Investigating the Relationship Between Social and Cultural Factors and Foreign Investment
الموضوعات : مجله بین المللی علوم اجتماعیKarim Yazdani 1 , Hossein Dehghan 2 , Tali’e Khademiyan 3
1 - Ph.D. Student of Sociology, North Tehran Branch, Islamic Azad University, Tehran, Iran
2 - Assistant Professor of Sociology, North Tehran Branch, Islamic Azad University, Tehran, Iran
3 - Assistant Professor of Sociology, North Tehran Branch, Islamic Azad University, Tehran, Iran
الکلمات المفتاحية: capital, investment, Foreign investment, Growth, development,
ملخص المقالة :
It is vital to pay attention to foreign investment in developing countries or the ones with emerging markets. The aim of this study was to identify social and cultural factors affecting foreign investment in Iran’s East Azerbaijan province. The research variables include mutual social trust, participation, modernity and cultural differences and the dependent variable in this research is foreign investment. In this research, different theories have been used, including the theory of Parsons, Lerner, Coleman, Myrdal and Giddens. The research method was surveying and questionnaires were used to collect data. The results obtained from Cronbach's alpha and factor analysis showed high validity and reliability of the questions. The statistical population was from among the officials of foreign investment and foreign investors in the cities of Tabriz and Julfa. The sample size was done by Cochran's method, which obtained 429 people in the field of foreign investment. Finally, the samples were selected by proportional stratified sampling method and simple random sampling method. Pearson was used for bivariate analysis and regression was used for multivariate analysis. The results showed that there is a correlation between independent and dependent variables. In the multivariate analysis, among the variables introduced in the step-by-step method, the mutual social trust variable was selected as the variable that had the greatest effect on the dependent variable because it had a high prediction coefficient.