Consolidating SWOT analysis with nonhomogeneous uncertain preference information |
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| Authors: | Chang-Yuan Gao Ding-Hong Peng |
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| Affiliation: | 1. Ghent University, Department of Agricultural Economics, B-9000 Ghent, Belgium;2. International Rice Research Institute (IRRI), Los Baños, Laguna, Philippines;3. University College Dublin, School of Public Health, Physiotherapy & Population Science, Dublin 4, Ireland;4. University of Twente, Department Psychology of Conflict, Risk and Safety, NL-7500 AE Enschede, The Netherlands;5. Universitat Rovira i Virgili, Dept. Communication Studies, Tarragona 43002, Spain;6. Hylobates Consulting Srl, Rome, Italy;7. Assessment and Registration Agency, Food & Veterinary Service, Riga, Latvia;1. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, Jiangsu, China;2. College of Finance, Jiangsu Vocational Institute of Commerce, Nanjing 211168, China;1. Labovitz School of Business and Economics, University of Minnesota Duluth, 365Q LSBE, 1318 Kirby Drive, Duluth, MN 55812, USA;2. Labovitz School of Business and Economics, University of Minnesota Duluth, 385K LSBE, 1318 Kirby Drive, Duluth, MN 55812, USA |
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| Abstract: | SWOT analysis is an important support tool for decision-making, and is commonly used to systematically analyze organizations’ internal and external environments. However, one of its deficiencies is in the measurement and evaluation of prioritization of the factors and strategies. This paper is aimed to present a novel quantified SWOT analytical method based multiple criteria group decision-making (MCGDM) concept, in which the priorities of SWOT factors and groups are derived by multiple decision makers (DMs) with nonhomogeneous uncertain preference information (NUPI), such as interval multiplicative preference relations, interval fuzzy preference relations, and uncertain linguistic preference relations. In this method, the SWOT analysis provides a basic frame within which to perform analyses of decision situations, in turn, MCGDM methods assist in carrying out SWOT more analytically and in elaborating the results of the analyses so that SWOT factors and groups can be prioritized with respect to the entire SWOT. The uniform and aggregation of the NUPI and the derivation of priorities for SWOT groups and factors are investigated in detail. Finally, an example is to validate the procedure of the proposed method. |
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