Article ID: | iaor2008250 |
Country: | United Kingdom |
Volume: | 33 |
Issue: | 3 |
Start Page Number: | 223 |
End Page Number: | 234 |
Publication Date: | Jun 2005 |
Journal: | OMEGA |
Authors: | Tzeng Gwo-Hshiung, Chiou Hua-Kai, Cheng Ding-Chou |
Keywords: | decision theory: multiple criteria, fuzzy sets |
In actual environmental investment for industry, the stakeholders are often required to evaluate the investment strategies according to their own subjective preferences in terms of numerical values from various criteria, such as economic effectiveness, technique feasibility and environmental regulation. Thus, this situation can be regarded as a fuzzy multiple criteria decision-making (MCDM) problem, so the fuzziness and uncertainty of subjective perception should be considered. This paper proposes an alternative approach, the non-additive fuzzy integral, to cope with evaluation of fuzzy MCDM problems particularly while there is dependence among considered criteria. To illustrate the proposed procedure, the sustainable development strategy for aquatic product processors in Taiwan is investigated. In this paper we employ triangular fuzzy numbers to represent the decision makers' subjective preferences on the considered criteria, as well as for the criteria measurements to evaluate a sustainable development planning case for industry. Firstly, in this study we employ factor analysis to extract four independent common factors from those criteria. Secondly, we construct the evaluation frame using AHP composed of the above four common factors with twelve evaluated criteria, and then derive the relative weights with respect to considered criteria. Thirdly, the synthetic utility value corresponding to each sustainable development strategy is aggregated by the fuzzy weights with fuzzy performance values, and the best investment strategies can then be decided. Through this study, we successfully demonstrate that the non-additive fuzzy integral is an effective evaluation and appears to be more appropriate than the traditional simple additive weighted method, especially when the criteria are dependent.