Over recent years, the issue of corruption in the public construction sector has attracted increasing attention from both practitioners and researchers worldwide. However, limited efforts are available for investigating the underlying factors of corruption in this sector. Thus, this study attempted to bridge this knowledge gap by exploring the underlying factors of corruption in the public construction sector of China. To achieve this goal, a total of 14 structured interviews were first carried out, and a questionnaire survey was then administered (...) to 188 professionals in China. Two iterations of multivariate analysis approaches, namely, stepwise multiple regression analysis and partial least squares structural equation modeling were successively utilized to analyze the collected data. In addition, a case study was also conducted to triangulate the findings obtained from the statistical analysis. The results generated from these three research methods achieve the same conclusion: the most influential underlying factor leading to corruption was immorality, followed by opacity, unfairness, procedural violation, and contractual violation. This study has contributed to the body of knowledge by exploring the properties of corruption in the public construction sector. The findings from this study are also valuable to the construction authorities as they can assist in developing more effective anti-corruption strategies. (shrink)

Over recent years, the issue of corruption in the public construction sector has attracted increasing attention from both practitioners and researchers worldwide. However, limited efforts are available for investigating the underlying factors of corruption in this sector. Thus, this study attempted to bridge this knowledge gap by exploring the underlying factors of corruption in the public construction sector of China. To achieve this goal, a total of 14 structured interviews were first carried out, and a questionnaire survey was then administered (...) to 188 professionals in China. Two iterations of multivariate analysis approaches, namely, stepwise multiple regression analysis and partial least squares structural equation modeling were successively utilized to analyze the collected data. In addition, a case study was also conducted to triangulate the findings obtained from the statistical analysis. The results generated from these three research methods achieve the same conclusion: the most influential underlying factor leading to corruption was immorality, followed by opacity, unfairness, procedural violation, and contractual violation. This study has contributed to the body of knowledge by exploring the properties of corruption in the public construction sector. The findings from this study are also valuable to the construction authorities as they can assist in developing more effective anti-corruption strategies. (shrink)

Response strategy is a key for preventing widespread corruption vulnerabilities in the public construction sector. Although several studies have been devoted to this area, the effectiveness of response strategies has seldom been evaluated in China. This study aims to fill this gap by investigating the effectiveness of response strategies for corruption vulnerabilities through a survey in the Chinese public construction sector. Survey data obtained from selected experts involved in the Chinese public construction sector were analyzed by factor analysis and partial (...) least squares-structural equation modeling. Analysis results showed that four response strategies of leadership, rules and regulations, training, and sanctions, only achieved an acceptable level in preventing corruption vulnerabilities in the Chinese public construction sector. This study contributes to knowledge by improving the understanding of the effectiveness of response strategies for corruption vulnerabilities in the public construction sector of developing countries. (shrink)