Scenario-Based Assessment of Agritourism Development Using Hierarchical Principal Component Analysis: A Case Study of Iran

The development of agricultural tourism (agritourism) has gained increasing importance as a tool for improving rural economies and promoting sustainable natural resource management. This study proposes a scenario-based framework for agritourism development assessment using hierarchical principal component analysis in Iran. National spatial and statistical datasets, geographic information, topographic maps, and climatic data were used. Sub-criteria related to five main criteria including accessibility, risk and safety, environmental conditions, tourism attractions, and tourism facilities were prepared and normalized. First-level principal component analysis was independently applied to each criterion to reduce data dimensionality and generate weighted potential maps. Then, second-level principal component analysis was used to produce the final agritourism development potential map. To evaluate model robustness, a weight-based sensitivity analysis was performed. In addition, risk-oriented, development-oriented, and environment-oriented management scenarios were defined to examine the effects of alternative priorities on agritourism potential patterns. Results showed that the first principal component explained approximately 44% of the variance in accessibility, 48% in environmental conditions, 69% in tourism attractions, 90% in tourism facilities, and 38% in risk and safety, while the first three components explained more than 80% of variability for most criteria. At the second level, the first component explained about 64% of the total variance, indicating its dominant role in shaping the spatial pattern of agritourism potential. The proportion of the very high potential class in accessibility, risk and safety, tourism attractions, tourism facilities, and environmental conditions was 25%, 19.7%, 15.8%, 6.6%, and 1.8%, respectively, whereas only about 10% of the country fell into this class in the final map. Sensitivity analysis revealed that accessibility and environmental conditions had the greatest influence on model stability, whereas tourism attractions showed the most stable behavior. Scenario analysis indicated that the very high potential class increased to 13.9% under the development-oriented scenario, while it decreased to 10% and 9.1% under the environment- and risk-oriented scenarios, respectively.