Journal of Resource Management and Decision Engineering 5 Serial Number 17 2026 07 01 Analysis of Social and Cultural Factors Affecting the Development of Tourism Culture in Iran: A Case Study of Border Regions Analysis of Social and Cultural Factors Affecting the Development of Tourism Culture in Iran: A Case Study of Border Regions 1 12 10.61838/kman.jrmde.253 EN Journal Article 2025 10 01 <p>This study aimed to identify and analyze the social and cultural factors affecting the development of tourism culture in Iran and to prioritize these factors. The primary objective was to explain the existing paradox between Iran’s vast potential tourism capacities and the weak practical performance of this industry. The study adopted a mixed-methods (integrative) research design. In the quantitative phase, the research was conducted using a descriptive–survey method with a correlational approach. The statistical population consisted of all tourists visiting the border city of Bazargan (over 100,000 individuals). Based on the Morgan table, a sample size of 384 participants was determined and selected through simple random sampling. The data collection instrument was a researcher-developed questionnaire comprising 52 items, whose validity was confirmed using the content validity ratio method (CVR = 0.851) and whose reliability was verified using Cronbach’s alpha coefficient (ranging from 0.761 to 0.931 across components). Data were analyzed using SPSS software through descriptive and inferential statistics, including Pearson correlation and multiple linear regression analyses. The results of the regression analysis indicated that the model consisting of eight independent variables (cultural, social, economic, political, environmental, infrastructural, entrepreneurial, and security-related factors) explained a total of 52.7% of the variance in the dependent variable (tourism propensity) (R² = 0.527). Among these factors, five showed positive and statistically significant effects: cultural factors with a beta coefficient of 0.414 (the strongest predictor), political factors (0.220), safety and security (0.404), economic factors (0.172), and social factors (0.174). The three factors of environmental, infrastructural, and entrepreneurial dimensions were not statistically significant.</p> https://www.journalrmde.com/index.php/jrmde/article/download/253/267