• Journal of Smart Tourism
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• v.3 no.3
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• pp.29-40
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• 2023

This research aims to understand the role of online reviews in the local search context by examining the effects of reviews on the representation of tourism businesses on local search platforms (LSPs). By simulating tourists' local searches for restaurants on three LSPs, namely Google, Bing, and Yelp, this study examines how different ranking results are generated across the platforms and how online reviews contribute to the differences. The findings suggest that online reviews are incorporated into LSPs as ranking factors and, thus, affect tourists' decision-making by influencing the information search results in the local search context. As one of the earliest studies on local search, this study discusses how the existing knowledge about the role of online reviews in tourists' decision-making needs to be reevaluated in mobile and more dynamic environments, and offers practical implications for tourism businesses' search engine marketing.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.37-43
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• 2023

This study concluded that smart glass can combine realistic media and reasonable technologies to compensate for the disappointment of simple one-dimensional board game contents, suggest various games to board game contents that were only possible through advertisements and promotions, and can promote board games, tourism services, and insufficient tourism contents. Content development is highly complete as an educational content in that it can be omitted or repeated by customers, and it is expected to be a board game using interesting smart glasses for the MZ generation.

• 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.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.243-250
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• 2015

Mobile learning content implementing is IT tourism convergence study that IT convergence IT and tourism. Learning to increase the effectiveness of mobile learning content for each learning module, It proposed u-smart tourist information 2.0 systems. Mobile learning content, implementation is u-smart tourist information 2.0 can use the system. Convergence/integration of design patterns and XML is so interesting to students. This is the maximum benefit which is taught classes for each learning module divided into learning the Design Pattern NCS. As a result, the learner. In particular, attendance has come out better the effect of learning and improved. Another advantage is tourism, information content information quality mobile learning content for and construct a tourist information content that you can do in real time. Also, mobile learning content, implementation in the next NCS expected to use a lot of help in learning. This study is the result of increased learning the analysis of the lessons learned. Implement mobile learning content gives fun and interesting to the learner to ten design process using the u-Smart Tourist Information class 2.0.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.4
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• pp.481-488
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• 2020

In recent years, realistic contents technology such as virtual reality, augmented reality, and mixed reality has been spreading in travel and tourism industries, and hence there have been various smart tourism AR, VR contents developed. In the past, people mainly used books and Internet for travel, but the use of VR, AR and MR technologies will be used more for consumption of cultural leisure contents in the future. This study describes the Mixed Reality based Baekje Neungsa Cultural Heritage On-Site Guide System to accelerate smart tourism. In this study, the immersive mixed reality HMD was used to provide visitors with more intuitive and effective information about the historical, cultural and architectural values of Baekje Neungsa through virtual experiences. The cultural heritage on-site guide system module supports various Meta Data services and can be easily used for mixed reality content development by designating Meta Data scripts. This research can make contributions to the development of mixed reality based smart tourism contents.

• 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.

• Journal of Smart Tourism
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• v.1 no.2
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• pp.37-46
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• 2021

The travel-related applications on a smartphone help tourists make a reservation before their trip conveniently; use a map, direction guidance, and translation services during the travel; evaluate and recommend travel services communicating with others after their journey. This study examines the relationships among affordances and constraints provided by the mini-program, users' perceived value, and travel-related mini-program (TRMP) usage by analyzing the structural equation modeling. An online questionnaire was developed from the available scales in the published literature. A total of 651 TRMP users responded to the survey, and 448 valid responses were included for analysis. Affordance, including physical, cognitive, sensory, and functional affordance, significantly influenced the hedonic value of TRMP; utilitarian value except for cognitive affordance. There were negative relationships between unfamiliarity and both types of value. The utilitarian and hedonic value of TRMP significantly influenced both the exploitative and explorative use of TRMP. Travel-related mobile applications are dramatically increased in the tourism field. This research sheds light on TRMP usage, as a new and smart device, from a user's perspective based on the affordance theory. This study represents a valuable direction regarding the emerging travel-related online platforms in tourism.

• Journal of Smart Tourism
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• v.2 no.1
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• pp.21-31
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• 2022

This review paper aims at providing a systematic analysis of articles published in various journals and related to the uses and business applications of big data. The goal is to provide a holistic picture of the place of big data in the tourism industry. The reviewed articles have been selected for the period 2013-2020 and have been classified into 8 broad categories namely business strategy and firm performance; banking and finance; healthcare; hospitality; networks and telecommunications; urbanism and infrastructures; law and legal regulations; and government. While the categories are reflective of components of tourism industries and infrastructures, the meta-analysis is organized around 3 broad themes: preferred research contexts, conceptual developments, and methods used to research big data business applications. Main findings revealed that firm performance and healthcare remain popular contexts of research in the big data realm, but also demonstrated a prominence of qualitative methods over mixed and quantitative methods for the period 2013-2020. Scholars have also investigated topics involving the notions of competitive advantage, supply chain management, smart cities, but also ethics and privacy issues as related to the use of big data.

• Knowledge Management Research
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• v.21 no.4
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• pp.265-285
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• 2020

The inbound tourism market is recognized as a vital sector of the tourism industry today, but it is highly volatile due to each country's economic, social, and cultural variables. The causes of volatility vary according to the inbound country, and we intend to revitalize the stabilized tourism industry by minimizing risks. In this study, the portfolio theory was applied to derive the optimal combination for each country to achieve the minimum risk level's maximum growth rate. The number of inbound travelers and the average expenditure per person was simultaneously applied. As a result of the analysis, the best mix by country based on the number of inbound travelers was the UK, the United States, Germany, China, and Japan. Based on average spending, each country's best combinations were Thailand, Middle East, Singapore, Japan, Russia, Hong Kong, and Germany. It is expected to be able to establish a plan to operate the Korean inbound tourism market strategically.