Spatial analysis of tourism flows within rural settlements in the influence zone of Mashhad's tourism industry abstract
Analyzing tourism flows holds significant importance for governments and businesses, as the findings inform investment planning in areas such as infrastructure, goods and services, and transportation. In this context, analytical and spatial studies serve as effective tools for the optimal management of tourism flows and strategic planning within these sectors. Consequently, the primary objective of the current research is to identify key factors influencing rural tourism attraction flows. This research employs a descriptive-analytical methodology and serves an applied purpose. To operationalize the study, the tourism influence zone of
Mashhad was selected as the study area. Data analysis was conducted using SPSS software along with the Merec and Marcos multi-criteria decision-making models. Pearson's correlation was employed to examine the relationship between the Marcos model values for tourism flows and various spatial factors. Based on the theoretical framework, tourism flows were analyzed, and relevant indicators were identified accordingly. Consequently, tourism flows were categorized into three primary types: tourist flows, capital flows, and goods flows. Classification of the studied villages using the Jenks method indicated that the villages of Miami, Radkan, and Akhlmad Alia exhibit the strongest tourism flows, while Qarajangal and Khajeh Hossein Abad demonstrate the weakest tourism flows. Additionally, correlation analysis conducted with SPSS software revealed that the value of the Marcos model for tourism flows has a very strong, significant relationship with factors such as infrastructure availability, accessibility, precipitation levels, literacy rate, youth population ratio, and sex ratio. A strong, significant relationship was also observed with the number of attractions, temperature, elevation (in meters), Bartkefel 95, population size, and household size. Furthermore, a moderate, significant relationship was found with climate type, availability of catering services, and availability of accommodation services.
