An investigation of the role of scale values in the DS/AHP method of multi-criteria decision making

Journal of Multi-Criteria Decision Analysis

Volumn 11, Issue 6, 2002, Pages 327-343

  Beynon, Malcolm J ^a  

^a CARDIFF UNIVERSITY   (United Kingdom)

Author keywords

AHP; Dempster shafer theory; Ignorance; Multi criteria decision making; Scale values

Indexed keywords

EID: 33746826619     PISSN: 10579214     EISSN: 10991360     Source Type: Journal    
DOI: 10.1002/mcda.339     Document Type: Article

References (43)

1. Allenby, GM., Ginter, JL., 1995. The effects of in-store displays and feature advertising on consideration sets. International Journal of Research in Marketing 12: 67-80.
2. Beynon, MJ., Curry, B., Morgan, PH., 2000. The Dempster-Shafer theory of evidence: an alternative approach to multicriteria decision modelling. OMEGA 28(1): 37-50.
3. Beynon, M., Cosker, D., Marshall, D., 2001. An expert system for multi-criteria decision making using Dempster Shafer theory. Expert Systems with Applications 20(4): 357-367.
4. Beynon, M., 2002a. DS/AHP method: A mathematical analysis, including an understanding of uncertainty. European Journal of Operational Research 140(1): 104-117.
5. Beynon, M., 2002b. An analysis of distributions of priority values from alternative comparison scales within AHP. European Journal of Operational Research 140(1): 148-164.
6. Bloch, B., 1996. Some aspects of Dempster-Shafer evidence theory for classification of multi-modality images taking partial volume effect into account. Pattern Recognition Letters 17: 905-919.
7. Buchanan, JT., Corner, JL., 1997. The effects of anchoring in interactive MCDM solution methods. Computers and Operations Research 24(10): 907-918.
8. Butler, AC., Sadeghi, F., Rao, SS., LeClair, SR., 1995. Computer-aided design/engineering of bearing systems using the Dempster-Shafer theory. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 9: 1-11.
9. Caselton, WF., Luo, W., 1992. Decision making with imprecise probabilities: Dempster-Shafer theory and application. Water Resources Research 28: 3071-3083.
10. DeKorvin, A., Shipley, MF., 1993. A Dempster-Shafer based approach to compromise decision making with multiattributes applied to product selection. IEEE Transaction on Engineering Management 40(1): 60-67.
11. Dempster, AP., 1968. A generalization of Bayesian inference (with discussion). Journal of Royal Statistical Society Series B 30(2): 205-247.
12. Donegan, HA., Dodd, FJ., McMaster, TB., 1992. A new approach to AHP decision-making. The Statistician 41: 295-302.
13. Ducey, MJ., 2001. Representing uncertainty in silvicultural decisions: an application of the Dempster-Shafer theory of evidence. Forest Ecology and Management 150: 199-211.
14. Dyer, JS., Wendell, RE., 1985. A critique of the analytic hierarchy process. Working Paper 84/85-4-24, Department of Management, The University of Texas, Austin.
15. Finan, JS., Hurley, WJ., 1999. Transitive calibration of the AHP verbal scale. European Journal of Operation Research 112: 367-372.
16. Goldstein, WM., Einhorn, HJ., 1987. Expression theory and the preference reversal phenomenon. Psychological Review 94: 236-254.
17. Hogarth, RM., 1987. Judgement and Choice, 2nd edn. Wiley: New York.
18. Jensen, RE., 1984. An alternative scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology 28: 317-332.
19. Kok, M., Lootsma, FA., 1994. Pairwise comparison methods in multi-objective programming with ap-plications in a long-term energy-planning model. Technical Report No. 84-19, Delft, University of Technology.
20. Lootsma, FA., 1993. Scale sensitivity in the multiplicative AHP and SMART. Journal of Multi-Criteria Decision Analysis 2: 87-110.
21. Lund, JR., Palmer, RN., 1986. Subjective evaluation: linguistic scales in pairwise comparison methods. Civil Engineering Systems 3: 182-186.
22. Ma, D., Zheng, X., 1991. 9/9 - 9/1 Scale Method of AHP. Proceedings of the Second International Symposium on the AHP: 197-202.
23. Miller, GA., 1956. The magical number seven, plus or minus two: some limits on our capacity for processing information. The Psychological Review 63: 81-97.
24. Poyhonen, M., Hamalainen, RP., Salo, AA., 1997. An experiment on the numerical modeling of verbal statements. Journal of Multi-Criteria Decision Analysis 6: 1-10.
25. Poyhonen, M., Hamalainen, RP., 2001. On the convergence of multiattribute weighting methods. European Journal of Operational Research 129: 569-585.
26. Prabhu, TR., Vizayakumar, K., 1996. Fuzzy hierarchical decision making (FHDM): a methodology for technology choice. International Journal of Computer Applications in Technology 9(5/6): 322-327.
27. Roberts, JH., Lattin, JM., 1991. Development and testing of a model of consideration set composition. Journal of Marketing Research XXVIII: 429-440.
28. Saaty, TL., 1977. A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology 15: 59-62.
29. Saaty, TL., 1980. The Analytic Hierarchy Process. McGraw-Hill: New York.
30. Saaty, TL., 1987. Concepts, theory, and techniques: rank generation, presentation, and reversal in the analytic hierarchy decision process. Decision Sciences 18: 157-177.
31. Saaty, TL., 1995. Transport planning with multiple criteria: the analytic hierarchy process applications and progress review. Journal of Advanced Transportation 29(1): 81-126.
32. Saaty, TL., Kearns, KP., 1985. Analytical planning: the organisation of systems. International Series in Modern Applied Mathematics and Computer Science, vol. 7. Pergamon Press: New York.
33. Salo, AA., Hamalainen, RP., 1997. On the measurement of preferences in the analytic hierarchy process. Journal of Multi-Criteria Decision Analysis 6: 309-319.
34. Shafer, G., 1976. A Mathematical Theory of Evidence. Princeton University Press: Princeton.
35. Shafer, G., 1990. Perspectives in the theory of belief functions. International Journal of Approximate Reasoning 4: 323-362.
36. Shipley, MF., deKorvin, A., Omer, K., 2001. A fuzzy logic-based decision model to satisfy goals for successful product/service introduction. European Journal of Operational Research 135: 209-219.
37. Smets, P., 1994. What is Dempster-Shafer’s model? In Advances in the Dempster-Shafer theory of evidence. Yager RR, Fedrizzi M, Kacprzyk J. (eds). Wiley: New York, 5-34.
38. Smets, P., Kennes, R., 1994. The transferable belief model. Artificial Intelligence 66: 191-234.
39. Tversky, A., Simonson, I., 1993. Context-dependent preferences. Management Science 39(10): 1179-1189.
40. VonNitzsch, R., Weber, M., 1993. The effect of attribute ranges on weights in multiattribute utility measurements. Management Science 39(8): 937-943.
41. Webber, SA., Apostolou, B., Hassell, JM., 1996. The sensitivity on the analytic hierarchy process to alternative scale and cue presentations. European Journal of Operational Research 96: 351-362.
42. Yang, J-B., Singh, MG., 1994. An evidential reasoning approach for multiple-attribute decision making with uncertainty. IEEE Transactions on Systems, Man, and Cybernetics 24(1): 1-18.
43. Yen, J., 1989. GERTIS: A Dempster-Shafer approach to diagnosing hierarchical hypotheses. Communications of the ACM 32(5): 573-585.