Understanding how to distribute economic, social, cultural and other opportunities as first step in spatial development planning can improve service delivery and increase equilibrium between regions. This research aimed at study and analysis of 31 provinces of Iran based on social indicatros enjoyment. Therefore, the present study is applied in terms of purpose and descriptive-analytical in terms of nature and method of research. Required data collected through the statistical yearbook of 1395 (2016) in the form of 52 important social indicators including social, cultural, welfare, educational and health components. Shannon entropy, coefficient of variation (C.V), WASPAS used to Wheightining of criterias, analysis of indicators dispersion and determining the level of development of provinces respectively in the context of MATLAB. The result shows that there is a lack of social development balance between Iran provinces. Tehran, Isfahan, Khorasan Razavi and Fars are four provinces that placed at higher level of social development and Alborz, Zanjan, Chaharmahal Bakhtiari, Semnan, South Khorasan, North Khorasan, Ilam and Kohgiluyeh and Boyer Ahmad are placed at the most deprived areas of the country in terms of social indicators. Overall, the results show that social development status in Iran's provinces is not synonymous with social and spatial justice and requires proper and effective attention and management.

One of the pillars of spatial planning is determining the role and function of regions based on their competitive advantages. By developing innovative infrastructure that supports production, regional competitiveness improves regional efficiency and forms a network of complementary and reciprocal relations between regions, which ultimately leads to the capital attraction, value creation, and integrated regional development. In this regard, the present study aims at identifying the creative regions of Iran and determining the competitive advantages of those regions. This study is explanatory applied in terms of purpose and descriptive-analytical in terms of methodology. Derived from the document analysis of secondary sources, quantitative data was used to analyze both creativity and competitiveness. The data used to identify creative regions included the number of scientific and research centers and companies, consulting engineers, the industries with high and medium technology, employees in the manufacturing sectors, and the university students of the provinces of Iran. Moreover, the number of employees in major activity groups was used to determine competitiveness. Factor analysis and cluster analysis were performed to identify creative regions, while correspondence analysis was performed to determine competitive advantages in SPSS software. The results show that the provinces of Tehran, East Azerbaijan, Isfahan, Khuzestan, Fars, Kerman, and Mazandaran have the knowledge infrastructure capacity required for creative regions. Isfahan’s share of construction is 11.1 percent, while Tehran’s share of information is 41.2 percent. The interpretation of angles smaller than 0.2 between correspondence analysis vectors reveals that Tehran and Isfahan provinces have competitive advantage in information and communication and manufacturing, respectively. It was also found that most regions of the Iran do not have a specialized role and the competitive advantages of the provinces are not supported by the knowledge infrastructure of the regions.