The transportation systems are facing major challenges due to changes social environment caused by the COVID-19 pandemic. How to construct a suitable evaluation criterion system and suitable assessment method to evaluate the status of the urban transportation resilience has become a predicament nowadays. Firstly, the criteria for evaluating the current state of transportation resilience involve many aspects. New features of transportation resilience under epidemic normalization are exposed, and previous summaries focusing on resilience characteristics under natural disasters can hardly reflect the current state of urban transportation resilience comprehensively. Based on this, this paper attempts to incorporate the new criteria (Dynamicity, Synergy, Policy) into the evaluation system. Secondly, the assessment of urban transportation resilience involves numerous indicators, which make it difficult to obtain quantitative figures for the criteria. With this background, a comprehensive multi-criteria assessment model based on q-rung orthopair 2-tuple linguistic sets is constructed to evaluate the status of transportation infrastructure from perspective on the COVID-19. Then, an example of urban transportation resilience is given to demonstrate the feasibility of the proposed approach. Subsequently, sensitivity analysis about parameters and global robust sensitivity analysis are conducted, and comparative analysis of existing method is given. The results reveal that the proposed method is sensitive to global criteria weights, so it is suggested that more attention should be paid to the rationality of the weight of criteria to avoid the influence on the results when solving MCDM problems. Finally, the policy implications regarding transport infrastructure resilience and appropriate model development are given.

With increased environmental protection awareness, sustainability has been incorporated into supply chain management. Sustainable supplier selection and evaluation have become an acritical part of supply chain management. They can significantly improve the supply chain’s operational performance and enhance enterprises’ competitiveness. Based on trapezoidal interval type-2 fuzzy numbers (TIT2FNs) and cloud probability dominance relations (PDR), manufacturers can make more tangible and environmentally friendly decisions in the SSSE process. In this paper, a SSSE indicator system is first established using the necessary economic, environmental, and social factors. The importance of the indicators described in linguistic terms is transformed into TIT2FNs, and the weight of each indicator is calculated. In order to prevent candidate suppliers from promoting performance maliciously, different weights are given according to the impact of the enterprise’s historical performance on the present. Finally, the cloud PDR method is used to determine the optimal sustainable supplier. A case study and analysis are provided to show the feasibility and superiority of the proposed method.

With improvements in consumers’ environmental awareness and the promulgation of environmental regulations, an increasing number of companies are beginning to pay attention to green product design, pricing, and purchasing strategies. However, due to demand fluctuations and cost changes brought about by green product design and manufacturing, understanding corporate behavior preferences and constructing non‐single‐period pricing and procurement strategies can profoundly affect long‐term cooperation among green supply chain members. This paper constructs six scenarios in which decision‐makers have altruistic preferences simultaneously or separately and whether the retailer adopts strategic inventory. In addition, the impact of altruistic preferences and strategic inventory on the decision‐making and profits of the two‐period supply chain for marginal cost‐intensive green products (MIGPs) are analyzed. The results show that altruistic preferences and purchasing strategies do not affect MIGPs’ greening levels. Besides, the retailer’s strategic inventory is still an effective bargaining tool but is not necessarily beneficial to profits. Noteworthy, when deciders exhibit altruism simultaneously or alone, the effects on certain decisions and strategic inventory range are significantly different. Finally, the retailer’s altruistic preference may not affect the green supply chain’s profits, but the manufacturer’s altruism improves total profits.

The evaluation of manufacturing component suppliers is focused on economic indicators, with insufficient emphasis on green indicators and no consideration of the correlation between indicators. Firstly, indicators related to green production are incorporated into the supplier evaluation system. Then, for the problem that attributes in decision making can be divided into different categories and there are interrelationships between attributes of the same category, a multi-attribute decision-making (MADM) method based on the partitioned Maclaurin symmetric mean operator (PMSM) is proposed. Finally, the proposed MADM method was applied to the evaluation of component suppliers considering green production. Comparing popular decision methods with the newly proposed method for validation, it was demonstrated that the proposed multi-attribute decision method is highly flexible and versatile. Furthermore, the newly proposed aggregation operator can not only handle the correlation between multiple attributes, but also be converted to other general aggregation operators through parameter adjustment.