With the increasing prevalence of digital technology, the inherent influencing mechanisms by which digital empowerment fosters rural environmental governance remain a critical area of inquiry. However, existing research neglects the dual effects of digital technology on rural environmental governance from the aspect of stakeholders’ engagement. To address this gap, this study develops an integrated framework to investigate not only the direct impact of digital empowerment on rural environmental governance but also the mediating roles of stakeholders’ engagement and governance mechanisms, alongside the moderating role of perceived technology anxiety. Grounded in theoretical frameworks and extensive literature reviews, this study analyzes data from Jiangsu province in 2025 using an Ordinary Least Squares (OLS) model. The baseline regression results reveal that digital empowerment significantly promotes rural environmental governance, even after endogeneity analysis. Moreover, the results of the mediation effect show that digital empowerment enhances the level of rural environmental governance by accelerating stakeholders’ engagement and improving governance mechanisms. Furthermore, the moderating effect results imply that perceived technology anxiety may inhibit the negative effect of digital empowerment on rural environmental governance. Additionally, regional disparities exist in the influences of digital empowerment on rural environmental governance, with rural areas in Southern Jiangsu exhibiting a more pronounced effect compared to other regions.

Public–private partnership (PPP) projects have the features of extended investment cycles, diminished returns, and high demand for technology. Inadequate utilization of these projects may result in an accumulation of new implicit debt for the government. Consequently, it becomes imperative for the government to manage and mitigate implicit debt risks associated with urban rail transit PPP projects, which is a crucial prerequisite for ensuring the progression of such projects and the unhindered functioning of the financial system. The objective of this study is to investigate the factors that influence government implicit debt risks in urban rail transit PPP projects from the perspective of policy. This study employs the grounded theory method to develop a comprehensive framework model that identifies the influencing factors of government implicit debt risk in urban rail transit public–private partnership (PPP) projects. The contributions of this study are twofold: (1) it highlights the role of policy as a significant determinant of implicit debt risks of urban rail PPP projects, which contain governmental subsidies, external environmental risk sharing, and supporting measures. Specifically, government subsidies directly contribute to the government’s implicit expenses, thereby impacting the level of implicit debt risks associated with urban rail transit PPP projects. Supporting measures exert an indirect influence on the implicit debt risks of the government, thereby imposing a significant burden on local fiscal expenditure. External environmental risk sharing, as an external factor, leads to an increase in fiscal expenditure due to the government’s social responsibility; and (2) it provides a qualitative method that examines the government implicit risk factors associated with urban rail trait PPP projects based on grounded theory. The model that examines the influencing factors of government implicit debt risk in urban rail transit PPP projects adopts a policy perspective, which can inform policymakers on a heretofore unexplored adverse effect of guarantee policy.

Cross-Department Coordination of Emergency Management (CDCEM) is considered a critical dimension in China to solve the problem of emergency management. The Decision Experiment and Decision-Making Trial and Evaluation Laboratory (DEMATEL) is a method used to build the structural correlation of criteria in uncertain environments to identify critical success factors (CSFs). There are coupling correlations and one-way correlations for interrelationship comparisons between selected factors of CDCEM. Therefore, there are two different assessment scales. However, most previous studies applied the DEMATEL method with a single assessment scale to identify CSFs. To fill this gap, an IFS-IVIFS-DEMATEL method is provided to comprehensively identify the CSFs of CDCEM in this study. The intuitionistic fuzzy set (IFS) is regarded as the assessment scales of coupling correlation, and the interval-valued intuitionistic fuzzy set (IFIVS) is regarded as the assessment scales of one-way correlation. The two different types of assessment scales were transformed into interval information in the improved approach. Then, using the conduction correlation among factors, a comprehensive correlation matrix was constructed. After that, the ranking of the central degree and cause degree of the factors according to the traditional DEMATEL method was obtained. Finally, a case study of Nanjing’s CDCEM was illustrated to demonstrate that the proposed method is more suitable and reasonable. It is found that the factors of “cross-department organization”, “cross-department information communication and transmission”, “information sharing technology platform”, “cross-department material supply capability”, and “cross-department prediction and early warning” in Nanjing are CSFs in CDCEM, which should be emphasized to strengthen CDCEM. The findings of this study shed light on the cross-department coordination of emergency management mechanisms in uncertain situations, which would be beneficial for improving the efficiency of governmental management.

An emergency information response system (EIRS) is a system that utilizes various intelligence technologies to effectively handle various emergencies and provide decision support for decision-makers. As critical success factors (CSFs) in EIRS play a vital role in emergency management, it is necessary to study the CSFs of EIRS. Most previous studies applied the Decision Experiment and Decision-Making Trial and Evaluation Laboratory (DEMATEL) method with complete evaluation information to identify CSFs. Due to the complexity of the decision-making environment when identifying CSFs of EIRS, decision-makers sometimes cannot provide complete evaluation information during the decision-making process. To fill this gap, this paper provided a Similar-DEMATEL method to impute the missing values and identify CSFs of EIRS, which may avoid the dilemma of decision distortion and make decision-making results more accurate. It is found that the factors of Information mining capability, Equipment support capability, Monitoring and early warning capability, and Organization participation capability are the CSFs in EIRS. Our proposed method differs from previous research, such as the mean imputation method, to impute the missing values. We compared the differences between the proposed method and the mean imputation method and gave the advantages of the proposed method. Our method focuses more on uncertain decision-making environments, which is conducive to improving the efficiency of EIRS in emergency management, and therefore it is more widely adopted.