Decision-making and planning in eco-wellness tourism can vary depending on time, resources, and the perspectives of stakeholders, as it is often challenging to generalize the results of decision-making models across different scenarios. Hence, the primary objective of this study was to propose a scenario-based framework for optimising eco-wellness tourism development. For this purpose, maps of 26 factors affecting the evaluation of nature-based eco-wellness tourism, including water, climatic, and kinetic therapies, were used in the Ardabil province of Iran. Weighted criteria maps are integrated into suitability maps for various wellness tourism products under different scenarios, ranging from very pessimistic to very optimistic, using the Ordered Weighted Averaging (OWA) operator. Then, to identify areas of consensus, scenario-based maps for water, climate, and kinetic therapies are combined. In the very pessimistic (optimistic) scenario, climate-only therapy accounts for 0.91% (2.23%), water-only therapy for 1.07% (8.44%), and kinetic-only therapy for 3.5% (5.81%) of the area. The most significant expansion is observed in areas integrating all three therapies—climate, water, and kinetic—which increase from 3.23% in the very pessimistic scenario to 14.5% in the very optimistic scenario. The findings have substantial insights for policymakers, tourism planners, and investors in developing and promoting unique eco-wellness experiences that benefit tourists. The methodical approach and choice of data and parameters in the study can be inspirational and adjustable for relevant studies.

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.

Urban managers and decision-makers may approach Urban Environmental Quality (UEQ) assessment with perspectives that range from highly pessimistic to highly optimistic scenarios. The objective of this study was to introduce a scenario-driven spatial decision support system framework for optimizing UEQ zoning. The proposed framework includes six steps: (1) building a geodatabase of criteria, (2) standardizing criteria using minimum and maximum methods, (3) determining criteria weights using the Analytic Hierarchy Process (AHP) method, (4) combining criteria and creating scenarios using the OWA method, (5) analyzing UEQ maps with statistical analyses, and (6) examining variability through histogram analysis of UEQ values across scenarios. The results indicate that, among environmental and infrastructural criteria, air pollution and population density had the most significant impact on UEQ zoning in Isfahan city. In the five decision-making scenarios (highly pessimistic, pessimistic, neutral, optimistic, and highly optimistic), 8% (19), 12% (15), 16% (12), 21% (8), and 25% (5) of Isfahan’s area were classified as poor, respectively. Additionally, the percentage of the population in poor classes across the scenarios was 5% (14), 10% (11), 13% (7), 17% (5), and 20% (3), respectively. The findings demonstrate that the proposed framework offers high flexibility and capability for assessing UEQ across different decision-making scenarios.

The dynamism of adventure tourism necessitates the precise identification of areas with suitable natural, infrastructural, and service capacities for hosting activities. The aim of this study is to assess the multi-scenario spatial suitability for the sustainable development of adventure tourism camps using a Geographic Information System (GIS)-based Multi-Criteria Decision-Making (MCDM) approach. The datasets used included topographic, climatic, environmental, accessibility, natural and cultural attraction, and service infrastructure indicators. The relevant criteria were first standardized, and their weights were determined using the Analytic Hierarchy Process (AHP). Subsequently, the layers were integrated through a Weighted Linear Combination (WLC) model. Four scenarios were designed for sensitivity analysis: the first scenario with balanced weight distribution (S_bal), the second prioritizing accessibility (S_acc), the third focusing on natural attractions (S_att), and the fourth emphasizing services (S_serv). The results indicated that approximately 21% and 9% of Chaharmahal and Bakhtiari province have high and very high potential for adventure activities, respectively, which were selected as initial options for the multi-scenario analysis. In the balanced (S_bal) scenario, 31% and 13% of the area of these options fell into high and very high suitability classes, respectively. The Service-Based Scenario (S_serv) increased the share of high and very high suitability areas to 34% and 19%, while Accessibility-Based Scenario (S_acc) reduced these classes to 27% and 10%. In the Attraction-Based Scenario (S_att), the areas in the high and very high suitability classes were 30% and 12%, respectively. The findings demonstrate that altering the priority of components can significantly change the spatial pattern of suitability, and sustainable planning of adventure tourism activities should be conducted based on management objectives and regional capacities. The proposed framework is generalizable to other regions and can serve as a basis for decision-making in balanced development, optimal infrastructure allocation, and sustainable management of adventure tourism.