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dc.contributor.authorMing Shan
dc.contributor.authorAlbert P. C. Chan
dc.contributor.authorYun Le
dc.contributor.authorBo Xia
dc.contributor.authorYi Hu
dc.date.accessioned2017-05-08T22:11:29Z
dc.date.available2017-05-08T22:11:29Z
dc.date.copyrightOctober 2015
dc.date.issued2015
dc.identifier.other38861538.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl/handle/yetl/73153
dc.description.abstractCorruption has been identified as the greatest obstacle to economic and social development. Public construction projects, in particular, face high corruption risk as public construction sector has been consecutively deemed as the most corrupt one. Despite considerable efforts have been undertaken to measure corruption at a nation level, few researchers focus on the measurement of corruption in construction projects. This paper develops a fuzzy measurement model for the potential corruption in public construction projects in China. Through semistructured interviews with 14 experts, and then a questionnaire survey with 188 respondents, 24 measurement items of corruption were identified and further categorized into five constructs. The fuzzy set theory was then adopted to quantify each measurement item, construct, and the overall corruption level. This model can facilitate in evaluating, revealing, and monitoring corruption in public construction projects. Although this paper focuses on measuring corruption in public construction projects in China, similar research methods can be applied in other countries around the world and thus contribute to the global body of knowledge of corruption.
dc.publisherAmerican Society of Civil Engineers
dc.titleMeasuring Corruption in Public Construction Projects in China
dc.typeJournal Paper
dc.journal.volume141
dc.journal.issue4
dc.journal.titleJournal of Professional Issues in Engineering Education and Practice
dc.identifier.doi10.1061/(ASCE)EI.1943-5541.0000241
dc.treeJournal of Professional Issues in Engineering Education and Practice:;2015:;Volume ( 141 ):;issue: 004
dc.contenttypeFulltext


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