With the rapid development of urbanization, problems such as the tight supply and demand of water resources and the pollution of the water environment have become increasingly prominent, and the pressure on the carrying capacity of water resources has gradually increased. In order to better promote the sustainable development of cities, it is extremely important to coordinate the relationship between water resources and economic society. This study analyzed the current research status of water resources carrying capacity from two aspects, i.e., research perspective and research methodology, established an innovative evaluation system, and used the principal component analysis to analyze the water resources carrying capacity in Huai’an City, an important city in China’s Huaihe River Ecological Economic Zone. Based on the results, it is found that the water resources carrying capacity of Huai’an City has been declining year by year from 2013 to 2019. Based on the evaluation results, suggestions and measures to improve the water resources carrying capacity of the empirical city are proposed to provide an important decision basis for the coordinated development of urban economy, society, and water resources.

In construction safety management practices, identifying key stakeholders and specifying their safety behavior patterns are critical to avoid unsafe practices, which are the major cause of construction accidents. This paper argues that the main contractor and construction workers are key safety stakeholders in the construction safety management in China. The purpose of this paper is to develop an evolutionary game model to explore the safety behavior strategies of the main contractor and construction workers. In this framework, we explored the effects of model parameter changes on the evolution of safety behavior strategies and verify the evolution paths under different initial values by numerical simulations. The findings of this paper are as follows: Firstly, the safety and stability of construction projects are related to the possible losses caused by accidents, the amount of work required by construction workers to comply with safety regulations, the gain of bravado, the probability of accidents, and cost savings from the main contractor’s lax supervision. Secondly, the role of restraining the unsafe behavior of construction workers through the form of fines is limited, and increasing the fines to the main contractor cannot effectively reduce the unsafe behaviors. Thirdly, strengthening safety education, creating a safe atmosphere, and optimizing operating procedures are effective measures to improve the effectiveness of safety behavior. This study further extends the application of evolutionary game theory to construction safety management, and the findings can provide clear guidance for the development of effective incentives and constraints on safety behavior.

The phrase ‘green cities’ refers to an idealised and modernised urban development model that features harmonious development among the environment, ecology, society, culture, and the inhabitants of a city. Harmonious humanistic relations and green pathways have become predominant models in modern urban development. Green city construction has drawn considerable attention. However, the construction and development of green cities involves numerous problems. The various needs of different populations must be coordinated to foster the green development of a city. In this study, the analytic hierarchy process was used to classify factors related to green city construction into different levels. The scope of the empirical verification was eight cities alongshore the drainage area of the Jiangsu section of the Beijing–Hangzhou Canal. Data from 2009, 2014, and 2019 were selected for analysis. Both quantitative and qualitative analyses were performed using these data, and standards were established to serve as a reference for city administrators in the process of decision-making regarding green city construction.

The world produces a huge amount of urban construction waste each year. Scientific planning of the construction waste recycling path is urgently needed to improve the recycling of construction waste. Existing construction waste recycling models do not pay sufficient attention to the uncertainty of the recycling quantity, which limits their ability to provide support for solving practical problems. The purpose of this paper is to solve the problem of uncertain recycling quantities in optimizing the urban construction waste recycling path. Thus, this paper first builds a recycling model for a deterministic environment with the economic objective as the decision criterion and the transportation flow, construction waste treatment capacity and capability, and environmental and social impact as the constraints. Then, a robust optimization method is adopted to optimize the deterministic model for the uncertainty of the recycling quantity. The data of this paper are from Nanjing, China. The validity of the model and the evolution of the recycling path are tested based on the data of Nanjing. The findings of this paper are as follows: Firstly, the robust model is cost-effective in the face of uncertainty in supply. Secondly, the robust model has greater total treatment capacity. Even in the worst-case scenario, it can guarantee a higher treatment capacity. Thirdly, both models follow the proximity principle which reduces the transportation costs and only slowly increases the total cost of the robust model. This paper provides a scientific and convenient tool to plan the recycling path of construction waste in large cities.

E-commerce platforms are increasingly adopting cross-platform targeted advertising strategies, and the design of such strategies warrants attention. Focusing on cooperation between e-commerce and social media platforms, this study considers targeting precision, advertising intensity, privacy concerns and social utility on the effectiveness of targeted advertising. Using a game-theoretic model, we examine the decision between single- and cross-platform for e-commerce platforms in fully and partially overlapping user groups. The main findings indicate that (1) the social utility of social media platforms is a key factor in implementing cross-platform targeted advertising; (2) cross-platform targeted advertising is not always the optimal choice for e-commerce platforms; and (3) low-precision cross-platform strategy achieves three-party optimum in fully and partially overlapping user groups. The implications of the main findings include: (1) e-commerce platforms should prudently use social media platforms instead of relying excessively on their traffic; (2) e-commerce platforms should not regard cross-platform cooperation as the default option but as a differentiated, situation-specific decision; and (3) e-commerce platforms should promote co-creation of value and proprietary data accumulation when cooperating with social media platforms. The findings can help e-commerce platforms to choose proper targeted advertising strategy in practice. This study also provides a theoretical supplement for cross-platform targeted advertising research.

Purpose: In practice, platform partnerships may be unstable, and privacy protection strategies may vary across platforms. This study examines optimal cooperation and privacy protection strategies for third-party platforms implementing cross-platform targeted advertising in competitive markets. Design/methodology/approach: We develop a game-theoretic model involving two competing third-party platforms, one e-commerce platform, consumers, and advertisers. Equilibrium outcomes are derived using backward induction. The model captures platforms' decisions regarding cross-platform cooperation and privacy protection strategies. Findings: In cross-platform targeted advertising, cross-platform cooperation does not necessarily confer a competitive advantage on cooperating third-party platforms. Both symmetric and asymmetric cooperation can arise in equilibrium, depending on competition in the consumer and advertiser markets. Privacy protection does not necessarily increase platform profits, and its effects depend on the relative strength of competition along the content and privacy protection dimensions. Third-party platforms do not always choose high levels of privacy protection. Their choices depend on consumer privacy concerns and rivals' strategies, while asymmetric protection can provide a basis for differentiation. Originality/value: This study examines competing third-party platforms' decisions on cooperation with an e-commerce platform and privacy protection in cross-platform targeted advertising. It extends platform coopetition research by explaining how vertical data cooperation reshapes horizontal competition and advances privacy strategy research by examining the relative strength of competition along the content and privacy protection dimensions. The findings help third-party platforms assess when cooperation increases profits and which privacy protection strategy is preferable.