In developing countries such as China, commercial fishermen’s occupational health risks are rarely studied despite being extremely critical for the sustainable development of the fisheries sector. In this study, we attempt for the first time to categorize and prioritize multiple types of health risks posed by these fishermen. This was accomplished by conducting a structured questionnaire survey between 9 January 2022 and 24 May 2022. We sought the professional opinion of fishermen that were located in the coastal areas of Zhejiang, China, namely Zhoushan (121 responses, 64%), Taizhou (66 responses, 49%), and Wenzhou (94 responses, 53%). This study used two hundred eighty-one questionnaires with a consistency ratio (CR) below 0.1 and completed in every respect. Fuzzy Analytical Hierarchical Process (Fuzzy AHP) and Importance Performance Analysis (IPA) statistics were employed to perform statistical analysis. Results have revealed that commercial fishermen’s health is affected by five main risk factors, namely natural (0.058), biological (0.088), social (0.152), psychological (0.234), and physical (0.468), which are arranged from the least to the most significant risk factors. As for the performance of the main risk factors, the physical risk was ranked first (4.786), followed by social risk (4.571), psychological risk (4.214), biological risk (4.000), and natural risk (3.429). These research findings can serve as guidelines for managers. Moreover, this study discusses ramifications, constraints, and proposals for future research.

The economic impact of a public emergency, such as the COVID-19 pandemic, is often reduced by micro and small businesses (MSEs) undertaking sustainability-oriented innovation for public emergencies (SOIPE), which includes production and service innovation, information innovation, marketing innovation, and labor innovation. The originality of this study lies in its prediction and evaluation of COVID-19′s challenges and SOIPE’s requirements to have a keen observation and discovery ability. In this paper, we combined nominal group technique, fuzzy analytical hierarchy process, least squares, and a case study to investigate governance, economic, financial, sociocultural, and environmental sustainability and demonstrate the MSEs’ sustainability evaluation model. In a qualitative study and literature review, MSEs were found to use SOIPE in a variety of ways. Some studies focused on marketing innovation, while others were hampered by their limited understanding. From both a theoretical and empirical perspective, this study suggests that MSEs should identify their optimal SOIPE based on the impact and volatility of a public emergency. In addition, this study presents an assessment of the impact and environmental volatility of a public emergency, as well as MSEs’ SOIPE, which is more helpful for enterprises. Finally, this study creatively introduces the SOIPE of MSEs, which has important policy ramifications.

China has a large number of gas stations, with which thousands of workers are associated. There is abundant online literature documenting the various occupational health risks these workers face. However, this literature has many flaws to address, and it falls short of suggesting measures to manage these risks. This study strives to fill that gap, and aims to improve the occupational health of gas station workers through comprehensive risk management and performance analysis. To this end, a reasonable volume of reliable data, i.e., 208 completed questionnaires, were analyzed through current statistical routines, viz., fuzzy Analytical Hierarchy Process (AHP) and Importance Performance Analysis (IPA). These methods were employed to hierarchically organize the main factors and sub-factors of physical risk management, chemical risk management, biological risk management, physiological risk management and psychological risk management according to their appraised importance, and screen out the risk management stratagem for priority improvement. Research findings reveal that chemical risk and biological risk response schemes have the lowest performance, and need to be prioritized for improvement. Furthermore, this study argues that we can safeguard the occupational health of gas station workers through appropriate risk management strategies. It also elaborates on implications, limitations and future research directions.

In Pakistan, the fisheries sector is capable of making a significant contribution to the national economy. However, the proper and sustainable development of this sector is essential to its success, and we need to be aware of all the risks that it faces. At present, there is a dearth of comprehensive research that details, compares, and proposes applied measures to mitigate the risks facing the fisheries sector. Thus, this study is the first novel attempt to fill this gap. The data were collected through a survey and analyzed by multi-criteria decision analysis (MCDA). The study postulates that Sindh fisheries are affected by five main risk factors, namely technical, market, ecological, natural, and management. These risk factors are arranged from least to most significant. With regard to the performances of the main risk factors, management risk was ranked as the greatest risk, followed by ecological risk, natural risk, and technical risk. The findings of this study provide a road map for managerial decisions. Furthermore, this study also presents some potential limitations related to the scale of the data and analysis methods. Future studies may therefore use data collected on a large scale and alternative quantitative approaches.

Environmental, social, and governance (ESG) frameworks increasingly shape corporate strategy and sustainable development, yet the behavioral mechanisms underlying ESG compliance remain insufficiently understood. Traditional economic models typically assume fully rational decision-making and overlook how psychological factors influence corporate sustainability choices. This study integrates behavioral game theory with organizational psychology to examine how trust, fairness, and loss aversion affect corporate ESG compliance in a multi-stakeholder environment. An evolutionary multi-agent game model involving regulators, firms, investors, and consumers under bounded rationality is developed. Behavioral parameters—trust, fairness preferences, and loss aversion—are incorporated into payoff structures to analyze their effects on cooperative equilibrium outcomes. Simulation results indicate that higher levels of institutional trust and fairness significantly increase ESG compliance and reduce greenwashing behavior, accelerating convergence toward cooperative equilibria. In contrast, excessive loss aversion generates unstable compliance driven primarily by fear of penalties rather than intrinsic commitment to sustainability. Sensitivity analysis further identifies behavioral thresholds where modest increases in trust produce substantial improvements in ESG adoption. The findings highlight ESG governance as a behavioral coordination challenge rather than purely an economic optimization problem. This research provides insights for policymakers and corporate leaders seeking to promote sustainable business practices and contributes to advancing the United Nations Sustainable Development Goals, particularly responsible consumption and production, climate action, and sustainable economic growth.