Economy

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Objective: Agritourism creates new forms of interaction between agricultural producers and visitors while utilizing existing rural resources. In addition to strengthening local economies, it contributes to the preservation of agricultural land against pressures arising from large-scale retail expansion and global food supply chains. Given the growing importance of this sector, the present study investigates the factors influencing agritourism development in the rural areas of the Central District of Ardabil County, Iran.
Methods: This applied research adopted a descriptive–analytical approach. Data were collected through both documentary and field-based methods. The statistical population consisted of household heads engaged in agricultural land utilization. Based on Cochran’s formula, a sample of 380 respondents was selected through simple random sampling. Structural Equation Modeling (SEM) using the Partial Least Squares (PLS-SEM) approach was employed to analyze the data.
Results: A total of 67 indicators were initially examined, of which seven were excluded due to insufficient factor loadings. The measurement model demonstrated satisfactory validity and reliability. The structural model confirmed significant relationships between agritourism development and its determining factors. The highest factor loadings were associated with organizing cultural and recreational festivals, improving street lighting, and promoting crop diversification and agricultural product branding. Furthermore, the highest t-value (43.961) was observed for the relationship between agritourism development and socio-cultural factors, indicating the dominant role of this dimension in fostering agritourism development.
Conclusions: The development of agritourism in the Central District of Ardabil requires effective integration of managerial, policy, and legal dimensions. Agritourism can stimulate comprehensive socio-economic and cultural development, thereby contributing to sustainable rural development. Strengthening agritourism initiatives can enhance employment opportunities, improve household incomes, reduce rural outmigration, and increase the value-added potential of agricultural products and rural handicrafts.
 

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Objective: Saffron is a drought-resistant crop that has recently been promoted as an alternative agricultural product in Javanrud County, western Iran. Given the novelty of saffron cultivation in the region, this study aimed to assess its development potential and identify appropriate strategies for its expansion.
Methods: A mixed-methods case study approach was employed. The study population consisted of saffron growers and agricultural experts in Javanrud County. Data were collected through semi-structured interviews with 16 experienced saffron farmers and 10 agricultural specialists selected through purposive sampling. SWOT analysis was applied to identify internal and external factors affecting saffron cultivation. Subsequently, the Quantitative Strategic Planning Matrix (QSPM) was used to prioritize development strategies.
Results: The results revealed seven major strengths, among which family-based production capacity and favorable regional conditions for saffron cultivation were the most important. Seven major weaknesses were also identified, including limited acceptance of saffron as a cropping pattern and inadequate packaging and marketing practices. Opportunities included the compatibility of saffron cultivation with the local climate and access to broader markets, while major threats involved market limitations and insufficient provision of inputs and equipment by agricultural support institutions. Overall, the aggressive (SO) strategy was identified as the most suitable development strategy.
Conclusions: The findings provide practical guidance for agricultural policymakers and extension organizations in Kermanshah Province and Javanrud County to formulate effective strategies for promoting sustainable saffron cultivation.

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Objective: Artificial Intelligence (AI) has emerged as a transformative technology with significant potential to enhance rural development through improving productivity, decision-making processes, and access to information. This study aimed to investigate the role of AI in empowering rural communities, considering the mediating effect of managerial support in the rural areas of Natanz County, Iran.
Methods: The research adopted an applied, descriptive-survey design. The statistical population consisted of all rural residents of Natanz County, from which 371 respondents were selected using Cochran’s sampling formula. Data were collected through a structured questionnaire comprising three dimensions: artificial intelligence (5 items), rural empowerment (19 items), and managerial support (6 items). The validity of the instrument was confirmed through face, content, and construct validity, while reliability was verified using Cronbach’s alpha coefficient (0.86). Data were analyzed using Structural Equation Modeling (SEM) in SmartPLS software.
Results: The findings revealed that AI had a significant positive effect on rural empowerment (β = 0.636, T = 12.002) and managerial support (β = 0.392, T = 3.875). Furthermore, managerial support significantly influenced rural empowerment (β = 0.332, T = 5.533). Sobel test results confirmed the mediating role of managerial support in the relationship between AI and rural empowerment (T = 7.678). The results indicate that AI can substantially contribute to rural empowerment by enhancing agricultural productivity, improving access to education and healthcare services, facilitating market connectivity, and supporting informed decision-making. Effective managerial support and appropriate infrastructure are essential for maximizing the developmental benefits of AI in rural communities.
Conclusions: The study highlights the importance of integrating AI technologies into rural development strategies to foster sustainable socio-economic transformation and reduce rural–urban disparities.
 

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Objective: Designing and implementing employment programs constitutes one of the most important responsibilities of the government in Iran. Various governmental organizations have undertaken numerous initiatives to promote employment; however, statistical evidence indicates that despite the implementation of multiple employment-generation strategies and programs, the employment situation of young people has not improved substantially, and youth unemployment rates remain significantly higher than the national average. This study seeks to explain the factors underlying the success or failure of employment policies and programs implemented during the past two decades.
Methods: This study employs a documentary analysis approach. The analyzed documents include employment action plans, policy reports, and implementation reports related to employment-generation initiatives. Most of these documents were produced by the Islamic Consultative Assembly Research Center, the Ministry of Cooperatives, Labour and Social Welfare, and the Ministry of Sports and Youth. The documents were systematically examined to identify trends in employment policy development and to provide a theoretical interpretation of these changes. Data were coded and analyzed using thematic analysis.
Results: Existing studies in this field can generally be classified into two categories. The first group explains the effectiveness of employment programs primarily through economic growth and investment, arguing that employment initiatives are unlikely to achieve their objectives without sustained economic expansion and increased investment. The second group attributes the limited effectiveness of employment policies to the outdated nature of program titles and intervention frameworks. Through a longitudinal analysis of employment policy documents, this study demonstrates that the titles and frameworks of employment programs have largely been updated over the past two decades. Nevertheless, the findings reveal that the principal challenges affecting the design and implementation of employment programs are a lack of transparency, insufficient monitoring and evaluation mechanisms, and weak institutional coordination.
Conclusions: The study concludes that employment policies and programs suffer from structural weaknesses, including inadequate transparency, ineffective oversight, and poor coordination among relevant institutions, all of which contribute to their limited effectiveness. Enhancing transparency, accountability, and inter-organizational coordination requires establishing a balanced and constructive relationship among the state, the market, and civil society. Such an institutional arrangement can significantly improve the quality and effectiveness of employment policies, particularly those targeting youth employment.

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Purpose: Creative tourism, as a component of the vast tourism industry, can play a major role in empowering local communities, diversifying economic growth, and generating new employment opportunities in rural areas in connection with sustainable rural entrepreneurship and other economic sectors. Accordingly, the present study aims to identify the key factors and driving forces influencing the effects of creative tourism on the development of sustainable rural entrepreneurship.
Methodology: The research is applied in purpose and descriptive–analytical in nature, employing a futures studies approach. Data were collected through both documentary (library sources and scientific journals) and field methods (questionnaires). To extract the key drivers, the questionnaire was designed in five main dimensions: socio-cultural, economic, environmental, physical, and institutional-organizational. The sample population consisted of 25 experts and specialists in creative tourism and sustainable entrepreneurship. The validity and reliability of the questionnaire were confirmed through expert judgment. Data analysis and structural influence analysis of the key indicators were conducted using MICMAC software.
Findings: The results revealed that among the 91 factors examined across five dimensions, 20 key drivers were identified, including: strengthening intergenerational cooperation (39), public awareness of cultural and social values (38), reducing economic dependence on agriculture (49), creating new export opportunities (49), environmental awareness of tourists (48), encouraging green businesses (47), creating natural camping sites (49), developing cultural-tourism centers (48), creating a database of rural entrepreneurs (46), increasing financial transparency (42) and etc.
Conclusion: The findings demonstrate that creative tourism can serve as an effective instrument for promoting sustainable rural entrepreneurship. Structural analysis indicates that enhancing social collaboration, revitalizing handicrafts, reducing agricultural dependency, and fostering new economic opportunities significantly contribute to rural entrepreneurial sustainability.
 

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User satisfaction in rural ecotourism accommodations has become a critical determinant of success in the tourism industry. With the rapid growth of online booking platforms such as Jabama and intensifying competition, data-driven analysis is increasingly essential for identifying the factors influencing satisfaction. Despite the growing popularity of ecotourism in Iran, few studies have applied advanced and interpretable machine learning methods to explore this topic. The rise of the sharing economy and digital accommodation platforms has transformed user experiences, emphasizing the importance of evidence-based insights.

This study collected data from 1,123 rural ecotourism lodgings listed on the Jabama platform using Python and the Selenium library. Independent variables included information quality, cleanliness, value for money, check-in experience, hosting quality, and location, while user satisfaction ratings served as the dependent variable. Regression-based models—linear regression, decision tree, random forest, gradient boosting, and support vector regression (SVR) with an RBF kernel—were implemented. Model performance was evaluated using mean squared error (MSE), the coefficient of determination (R²), and 5-fold cross-validation to ensure reliability and robustness.

The results showed that random forest and gradient boosting achieved the highest accuracy, with R² values above 0.86 and MSE below 0.012. Feature importance analysis revealed that information quality (importance score = 0.442), cleanliness, and value for money were the strongest predictors of user satisfaction. The decision tree model provided interpretable decision rules, highlighting the central role of information quality at the root level and the subsequent influence of cleanliness and value for money. These findings underscore the potential of interpretable machine learning approaches for enhancing user satisfaction analysis in Iran’s ecotourism sector and guiding data-informed managerial decisions.

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Objective: The main goal of this research is to identify, prioritize, and analyze the challenges and problems related to agriculture and natural resources in the Lower Atrak River basin, with a focus on the Chat region of Gonbad-e Kavus County. Relying on the perspectives of local elites, experts, and stakeholders, the study strives to explain the causal relationships between the human and natural factors influencing these challenges and to provide a basis for informed decision-making for sustainable resource management.
Methods: This research is qualitative in nature and applied in its objective. Data were collected through the review of upstream documents and a specialized questionnaire based on a five-point Likert scale. The reliability of the research instrument was assessed using Cronbach’s Alpha coefficient. To prioritize the issues and problems, the non-parametric Friedman test was employed. Furthermore, the DPSIR conceptual model was used as the analytical framework for the research to analyze the causal relationships among the driving forces, pressures, states, impacts, and responses. 
 

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Objective: Farming of native poultry at the village level will provide entrepreneurship and employment for rural women, provide needed protein, improve rural income and sustainable rural development. Despite the benefits of native poultry, the acceptance of this rural activity has not received much attention. Therefore, identifying the factors affecting of native poultry farming among villagers in Mazandaran province can provide grounds for improving the villagers' willingness to carry out this native activity.
Methods: The present study is quantitative and descriptive-survey. The statistical population is the total number of native poultry farmers in Mazandaran province, 64725 people. Multi-stage sampling method was used to select the sample. 382 native poultry farmers were randomly selected as samples. The required data were collected through a researcher-made questionnaire. The validity of the questionnaire was confirmed by asking experts and the reliability was confirmed by calculating Cronbach's alpha coefficient.
Results: Personal-professional factors and social-environmental factors explain 73% of the changes in perceived usefulness and 36% of the changes in perceived ease of use. Perceived usefulness, attitude, subjective norm, and perceived behavioral control explain a total of 74% of the changes in behavioral intention, perceived behavioral control and behavioral intention explain about 64% of the changes in native poultry farming behavior.
Conclusions: The main essence of the proposed model is behavioral intention over behavior, but perceived behavioral control is also an important variable that, along with behavioral intention, affects native poultry farming even more intensely. Increasing the risk-taking power of producers, improving the knowledge and skills of producers, raising public awareness for the consumption of native poultry, expanding the cooperative of native poultry producers, and providing low-interest and targeted bank loans are among the suggestions for the development of native poultry farming in Mazandaran province.
 

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The aim of the current research is to identify spatial processes affecting the development of rural entrepreneurship in order to identify existing and emerging theoretical perspectives. The research method in the current study is applied in terms of purpose and in terms of methodology, it is a combination of systematic review and qualitative content analysis. The statistical population of the research is articles extracted from magazines related to the field of rural entrepreneurship and geography in valid databases. The research population is 113 articles over a period of 22 years from 2000-2023. In the next step, irrelevant articles were removed by screening and finally, 38 Latin scientific articles were analyzed as the research community from the total of studies. For analysis, open, axial and selective coding was used in the software environment (Atlas Ti). Also, the opinions of 5 experts have been used for validation. The research findings included 212 primary codes that were conceptualized in 26 categories and four dimensions and one component (social-spatial). Examining the time distribution of the articles showed that the first articles were published in 2007 and remained stagnant until 2014, and after that, there was an increasing trend until now. Such thematic distribution of articles have been published in social, spatial and economic fields, respectively. The research results showed that rural entrepreneurship is strongly influenced by spatial factors. These studies have been affected by the conceptual evolution of space literature and at the same time as the conceptual evolution of this discourse, its proposed components have also changed and changed from a traditional perspective to a socio-spatial concept. Therefore, space acts as a platform for social interactions and plays an important role in the formation of social and spatial networks that affect the development of rural entrepreneurship

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The research was fundamental in terms of purpose and mixed and exploratory in terms of method. In the qualitative part, the inductive content analysis method was used, and in the quantitative part, the interpretive structural method with the integrated ISM-DEMATEL technique was used. The study population consisted of academic experts, welfare experts, and relevant organizations that are directly related to the employment of disabled people, and disabled people. The study population consisted of academic experts, welfare experts, and relevant organizations that are directly related to the employment of disabled people, and disabled people. Data were collected through a review of secondary studies, semi-structured interviews, focus groups, and a researcher-made questionnaire. In the qualitative section, the results showed that the categories of networking and market development for products, sustainability and continuous improvement of the plan, implementation of career counseling based on the type of disability and climate, psychological capacity building and skill empowerment, financial and infrastructure support, and identification of applicants and individuals susceptible to job creation are effective factors in creating a sustainable employment model for people with disabilities. The results of the quantitative section showed that the first step was to identify applicants and people who are susceptible to job creation; the second step was to implement career counseling based on the type of disability and climate; the third step was to build psychological capacity and skill empowerment and financial and infrastructure support; and the fourth step was to build networks and markets for products, leadership, and continuous business improvement.
 

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Objective: The objective of this research is to analyze the phenomenon of rural shrinkage with an emphasis on the role of space commodification and migration.
Methods: This study employs a descriptive-analytical research methodology based on field and documentary observations. The sample size determination for both the expert questionnaire (on factors of space commodification) and the villager questionnaire (on factors influencing migration) utilized theoretical saturation. The sampling method for both the expert and citizen questionnaire sections was purposive non-probability sampling.
Results: 
The findings indicated that the most significant factors influencing rural migration, in order of importance, include: inefficient performance of city officials, family poverty, and inequality in facilities and services between this village and the provincial center and other destination cities, and so on. Based on the DANP model, the most significant factors affecting the commodification of rural space in relation to the phenomenon of urban shrinkage, in order of importance, include: destruction of natural landscapes, sense of alienation from space, change in land use of agricultural lands, sense of privatization of space, unemployment in the village, and so on.
Conclusions: The results demonstrated that rural shrinkage in Saqqez is a victim of the space commodification logic driven by neoliberal capitalism and the inefficiency of local governance. Migration, a key agent in this process, itself perpetuates the vicious cycle of shrinkage.