Japan’s tourism industry has been severely affected by the COVID-19 pandemic and disasters such as earthquakes. Maintaining sustainable tourism management is required even under these circumstances. In addition, the decline in the number of people working in the tourism industry due to the declining birthrate is an issue that must be resolved. One of the possible solutions to these issues is to promote local and neighboring tourism (micro-tourism), and cultivate the local respect and increase the tourist population of the area. However, it is difficult to arouse and maintain motivation and desire to return due to novelty and surprise, when it comes to sightseeing in the local area or neighboring areas. Therefore, this study focused on the design method of gamification and developed a tourism application that can increase tourism satisfaction and the desire to revisit even familiar local tourist destinations. In the development, one of Ishikawa Prefecture’s representative tourist spots (Kenrokuen garden) was targeted. The garden is located in the center of Kanazawa city. The application name is ‘Mawari-michi Kenrokuen.’ This paper reports on the results of its design, development, and operation verification. In this study, the verification experiment of the application using students living near Kanazawa as subjects was conducted. As results, the following effects were obtained by using this application, namely increased tourism satisfaction and increased desire to revisit tourist spots that had not been visited.

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When local governments engage in tourism promotion, they can benefit from increasing open image data. However, they face difficulties in searching for appropriate images from a large number of directories and images. This study aims to solve this issue by developing and introducing an application that facilitates the search of potential candidates for open image data. First, to display images in order of attractiveness, we developed a model to assess the attractiveness of images and assigned attractiveness scores to all images of a local government. Second, to support keyword searches with common nouns, descriptions were added to them using an existing generative model. Third, to display a list of similar images, we grouped them based on the cosine similarity of their vector representations. Then, an application was developed that could reference these metadata. This application was introduced into the actual workflows in Hida City. where it received high ratings in a user survey. This application enables public officers to search for attractive images more efficiently and comprehensively. Meanwhile, through this introductory experiment, we have found that some local governments are interested in releasing thousands of open image data. Therefore, it is considered essential to develop an integrated method.

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In recent years, the role of civic pride and aesthetic experiences in fostering sustainable regional development has become a focus of research, particularly in communities facing economic and social challenges. This study examines how residents’ daily aesthetic experiences impact their sense of civic pride to support effective regional revitalization strategies. Focusing on Xiuwu County in China and Chishang Township in Taiwan—two regions with shared cultural roots but distinct administrative histories. This research uses questionnaire surveys as the primary method to analyze the influence of aesthetic experiences on civic pride. Factor analysis identified “community involvement” and “regional identity” as essential factors of civic pride in both areas, though the factors shaping aesthetic experiences differed; Xiuwu’s civic pride is strongly linked to natural landscapes and local customs, while Chishang’s is closely associated with local identity and self-expression. Regression analysis further proves a significant contribution of daily aesthetic experiences to civic pride, underscoring the importance of incorporating residents’ aesthetic engagement in regional revitalization policies. These findings suggest that aligning policy with residents’ aesthetic values and local identity can foster community engagement and strengthen sustainable development, offering valuable guidance for creating culturally resonant, community-focused strategies.

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This study analyzes tourist behavior during the recovery process of tourism demand following the COVID-19 pandemic. The survey was conducted from April 2020 to October 2023, encompassing tourist destinations and business areas in the Kansai region of Japan. The research sites included the following locations: Kyoto Station, Osaka Station, Shinkyogoku, Kiyomizu Temple, Kinkakuji Temple, Arashiyama, Byodoin, and Todaiji Temple. This study examined mobile phone network statistical population data to deduce the number of visitors at specific tourist destinations and examine their characteristics. Despite the pandemic, the declining tourist population quickly recovered in October 2020 in business and commerce areas. However, the recovery in dedicated tourist areas proceeded more gradually. Regarding visitors’ place of residence, the population at Kyoto Station and Osaka Station in 2020 exhibited a notably reduced proportion of visitors from distant regions. In 2021, a higher proportion of visitors originated from closer geographical proximities, likely as a strategic measure to minimize potential COVID-19 transmission risks.

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In Japan, young people tend to move to urban areas in search of jobs as the declining birthrate and aging population progresses. As a result, the aging of the population in rural areas is progressing and it is difficult to maintain the communities. In order to break this situation, appropriate measures are needed. It is important that young people stay in a rural area. They are the next generation. It is very difficult to derive fundamental measures to stop the declining trend of Japan’s total fertility rate. However, it would be possible to keep the rate of decline low. If some measures are not taken immediately to stop the outflow of young people to urban areas, many rural areas may rapidly disappear. This trend is an issue that is also consistent with other countries, and it is desirable to develop measures as a model for the world. The Population Strategy Council announced “744 municipalities having the risk of disappearing.” Several local governments (rural areas) in Hokuriku are included in this category. The governments that are far from the prefectural capital tend to fall into this category and many social infrastructures tend to be concentrated near prefectural capitals. In this paper, an increase of a “connected population” (Kankei Jinkou in Japanese) is proposed as one of the measures to avoid becoming a disappearing local government. The possibility of regional revitalization is created due to the measure. It can be also expected to ease the population decline rate to some extent. This is consistent with Goal 11 of the SDGs (Sustainable Cities and Communities). Nanto City, Toyama Prefecture, which was listed as municipalities having the risk of disappearing, is selected as the research area.

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Global tourism has recently gained momentum alongside the expansion of the global economy. Japan is increasingly focusing on tourism as a valuable boost to its economy. This study investigates the trends of outbound tourists to gain insight into inbound tourism. We selected passport statistics as a novel data source for inclusion in our analytical model. Logarithmic multiple regression analysis was conducted using the number of Japanese nationals departing Japan and the number of newly issued general passports as the objective variables. We included the size of the working-age population and the exchange rate, or the working-age population and the productivity index, as parameters, respectively. In both cases, the logarithmic model displayed a good fit. We demonstrate the effectiveness of introducing a previously unexplored ‘passport’ factor into models when forecasting international tourist numbers.

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This study discusses the relationship between market growth and the tourism boom that occurred in island regions from 1970 to the 80s, the economic growth period in Japan. The Izu Islands and Okinawa were selected as the target areas for this study because they became well-known tourist destinations during this period. Monthly data were used to construct a regression model addressing the relationship between market expansion and tourism demand. In general, time-series models, such as monthly data estimated by ordinary least squares, could lead to errors due to serial correlation. Hence, this study used Cochrane-Orcutt estimation to overcome this issue. The empirical results show that the domestic market has a positive effect on tourism demand in Okinawa, whereas it has a negative impact on the Izu Islands. Based on the results, peripheral areas, such as island regions, may be spotlighted as tourism destinations along with domestic economic growth. However, the demand for tourism has not developed domestic tourism destinations. Overall, this study concludes that the influence of investment by the private sector likely causes contradictory results between regions.

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Indonesia’s tourism industry plays an important role in the economy, supported by natural and cultural beauty. VR technology transforms interaction by offering an immersive experience for potential tourists, becoming an effective promotional tool to attract visitors. Taman Apung Mas Kemambang Tourism in Purwokerto has adopted VR as a marketing strategy to introduce the beauty of the tourist attraction. This study aims to evaluate the impact of the use of VR technology on tourist visit plans to Taman Apung Mas Kemambang, using logistic regression to analyse the relationship between VR user experience and other factors that influence visit decisions. The results of this study show that descriptive analysis and logistic regression provide significant insights into the factors that affect the interest of visitors to visit Taman Apung Mas Kemambang Tourism. The logistic regression model used has a very high degree of fit, with a Pseudo R-squared value of 1,000 and a low log-likelihood value, despite the risk of overfitting. Variables such as gender, age, frequency of use, probability of visiting, and friend recommendations proved to have a significant effect, where friend recommendations had the highest coefficient. The model also showed 100 % accuracy in classifying visitor interest after a VR experience, confirming the potential of VR technology as an effective tool in improving tourist interest and visit decisions.

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