Many real-life problems are multi-objective by nature that requires evaluation of more than one criterion, therefore MCDM has become an important issue. In recent years, many MCDM methods have been developed; the existing approaches have been improved and extended. Multi criteria decision analysis has been regarded as a suitable set of methods to perform sustainability evaluations. Among numerous MCDM methods developed to solve real-life decision problems, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) continues to work satisfactorily in diverse application areas. In this paper, a novel sorting method (TOPSIS-Sort) based on the classic TOPSIS method is presented. In the TOPSIS-Sort approach an outranking relation is used for sorting purposes. The proposed approach uses characteristic profi les for defi ning the classes and outranking relation as the preference model. Application of the proposed approach is demonstrated by classifying 22 districts of Tehran into fi ve classes (but none of the districts fi ts into Classes 4 and 5), representing areas with different levels of environmental quality. An analysis and assessment of the environmental conditions in Tehran helps to identify the districts with the poor environmental quality. Priority should be given to these areas to maintain and improve the quality of environment. The results obtained by the TOPSIS-Sort give credence to its success, because the results of sorting confi rm our and specialists’ evaluation of the districts. This research provides appropriate results with respect to the development of sorting models in the form of outranking relations. The model, proposed by this study, is applicable to the other outranking methods such as ELECTRE, PROMETHEE, etc.

The development of small businesses in rural areas as a key strategy for sustaining the population and improving the quality of life of villagers has always been a concern for many developed and developing countries. Some rural areas provide their villagers with favorable conditions for the development of businesses in order to enjoy the potential in the field of tourism. Sustainable development in these areas can be achieved with systematic attention and planning. In the present work, the spatial analysis of the distribution of small businesses in the eastern parts of Gilan Province was studied with an emphasis on tourism in mountainous regions. The study population consisted of all villages in the east part of Gilan Province, and the sample included all businesses officially supported by the Omid Entrepreneurship Fund. The research method was a descriptive analytic in which GIS software and the G statistic were used for the analysis of spatial correlation, clustering, hot and cold spots analysis and buffer zones. Finally, the results of the study showed that the spatial distribution of businesses in different economic sectors (agriculture, industry, services and tourism) were different between 2011 and 2016 in the way the cluster pattern was formed in agricultural and service activities. A cluster pattern cannot be considered in the tourism and industrial activities, but there is a random (point) pattern; in this regard, the results indicate the importance of the factor of distance between the village and the city center in the distribution of tourism businesses. In addition, the highest levels of support for businesses were in the agricultural and services sectors, while the lowest support was in industry and tourism. Finally, the results showed that the distribution of businesses in all activities was much higher in the plains and valleys as compared to the mountainous and hill areas.

Urban resilience refers to the capacity of an urban system to fully recover from unforeseen calamities. This study aims to assess the physical resilience indicators used to measure urban resilience in Tehran, the political and economic capital of Iran, and to pinpoint the most significant direct and indirect influences on urban resilience. The research process divided into two parts. The environmental scanning approach (reviewing papers and published sources, interviewing specialists, and monitoring conferences) and the literature review were employed in the first part to compile a database of the key information on the elements impacting physical resilience. The most significant factors impacting physical resilience over the next ten years were requested to be identified by specialists and intellectuals in the second part. Finally, the MicMac program was used to analyze the data after 29 variables were specified in Delphi. In light of the trace-analysis-dependence diagram, which depicts the instability of the influential factors and the persistence of their impact on other variables, the results demonstrate that Tehran’s physical resilience is in an unstable condition. According to the results, the factors that have the maximum impact on other variables are granularity drivers, emergency evacuation capacity, rescue and security spaces (emergency, fire station, and police station), impermeability, rate of the amendment and retrofitting measures in the buildings of each zone, building age, and the compatibility of land uses. The variables that are most susceptible to change from other variables include the distribution status of dangerous land uses, the quality of the buildings, the rate of historically vulnerable buildings, the vulnerability of internal and external roads, the rate of improvements and retrofitting measures in buildings in each zone, as well as historically vulnerable historical buildings.