Collusive bidding has been a deep-seated issue in the construction market for a long time. The strategies implemented by bid riggers are deliberate, interactive, and complex, suggesting that antitrust authorities have difficulty preventing collusive behaviors. Based on game payoff matrixes, this study proposes a system dynamics (SD) model to present the deterrence of punitive measures, namely the certainty of punishment (CoP) and the severity of punishment (SoP), on regular bidders’ to-collude decision-making. Data were collected from the Chinese construction industry to test the proposed SD model. While the model was supported, the results indicate that the CoP has a greater impact than the SoP on deterring regular bidders from making to-collude decisions. Furthermore, these two punitive measures cannot be replaced by each other, given the same deterrence effects. Thus, the study demonstrates the usefulness of deterrence theory to inhibit collusive bidding in the construction sector. It also sheds some light on the formulation of competition policy from the perspective of deterrence.

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Urban regeneration (UR) has been a leading concern in urban studies globally. China’s rapid urbanization has undergone profound urban decay and social contestation, for which UR has emerged as a viable solution. However, UR is not without its drawbacks. It has caused emerging spatial and planning problems; however, few studies have explored the characteristics and issues of UR from the view of spatial analytics on the city scale. This study aims to depict the distribution characteristics of UR projects in Chinese cities and to reveal whether it meets the requirements of urban development from the planning perspective. The nearest neighbor index and its hierarchical clustering, as well as kernel density estimation are used in conjunction to investigate the spatial distribution characteristics; and the relationship between project distribution and each urban development indicator is explored using mixed spatial characteristics analyses, such as buffer analysis, space syntax, and heat mapping. Considering Shenzhen as the empirical study city, this research is based on all officially released data of implemented UR projects between 2010 and 2021. The findings imply that the UR projects in Shenzhen are mostly located in areas with higher economic development levels and accessibility with areas witnessing industrial restructuring and severe urban decay being prone to be designated for UR initiatives. The spatial distribution characteristics disclose the challenges inherent in the mix of top-down and market-driven UR approaches as well as the dilemma of the center-periphery pattern in UR implementation. Furthermore, the contradiction between the growing population and limited land resources as well as the barriers to industrial clustering formation are also revealed. This study enriches the methodological framework for spatial and visualization studies of urban regeneration in worldwide cities and sheds light on how to promote UR in regard to urban sustainability with ramifications for future urban development in other Chinese cities.