Evaluation of tourism destination villages in terms of smart village components (case study: Qom province)

Introduction

Rural tourism has emerged as a significant economic source in many countries and plays a crucial role in local development policies. It is considered an economic panacea for rural areas, an enhancer of livability, a stimulus for the revival of settlements, an improvement in the living conditions of rural communities, and a catalyst for the reconstruction and economic and social development of rural areas. Qom province is located in the center of the country's transportation gravity and has high potential and numerous natural, scientific, cultural, and historical attractions, making it a prime location for rural tourism. Currently, the 12 tourist destination villages in this province offer favorable conditions for both urban and religious tourists. However, despite the high potentials and capacities of rural tourism and government policies to develop tourism in rural areas, they still face many challenges. One strategy proposed to address these issues is the intelligent development of rural tourism destinations. The present study investigates the level of perception of villagers on the intelligence of different geographical spaces, based on Cohen's six-dimensional model, which is used to measure the intelligence of different areas.



Methodology

The purpose of this study is to identify the dimensions of smart rural tourism destinations and define their indicators based on globally recognized models. The research method used is descriptive, analytical, and practical. The documentary method was used to identify the dimensions, and the statistical population is the target villages of tourism in Qom province. In 1401, the General Administration of Cultural Heritage, Handicrafts, and Tourism of Qom province identified 12 villages that were targeted for tourism, and all these villages were investigated. Using Cochran's formula with an error of 0.64, a sample size of 222 rural households (host community) was selected and estimated according to the sample household size of each village using the distribution method. To quantify the smart village, 44 indicators were used according to the six dimensions of smart governance, smart environment, smart dynamics, smart economy, smart people, and smart life on the Likert scale. Cronbach's alpha coefficient of 0.76 indicates the good reliability of the research tool since the scale of dimensions investigated in the smart village structure was upgraded from a rank to a distance. In this study, a one-sample T-test was used to compare the average evaluation of the respondents with the theoretical median value in SPSS software.



Results

The T-Tech test has revealed that the tourism target villages in Qom province are lacking in terms of smart village components. On the Likert scale, the average score for smart economy, smart environment, smart life, and smart mobility was 1.7, 1.8, 1.9, and 2.2, respectively, which is below average. The average smart governance and smart people scores were 2.3 and 2.2, respectively, which are also low. Overall, the average intelligent development in rural tourism destinations in Qom City is unfavorable at 2.07. The average of all smart components in all the investigated villages is low and very low. According to the results of the one-way variance analysis test, the average difference in people's perception of the components of smart tourism destinations is significantly lower than the average and weak. Fordo village has the highest average score with 2.44, whereas Bidhand village has the lowest average score with 1.85 concerning intelligent development of tourist destinations.



Discussion

The tourist villages in Qom City have a long way to go to become truly smart. To achieve this, the first step is to ensure optimal access to smart tools, including ICT. Before taking any action, it is necessary to focus on obtaining these tools. A smart village must have appropriate technology infrastructure, which includes facilities like high-speed internet, advanced communication networks, and information systems. Unfortunately, many villages have limited access to these infrastructures, which requires investment and development in technology infrastructure, smart software, equipment, and tools, all of which are costly. Apart from this, there is also a need to change the views of those in charge to accept new and smart technologies. One of the major problems is the adoption of smart technologies in rural areas due to limited access to ICT infrastructure, lack of knowledge and skills in using digital tools among people and tourism workers, and the digital divide between rural and urban areas. Not paying attention to the appropriate distribution of necessary infrastructure and facilities only exacerbates this divide. This affects the skills of beneficiaries, digital literacy, and their ability to use technology for competitive advantage.



Conclusion

It is observed that rural people have a low perception about the components of smart tourism destinations. In order to achieve smart tourism, it is important that rural households have access to information and communication technology. This access is fundamental for the development of smart tourism in rural areas. The government plays a key role in promoting smart tourism technology in rural areas by adopting appropriate policies to bridge the digital gaps and increase the adoption of smart tourism technologies. Capacity building programs should also be implemented in this regard. Researchers interested in this field should focus on capacity building, digitization, stakeholder participation, sustainability, and effective public service platforms to promote smart tourism technologies in rural destinations