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.

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.

As the Coronavirus disease 2019 (COVID-19) epidemic spreads all over the world, governments of various countries are actively adopting epidemic prevention measures to curb the spread of the disease. However, colleges and universities are one of the most likely places for cluster infections. The main reason is that college students have frequent social activities, and many students come from different countries, which may very likely cause college campuses to be entry points of disease transmission. Therefore, this study proposes a framework of epidemic prevention work, and further explores the importance and priority of epidemic prevention works. First of all, 32 persons in charge of epidemic prevention from various universities in Taiwan were invited to jointly formulate a campus epidemic prevention framework and determined 5 dimensions and 36 epidemic prevention works/measures/criteria. Next, Bayesian best worst method (BWM) was used to generate a set of optimal group criteria weights. This method can not only integrate the opinions of multiple experts, but also effectively reduce the complexity of expert interviews to obtain more reliable results. The results show that the five most important measures for campus epidemic prevention are the establishment of a campus epidemic prevention organization, comprehensive disinfection of the campus environment, maintenance of indoor ventilation, proper isolation of contacts with confirmed cases, and management of immigration regulations for overseas students. This study provides colleges and universities around the world to formulate anti-epidemic measures to effectively reduce the probability of COVID-19 transmission on campuses to protect students’ right to education.

The purpose of this study was to explore the influencing factors of users using Nike+Run Club App by Theory of Reasoned Action (TRA) as the theoretical basis and add the perceived playfulness into the research framework. This study took the users of the Nike+Run Club App as the research subject and distributed 360 questionnaires by snowballing sampling, a total of 351 valid questionnaires. All data were analyzed by descriptive statistics, confirmatory factor analysis, and structural equation models. Overall, the results reveal that extending TRA could be a well-explained users behavior in the mobile application. The study found that the less the efforts spent in learning, the more positive the influence on attitude, thus affecting users behavior. Therefore, this study proposed the following suggestions: People are pursuing a clearer and simple interactive function, a simplistic design; or adding instructions next to the new features will make the Nike+Run Club App more perfect. Emphasize the users entertainment needs, develop interesting tasks, or games to make users feel interesting, and then be willing to continue to use the Nike+Run Club App.

Medical tourism (MT) is the activity of traveling domestically or abroad to receive medical services. The scope of medical treatments covers dentistry, surgery, antiaging procedures, preventive medicine, and even some health-related treatments (meditation, physiotherapy, psychotherapy, addiction treatment, psychiatry, etc.). Due to the global boom in MT, governments are actively promoting MT packages to capture this huge business opportunity. However, what are the key factors that make MT development successful or unsuccessful? How can the performance of current MT operators be evaluated? And, how can the performance of underperforming operators be improved? This paper addresses these questions by proposing a MT assessment framework that summarizes the potential key factors of MT. In addition, this study proposes a model that integrates the Bayesian Best-Worst Method (Bayesian BWM) and grey Preference Ranking Organization Method for Enrichment Evaluations based on Aspiration Level (grey PROMETHEE-AL) to assess the performance of assessed MT operators. The Bayesian BWM not only aggregates the judgments of multiple experts but also generates a set of objective group criteria weights. Besides, the modified PROMETHEE incorporates the grey theory and aspiration level concept to increase the usefulness of the original PROMETHEE. The results of the analysis show that the two most critical criteria for MT are “the operators have cloud computing systems to analyze the travelers’ sensor data in real-time and accurately to provide customized medical services” and “multilingualism and communication skills of medical travel-related personnel.” Poor performers in the travel industry can be improved by prioritizing the criteria in order of importance. The management implications of this study can be used as a basis for performance evaluation by operators and government health care organizations.

Background. In the study of wearable device users, it was found that the intentional motives for using wearable devices were a novelty, fun, and popular trends, but whether the needs and functions of device users will change due to the change the time is the focus of this study. Objectives. This ...