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Entropic Risk Analysis by a High Level Decision Support System for Construction SMEs |
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| Authors: | L. C. M. Tang A. Y. T. Leung C. W. Y. Wong |
| Affiliation: | 1Lecturer in Construction Management, School of Construction Management and Engineering, Univ. of Reading, Whitenights, P.O. Box 219, Reading RG6 6AW, U.K. (corresponding author). E-mail: l.tang@reading.ac.uk 2Professor (Chair), Dept. of Building and Construction, City Univ. of Hong Kong, 83 Tat Chee Ave., Kowloon Tong, Hong Kong, People’s Republic of China. E-mail: andrew.leung@cityu.edu.hk 3Teaching Associate, Dept. of Construction, Hong Kong Institute of Vocational Education, 18 Tsing Wun Rd., Tuen Mun, New Territories, Hong Kong, People’s Republic of China. E-mail: christywwy@vtc.edu.hk |
| Abstract: | The method of entropy has been useful in evaluating inconsistency on human judgments. This paper illustrates an entropy-based decision support system called e-FDSS to the solution of multicriterion risk and decision analysis in projects of construction small and medium enterprises (SMEs). It is optimized and solved by fuzzy logic, entropy, and genetic algorithms. A case study demonstrated the use of entropy in e-FDSS on analyzing multiple risk criteria in the predevelopment stage of SME projects. Survey data studying the degree of impact of selected project risk criteria on different projects were input into the system in order to evaluate the preidentified project risks in an impartial environment. Without taking into account the amount of uncertainty embedded in the evaluation process; the results showed that all decision vectors are indeed full of bias and the deviations of decisions are finally quantified providing a more objective decision and risk assessment profile to the stakeholders of projects in order to search and screen the most profitable projects. |
| Keywords: | Artificial intelligence Construction industry Decision support systems Entropy Risk management |