Nomadic regions of Iran with their unique cultural and natural attractions are considered as one of the most important options for the development of ecotourism in the country. However, the framework and factors of nomadic tourism development have been less considered in previous studies. Accordingly, the present study aims to provide a model for the development of nomadic tourism by using the structural modeling-interpretation approach. For this purpose, the required data were collected and analyzed from the Shahsavan nomadic areas in northwestern Iran with a qualitative-quantitative research approach. For this purpose, using snowball sampling and through semi-structured interviews with 19 tourism experts consisting of university professors, tourism experts and nomadic community, the dimensions and factors affecting the development of nomadic tourism were identified and categorized. In the next step, using interpretive structural modeling (ISM), the relationships between the dimensions were determined and analyzed in an integrated way, then using MICMAC analysis, independent, dependent, effective and two key aspects in the development of nomadic tourism were identified. The results showed that empowerment of nomadic community as the key two-way variable is one of the most important drivers of nomadic tourism development and its strengthening and development should be a priority in policy and planning for nomadic tourism development. On the other hand, social capital, government activism, structural-institutional factors were identified as strategic variables affecting the development of nomadic tourism.

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.

The coronavirus pandemis caused many operational challenges for hotel management. In this situation, it became clear that many hotels and accommodation centers do not use performance management systems. On the contrary, they have performance evaluation systems that usually include annual evaluation and review, and there is little alignment between the hotel's performance and its strategic goals. It only focuses on the past performance of the hotel. Therefore, the necessity of identifying suitable criteria for performance management rather than its evaluation is felt in hotels. For this purpose, in this article, criteria for designing the performance management model in hotels with the meta-synthesis method were collected and leveled using the structural-interpretive modeling approach according to the opinion of experts. In this article, 14 criteria have been identified that will help to improve the management of hotel performance in the critical conditions of the corona outbreak and are in line with the essential administrative, strategic, and communication goals, development, and maintenance of hotels. Therefore, they can help address performance management challenges. In the classification of identified criteria, "government policies and leadership skills" were the most effective criteria, and "customer loyalty and reduction of hotel costs" were among the most effective criteria.

Introduction: Today, the effectiveness of an organization is directly explained by the quality of its human resources. One of the most challenging issues that the healthcare sector faces is human resource management risks. The aim of this study was to present an interactive and process model and plot the structural relationships of human resource risks in the healthcare sector. Methods: This research was a quantitative research based on the structuralinterpretive modeling method. Participants included 19 managers and human resources experts of medical centers in Kashan and Aran-Bidgol, who were selected by purposive and snowball sampling. In this study, the structuralinterpretive modeling method was used to structure and plot the interactive relationships of 14 critical risks of human resources in the healthcare sector. Results: The 14 main risks of human resources in the health sector were classified into four levels using structural-interpretive modeling. Thus, the risks of ‘, perspective based on the non-strategic role of the human resources unit’, , ‘, perspective based on the inefficient performance of the human resources unit’,and ‘, risk of selection and employment’,are in the fourth level, and ‘, financial’,and ‘, behavioral’,risks are in the first level. Conclusion: According to the structural-interpretive modeling method, the risk of inappropriate attitude towards the role and performance of human resource management and the risk of hiring and using human resources, as key and critical risks, are the driving force behind other risks in the field of human resources in the health sector. Therefore, to manage and reduce other risks in the field of human resources, it is necessary that we manage them in the healthcare sector.

Aim: The purpose of the present study was to develop an immortality model of managers in the Iranian banking system using the structuralinterpretive modeling method. Method: The research method was exploratory in terms of the qualitative approach. Content analysis and review of relevant texts and interviews with selected experts through non-random and snowball techniques to theoretical saturation were used for data collection. Result: The questionnaire's data were analyzed using structural-interpretive modeling and plotted at three levels in an interactive network, which resulted in the "customer orientation" factor and was at the highest level. The influence power and degree of dependence of these factors on each other in the influence-dependence power matrix were examined. Conclusion: "customer orientation" and "delegation" indices in the affinity-dependency power matrix of the dependent region mean the highest dependency and least influence, and the factors of "effective communication, " "planning, " "systems, " "risktaking" lies in the connected area which has the highest penetration power and the highest amount of dependency.

The purpose of this study is to identify the role of sport as a soft power for Iran to facilitate its diplomatic relations after the nuclear deal. The research method used in this study is mixed (qualitative and quantitative): in the qualitative part of the analysis, the study sample was selected via Snowball sampling based on partricipants’,expertise in the sport diplomacy of Iran after two rounds of Fuzzy Delphi Method (FDM) exploratory factor analysis. Seven components of political currents, cultural exchange, peacemaking, national unity, economic development, transformation, communication, and religious currents were extracted. After identifying the study’, s research variables in a structuralinterpretive modeling, the relationship between variables was examined through a structural equation modeling test. The results of the structural equation model indicated that political currents, cultural exchange, transformation and communication had a direct and significant effect on national unity. The relationship between political and peacebuilding was not confirmed, but national unity and excellence in peace diplomacy had a direct and significant impact on the economic development of societies.

One of the emerging theoretical subjects in the public administration discipline is the strategic public policy that results from the combination of theoretical literature in the two fields of "public policy" and "strategic management". This qualitative research is aimed to structural-interpretative policy analysis in national-level strategic issues. Considering the wide range of issues at the national level, decision making based on environmental issues in the country has been at the center of attention. The main question of the research is that what is the policy making levels in the national strategic issues with an emphasis on environmental issues? In order to answer this question, the combination of qualitative methods of thematic analysis and structuralinterpretation modeling has been used. Thematic analysis method through conducting interviews with experts and coding of written data eventually led to the emerging of 13 global themes. Finally, these themes are followed by the steps in structuralinterpretive modeling and paired relationship at six levels of problem solving, key actors, independent actors, government actors, citizen actions, global actors & National laws. These levels in fact represent policy making layers on national-level strategic issues focusing on environmental issues.

The aim of this study was to design a model for empowering managers in the banking industry based on a mixed study with a descriptive-exploratory approach. The statistical population of the study included academic experts as well as senior managers of the Central Bank (such as board members, managers, heads of departments and senior experts in the central bank). The statistical sample up to the theoretical saturation stage of the data was selected by 15 people in a purposeful judgment method. Data collection tools in this study include a semi-structured interview and a basic expert questionnaire that the validity of the measurement tools was confirmed by the content method and the reliability of the interview was confirmed by the open test method. Data analysis was performed in the qualitative part by thematic analysis method and in the quantitative part by soft structuralinterpretive modeling (ISM) method. The results of content analysis led to the identification of themes and categories related to the empowerment of managers in the banking industry. Also in the second part, based on the identified themes and categories and using soft structural-interpretive modeling method, a model for empowering managers in the banking industry was designed, which was presented at five levels and includes major categories such as "structural enablers", "Are "managerial empowerments", "knowledge empowerments", "motivational empowerments", "empowering actors", "psychological empowerment", "behavioral empowerment", and "behavioral consequences".

The purpose of this research is identifying and leveling factors affecting research and development strategies in domestic automotive companies with emphasis on structuralinterpretive modeling. The present study is mixed in terms of developmental purpose and method. In the qualitative part, they participated with 20 managers of domestic automobile companies using the snowball sampling method using semi-structured interviews, and in the quantitative part, Delphi questionnaire was first given to 45 experts, and then for the level About 50 experts from the domestic automotive industry participated. In the qualitative part, using the theme analysis method, 7 components of business strategy, support policies, investment attraction, intellectual capital, cultural development, research and development implementation network, and research and development management were identified. In the quantitative part of validation, the identified indicators were confirmed by the consensus of experts and using the fuzzy Delphi method. Qualitative sector coding process analysis has led to the identification of 7 components of business strategy, supportive policies, investment attraction, knowledge capital, cultural development, and research and development implementation network and research and development management. The identified components are included in the quantitative section of the ISM questionnaire. Based on the results obtained from the ISM analysis, it can be acknowledged that there are direct and indirect effects in the matrix,the most influential factor is supportive policies and the most dependent in the matrix is the direct effects of attracting investment and knowledge capital in the matrix of indirect effects.

Introduction: One of the important factors that may affect the destination of development is medical and healthcare tourism. The presence of experts in medical tourism and the geographical location of Iran is one of the most important factors in the sustainable development of Iran. This study aimed to identify and prioritize the components of the medical and healthcare tourism entrepreneurship ecosystem (EE) in Iran with a structuralinterpretive modeling approach. Methods: This research is methodologically a mixed (qualitative-quantitative) exploratory type, and its participants were health tourism experts and entrepreneurs. The method for selecting the participants was Purposeful sampling. 15 participants were interviewed based on theoretical saturation. The data collection tools were interviews and questionnaires. Also, to analyze the data in this research, we used two overlapping processes of open and axial coding and structural-interpretive modeling. Results: The results of data analysis showed that the components of the health tourism EE were included in the seven main dimensions of law, regulations and governance factors, financing and investment, the role of culture, influential institutions (universities and Educational centers), influential regional market factors, the role of human capital, and effective infrastructure. Conclusion: Researchers examining entrepreneurial ecosystems have not studied the role of a regional level of analysis. The results of qualitative analysis and Interpretive Structural Modeling (ISM) showed that to create the entrepreneurial ecosystem of the medical and healthcare tourism, the central factors resulting from qualitative research interacted with each other at three different levels, and the set of factors at these levels caused the medical sciences university to move towards creating an Entrepreneurial ecosystem drive in the university.