A User Profile of Tendering and Bidding Corruption in the Construction Industry Based on SOM Clustering: A Case Study of China

Tendering and bidding is considered the stage most vulnerable to corruption in the construction industry. The prevalence of collusive tendering and bidding induces frequent accidents and even sabotages the fairness of the construction market. Although a large number of tendering and bidding corruption cases are investigated in China every year, this information has not been fully exploited. The profile of the different corruptors remains vague. Therefore, this study uses the user profile method to establish a corruptor characteristic model based on the human paradigm, where 1737 tendering and bidding collusion cases were collected from China to extract the features. Four types of specific corruption groups are detected based on self-organizing feature map (SOM) cluster analysis, comprising low-age corruptors, grassroots mild corruptors, middle-level collapsing corruptors, and top leader corruptors. Furthermore, the profiles of different cluster corruptors are described in detail from four dimensions. This study reveals the law of tendering and bidding corruption from the perspective of the user profile and suggests that a user profile system for corruption in bidding should be developed in the process of the precise control of corruption, which promotes the transformation from strike after corruption to prevention beforehand. It is conducive to forming the resultant force of big data for precise anti-corruption.