Evaluating and prioritizing the service quality of higher education is an essential issue for the successful implementation of Education for Sustainable Development (ESD). This study investigates an evaluation framework to assess the performances of higher education institutes (HEIs) within the context of ESD based on student-perceived service quality. First, a conceptual model of the evaluation indicator system is explored by embedding sustainability-related indicators into the fuzzy SERVQUAL scale. Then, the evaluation of student-perceived service quality can be thought of as a problem of multicriteria decision-making (MCDM) that involves uncertainty and bounded rationality. Thus, an evaluation technique called hybrid fuzzy TODIM-ERA is proposed to address such evaluation problems by synthesizing the theoretical strengths of the intuitionistic fuzzy set theory, the evidential reasoning algorithm (ERA), and the TODIM (an acronym in Portuguese for interactive and multicriteria decision-making). Finally, a case study of five Chinese HEIs in maritime transportation is used to demonstrate the effectiveness and robustness of the proposed framework. Results provide the ranking order of all the alternative HEIs and the improvement strategies of each HEI for student-perceived service quality dimensions.

Population distribution has a huge influence on the development of port economic circle (PEC) in Ningbo. Residential satisfaction is one of key elements that determine housing location choice and, thus, the success of population distribution policy. To provide suggestions for the development of PEC, this study conducted a survey to investigate residential satisfaction and related factors in 11 port communities, which are located in the harbour area of Beilun, Zhenhai and Meishan in Ningbo. A total of 403 valid samples were collected through face-to-face interviews. The Likert scale was used to express satisfaction levels, with the highest level of 5 and the lowest level of 1. The survey data indicate that the mean value of residential satisfaction is 3.41, 3.40 and 3.49 in Beilun, Zhenhai and Meishan, respectively. Middle level residential satisfaction is noted in the port communities of Ningbo. A linear regression was performed to analyse the relationship between residential satisfaction and influence factors in terms of the demographic and socioeconomic features of the respondents and attributes of the house and neighbourhood. The results of the regression analysis show that household income, design of housing, type of community, population density and distance to the district commercial centre are the most influential factors of residential satisfaction. The findings suggest making regulations to enforce the design standards of new buildings. Moreover, measures to improve the accessibility and quality of public facilities and services in the communities should be encouraged to increase the attractiveness of neighbourhoods in the port area. Promoting land use with mixed commercial and residential functions is also suggested for the development of PEC.

Currently, enterprises are paying more and more attention to green innovation in order to reduce the negative impact on the environment and achieve sustainable development. Different from evaluating the green innovation ability of enterprises, how to evaluate a person’s green innovation ability from the perspective of open innovation is a new direction. This study aims at proposing a novel framework to evaluate college students’ green innovation ability. First, a set of criteria to evaluate college students’ green innovation ability is determined by experts using the panel consensus approach. Second, the best worst method (BWM) is used to calculate the weights of criteria. Lastly, modified fuzzy technique for order of preference by similarity to ideal solution technique (TOPSIS) technique is adopted to rank college students’ green innovation ability. Moreover, a case study is presented to verify the validity of the proposed method. The results provide implications for academic, industry, and policymakers. Specifically, through the evaluation of college students’ green innovation ability, universities can find the inadequacies in culturing students’ green innovation ability and strengthen education in the aspects corresponding to the criteria with high global weights. Companies can select the talented internship students with green innovation ability as employees and should realize that it is good for them to cultivate college students with universities. Policymakers of the education department can trace the quality of education in college senior students’ green innovation ability every year. In addition, they should pay more attention to establish policies regarding those criteria with high global weights.

Marine oil spills significantly adversely affect the socio-economic environment and marine ecosystems. Establishing an efficient emergency cooperation mechanism that enables swift and coordinated responses from all stakeholders is crucial to mitigate the harmful consequences of such spills and protect regional security. This study uses stochastic evolutionary game theory to develop an emergency cooperation model, focusing on the strategic interactions and dynamic evolution between three main parties: the local government, port enterprises, and specialized oil spill cleanup units. The findings indicate the following: (1) The strategy choice of the local government plays a dominant role in the three-party game and has a significant guiding effect on the behavioral decisions of port enterprises and specialized oil spill cleanup units. (2) The strength of the government’s reward and punishment mechanism directly affects the cooperation tendency of the port enterprises and specialized oil spill cleanup units. (3) When the emergency response is more efficient and the cooperation effect is significant, the cleanup units may choose negative cooperation based on payoff maximization in order to prolong the cleaning time. (4) In the process of system evolution, the strategies of local governments and port enterprises are more stable and less affected by random perturbations, while the strategy fluctuations of cleanup units are more sensitive. The findings enrich the theoretical framework for handling marine oil spill emergencies and provide valuable insights for developing efficient collaborative mechanisms and formulating well-grounded regulatory incentive policies.

Marine oil spills pose substantial risks to human society and ecosystems, resulting in significant economic and ecological consequences. Timely containment of oil films is a complex and urgent task, in which the efficient scheduling of oil containment booms plays a crucial role in reducing economic and ecological losses caused by oil spills. However, due to dynamically changing marine oil spills, the length of boom required and the losses caused by oil spills are inherently uncertain. This study aims to optimize the containment of oil films, exploring the interrelationships among oil films, spill losses, and scheduling decisions for booms. By incorporating economic and ecological losses into decisions, this study proposes a scheduling model for oil containment booms to minimize spill-related losses while reducing scheduling time. Additionally, an improved Multi-Objective Grey Wolf Optimization algorithm is used to solve the problem. A hypothetical case study is then conducted in the Zhoushan sea area of the East China Sea. The proposed scheduling scheme achieves a containment time of 8.9781 h and reduces total spill losses to CNY 313.68 million. Compared with a scheme that does not consider spill losses, the proposed method achieves a nearly 24% reduction in losses while maintaining comparable efficiency.

The economic efficacy of logistics infrastructure is being reshaped by the dual forces of digitalization and the labor market. However, a new-era “investment return paradox” has emerged. Digitalization and an abundant labor force are theoretically positive forces, so why does their combination, when coupled with capital investment, paradoxically engender negative emergence that suppresses growth? Conceptualizing the regional economy as a Socio-Technical System (STS), this paper unravels this paradox by identifying and theorizing an “adaptive lag trap”. Using provincial panel data from China, we first provide empirical validation for this trap, identifying a significant negative three-way interaction involving labor quantity (coef. = −0.218, p < 0.05). We then demonstrate that high-skilled labor quality is the key to mitigating this trap. While its direct interactive effects are not statistically significant, our analysis uncovers a robust and theoretically potent pattern: a higher-skilled workforce systematically reverses the negative trend of the interaction effect. The split-sample test provides the clearest evidence of this pattern, showing the coefficient pivoting from negative (−0.0572) in the low-skill subsample to positive (+0.109) in its high-skill counterpart. Our findings establish that high-skill human capital is a necessary condition to circumvent the “adaptive lag trap”, underscoring the imperative for a policy shift from investing in the scale of labor to cultivating its skill structure within a co-evolutionary framework.