Floods are among the most common and destructive natural disasters confronted by cities and are further aggravated by rapid climate change and increasing urbanization, posing a great challenge to flood risk management. To cope with uncertainty, there is a need to move towards approaches to managing flood risk by taking resilience into consideration. While the evaluation of urban flood resilience has gained much attention in recent decades, studies on quantitative measurement using multiple criteria decision making (MCDM) approaches are rare. In addition, the results determined by different MCDM methods may exhibit considerable variability. It is an intractable task to gather a group consensus from these methods. In this regard, in this paper, we propose a group-decision-making framework for measuring urban resilience to flooding, combining three stages, which are (i) normalizing the data, (ii) weighting the criteria and (iii) aggregating the results. Four objective MCDM methods—i.e., the variation coefficient method, Shannon weighting method, CRITIC and ideal point method—are proposed and treated as reliable methods. A stochastic multi criteria acceptability analysis is adopted to integrate those results into a composite resilience index. The proposed methodology is applied to the resilience evaluation problem of 41 cities in the Yangtze River basin, and the results are compared with those obtained with the four MCDM methods. It is demonstrated that our method considers all possible preferences among the results provided by various MCDM methods and is thus more robust and acceptable.

To study the impact of government subsidies and altruistic preferences on green supply chain innovation, Stackelberg game theory and numerical simulation are used to analyze and verify the optimal decision-making of enterprises under different decision-making models. The results show that the two methods of government subsidies can improve product greenness, corporate profits, and overall supply chain performance. While only the unilateral altruistic preference of the manufacturer or retailer can improve product greenness, the profit of the other member, and the overall profit of the green supply chain, doing so will reduce its own profit. When the two members have the same degree of altruistic preference, the retailer’s altruistic preference is more conducive to improving product greenness. Increasing government subsidies can strengthen, to a certain extent, the effect of altruistic preference on product greenness, the profit of the other member, and the profit of the green supply chain. However, when the manufacturer implements altruistic preference, if the government subsidy exceeds a certain range, then the increase in the government subsidy will accelerate the decline of the manufacturer’s own profit.

This study studies a supply chain consisting of one supplier and two retailers and analyzes the optimal decisions of ordering quantity in four types of no fairness concern, horizontal fairness concern, vertical fairness concern, and dual‐fairness concern and the impacts of fairness concern on supply chain. The results show that (1) vertical fairness concern can decrease the ordering quantity of the retailer with vertical fairness concern and the wholesale price and improve the ordering quantity of the retailer without fairness concern; (2) horizontal fairness concern can increase the ordering quantity of the retailer with horizontal fairness concern and improve the ordering quantity of the retailer without fairness concern, but does not influence the wholesale price; and (3) dual‐fairness concern can decrease the ordering quantity of the retailer with dual‐fairness concern and the wholesale price and improve the ordering quantity of the retailer without fairness concern as a whole. The numerical analysis also proves the findings.