In 2011, the Chinese government launched a disaster mitigation and preparedness program called the Resettlement of South Shaanxi (RSS). Due to the wide geographical scope and complex interests, the possibility of conflicts was increased during and after resettlement. Efficient risk communication improves the supply of information about risks and meets the risk-related information needs of individuals. Using the risk information seeking and processing (RISP) model, this research applied a structural equation model and survey with a structured questionnaire to study ways to improve risk communication in disaster resettlement. A total of 616 valid questionnaires were provided by study respondents in resettlement sites in Ziyang County, Ankang City, Shaanxi Province. The results indicated the following: (1) the public’s information seeking behavior relies more on village committees and village officials than other channels. Emerging information channels, such as Weibo and WeChat (social media applications in China), do not play leading roles in disseminating risk information. (2) There are differences between the information channels used by residents and the channels that residents believe the most. (3) Relevant channel beliefs, information sufficiency, perceived hazard characteristics, and self-efficacy directly influence risk information seeking behavior. However, the capacity to gather information has non-significant direct influences on information seeking behavior. (4) Perceived hazard characteristics and self-efficacy drive risk information seeking behavior in both direct and indirect ways through information sufficiency.

With the purpose of limiting the drastically increasing quantity of travel volumes and the sustainability of urban traffic systems, many cities have implemented urban traffic restriction (UTR) policies. However, insufficient stakeholder involvement in UTR policy assessment often leads to a lack of social and political support, in addition to a lack of acceptability with respect to policy implementation. In this background, participatory system dynamics modeling (PSDM) is presented as a methodology to engage stakeholders in UTR policy assessment. By the proposed methodology, a comprehensive case study of UTR policy in the city of Xi’an was illustrated. Based on the assessment results, the leverage point influencing the performance of the UTR policy was identified and discussed, with different policy scenarios simulated and tested. The simulation results show that developing public transportation while implementing UTR policy was indicated as the most reasonable solution at the present stage, and the annual growth rate of private cars should be monitored in the future. The results confirmed that the PSDM methodology can facilitate the system thinking of stakeholders, which is important to reach consensus-based assessment results and to enhance the social support for UTR policy.

Understanding Farmer households’ subjective flood risk cognition is important for effectively mitigating the impacts of flood, and adequate disaster preparedness reduces the impact of floods on the sustainability of farmers’ livelihoods. The existing literature focuses on objective flood risk assessment and subjective–objective risk consistency and less systematically explores the correlation between Farmer households’ subjective flood risk cognition and disaster preparedness. Therefore, this study aims to explores the correlation between Farmer households’ subjective flood risk cognition and disaster preparedness. This study employed a random sampling method to conduct a survey among 540 households in Gaoxian County, Jiajiang County, and Yuechi County, which are flood-prone areas in Southwest China. Based on the survey results, this research framework can be used to evaluate systems of subjective flood risk cognition and farmers’ disaster preparedness. We chose the Tobit Regression Model to empirically explore the correlation between subjective flood risk cognition and farmers’ disaster preparedness. The results showed that among the 540 surveyed farmers, their overall subjective flood risk cognition was at a medium-high level (3.58), with self-efficacy more than response efficacy, more than threat, and more than probability. Further, the overall disaster preparedness of farmers was at a medium level (0.5), with physical disaster preparedness more than emergency disaster preparedness and more than knowledge and skills preparedness. The regression analysis showed that the probability of flooding and the threat in Farmer households’ subjective flood risk cognition were positively related to disaster preparedness, whereas self-efficacy, response efficacy, and overall risk cognition in Farmer households’ subjective flood risk cognition were negatively related to disaster preparedness. This study is representative of or may serve as a reference for building governance systems and disaster prevention in other flood risk areas in Southwest China.

Crises can trigger multi-dimensional transformations in public administration systems. This study focuses on the integrated mechanism of learning during crisis to enhance our understanding of emergency management optimization in complex crisis environments. This study constructs an integrated analytical framework that integrates organizational adaptation and policy change to explain crisis learning in local governments and examines the sequential adaptive evolution of Xi’an City’s responses to the Delta and Omicron COVID-19 variants using network analysis and policy text analysis. The findings reveal that learning during crisis in Chinese local governments follows a practice emergence-policy institutionalization feedback loop: ad-hoc special work teams emerged to break rigid bureaucratic labor divisions, and their proven successful practices were institutionalized as permanent emergency working groups in revised emergency plans. This transition from a pure hierarchical structure to a function-led hybrid governance structure shifts local crisis governance from passive reactive response to proactive risk preparedness.