjoint analysis is proposed for dynamic stochastic multi-criteria decision making problems, in which the information about criteria weight is unknown and criteria values follow some kinds of distributions. Decision-maker’s attitude towards risk is introduced into this paper. First, data is collected by investigation and criteria weights are derived by conjoint analysis. The prospect values of each alternative in different periods are calculated according to distribution function. Then, index distribution decides time sequence weight, and overall prospect values of each alternative are obtained and ranked by aggregating prospect values in different periods. Finally, an example of choosing the best product illustrates the feasibility and effectiveness of this method.


Keywords


Dynamic stochastic; Multi-criteria decision making; Prospect theory; Conjoint analysis

Full Text:

PDF

References


Goda, K., & Hong, H. P. (2008). Application of cumulative prospect theory: Implied seismic design preference. Structural Safety, 30(6), 506-516.

Hu, J. H., Chen, X. H., & Liu, Y. M. (2009). Multi-criteria decision making method based on linguistic evaluation and prospect theory. Control and Decision, 24(10), 1477-1482.

Hu, J. H., & Xu, Q. (2011). Multi-criteria decision making method with interval number based on prospect theory. Statistics & Information Forum, 1(9), 23-27.

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica: Journal of the Econometric Society, 47(2), 263-291.

Lahdelma, R., & Hokkanen, J. (1998). SMAA-stochastic multi-objective acceptability analysis. European Journal of Operational Research, 106(1), 137-143.

Lahdelma, R., & Salminen, P. (2001). SMAA-2: Stochastic multi-criteria acceptability analysis for group decision making. Operations Research, 49(3), 444-454.

Lahdelma, R., & Salminen, P. (2002). Pseudo-criteria versus linear utility function in stochastic multi-criteria acceptability analysis. European Journal of Operational Research, 141(2), 454-469.

Lahdelma, R., & Salminen, P. (2009). Prospect theory and stochastic multi-criteria acceptability analysis. Omega, 37, 961-971.

Lin, Y. H., Lee, P. C., & Ting, H. (2008). Dynamic multi-attribute decision making model with grey number evaluations. Expert System with Application, 35, 1638-1644.

Luce, R. D., & Tukey, J. W. (1964). Simultaneous conjoint measurement: A new type of fundamental measurement. Journal of Mathematical Psychology, 1(1), 1-27.

Miyamoto, J. M., & Multiattribute, W. P. (1996). Utility theory without expected utility foundations. Operation Research, 44, 313-326.

Prelec, B. D. (1998). The probability weighting function. Econometrica, 66(3), 497-527.

Shen, H., & Ke, H. X. (1998). Principle and application of conjoint analysis. Application of Statistics and Management, 1(4), 39-45.

Tesfamariam, A. R. S. (2007). Probability density functions based weights for ordered weighted averaging (OWA) operators: An example of water quality indices. European Journal of Operational Research, 182(3), 1350-1368.

Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5(4), 297-323.

Wang, J. Q., & Zhou, L. (2010). Grey-stochastic multi-criteria decision making approach based on prospect theory. Systems Engineering—Theory & Practice, 30(9), 1658-1664.

Wang, X. F., & Yang, X. J. (2010). Dynamic stochastic multiple attribute decision making method with incomplete certain information. Systems Engineering—Theory & Practice, 30(2), 332-338.

Wu, G., & Gonzalez, R. (1996). Curvature of the probability weighting function. Management Science, 42(12), 1676-1690.

Zaras, K. (1999). Rough approximation of pairwise comparisons described by multi-attribute stochastic dominance. Journal of Multi-Criteria Decision Analysis, 8, 291-297.

Zeng, J. M. (2007). An experimental test on cumulative prospect theory. Journal of Jinan University (Nature Science Edition), 28(1), 44-47, .

Zhu, Z. P. (2000). Research on the method and the case for conjoint analysis. Science Research Management, 21(5), 95-102.




DOI: http://dx.doi.org/10.3968/5235

Refbacks

  • There are currently no refbacks.


Copyright (c)



Share us to:   

Reminder

  • How to do online submission to another Journal?
  • If you have already registered in Journal A, then how can you submit another article to Journal B? It takes two steps to make it happen:

1. Register yourself in Journal B as an Author

  • Find the journal you want to submit to in CATEGORIES, click on “VIEW JOURNAL”, “Online Submissions”, “GO TO LOGIN” and “Edit My Profile”. Check “Author” on the “Edit Profile” page, then “Save”.

2. Submission

  • Go to “User Home”, and click on “Author” under the name of Journal B. You may start a New Submission by clicking on “CLICK HERE”.


We only use three mailboxes as follows to deal with issues about paper acceptance, payment and submission of electronic versions of our journals to databases:
caooc@hotmail.com; mse@cscanada.net; mse@cscanada.org

 Articles published in Management Science and Engineering are licensed under Creative Commons Attribution 4.0 (CC-BY).

 MANAGEMENT SCIENCE AND ENGINEERING Editorial Office

Address:1055 Rue Lucien-L'Allier, Unit #772, Montreal, QC H3G 3C4, Canada.

Telephone: 1-514-558 6138
Http://www.cscanada.net Http://www.cscanada.org

Copyright © 2010 Canadian Research & Development Centre of Sciences and Cultures