In recent years, the awareness of sustainable tourism has risen around the world. Many tourism industries combine sports to attract more customers to facilitate the development of the economy and the promotion of local culture. However, it is an important task to establish a comprehensive tourism evaluation framework for sustainable sports tourism. This study proposes a Multi-Criteria Decision-Making (MCDM) model to discuss the above issues, using the Bayesian Best Worst Method (Bayesian BWM) to integrate multiple experts’ judgments to generate the group optimal criteria weights. Next, the modified Visekriterijumska Optimizacija i Kompromisno Resenje (VIKOR) technique is combined with the concept of aspiration level to determine the performance of sports attractions and their priority ranks. In addition, this study adds a perspective of institutional sustainability to emphasize the importance of government support and local marketing. The effectiveness and robustness of the proposed model is demonstrated through potential sports tourism attractions in Taiwan. A sensitivity analysis and models comparison were also performed in this study. The results show that the proposed model is feasible for practical applications and that it effectively provides some management implications to support decision-makers in formulating improvement strategies.

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The development of sports tourism is gaining momentum around the world, with many tourism industries combining sports events and programs to attract more domestic and overseas customers to promote economic and culture. Sustainability awareness has been gaining attention from many international organizations, resulting in the rise of sports tourism that incorporates sustainability. Therefore, the development of a valid and applicable sustainable sports tourism (SST) assessment model is an important task. In this study, a hybrid Multiple Attribute Decision-Making (MADM) model is proposed to measure the development performance of SST. The aims of this study include developing a SST assessment framework, identifying the mutual influential relationships among attributes, generating attribute influence weights, and calculating the performance of the evaluated items. The proposed model is divided into three stages. First, a cause-and-effect diagram is generated using the Grey Decision-Making Trial and Evaluation Laboratory (GDEMATEL) to describe the interactions and feedback among the attributes. Then, the GDEMATEL-based Analytic Network Process (GDANP) is applied to generate the influence weights of the attributes and their rankings. Finally, the expanded Probability-based Grey Relational Analysis (expanded PGRA) was applied to calculate the performance of the evaluated items and to determine the gap between evaluated items and the aspiration level. This study improves the original PGRA technique by introducing the concept of aspiration level into the PGRA calculation process, thereby replacing the traditional concept of “relative satisfaction” with “aspiration level”. In addition, the expanded PGRA can assess a single rated item without being limited to at least two items. We used the Sun Moon Lake Scenic Area in Taiwan as a model demonstration. The results show that the top three attributes that need to be strengthened are disease prevention and treatment, local social welfare and protection, and sports diversity. In the Sun Moon Lake, intersection control should be set up to ensure the health status of visitors and local residents. In addition to epidemic prevention, more measures and behaviors should be developed to deal with tourism diseases. We suggested that subsidies be provided to local residents to rebuild the fences around their homes to avoid disturbances caused by the influx of tourists. Moreover, the local government can create more sports events with special characteristics that can attract tourists to come again and again.

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