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Finding an appropriate place for temporary housing after an earthquake is one of the main challenges of disaster risk management, especially in developing countries. Therefore, it is necessary to create pre-disaster location plans for the homeless population. This study aims to systematically find safe places and select suitable sites according to influential factors.

The research methodology used is a descriptive–analytical method. A field survey with a quantitative–qualitative approach is applied to recognize physical vulnerabilities and select suitable sites for temporary settlements. Due to the occurrence of several earthquakes in recent decades around the city of Isfahan, Iran, this area has been studied. Fuzzy analytic hierarchy process, geographic information system and rapid visual screening have been used for data analysis.

According to the site selection and vulnerability criteria and their prioritization, the findings indicate that 60% of the study area is vulnerable. Moreover, vacant lots, stadiums and public green spaces that can be used as multi-purpose sites are the most appropriate options for the temporary settlement.

The research criteria are generalizable and can be used for decision-making, concerning urban fabric vulnerability and site selection of temporary housing in cities exposed to earthquake risk.

Cultural features, accessibility, land conditions, the slope and type of land, availability and construction materials were addressed in locating temporary settlements. In addition to vacant lots and open spaces, safe buildings were also identified for temporary housing, and religious minorities and similar communities were considered.

The purpose of this study is to identify and prioritize the critical success factors (CSFs) of knowledge management (KM) implementation through a novel hybrid model, namely, Fuzzy Delphi method (FDM), interpretive structural modeling (ISM) and revised Simos, which is one of group decision-making (GDM) approaches.

The CSFs of KM implementation were identified through a systematic literature review. FDM was adopted to determine the CSFs in the Iranian oil industry. Then, a novel hybrid model consisting of ISM and revised Simos techniques were used to classify and prioritize the CSFs.

The obtained results suggest that there are 13 CSFs of KM implementation. The result of ISM shows that the CSFs of KM implementation were classified into five levels. The result of revised Simos reveals that the “human resources management” obtained the highest priority and “leadership commitment and support” and “intellectual capital” ranked second and third, respectively.

As this research was performed in the Iranian oil industry, caution should be taken regarding the generalizability of the obtained results.

The top managers of the surveyed companies could get acquainted with CSFs of KM implementation in their organization and use a GDM technique that has various advantages to solve the relevant problems.

This paper provides a twofold contribution to expand KM and GDM literature and to the best knowledge of the authors, it is a novel hybrid GDM model of its kind.