Analysis of Spatial heterogenity of development undicators and rankings of provinces of Iran by spatial Statistical techniques and multi-criteria decision making

This study aimed to explore the development of provinces in Iran. To achieve this goal, 71 indices in 6 regions obtained from the statistical yearbooks of 2016 were used to investigate the development of the provinces. This is an applied research. Shannon’s entropy method was used for weighting and Electre and Vikor’s multipleattribute decisionmaking techniques were used to measure development. To have uniform results, Copeland’s technique was used. Also spatial statistical techniques,hot spots method, clusters and non-clusters were utilized for cluster and non-cluster mapping and spatial analysis of inequalities. The results showed that only Semnanprovince was in a very good condition and provinces like Isfahan, Yazd, Ardabil, and Chaharmahal and Bakhtiari were in a good condition. Among other provinces, Alborz, Kerman, Kurdistan and Khorasan Razavi were deprived areas and the provinces of Hormozgan and Sistan were very deprived. The results of spatial statistics analysis using hot spots analysis based on Copeland’s scorerevealed that Semnan and Mazandaran provinces with 95% probability and Golestan, Tehran, and Isfahan provinces with 90% probability were hot spots. Sistan and Baluchestan and Hormozgan provinces were 90% likely to be cold spots. The other provinces of the country did not form statistically significant hot or cold spots. The analysis of clusters and non-clusters using Copeland’s method indicated that Semnan province was a high-value cluster (HH) and Alborz province was a non-cluster surrounded by high values (LH).