Data analysis for policy-making: the use of social network analysis in the formation and analysis of the ecosystem of Iranian tourism industry websites

The contemporary tourism industry is undergoing a transformative phase due to factors such as increased global travel, improved infrastructure, and widespread adoption of digital technology. This exponential growth has turned the tourism sector into a suitable platform for emerging developments. Understanding user behavior has become a crucial factor for businesses in the tourism industry to attract audiences, enhance satisfaction, and ensure loyalty. However, there is a significant lack of comprehensive research in this field, which poses challenges for data-driven decision-making and alignment with evolving perspectives. This paper utilizes social network analysis to examine and analyze the communication network of Iranian tourism websites and understand the consumer behavior of Iranian users towards tourism services. The study identifies eight distinct communities of tourism websites: ticket and tour purchasing forums, accommodations (hotels), online taxi services, accommodations (suites and cabins), food and cooking, location-based services, bus tickets and international tours, and migration. Through analyzing the relationships between these communities, valuable insights into mutual communication and communication patterns in the tourism ecosystem are presented. These findings contribute to facilitating sustainable and innovative future pathways by providing practical insights and policy recommendations for industry stakeholders.