Bidder collusion seriously undermines the fair competition of the construction project market, and effective identification of collusion behaviors is of vital importance to the implementation of proactive regulation and supervision. In this paper, the data of construction project bidders from 2011 to 2018 are selected in Shaanxi Province, China, and a bidder network of construction projects is constructed. The collusion suspicion of bidders is analyzed from the macro-, meso-, and microlevels. The results show that the bidder network has features as small world at macrolevels, and it is easy for bidders to involve in collusion. The network community formed by construction, supervision, and survey and design bidding enterprises is analyzed at the mesolevel, and the collusion of supervision enterprises is found to have the highest suspicion At the microlevel, the characteristic value judgment and community division are adopted to analyze the collusion suspicion, which is divided into high, medium, and low according to the possibility. Through a comparison with the actual data, it is found that the method proposed in this paper can effectively identify the collusion behavior of construction project bidders. This paper proposes red, yellow, and green warning mechanism and formulates hierarchical accurate management preparedness, which can provide some suggestions to help prevent bidders from colluding.
The shortage of water resources has seriously restricted the sustainable development of China’s economy. Contracted water-saving management (WSMC) has emerged as an important measure to effectively alleviate this problem. However, the rationality and fairness of benefit allocation affect the stakeholders’ enthusiasm for participating in the project. The lack of a water-saving benefit allocation scheme is one of the critical obstacles hindering the implementation and promotion of the project. This study identifies the core stakeholders in WSMC projects in Field-project in an irrigation district. Then, with comprehensive consideration of the importance, cost input, risk-taking, and effort of each participant, we examined the benefit allocation scheme in the WSMC projects of Field-project in an irrigation district by building a model based on Nash Equilibrium, Shapley value method, and modified Shapley value method. We found that the case in which the WUA E implements the WSMC project alone yields the lowest total revenue of the schemes considered, and each participant’s benefit is also at the lowest. Nash Equilibrium can achieve the maximum expected return for both participants. With the Shapley value method, the WUA E earns the largest benefits, accounting for 57.5% of total revenue, followed by the WSSE D. Under the calculation principle of the modified Shapley value model, the WUA E’s benefit decreases significantly, implying that the revenues previously earned by the WUA E are transferred to the WSSE D. This result is due to the below-average levels of importance, cost input risk-taking, and effort for WUA E in the project. It can be seen that the modified Shapley value method is more suitable for benefit allocation of the WSMC project of Field-project in an irrigation district. Finally, a typical case study in China on a shared WSMC project of Field-project in an irrigation district showed how the proposed method works. Then, we proposed policy implications for promoting project implementation from three perspectives: stakeholders, income distribution, and risk management, and identified the limitations of the research and outlined the future research directions.
Contracted water-saving management (CWSM) has emerged as a powerful model for water-saving actions. In a CWSM project, whether the benefit allocation among the stakeholders is fair and reasonable will affect the enthusiasm of stakeholders for participating in the project, as well as the stability of the project’s operations. This study identifies core stakeholders in CWSM projects of colleges/universities. Then, a preliminary benefit allocation model is constructed through the Shapley value method, risks are identified, and a modified model is developed based on the COWA-gray fixed weight clustering method. Finally, a CWSM project launched by a Chinese university is studied to verify the applicability of the modified model.
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