Application of the fuzzy weighted average in strategic portfolio management

Decision Sciences

Volumn 36, Issue 3, 2005, Pages 489-511

  Lin, Chinho ^a,d   Tan, Bertram ^b   Hsieh, Ping Jung ^c  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

^b KUN SHAN UNIVERSITY   (Taiwan)

^c NATIONAL FORMOSA UNIVERSITY   (Taiwan)

^d NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Fuzzy Weighted Average; Integer Linear Programming; Portfolio Matrix; Strategic Portfolio Management

Indexed keywords

EID: 27844498282     PISSN: 00117315     EISSN: 15405915     Source Type: Journal    
DOI: 10.1111/j.1540-5414.2005.00081.x     Document Type: Article

References (49)

1. Ansoff, H. I., & McDonnell, E. J. (1990). Implanting strategic management. Englewood Cliffs, NJ: Prentice-Hall.
2. Archer, N. P., & Ghasemzadeh, F. (1999). An integrated framework for project portfolio selection. International Journal of Project Management, 17(4), 207-216.
3. Bellman, R. E., & Zadeh, L. A. (1970). Decision-making in a fuzzy environment. Management Science, 17(4), 141-164.
4. Bohanec, M. (1995). Knowledge-based portfolio analysis for project evaluation. Information and Management, 28(5), 293-302.
5. Bozdag, C. E., Kahraman, C., & Ruan, D. (2003). Fuzzy group decision making for selection among computer integrated manufacturing systems. Computers in Industry: Amsterdam, 51(1), 13-29.
6. Burn, S. A., Liu, L., & Feng, C. W. (1996). The LP/IP hybrid method for construction time-cost trade-off analysis. Construction Management and Economics: London, 14(3), 265-276.
7. Buyukozkan, G., & Feyzioglu, O. (2004). A fuzzy-logic-based decision-making approach for new product development. International Journal of Production Economics, 90(1), 27-45.
8. Chan, Y. C. (2004). Use of capital budgeting techniques and an analytic approach to capital investment decisions in Canadian municipal governments. Public Budgeting & Finance, 24(2), 40-58.
9. Chien, T. W., Lin, C., Tan, B., & Lee, W. C. (1999). A neural networks-based approach for strategic planning. Information & Management, 35(6), 357-364.
10. Chiu, Y. C., Shyu, J. Z., & Tzeng, G. H. (2004). Fuzzy MCDM for evaluating the e-commerce strategy. International Journal of Computer Applications in Technology Geneva, 79(1), 12-22.
11. Dong, W. M., & Wong, F. S. (1987). Fuzzy weighted average and implementation of the extension principle. Fuzzy Sets and Systems, 21(2), 183-199.
12. Dubois, D., & Prade, H. (1978). Operations on fuzzy numbers. International Journal of Systems Service, 9(6), 613-626.
13. Edvinsson, L., & Malone, M. S. (1997). Intellectual capital: Realizing your company's true value by finding its hidden brainpower. New York: HarperBusiness.
14. Ghasemzadeh, F., & Archer, N. P. (2000). Project portfolio selection through decision support. Decision Support Systems, 29(1), 73-88.
15. Ghasemzadeh, F., Archer, N., & Iyogun, P. (1999). A zero-one model for project portfolio selection and scheduling. The Journal of the Operational Research Society, 50(7), 745-755.
16. Hahn, E. D. (2003). Decision making with uncertain judgments: A stochastic formulation of the analytic hierarchy process. Decision Sciences, 34(3), 443-466.
17. Hatten, K. J., & Hatten, M. L. (1987). Strategic management. Englewood Cliffs, NJ: Prentice-Hall.
18. Hatten, K. J., & Rosenthal, S. R. (1999). Managing the process-centered enterprise. Long Range Planning, 52(3), 293-310.
19. Hax, A. C., & Majluf, N. S. (1983). The use of the industry attractiveness - business strength matrix in strategic planning. Interfaces, 13(2), 54-76.
20. Hax, A. C., & Majluf, N. S. (1991). The strategy concept and process. New York: Prentice-Hall.
21. Herrera, F., Herrera-Viedma, E., & Verdegay, J. L. (1996). A model of consensus in group decision making under linguistic assessments. Fuzzy Sets and Systems, 78(2), 73-87.
22. Hsu, C. C., & Chen, C. Y. (2003). Applications of improved grey prediction model for power demand forecasting. Energy Conversion & Management, 44(14), 2241-2250.
23. Hsu, C. I., & Wen, Y. H. (2000). Application of grey theory and multiobjective programming towards airline network design, European Journal of Operational Research, 127(3), 44-68.
24. Hsu, H. M., & Chen, C. T. (1996). Aggregation of fuzzy opinions under group decision making. Fuzzy Sets and Systems, 79(3), 279-285.
25. Juan Carlos, L. L., & Eduardo, F. G. (2003). A new method for group decision support based on ELECTRE III methodology. European Journal of Operational Research, 148(1), 14-27.
26. Klapka, J., & Pinos, P. (2002). Decision support system for multicriterial R&D and information systems project selection. European Journal of Operational Research, 140(2), 434-446.
27. Lee, D. H., & Park, D. (1997). An efficient algorithm for fuzzy weighted average. Fuzzy Sets and Systems, 87(1), 39-45.
28. Levary, R. R., & Seitz, N. E. (1990). Quantitative methods for capital budgeting. Cincinnati, OH: South-Western Publishing Co.
29. Liou, T. S., & Wang, M. J. (1992). Fuzzy weighted average: An improved algorithm. Fuzzy Sets and Systems, 49(3), 307-315.
30. Lo, S. P., & Lin, Y. Y. (2004). Application of abductive polynomial network and grey theory to drill flank wear prediction. Applied Artificial Intelligence, 18(8), 713-734.
31. Ngwenyama, O. K., Noel, B., & Ayodele, M. (1996). Supporting facilitation in group support systems: Techniques for analyzing consensus relevant data. Decision Support Systems, 16(2), 155-168.
32. Pap, E., Bosnjak, Z., & Bosnjak, S. (2000). Application of fuzzy sets with different t-norms in the interpretation of portfolio matrices in strategic management. Fuzzy Sets and Systems, 114(1), 123-131.
33. Ray, T. G., & Triantaphyllou, E. (1998). Evaluation of ranking with regard to the possible number of agreements and conflicts. European Journal of Operational Research, 106(1), 129-136.
34. Ringuest, J. L., Graves, S. B., & Case, R. H. (2004). Mean-Gini analysis in R&D portfolio selection. European Journal of Operational Research, 154(1), 157-169.
35. Robinson, E. P., & Lawrence, F. B. (2004). Coordinated capacitated lot-sizing problem with dynamic demand: A lagrangian heuristic. Decision Sciences, 55(1), 25-53.
36. Rowe, A. J., Mason, R. O., & Dickel, K. E. (1994). Strategic management. Menlo Park, CA: Addison Wesley.
37. Schrage, L. (1991). UNDO: An optimization modeling system (4th ed.). Redwood City, CA: Scientific Press.
38. Shirland, L. E., Jesse, R. R., Thompson, R. L., & Iacovou, C. L. (2003). Determining attribute weights using mathematical programming. Omega, 31(6), 423-437.
39. Tan, B., Lin, C., & Hsieh, P. J. (2003). Application of fuzzy set theory and multi-objective decision making in project portfolio selection. NTU Management Review, 13(2), 101-135.
40. Tan, K. H., & Platts, K. (2003). Linking objectives to actions: A decision support approach based on cause-effect linkages. Decision Sciences, 34(3), 569-593.
41. Thieme, R. J., & Song, M. (2000). Artificial neural network decision support systems for new product development project selection. Journal of Marketing Research, 37(4), 499-507.
42. Vanegas, L. V., & Labib, A. W. (2001). Application of new fuzzy weighted average method to engineering design evaluation. International Journal of Production Research, 39(6), 1147-1162.
43. Walukiewicz, S. (1991). Integer programming. Dordrecht, Netherlands: Kluwer Academic Publisher.
44. Waterhouse, J., & Svendsen, A. (1998). Strategic performance monitoring and management. Toronto, Canada: CICA.
45. Wu, C. C., & Chang, N. B. (2004). Corporate optimal production planning with varying environmental costs: A grey compromise programming approach. European Journal of Operational Research, 155(2), 68-95.
46. Yeh, J. M., Lin, C., Kreng, B., & Gee, J. Y. (1999). A modified procedure for synthesizing ratio judgments in the analytic hierarchy process. Journal of the Operational Research Society, 50(8), 867-873.
47. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353.
48. Zhu, Z., Sivakumar, K., & Parasuraman, A. (2004). A mathematical model of service failure and recovery strategies. Decision Sciences, 35(3), 493-525.
49. Zimmermann, H. J. (1991). Fuzzy set theory and its application. Boston: Kluwer Academic.