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- Publisher Website: 10.1080/01446190902883049
- Scopus: eid_2-s2.0-68049120612
- WOS: WOS:000213267700006
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Article: An entropy-based financial decision support system (e-FDSS) for project analysis in construction SMEs
Title | An entropy-based financial decision support system (e-FDSS) for project analysis in construction SMEs |
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Authors | |
Keywords | Genetic algorithm Fuzzy logic Entropy Decision support system Project management |
Issue Date | 2009 |
Citation | Construction Management and Economics, 2009, v. 27, n. 5, p. 499-513 How to Cite? |
Abstract | Uncertainty contributes a major part in the accuracy of a decision-making process while its inconsistency is always difficult to be solved by existing decision-making tools. Entropy has been proved to be useful to evaluate the inconsistency of uncertainty among different respondents. The study demonstrates an entropy-based financial decision support system called e-FDSS. This integrated system provides decision support to evaluate attributes (funding options and multiple risks) available in projects. Fuzzy logic theory is included in the system to deal with the qualitative aspect of these options and risks. An adaptive genetic algorithm (AGA) is also employed to solve the decision algorithm in the system in order to provide optimal and consistent rates to these attributes. Seven simplified and parallel projects from a Hong Kong construction small and medium enterprise (SME) were assessed to evaluate the system. The result shows that the system calculates risk adjusted discount rates (RADR) of projects in an objective way. These rates discount project cash flow impartially. Inconsistency of uncertainty is also successfully evaluated by the use of the entropy method. Finally, the system identifies the favourable funding options that are managed by a scheme called SME Loan Guarantee Scheme (SGS). Based on these results, resource allocation could then be optimized and the best time to start a new project could also be identified throughout the overall project life cycle. |
Persistent Identifier | http://hdl.handle.net/10722/265561 |
ISSN | 2023 Impact Factor: 3.0 2023 SCImago Journal Rankings: 0.874 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Tang, Llewellyn C.M. | - |
dc.contributor.author | Leung, Andrew Y.T. | - |
dc.date.accessioned | 2018-12-03T01:21:02Z | - |
dc.date.available | 2018-12-03T01:21:02Z | - |
dc.date.issued | 2009 | - |
dc.identifier.citation | Construction Management and Economics, 2009, v. 27, n. 5, p. 499-513 | - |
dc.identifier.issn | 0144-6193 | - |
dc.identifier.uri | http://hdl.handle.net/10722/265561 | - |
dc.description.abstract | Uncertainty contributes a major part in the accuracy of a decision-making process while its inconsistency is always difficult to be solved by existing decision-making tools. Entropy has been proved to be useful to evaluate the inconsistency of uncertainty among different respondents. The study demonstrates an entropy-based financial decision support system called e-FDSS. This integrated system provides decision support to evaluate attributes (funding options and multiple risks) available in projects. Fuzzy logic theory is included in the system to deal with the qualitative aspect of these options and risks. An adaptive genetic algorithm (AGA) is also employed to solve the decision algorithm in the system in order to provide optimal and consistent rates to these attributes. Seven simplified and parallel projects from a Hong Kong construction small and medium enterprise (SME) were assessed to evaluate the system. The result shows that the system calculates risk adjusted discount rates (RADR) of projects in an objective way. These rates discount project cash flow impartially. Inconsistency of uncertainty is also successfully evaluated by the use of the entropy method. Finally, the system identifies the favourable funding options that are managed by a scheme called SME Loan Guarantee Scheme (SGS). Based on these results, resource allocation could then be optimized and the best time to start a new project could also be identified throughout the overall project life cycle. | - |
dc.language | eng | - |
dc.relation.ispartof | Construction Management and Economics | - |
dc.subject | Genetic algorithm | - |
dc.subject | Fuzzy logic | - |
dc.subject | Entropy | - |
dc.subject | Decision support system | - |
dc.subject | Project management | - |
dc.title | An entropy-based financial decision support system (e-FDSS) for project analysis in construction SMEs | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1080/01446190902883049 | - |
dc.identifier.scopus | eid_2-s2.0-68049120612 | - |
dc.identifier.volume | 27 | - |
dc.identifier.issue | 5 | - |
dc.identifier.spage | 499 | - |
dc.identifier.epage | 513 | - |
dc.identifier.eissn | 1466-433X | - |
dc.identifier.isi | WOS:000213267700006 | - |
dc.identifier.issnl | 0144-6193 | - |