Document Type : Research Article
Authors
Department of Human Geography and Spatial Planning, Faculty Earth Sciences, Shahid Beheshti University, Tehran, Iran
Abstract
Smartization of rural areas, as an emerging approach to rural infrastructure development, plays a crucial role in economic empowerment and in reducing the vulnerability of rural households. Accordingly, the present study aims to identify the key factors and driving forces influencing the economic resilience of rural households in the face of climate change. In terms of purpose, the research is applied, and in terms of nature, it is descriptive analytical, adopting a futures studies approach. Data were collected through documentary review and field surveys using a structured questionnaire. The statistical population consisted of 35 experts and specialists in the field of rural development. The validity and reliability of the questionnaire were confirmed through expert judgment, and data were analyzed using MICMAC software. The findings revealed that among 50 examined indicators, 16 key driving forces were identified. In the dimension of supportive policies, the most significant factors included improved access to financial markets, increased income from agriculture-related activities and strong government support with adequate access to support facilities. In the dimension of post–climate shock recovery policies, key variables included the provision of loans and financial assistance to affected households, the capacity for business creation and development and access to suitable employment opportunities in rural areas and surrounding cities.
Introduction
Global trends indicate that, despite the gradual decline in rural populations, these areas still host a significant portion of the world’s population and play a crucial role in food production, environmental protection, and economic development. However, rural regions particularly in developing countries face serious challenges such as poverty, weak infrastructure, limited access to services, degradation of natural resources, and most notably, climate change. These challenges have placed rural households' livelihood security under substantial threat. In response to these issues, the concept of "smart villages" has emerged as an innovative model in rural development. By leveraging modern technologies, participatory governance, and locally driven solutions, this approach seeks to enhance economic resilience and improve the quality of life for rural residents. In this study, the concept of smart villages is referred to as smartization, emphasizing the systematic integration of smart technologies, governance, and innovation in rural development. While preserving traditional lifestyles, smart villages enable flexible responses to environmental and social risks. Within this context, the economic resilience of rural households-their ability to cope with the consequences of climate change-holds a central position. This study, adopting a foresight approach and focusing on the three counties of Ferdows, Boshrouyeh, and Sarayan, aims to identify the key drivers of smartization and examine its impacts on the economic resilience of rural households in the face of climate change.
Material and Methods
This study is applied in terms of its objective and descriptive–analytical in nature, adopting a foresight-oriented approach. The required data were collected through both documentary and field methods. Documentary data consisted of library resources, scholarly articles, and policy documents related to smart development, economic resilience, and climate change. Field data were gathered through a structured expert questionnaire based on the Cross-Impact Analysis method (MICMAC).
The designed questionnaire focused on two main dimensions: first, supportive policies and measures influencing the economic resilience of rural residents in the face of climate change; and second, key components of economic recoverability following climate-related shocks. The statistical population consisted of 35 experts and knowledgeable professionals in the fields of smart village development, economic resilience, and climate change. Participants were selected based on criteria such as research experience, involvement in applied projects, and familiarity with the socio-economic conditions of Ferdows, Boshrouyeh, and Sarayan counties. The sample included faculty members from Shahid Beheshti University and Ferdowsi University of Mashhad, as well as local experts from relevant executive organizations such as municipalities and district governorates. To validate the research instrument, expert opinions from academic specialists were employed, and the necessary revisions were made according to their suggestions. Data analysis was performed using MICMAC software. Initially, the relationships between variables were assessed on a scale from zero (no influence) to four (very high influence), and the cross-impact matrix was subsequently completed. Finally, the key variables with the highest levels of influence and dependence were identified and introduced as forward-looking drivers for enhancing the economic resilience of rural households.
Results and Discussion
The findings of this study examine the impact of smart village development on the economic resilience of rural households in the face of climate change in the three counties of Ferdows, Boshrouyeh, and Sarayan. Descriptive results showed that 80% of respondents were male and 20% female. In terms of educational background, 75% held a PhD, 20%had a Master's degree, and 5% held a Bachelor's degree. Based on data obtained from field surveys and literature review, the factors influencing economic resilience were identified in two main dimensions: supportive policies and components of recovery following crises. Using the MICMAC structural analysis model, the level of influence and dependence of these variables was assessed. In the 25×25 matrices for both dimensions, approximately 85% of cells were filled, indicating numerous interrelationships among the variables. A total of 533 relationships were examined, of which 92 had no influence, 202 were weak, 238 were moderately strong, and 80 were very strong. Additionally, 13 potential relationships were identified in the dimension of supportive policies. In the analysis of direct influences, eight key drivers were identified in the dimension of supportive policies. These included: government support and access to backup services, increased investment in rural areas, development of communication infrastructure, growth in agricultural income, targeted regional policymaking, diversification of income sources, entrepreneurship development, and access to financial markets. These factors exerted the highest levels of influence on other variables. Regarding indirect influences, variables such as increased agricultural income, rural investment, government support, income diversification, financial management, entrepreneurship, electronic marketing, and access to financial markets showed the highest levels of indirect impact. The matrix of direct and indirect influences revealed that key factors such as government support, private sector investment, communication infrastructure, agricultural income, and regional policymaking ranked highest in terms of influence. In terms of dependency, the five variables with the greatest direct and indirect dependency were rural investment, agricultural income, government support, financial management, and income diversification. In the second-dimension components of recovery following crises six key drivers were identified: access to alternative income sources, regaining suitable employment, development of non-agricultural activities, utilization of government assistance, poverty reduction, and access to smart economic systems. These variables play a vital role in the post-crisis economic reconstruction of rural communities. In the area of indirect effects within the recovery dimension, variables such as reduced use of chemical inputs and increased compost usage, job recovery, alternative income, access to smart systems, and government support demonstrated the highest levels of indirect influence. Moreover, in the direct influence ranking matrix, variables such as financial empowerment, increased satisfaction with rural living conditions, development of non-agricultural businesses, alternative income, and job creation contributed the most to economic recovery. These factors played key roles in both direct and indirect impacts. Ultimately, the findings indicate that integrating intelligent supportive policies with effective recovery components can significantly enhance the economic resilience of rural households. The identified key drivers provide a foundation for policymakers to develop effective strategies for adapting to climate change and ensuring the economic sustainability of rural areas.
Conclusion
This study aimed to identify the key factors and drivers influencing the economic resilience of rural households in the face of climate change, with a focus on the role of smart technology in this process, in the counties of Ferdows, Sarayan, and Boshrouyeh. The findings revealed that supportive policies, such as government support, increased investment opportunities, the adoption of new technologies, electronic marketing, and support for entrepreneurship, play a significant role in enhancing the economic resilience of rural communities. Additionally, factors such as access to loans and financial facilities, the development of non-agricultural employment, the creation of diverse job opportunities, and the use of smart economic systems were found to be crucial in recovery following climate crises. The findings suggest that smart technology can improve technological infrastructure, strengthen information flow, and develop digital markets, thereby increasing the capacity of rural communities to adapt to climate change. These results align with previous domestic and international studies and emphasize the role of dual-driven factors in enhancing economic resilience. Based on these findings, it is recommended that policymakers prioritize the development of smart infrastructure, targeted financial support, the enhancement of digital skills, and the promotion of technology driven businesses to strengthen the economic resilience of rural areas. Furthermore, the design of participatory local policies focusing on empowering rural residents and encouraging them to remain in rural areas could pave the way for the sustainability of rural economies in the face of climate-related risks.
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