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Purpose In Iran, the frequent occurrence of disasters has always been a major problem. In recent decades, disasters have created considerable challenges, especially in cities. Hence, understanding the levels of urban resilience (UR) and planning for addressing vulnerabilities plays a key role in the era of increasing risks and uncertainties. The present study aims to provide a comprehensive overview of the state of resilience of Iranian cities. Design/methodology/approach A systematic literature review method was used to determine how resilient Iranian cities are. To find relevant studies, the authors searched Iranian and international databases such as Scopus, ScienceDirect, SID and Magiran. There was no restriction on the inclusion date, meaning that all papers published up until September 16, 2021 were considered for inclusion. The PRISMA framework was used for literature search and selection and, finally, 153 studies focused on 52 cities of Iran were selected for the systematic review. Findings In general, the results showed that the level of resilience was low in Iranian cities. Also, informal settlements, worn-out urban fabrics and the central parts of cities showed lower resilience than other parts. Originality/value The results of the study can be used to inform municipal authorities, urban planners and non-governmental organizations of the actions that need to be taken to enhance the resilience of Iranian cities.

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The present study attempted to examine the impact of inhabitants’ perceptions and local community participation on supporting sustainable tourism development. The goal of the current study was to determine how local community involvement and local views affected the development of a sustainable tourism industry. Inhabitants’ positive/negative perceptions and local community participation had direct but differential effects on supporting sustainable tourism development. Findings revealed that positive perceptions of residents affected their support for tourism development at twice the rate than their negative perceptions did, which indicated their higher readiness for participating in the tourism development process. Moreover, findings showed that using 16 latent variables to form a structural model and a path analysis method was good enough in terms of covering the research questions and analyzing the dataset.

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