In the digital age, online user reviews have become a crucial source of experiential data for evaluating service quality in the tourism industry. This study analyzes and assesses online reviews of ecolodges in Iran using data-driven methods and advanced web scraping techniques. Data from 1,015 active ecolodges listed on the Jabama platform were collected and analyzed utilizing Python and the Selenium library. Non-parametric Kruskal-Wallis tests were conducted to examine significant differences between provinces across key indicators, including overall satisfaction, check-in process, cleanliness, hospitality, location, and perceived value for money.



The findings reveal that the quality of tourism experiences results from the interaction among multiple service elements. Provinces such as Hamedan, North Khorasan, and Markazi exhibited superior performance in cleanliness (χ² = 59.1, p < 0.001), check-in process (χ² = 37.5, p = 0.052), and hospitality (χ² = 53.5, p < 0.001), and achieved higher overall satisfaction scores (χ² = 63.2, p < 0.001), indicating a positive synergy between these factors. Conversely, provinces like Tehran and Mazandaran, despite high tourist volumes, showed weaker performance in value for money (χ² = 66.8, p < 0.001) and cleanliness, suggesting a misalignment between infrastructure capacity and tourist demand.



Additionally, the analysis of location (χ² = 92.2, p < 0.001) highlights the significance of geographical advantages, with provinces such as Isfahan and Fars performing better due to more favorable locations. The study emphasizes the importance of standardizing service quality, investing in infrastructure in underdeveloped regions, and utilizing real user-generated data to improve the tourism sector.