Introduction: Smart villages are capable of facilitating entrepreneurial opportunities in agriculture, enhancing healthcare, educational, and infrastructural services, ensuring optimal resource use, and contributing to sustainable development in rural areas, ultimately leading to improvements in quality of life and socio-economic well-being. The European Union defines smart villages as communities and areas that can focus on their strengths and potential capabilities, create new opportunities, and maintain traditional networks while leveraging existing and innovative tools to improve the quality of life for residents. In smart villages, innovation, knowledge, information and communication technologies, the Internet of Things, and smart technologies are utilized to reinforce both traditional and new networks. The need for the establishment of smart villages to enhance quality of life, address unemployment and employment issues, reduce poverty, and improve infrastructure and amenities is an undeniable reality. This necessity leads to improved living standards, decreases in deprivation, and ultimately fosters sustainability in rural areas, providing a remedy for the current poverty and underdevelopment faced by many villages. Given the limited number of smart villages in Iran, particularly in Kermanshah province, the establishment of such villages is essential for achieving sustainable development and reducing existing deprivations. It is noteworthy that the strategy for developing smart villages varies depending on local conditions and the functions of different villages, meaning that the concept of smart villages is not uniform across all rural areas. Therefore, smart villages development programs can encounter various challenges and obstacles, and identifying the hindering factors smart villages development as well as the drivers for such programs in rural communities is a critical and necessary endeavor. This research addresses the identification of hindering factors and drivers to smart villages development in the Sarfirouzabad district of Kermanshah County, with the aim of taking effective steps toward improving the conditions of the villages in this district and aiding the advancement of smart villages development in Kermanshah province.

Materials and Methods: The identification of hindering factors and drivers to the development of smart villages in the Sarfirouzabad district of Kermanshah County was carried out using a modified fuzzy Delphi technique through two consecutive rounds and force field analysis. The research sample consisted of 20 specialists and experts in the fields of agricultural extension, agricultural development, geography, and rural planning, as well as village heads from the Sarfirouzabad district, who were selected using a purposive sampling approach based on specific criteria. The data collection tool was a researcher-designed questionnaire grounded in relevant informational resources and the process governing the modified fuzzy Delphi method. The validity and reliability of the research instrument were confirmed through the implementation of triangular fuzzy Delphi rounds and the calculation of the agreement coefficient. Data analysis was performed using IBM-SPSS2026 and Excel2019 software. Subsequently, the data were coded and described and analyzed based on the force field analysis method in Path makerwin5.5 software.

Results and Discussion: Based on the results, there are nine hindering factors and eight drivers identified in the path to developing smart villages in the Sarfirouzabad district. Among the major hindering factors are the lack of familiarity among villagers with innovative tools and technologies, the low priority of smart villages development among policymakers considering current priorities and issues, over-dependence on traditional agricultural methods, the absence of a comprehensive model and solutions for smart villages development, lack of cooperation from executive agencies in advancing smart projects, unawareness of villagers regarding the benefits of smart technologies, migration of educated youth from villages, shortage of skilled human resources, the absence of essential infrastructure for the development of smart villages such as access to high-speed internet, and the high costs of smart technologies for low-income villagers. Conversely, key drivers in this process include the existence of local governments that are interested and knowledgeable about smart technologies, a high willingness among villagers to adopt smart technologies, relatively high local community interest in village development, access to both online and local markets for selling agricultural products and handicrafts, sustainable access to high-speed internet in villages, support for rural entrepreneurship based on new technologies, availability of educational facilities in the field of smart technologies, and the presence of essential infrastructure for the development of smart villages such as smart transportation. The equilibrium point among these driving factors and hindering factors is 40.1. Regarding the identified hindering factors and drivers, the average of the inhibiting forces exceeds the equilibrium point, indicating a negative impact of these forces compared to the drivers in the development of smart villages in the studied district. Overall, the result reflects that the score of driving forces is weaker than that of the hindering factors, meaning that the development of smart villages in the Sarfirouzabad district is more hindered than propelled. To mitigate the hindering factors and strengthen the existing drivers, seven actionable measures were identified: establishing training workshops combined with access to high-speed internet, forming a local consortium to support technology-based entrepreneurship, developing local online marketplace platforms for selling products, organizing exhibitions and local technology events to raise awareness, establishing innovation and facilitation centers for training and consultancy, creating programs to attract educated youth to villages, and pursuing supportive policies from the government for the development of smart villages. After implementing these proposed actions, the equilibrium shifted from 38.25: -41.95 (against the plan) to 47.7: -34.17 (in favor of the plan). According to the research results, the implementation of the identified actionable measures significantly increased the average of driving forces while decreasing the average of inhibiting forces, thereby reducing their intensity.

Conclusion: The core findings of this study confirm that the overall impact of hindering forces outweighs the driving forces. This imbalance indicates that the development process of smart villages in the studied rural district is characterized by greater deterrence and less advancement, and realizing the potential of smartification requires a deep understanding of its roots. The predominance of hindering factors may signify structural and human limitations in the region. The lack of familiarity among villagers with new tools and technologies stands out as the most prominent hindering factor. This not only reflects unequal access to technology but also indicates a deficit in digital literacy and the necessary skills to utilize smart tools, acting as a major barrier to innovation adoption and technology utilization. This unfamiliarity creates a cycle of resistance to change, preventing active participation of villagers in the digital economy and hindering their enjoyment of its benefits. Another significant hindering factor is the weakness of communication and internet infrastructures. The absence of these infrastructures disrupts the connection of rural communities to knowledge networks and global markets, impeding the formation of an innovative local environment. This situation limits access to information, online education, and digital economic opportunities, effectively depriving villagers of the advantages of smartification. Over-reliance on traditional agricultural methods and the lack of an integrated model and solution are also key hindering factors to smart village development in the studied rural district. These factors may stem from cultural resistance to change and weakness in local capacity development, delaying adaptation to new agricultural technologies and the utilization of smart agriculture, thereby hindering structural transformation in the local economy. Conversely, driving forces such as the presence of informed and motivated local authorities, along with a spirit of synergy and innovation among villagers, are of great importance. These factors demonstrate the existence of social capital and local capabilities that can facilitate the formation of local innovation networks and knowledge dissemination by strengthening trust and participation. The presence of informed local leaders also plays a crucial role in mobilizing resources, directing developmental actions, and overcoming hindering factors. Based on these profound insights and aligned with the research findings, the policy framework for smart village development in Sarfirouzabad rural district must adopt a comprehensive and multifaceted approach that simultaneously covers human, economic, institutional, and infrastructural dimensions. To mitigate the lack of familiarity among villagers with new tools and technologies, it is proposed to design and implement a comprehensive rural technological empowerment program focusing on practical and continuous training workshops in local centers, utilizing local language and examples. Concurrently, to overcome over-reliance on traditional agricultural methods, the establishment of small smart demonstration farms showcasing the practical benefits of new technologies to farmers is essential. These farms can serve as successful models, reducing resistance to change and accelerating the adoption of new technologies. From an institutional and economic perspective, the compilation and presentation of successful case studies and robust analytical reports on smart villages to policymakers at national and local levels are crucial for elevating the status of this development in overarching priorities and allocating sufficient resources. Furthermore, the development of a local and dedicated online sales platform for rural products in collaboration with local institutions, along with comprehensive training in digital sales management and marketing, can facilitate access to online markets and contribute to the region's economic growth.