Economy

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• 175 variables were repeated at least 50 times in different studies.
• 8 variables (16%) had a low effect size (<0.3).
• 37 variables (74%) had a moderate effect size (0.3–0.5).
• 5 variables (10%) had a high effect size (>0.5).

1. Individual Factors (Competitiveness, enthusiasm, and ambiguity tolerance);
2. Economic Factors (Production & marketing, access to financial support);
3. Social Factors (Place attachment, NGOs, economic security);
4. Environmental Factors (Access to land & water, suitable natural conditions);
5. Infrastructure Factors (Physical infrastructure, business environment, market access);
6. Educational Factors (Entrepreneurial training);
7. Institutional Factors (Institution-building, media coverage, entrepreneurship laws).

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Objective: The aim of this research is to spatially analyze the economic impacts of reverse migration in rural areas, focusing on Natanz County.
Methods: This study employed a survey-based research method. A sample of 381 individuals was selected from 24 villages in Natanz County using stratified sampling and Cochran’s formula. Data were collected through literature reviews, field observations, in-depth interviews, and questionnaires. For data analysis, one-sample T-tests and Kriging interpolation in ArcGIS software were used.
Results: In terms of investment, the southern half of Natanz County—especially the villages of Ooreh and Goodarzan—showed higher levels of investment, with a mean score of 3.75. For infrastructure development, the central and southern areas had the highest levels, with mean scores of 4.8 and 4.0 respectively. Regarding demand for services, the highest scores were observed in both the northern and parts of the southern villages (mean score: 4), while the eastern and western regions showed the lowest levels of development in this regard (mean score: 2.47). In terms of income generation, the southern villages had a higher average score (3.5) than their northern counterparts.
Conclusions: Given the attractiveness of certain villages in Natanz County—especially those with advantages such as proximity and easy access to urban centers, closeness to tourism hubs, suitable elevation, and moderate climate—a substantial wave of migration to these areas seems likely in the future.

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Objective: In recent decades, the issue of empowering rural women has attracted significant attention from rural development planners. One of the factors that plays a crucial role in this process is the establishment and expansion of microenterprises. The present study was conducted with the aim of examining the impact of creating and developing microenterprises on the empowerment of rural women.
Methods: This study employed meta-analysis as a statistical and systematic method for synthesizing the findings of previous research in the field under investigation. The statistical population consisted of accessible studies addressing the relationship between microenterprises and rural women’s empowerment, published in scientific databases (Sid, Ensani, Noormags, Magiran, ScienceDirect, Google Scholar, and Scopus) during the years 2000–2024. In total, 720 studies were identified, of which 30 met the inclusion and exclusion criteria and were analyzed using CMA2 software. Based on the results of heterogeneity tests (Q index and I² statistic), a random-effects model was selected. Furthermore, to map the research network and identify frequently occurring concepts in this domain, VOSviewer software was used. For this purpose, research keywords were searched in international databases, and the extracted data from selected articles were stored in CSV format and imported into VOSviewer. Domestic sources were searched separately, and the relevant articles were manually entered into the software. Subsequently, scientometric indicators were analyzed using this tool.
Results: The results of the thematic network analysis using VOSviewer revealed co-occurrence between rural women’s empowerment and topics such as entrepreneurship, microcredit, and income. According to Begg and Mazumdar’s correlation test, the included studies demonstrated relative symmetry, confirming the absence of publication bias in the present research. The combined effect size was calculated at 0.453, which, based on Cohen’s criteria, indicates a moderate impact of microenterprise development on the empowerment of rural women.
Conclusions: The findings of this study demonstrate that the establishment and expansion of microenterprises have a significant and positive effect on the empowerment of rural women. Therefore, strengthening rural women’s businesses can serve as a key driver of empowerment, a process that requires supportive systems and institutional backing.
 

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Objective: This study aims to examine how traditional knowledge regarding the use of medicinal plants is preserved among indigenous people and to analyze the learning and teaching networks of this knowledge in Shah Kuh-e Sofla village using a network analysis approach.
Methods: To identify indigenous knowledge transmission methods, the learning and teaching networks related to medicinal plants in Shah Kuh-e Sofla were analyzed using network analysis. Semi-structured interviews and participatory observations were conducted with 53 residents during the spring and summer of 2023 and 2024 (1402–1403 Iranian calendar). Common network indicators such as degree centrality, betweenness centrality, density, and MDS were calculated, and visualizations were produced using UCINET and NetDraw software.
Results: Results show that the majority of indigenous residents prioritize medicinal plants as their primary treatment for diseases and possess knowledge of their therapeutic properties and processing methods. Network analysis revealed that mothers and grandmothers hold key roles in learning networks, while children and daughters-in-law dominate the teaching networks. This suggests vertical, intergenerational knowledge transfer within family-based rural communities, highlighting the pivotal role of women.
Conclusions: Given the proven value and hereditary transmission of indigenous knowledge, its documentation, preservation, and continuation are essential. The methodology used can be applied in other rural and nomadic areas to identify key knowledge holders and enhance the effective preservation and transmission of valuable, region-specific traditional knowledge.

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Objective: Food security is a major issue in sustainable development and in improving the quality of life of rural households. Agricultural production plays a crucial role in meeting nutritional needs and enhancing the livelihoods of rural communities. The purpose of this study is to examine the contribution of agricultural production to food security in rural households using a meta-analytic approach based on data extracted from reputable scientific databases.
Methods: The statistical population included studies related to the role of agricultural production in food security among rural households published in scientific databases—SID, Ensani, Noormags, Magiran, ScienceDirect, Google Scholar, and Scopus from 2000 to 2025. Based on the inclusion criteria, 27 studies were selected and analyzed using CMA2 software. In addition, VOSviewer was utilized to construct a thematic network and identify frequently used terms. Keywords were searched in international databases, and data from selected studies were stored in a CSV file for import into VOSviewer. A separate search was conducted for domestic sources, and their information was entered manually. Scientometric indicators were analyzed using VOSviewer. Due to heterogeneity in the data- identified through Q and I² indices- a random-effects model was selected.
Results: The thematic network analysis showed a meaningful relationship between agricultural production and food security in rural households. Begg and Mazumdar’s correlation test confirmed relative symmetry in the included studies, indicating an absence of publication bias. The overall effect size was estimated at 0.507, which, according to Cohen’s criteria, is considered high.
Conclusions: The results demonstrate that increased agricultural productivity leads to long-term improvements in food security among rural households. The vocabulary network analysis also showed that food security is linked to dietary quality and diversity, as well as challenges such as climate change, poverty, and gender issues, highlighting the need for comprehensive and integrated approaches to address these concerns.
 

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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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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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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.