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Sajad Amiri, Amirhossein Garakani, Adel Soleimani, Firoozeh Moghiminejad,
Volume 13, Issue 47 (6-2024)
Abstract

Objective: Integrated rural development planning is the result of a series of different developments in planning, economy, politics and sociology in the last decade, which has become necessary due to globalization and decentralization on a local or regional scale. This type of thinking mechanism planning It is based and problem-oriented and seeks to answer the three basic questions of what, why and how in a people-oriented and place-oriented framework and deals with this issue with integrated rationality. Planning issues and problems have emerged at the national level. The examination and evaluation of the ecosystem within the realm of global studies pertaining to integrated development planning hold significant importance, specifically in light of institutional pluralism, aimed at mitigating disparities in rural areas. Numerous insights can be gleaned from research outcomes and strategies in the realm of development and rural progress. Hence, the primary objective of the present study is to methodically scrutinize the knowledge network concerning integrated development planning by scrutinizing the co-occurrence network of terminologies and collaborative authorship within this domain, in order to uncover patterns of knowledge, origins, and their limitations.
Methods: This research is applied in terms of type, which uses the scientometric approach to review scientific documents. In the current research, the social network analysis method has been used to analyze and explain both vocabulary and authorship of related studies in the entire network. In the initial phase of the methodology, data was retrieved from the Scopus database, followed by stages of refining concepts, and ultimately, the conclusive data was scrutinized utilizing algorithms grounded in social network analysis through VOSviewer software.
Results: The findings revealed that among 93 scholarly works and 191 authors, countries like South Africa, England, and the United States exhibited the highest number of publications, with scholars such as Madziohendila, Van Niekerk, Asha, and Banda receiving notable references. Furthermore, the intellectual cluster associated with Chakwizera demonstrated the highest density within the network. Also, the results of this study showed that researches on integrated development planning have been carried out from different dimensions and in diverse and related ecosystems in such a way that it covers different levels and links from urban to rural spaces. Analysis of word co-occurrence also brought to light 6 distinct research clusters within the scope of integrated development planning studies, focusing on aspects like comprehensiveness, urban planning, local governance, participation, sustainable development, and spatial justice.
Conclusions: The insights garnered from scrutinizing the knowledge network and visualizing its structure in this study could potentially yield significant advancements in adopting a comprehensive, rational, and expert-driven approach to socio-political planning, thereby opening up new avenues for further study and implementation.

Mohamad Zaheri, Hossein Karimzadeh, Nabiollah Hosseini Shahpariyan,
Volume 13, Issue 50 (12-2024)
Abstract

Objective: Entrepreneurship plays a crucial role in job creation, wealth generation, and economic growth, serving as a key driver of community development. However, the emergence of rural entrepreneurship requires the establishment of a supportive ecosystem that fosters entrepreneurial activities. This study aims to identify the factors affecting rural entrepreneurship development through a meta-analysis approach, utilizing CMA3 software.
Method: This study analyzed all relevant research articles published in Iranian academic journals over the past 12 years. Using keyword-based searches in credible scientific databases, 13 research articles and 2 university dissertations met the inclusion criteria. The final meta-analysis incorporated 11 key factors and 343 variables.
Findings: The results indicate that out of all identified variables:
  • 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).
Among the 11 main influencing factors, 7 factors were the most frequently cited:
  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).
Conclusions: The meta-analysis approach highlights that rural entrepreneurship is shaped by multiple interrelated factors. This study integrates findings from diverse research to prioritize key influencing factors based on effect size, leading to the development of a comprehensive rural entrepreneurship model.

Mohammad Hossein Zarei Abyaneh, Mohammad Salmani, Mojtaba Ghadiri Masoum, Alireza Darban Astane, Zahra Torkashvand,
Volume 14, Issue 51 (6-2025)
Abstract

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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