Sociological analysis of social and cultural structures affecting investment attraction

Today, investing and having capital as one of the key issues of development is of very fundamental and decisive importance. Governments prefer to bring in an element such as the private sector in their absence or by their side to fulfill their roles and duties. The purpose of this research is to explain the structural factors affecting investment attraction in Lorestan province. The research method is a combination of quantitative type and survey technique and questionnaire tools were used and the theoretical model of the research which includes independent variables such as economic, infrastructural, judicial-police, political, administrative-organizational, cultural-social conditions and national level conditions and It is global, it was designed to explain and analyze investment attraction among investors. According to the stratification done by the respondents, the desire to invest in Lorestan is average downwards, the existing infrastructure in the province is average downwards, the economic conditions are average upward, the amount of judicial-police issues is average downwards, administrative issues - The organization is average downwards, cultural-social conditions are average downwards, political conditions are low, and the level of national and global conditions is also low. Also, there is a positive and significant correlation between the independent variables of the research, including economic, infrastructural, judicial-police, cultural-social, political, administrative-organizational, with the tendency to invest as the dependent variable of the research, but the variable of national and global conditions has a relationship Correlation is not meaningful. The multi-variable regression of the research shows that the political, administrative-organizational and cultural-social variables are the most effective variables in explaining and predicting the tendency to invest in the province, and the explanatory power of the regression or R2 of the research model is 52% in this sense. that these variables explain about half of the state of the dependent variabl.