Abstract
Regardless of how clean a city may appear to be, it can be tainted by the hidden forms of corruption. Hence, examining the prevalence of corruption and the effectiveness of anti-corruption measures (ACMs) are necessary to provide the information needed to promote or attain corruption-free city. However, determining the extent of corruption or the effectiveness of ACMs, especially regarding infrastructure project procurement and management, poses a new challenge. This study, therefore, employs a soft computing approach known as fuzzy synthetic evaluation to examine the effectiveness of ACMs. Twenty-six ACMs designed to curb the corrupt practices in infrastructure procurement processes are identified through a systematic review of the extant literature. Then, an empirical survey is conducted with experts in infrastructure procurement and management processes from Hong Kong. Results reveal that probing and transparency are the most effective ACMs. This empirical research is one of the first to examine the effectiveness of ACMs in infrastructure project procurement and management, thereby extending the body of knowledge on corruption-related studies in project (procurement and management)-related research and corruption-free cities. This study also offers practical implications that will inform industry practitioners, policymakers, and anti-corruption institutions about the effectiveness of ACMs and the need for improvement of less effective measures. Finally, this work contributes to the development of a holistic approach to corruption prevention in infrastructure project procurement and management.
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