• Journal of Smart Tourism
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• v.2 no.3
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• pp.17-30
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• 2022

The tourism sector of the Maldives has seen rapid growth since its inception in 1972. One significant development is the transformation of the market composition in recent years. China has surpassed traditional European markets as the single largest source market. In this regard, this study seeks to assess the seasonality in the Maldivian tourism sector using a monthly dataset of visitor arrivals from 2003 to 2019. The seasonality ratio, the seasonality indicator, the Gini coefficient and the seasonal index were used to examine the seasonality patterns. The results of this study show that there are three distinct peaks (January to April, August, and November to December) and two off-peaks (May to July and September) periods. The findings also reveal that the rise of the Chinese market has significantly lessened the seasonality of Maldivian inbound tourism. Finally, some important implications are discussed.

• The Journal of Information Systems
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• v.28 no.4
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• pp.49-64
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• 2019

Purpose The purpose of this paper is to observe the relative priorities of importances among IT services for Smart tourism as well as the relative priorities of importances among ways for developing the IT Services. Design/methodology/approach AHP analysis model was designed with 3 layers in order to recognize the relative importances priorities of IT services and the ways developing the IT services in Smart tourism. The factors in the top layer consist of Pre-trip IT services, During-trip IT services and Post-trip IT services. The lower factors in second layer of the Pre-trip IT services consists of Tourism information search, Online reservation and Price comparison. The lower factors of the During-trip IT services consists of Context recognition, Virtual Reality and Drone Application. The lower factors of the Post-trip IT services consists of Interactive Sharing and Tagging. The factor of third layer, the ways of developing the IT services consist of Company leading, University leading and Industry-University Collaboration. The structural questionnaire based on the AHP analysis model was designed and used to survey experts in IT and tourism areas. The collected data by the question investigation was analyzed by AHP analysis technique. Findings The importance priority of During-trip IT service was highest among in the three type IT services of tourism life cycle. The importance priority of Price comparison service was highest among IT services for Pre-trip. The importance priority of the Context recognition service was highest among IT services for During-trip. The Interactive sharing service was highest among IT services for Post-trip. It would be confirmed for the IT service development ways of Company leading to be suitable for most of the It services, such as Tourism information search, Online reservation, Price comparison, Context recognition, Virtual reality, Drone application, Interactive sharing.

• Asia pacific journal of information systems
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• v.29 no.3
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• pp.448-467
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• 2019

In a new age of smart tourism, free independent travelers (FITs) choose their travel routes in a more diversified and less predictable way with the aid of smart services. This paper focuses on the movements of Chinese outbound FITs in the U.S. in the year of 2018. 110 places to visit (destinations) extracted from 122 travel routes recommendations on Qyer.com, a major online travel community in China, are analyzed with social network analysis (SNA). Based on the results of SNA, employing degree centrality, eigenvector centrality, betweenness centrality, network visualization, and cluster diagram methods, some preferred cities and natural attractions outside city centers (i.e., New York City (NYC), Los Angeles, San Francisco, Washington D.C., and Niagara Falls) are identified. Moreover, it is found that NYC in the East and Los Angeles in the West play a major role in the movements of Chinese FITs. This study contributes to the body of knowledge on tourist destination movements and provides valuable implications for smart service development in the tourism and hospitality industry.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.31-36
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• 2018

The tourism industry has a great influence on national economy activation. The development of IT technology has enabled the collection and analysis of personal profile information, location information and activity information based on the characteristics, behavior, purchase propensity and interest of tourists. In order to realize this, the implementation of convergence smart tourism information service platform is completed by developing business model, IoT & Big Data integration management system, big data algorithm development and analysis platform in three stages. The underlying technology of the platform and algorithm needs a process of adopting open source, expanding the service element on the basis of it, and then complementing the problem through the test-bed demonstration test that connects the area. Using this platform, it is possible to develop a smart tourism environment that can provide customized services for each tourist by analyzing various information in an integrated manner. Also, it will be possible to improve the life of tourist destination residents and contribute to regional revitalization and job creation through the creation of smart tourism ecosystem focused on the region.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.61-68
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• 2021

The development of the fourth industry has enabled users to quickly share a lot of data online. We can analyze big data on information about tourist attractions and users' experiences and opinions using artificial intelligence. It can also analyze the association between characteristics of users and types of tourism. This paper analyzes individual characteristics, recommends customized tourist sites and proposes a system to provide the sacred texts of recommended tourist sites as AR services. The system uses machine learning to analyze the relationship between personality type and tourism type preference. Based on this, it recommends tourist attractions according to the gender and personality types of users. When the user finishes selecting a tourist destination from the recommendation list, it visualizes the information of the selected tourist destination with AR.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.115-123
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• 2021

The primary purpose of the study is to investigate museum visitors' intention to use of smart tourism contents by applying the extended technology acceptance model. The study conducted an online survey of a convenience sampling of individuals who visited the National Museum of Korea, and it conducted confirmatory factor analysis and structural equation modelling to test hypotheses of the study. The results showed that information quality of immersive digital gallery in the National Museum of Korea had a significant regression weight on both perceived ease of use and perceived usefulness, and perceived ease of use had a significant regression weight on perceived usefulness. Moreover, both perceived ease of use and perceived usefulness had a significant regression weight on intention to use. The findings indicate that it is necessary to develop smart tourism contents with easily accessible and usable digital applications for promoting smart tourism in the museum.

• Smart Media Journal
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• v.12 no.8
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• pp.18-25
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• 2023

The COVID-19 outbreak in 2020 caused continuous damage worldwode, especially the smart tourism industry was hit directly by the blockade of sky roads and restriction of going out. At a time when overseas travel and domestic travel have decreased significantly, the number of tourist hotels that are colsed and closed due to the continued deficit is increasing. Therefore, in this study, licensing data from the Ministry of Public Administraion and Security were collected and visualized to understand the operation status of the tourism and lodging industry. The machine learning classification algorithm was applied to implement the business status prediction model of the tourist hotel, the performance of the prediction model was optimized using the ensemble algorithm, and the performance of the model was evaluated through 5-Fold cross-validation. It was predicted that the survival rate of tourist hotels would decrease somewhat, but the actual survival rate was analyzed to be no different from before COVID-19. Through the prediction of the business status of the hotel industry in this paper, it can be used as a basis for grasping the operability and development trends of the entire tourism and lodging industry.

• Smart Media Journal
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• v.12 no.8
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• pp.9-17
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• 2023

The development of information and communication technology and the improvement of the development and dissemination of smart devices have caused changes in the form of tourism, and the concept of smart tourism has since emerged. In this regard, researches related to smart tourism has been conducted in various fields such as policy implementation and surveys, but there is a lack of research on application reviews. This study collects Trip Advisor application review data in the Google Play Store to identify usage of the application and user satisfaction through Latent Dirichlet Allocation (LDA) topic modeling. The analysis results in four topics, two of which are positive and the other two are negative. We found that users were satisfied with the application's recommendation system, but were dissatisfied when the filters they set during search were not applied or that reviews were not published after updates of the application. We suggest more categories can be added to the application to provide users with different experiences. In addition, it is expected that user satisfaction can be improved by identifying problems within the application, including the filter function, and checking the application environment and resolving the error occurring during the application usage.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.254-255
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• 2018

본 연구는 이러한 4차 산업혁명과 연계된 스마트관광도시를 육성하는데 있어 무엇이 필요하며 추후 나아가야할 방향에 대해 알아보고자 한다. 특히 최근 관광상품을 이용하는 고객들의 다양한 니즈(needs)를 파악하기 위해서는 빅데이터 기술과 호텔 및 관광관련 제품구매 등 지불과 관련 핀테크 기술 마지막으로 관광산업에 속한 기업들 서로가 데이터를 연결 및 공유할 수 있는 초연결 기술과 데이터 중심 관광도시 등 다양한 부분에 걸쳐 알아보고자 한다.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.3
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• pp.98-103
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• 2018

Globally, medical tourism draws attention as a national growth engine industry, and is actively expanding. Current medical tourism leans towards large hospitals making it difficult to attract new users. Users collect the information for medical tourism through various paths in order to receive medical consultations and customized tour services. To expand medical tourism to small and medium sized hospitals, it is necessary to have customized medical consultations, tours and interpreter services, which are the key elements of medical tourism. This paper suggests services that users can use to match medical consultations and find tours and interpreters they want at the same time. This paper suggests ways to provide integrated services based on the information experienced by users, combining the required items from the perspectives of each user, hospital and guide. To match the content provided by hospitals and guides with experience information from users systematically, this study suggests the convergence plan for a service model that can match the experience information between users and hospitals, between users and guides and between hospitals and guides systematically by operating the data in the universal container.