structural-interpretive modeling (ism)

Smart tourism is a newly emerging concept that highlights the growing reliance of tourism destinations on advanced information and communication technologies. Given the importance of this topic, this study aims to identify the factors influencing the development of smart tourism in the Azad region. The research adopts a descriptive-exploratory approach, with the statistical population comprising experts familiar with the development of smart tourism and the Aras Free Zone. Using the snowball sampling method, 10 experts were selected as the research sample. Structural-Interpretive Modeling (ISM) and MICMAC analysis were employed to analyze the data. The findings revealed that out of 33 initially identified factors, 22 were finalized as the key contributors to smart tourism development. Among these, six critical factors were identified: budget allocation, regional tourism potential, tourist needs assessment, e-government infrastructure, policymaking, and planning. These factors were deemed most influential in driving the development of smart tourism in the Aras Free Zone.

Aging is one of the serious issues of the 14th century in Iran. According to the current trend and organizational forecasts, Iran has entered the old age period and will enter the old age stage in the last one or two decades. Considering the negative effects that aging has on societies, it is necessary to identify the challenges and obstacles of this segment of society to be present in cities in order to provide a basis for planning as an elderly-friendly society/city. . Therefore, and considering the importance of the subject, this study aims to identify the challenges of citizenship for the elderly. The current research is exploratory and the statistical population of the research is made up of experts familiar with the subject, 10 of whom were selected as the statistical sample of the research using the snowball method. Structural-interpretive modeling (ISM) and MICMAC analysis were used to analyze the data. The results of the research showed that among the 23 initially identified factors, 14 factors obtained a CVR coefficient above 0.75 in the calculation of content validity and were recognized as the challenges of elderly citizenship. The categorization of challenges showed that the two factors of non-standard living environment and discrimination in providing services are the most key challenges of senior citizens, and solving them can have a great impact on meeting the needs of the elderly and realizing a city that is friendly to the elderly.

Regional inequality as one of the existing forms of inequality is one of the issues in the system of opportunity and its presence / absence and intensity / weakness has an important effect on the order and cohesion of society at different levels and dimensions. This is a serious problem, especially in developing countries. Due to the importance of this issue, this study seeks to identify the factors affecting regional inequality in Iran. The present study is a descriptive-exploratory study and the statistical population of the study consists of experts familiar with the issue of inequality and development of regions in Iran. Snowball, 10 of them were selected as a statistical sample of the study. Also, Content analysis, structural-interpretive modeling (ISM) and MICMAC analysis were also used to analyze the data. The results showed that out of 47 initially identified factors, 14 factors, including factors of poor planning, decisions of managers and planners and poor access to facilities and equipment, in calculating content validity, CVR coefficient above 0.75 and were recognized as the final factors of regional inequality. Also, the leveling of factors showed that the relevant factors can be classified into six levels. The factors of unique resources and capabilities were at the lowest level with 29% subscription and the factors of government centralism and inefficiency were at the highest level with 90% and 91% subscription. Their classification also showed that the factors of manpower constraint (with influence 10 and degree of dependence 5), lack of financial and investment resources (with influence 8 and degree of dependence 7) and lack of attention to research (with influence 13 and the degree of dependence 5) are the key factors of regional inequality and have a great impact on inequality.