In a retail store located in a tourist destination, tourists can be one of the potential consumers who should be concentrated on. The existence of the retail can support shopping tourism. This research develops a modified market basket analysis (MBA) framework to analyze the relationship between promotional programs and customer behavior in the retail sector. MBA is performed with the apriori algorithm to reveal the relationship between product and product, product and promotion, promotion and customer member, product and customer member. With this analysis, it is hoped that retailers can determine their promotional strategies to retain current consumers and attract new consumers, including tourists. Modified MBA is carried out by adding promotion variables to the point of sales (POS) data that will be analyzed. The framework was tested on a case study of a fashion retail store in the city of Yogyakarta, which is one of the tourism destinations in Indonesia.

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Following COVID-19, Japan’s foreign tourists increased, surpassing 25 million in FY 2023. Popular activities include skiing, pottery, and tea ceremonies. The Japanese government launched “the Project to Promote the Formation of Snow Resorts with High International Competitiveness” in 2020 to boost long-term stays and spending. This study analyses data on 16 ski resorts in the Project and examines ski resort word of mouth (WOM) and data, categorizing by country (Japan, China, and Europe), and before and after COVID-19. It uses principal component analysis to typify WOM, comparing results with basic ski resort data to provide guidelines for future development. WOM trends differ for Japanese but not Europeans pre/post-COVID. Ski resort development impacts WOM, influenced by European cultural backgrounds. The effects vary by country, with high skiing costs. Development is an effective public investment, enhancing inbound tourism and providing economic benefits.

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Using suitcase e-commerce sites as a subject of inquiry, this study aimed to examine the effect that differences in the amount of information in the “product image,” “product title,” and “product description” have on users’ perception of product functions. In addition, this study also evaluated the visibility of e-commerce sites. The factors examined in this study were “product image,” “product title,” and “product description,” and the amount of information in each factor was set as either high or low. For the image factor, the low amount information level displayed one image, while the high amount of information level displayed four images. For the product title, the low amount information level displayed only the product name, while the high amount of information level displayed the product name and words related to the suitcase’s functions. For the product description, the low amount information level displayed only an overview, while the high amount of information level displayed detailed information about the suitcase. This experiment used a within-participants design. Thirty-three men in their twenties who had no visual impairment participated in the experiment by examining the product factors and responding to a questionnaire. The questionnaire included four items on basic participant information, the following five items on the participant’s subjective evaluation of functional elements such as durability, convenience, appearance, texture, and size, and the one items on the participant’s subjective evaluation of the visibility of e-commerce sites. For each product factors, participants viewed e-commerce sites (for 30 seconds), answered measurement items (until completion), and took a break (for 15 seconds). Based on the analysis of the questionnaire responses, the study recommends that e-commerce sites make it easy to recognize the durability, convenience, appearance, texture, and size of suitcases by including a high amount of image information while limiting the amount of information contained in the product title to ensure the user-friendly nature of the site.

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We focus on small-scale historical buildings, which play an important role as local resources, and propose an audio guide system designed to introduce these buildings effectively. Specifically, we aim to create a low-cost, easily updatable system that local volunteer guides and building managers can easily utilize. Compared to conventional guided tours, this audio guide system can be operated with fewer staff members and enables tourists to learn about the history and culture of the buildings at their own pace. One key feature of the audio guide system is its support for multiple languages, catering to inbound demand, and providing audio and text formats. Additionally, the system employs generative AI technology to streamline the creation and updating of guide content. By leveraging generative AI, local volunteers, and staff can easily generate and update the content without needing specialized knowledge. For the demonstration experiment, the Cultural Path Area in Higashi Ward, Nagoya City, was selected as the site to evaluate the effectiveness of the proposed audio guide system. In this experiment, we assessed tourist satisfaction, understanding, and convenience when using the system, and identified areas for improvement and operational challenges. The results confirmed that a low-cost, easy-to-use audio guide system can contribute to the promotion of local tourism. This study proposes a novel approach to guide system development aimed at revitalizing local tourism. It provides a practical framework for collaboration between local communities and the tourism industry to promote the sustainable use of tourism resources.

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With the outbreak of COVID-19 at the end of 2019, online tours became more popular in the tourism industry. Online tours not only provide an alternative to actual trips but also have the potential to promote an intention to visit tourist destinations and increase the intention to purchase local products. To generate these positive outcomes, clarifying the structure of consumers’ evaluations of online tours is important. Therefore, this study aims to present and validate an evaluation model of online tours from the consumers’ perspective. We developed a research model based on previous studies in the services marketing literature. The research model was validated using online survey data sent to consumers who have experienced online tours. The results of Partial Least Squares Structural Equation Modelling (PLS-SEM) demonstrate that the hypotheses of the research model are supported. Specifically, the results indicate that the service quality of online tours positively affects satisfaction and marketing outcomes.

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The tourism industry is suffering from an acute labour shortage. To mitigate this gap, enhancing productivity through data-driven destination management has become imperative. Local communities therefore need to collect development-relevant data and leverage for planning and operations. Although data utilisation by non-expert users who manage tourist destinations is an important topic, only a limited number of studies have focused on it. In this research, we clarify the essential data utilisation requirements for non-expert users of urban time-series data. To derive these requirements, we examine weather forecasting, the most widely accepted and routinely employed form of time-series data utilisation. First, the end-to-end pipeline of meteorological information from data collection through analysis, prediction, and public dissemination was mapped. Next, we characterise the published data that constitute users’ points of contact with weather services, focusing on attributes such as temporal granularity and measurement scales, and highlight key considerations for collaboration with private-sector providers. From this examination, eleven features of weather forecast that foster user engagement were distilled. These features inform a set of practical requirements for ordinary users managing tourist destinations, among which are: data should be collected centrally by a public authority rather than by individual users; the authority should publish not only raw figures but also processed analytics; providing daily updated forecasts of current and future data is most important for users; and users should develop intuitive understandings of higher-scale data through repeated exposure to past data. The results offer actionable guidance for designing data utilisation that empower non-expert users to enhance tourist destination management.

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This study investigates the travel experiences of visually impaired tourists, focusing on the challenges they face, their awareness of accessible tourism services, and the role of self-advocacy in improving their travel experiences. Through qualitative interviews with 17 visually impaired adults, the research highlights the importance of knowledge, awareness, and empowerment in enhancing accessibility in the tourism industry. The findings reveal that many visually impaired individuals rely heavily on family members for travel assistance, leading to a lack of awareness about their rights and available technologies. The study emphasizes the need for inclusive design, multi-sensory tourism experiences, and digital accessibility to foster independence and improve the travel experience for visually impaired individuals.

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