Evaluating the Corruption Susceptibility Index of Infrastructure Procurement and Management in the Developed Context: The Case of Hong Kong

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2 Citations (Scopus)

Abstract

This study evaluates the susceptibility patterns of the procurement process of infrastructure projects to corruption in Hong Kong. An expert survey is conducted with infrastructure-related professionals from Hong Kong (HK) using nonprobabilistic sampling approaches. A total of 38 responses comprising both closed-ended and open-ended responses were retrieved and analyzed. This study employs a soft computing technique coupled with other descriptive tools to evaluate the susceptibility patterns. Whereas the contract stage of the process was revealed to be the highest-ranked susceptible stage of the procurement process, the model indicated that the procurement process in HK is relatively less prone to corrupt practices. Although there are notable studies on the subject matter, this study arguably is one of the first to examine the susceptibility patterns of the stages within the infrastructure procurement process to corruption in the specific context of a developed region. It contributes to the existing knowledge of corruption in infrastructure project procurement by revealing the respective stages of the procurement process that require more in-depth investigations and more stringent efforts not only to extirpate the vulnerabilities but also to develop measures that will safeguard the procurement process and related activities from corruption. The approach adopted in this study can guide the assessment of similar corruption-related constructs in other contexts or regions.

Original languageEnglish
Article number05021006
JournalJournal of Infrastructure Systems
Volume27
Issue number2
DOIs
Publication statusPublished - 1 Jun 2021

Keywords

  • Corruption
  • Fuzzy synthetic evaluation (FSE)
  • Hong Kong
  • Infrastructure projects
  • Project management
  • Susceptibility index (SI)

ASJC Scopus subject areas

  • Civil and Structural Engineering

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