Analysis of Foreign Tourists’ Behavioral Patterns and Perceptions in Rural Destinations - Hamdollah Sojasi Gheidari; Zahra Soleymani (برنامه ریزی فضایی)
AbstractAnalyzing tourists' photos' visual content proves to be an effective method for understanding their behaviors and preferences in tourism destinations. This approach can serve as a valuable tool for precision marketing of tourism destinations, including tourist villages. The present study employed a novel methodology by conducting visual analysis of data. The analysis considered the characteristics of the photos, describing the observable appearance of themes and specific features within the collection. Subsequently, the most significant items, their frequency, simultaneity, and categories were identified and the relevant items were coded. For this study, a sample of 548 uploaded photos of Iranian villages on Flickr was selected and analyzed. Through the photo analysis, 21 dominant scenes in villages were identified and further classified into 5 attractions and 9 types of tourism. ArcGIS was employed for spatial analysis to examine differences in tourists' perceptions and behaviors. The study findings revealed that attractions, such as landscapes, infrastructure, and scenes of rural houses had captured the interest of tourists visiting Iranian rural destinations. These attractions were perceived more frequently compared to others. Additionally, among the various types of tourism, rural tourism emerged as the predominant perception among tourists.Keywords: Tourism Perception, Tourists’ Behavior, Foreign Tourists, Rural Tourism, Iran IntroductionUnderstanding of competitive advantages, tourist behavior, and local attractions that appeal to tourists is crucial for effective tourism planning and management. In recent times, various types of data have been utilized in destinations to gain insights into tourists' behavioral patterns and develop competitive advantages. One prominent type of data that has gained popularity is tourist-generated photos taken at different destinations and tourist attractions. As visitors explore a destination, they capture photos that reflect their personal interpretation of the natural, social, physical, and cultural attractions they encounter. These photos and videos serve as a valuable source of information about diverse tourist destinations and sharing them on the internet and public virtual platforms allows for the dissemination of beauty, cultural richness, destination value, lifestyle, and specific activities. In the age of the internet, many tourists share their travel photos on social media and online galleries to document and share their experiences with friends and family. The choice of photos for uploading and sharing reflects their personal opinions about the visited destinations, which directly influence other travel and tourism enthusiasts, as a picture is worth a thousand words. In other words, photos or images play a vital role in conveying the image of a tourism destination and nowadays, travel destinations are predominantly promoted through captivating photographs. Therefore, the photos shared by tourists have the potential to disseminate their experiences related to the lifestyle, cultural aspects, activities, livelihood, and natural attractions of local communities. Materials and MethodsThe objective of this study was to identify tourist categories from various countries and analyze their perceptions and behavioral patterns in rural tourism destinations in Iran. The analysis was conducted through visual content analysis of the photos taken by tourists. All rural areas of Iran with photos published on Flickr by tourists were included in the study. In the past, accessing such images presented methodological challenges. However, in the digital age, many tourists willingly share their photos online and provide geotags, making it relatively easy to access a representative collection of photographs for a specific destination. Building upon the work of Zhang et al. (2019), visual content analysis was employed in this study. The systematic and observational method was utilized to explore how this phenomenon was represented. This method enabled the categorization of observable content into distinct groups. The analysis considered the characteristics of the photos. Initially, the visible themes and specific features of the collection were described followed by the identification of the most significant items, their frequency, simultaneity, and categories. Subsequently, the relevant items were coded. Research FindingsIn total, 21 distinct scenes were identified from the analysis of the photos. The analysis of photos shared by tourists from different countries revealed variations in their perceptions of rural scenery. European and North American tourists primarily focused on rural houses and landscapes. Asian tourists showed a greater interest in religious buildings and rural houses. Historical sites and rural houses attracted more North American tourists. Similarly, tourists from Oceania expressed a strong interest in historical sites and wildlife. Moreover, the analysis of differences among various continents in terms of the 21 scenes perceived by tourists indicated that most tourists from four continents perceived scenes, such as historical sites, rural houses, traditional attire, and rural lifestyle. These scenes were found to capture the interest of tourists from different continents and cultures. However, scenes depicting cooperation among villagers, music, rivers, and transportation routes were primarily noticed and appreciated by European tourists. The spatial distribution analysis of foreign tourists' trails in rural destinations provided insights into their overall behavioral patterns. According to the ArcGIS output, European tourists had the most extensive trail coverage. Meymand Village in Kerman Province and Abyaneh Village in Isfahan Province were the most observed trails for European tourists. Notably, both villages are UNESCO World Heritage sites in Iran and boast unique and distinctive architectural styles compared to other villages. In terms of trail distribution, North American tourists ranked second with a majority of their trails observed in Abyaneh and Nazarabad villages, both located in Isfahan Province. Asia ranked third in terms of trail distribution after Europe and North America with most trails observed in Chak Chak Village. This village located in Yazd Province holds significant religious importance as one of the holiest places of worship for Zarathustra's followers. Discussion of Results & ConclusionThis study aimed to investigate and analyze the perceptions and behavioral patterns of foreign tourists in rural destinations. The findings highlighted the diverse range of tourist attractions in Iranian rural areas, which offered significant tourism opportunities for foreign tourists and served as a competitive advantage for rural destinations. These attractions had a direct impact on tourists' interest and engagement. Considering the varied preferences and perceptions of foreign tourists towards rural destinations, the management organizations responsible for rural tourism can adopt tailored marketing strategies to effectively promote rural tourism destinations. For example, specific rural tourism packages can be designed and marketed to cater to the preferences of tourists from Asian and Oceanian countries, aligning with their perceptions. Furthermore, based on the observed behaviors of tourists, it is evident that greater emphasis should be placed on promoting rural tourist attractions that offer captivating landscapes and historical and ancient sites, as well as social and cultural experiences. These elements are the key factors in attracting and engaging foreign tourists in rural destinations. In conclusion, the findings of this study highlighted the importance of understanding tourists' perceptions and behaviors in rural tourism destinations. By leveraging the diverse attractions and adopting targeted marketing strategies, rural destinations in Iran can enhance their appeal and competitiveness in the global tourism market.