• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.279-290
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• 2022

The popularization of mobile Internet applications has accelerated the development of smart tourism industry. Based on TAM and VAM theories, this paper studies the influencing factors of tourism App users' willingness to continue using through complex network and data analysis methods. Through the research, it is found that the improvement of service level and design concept of smart tourism application can accelerate the aggregation of complex networks and improve user engagement. At the same time, reasonable price service experience value, convenience service experience value, interactive service experience value, emotional design perception, ease of use design perception, entertainment design perception and other factors can have a direct impact on users' intention to continue to use, and there is a significant correlation. The smart tourism App's convenience and price advantage are the root of its competitiveness. The design concept can affect users' emotional experience and perceptual experience, and help smart tourism App improve users' satisfaction.

• Journal of Korea Entertainment Industry Association
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• v.13 no.3
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• pp.1-12
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• 2019

The 4th industrial revolution has become a topic of 'experiential games' that utilize technologies such as virtual reality, augmented reality, and complex reality, and they are promoting various experiential game contents to attract tourists in the tourism industry have. The trend of tourism is the concept of the healing which aims to enhance the quality of life of the individual in the concept of simple travel, that is, the consumer is not satisfied with the sight, There are many changes in the form of tourism. In this study, domestic and foreign cases that utilized the fun and experience of tourism in the game were examined using case study methods. In domestic case, although service was provided by using smart phone, there is a problem that simple information is provided, mission quest method is not continuously provided, and the story is limited. I tried to find out the solution through this case. Developing and applying various experience contents, utilizing active investment and various stories for continuous service, and utilizing new technology such as virtual reality, it will bring about improvement of domestic tourism industry and satisfaction.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.25 no.1
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• pp.11-22
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• 2017

Aviation/tourism industry has a unique characteristic of high inter-dependance between customer and service-provider. It is the mental condition of service-provider that could influence on the attitude of the service-provider. Thus, it is important to manage the mental condition of the service employees to enhance a company's financial performance. This paper tries to analyze the combined model of both policy acceptance and service profit chain(SPC) models. First, service policy acceptance model tells how the service policy acceptance, which consists of policy compliance, trust, participation and policy failure, would influence on SPC model. According to empirical research, it was found that both the employees' policy compliance and the policy trust have a positive significant impact on their participation on service policy. In the policy acceptance model, the employee's voluntary participation based on their trust and compliance of the policy was proven to have a positive effect on increasing job satisfaction and customer orientation. Regarding SPC model, their participation in the policy had the strongest impact among variables on customer orientation. Such results implies the employees' participation on the policy could become the starting point to enhance the customer value.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.98-108
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• 2022

In this study, social network analysis was performed to compare and analyze changes in domestic tourism trends before and after the outbreak of COVID-19 in a situation where the damage to the tourism industry due to COVID-19 is increasing. Using Textom, a big data analysis service, data were collected using the keywords "travel destination" and "travel trend" based on the collection period of 2019 and 2020, when the epidemic spread to the world and became chaotic. After extracting a total of 80 key words through text mining, centrality was analyzed using NetDraw of Ucinet6, and clustered into 4 groups through CONCOR analysis. Through this, we compared and analyzed changes in domestic tourism trends before and after the outbreak of COVID-19, and it is judged to provide basic data for tourism marketing strategies and tourism product development in the post-COVID-19.

• Journal of Applied Tourism Food and Beverage Management and Research
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• v.14 no.2
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• pp.17-22
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• 2003

Although researchers have, during the past decade, become increasingly interested in customer satisfaction customer reaction, and service quality issues, very little of research has devoted to the family restaurant. Family restaurant industry is among the fastest growing sectors of the tourism market. This paper discusses the importance of the family restaurant product and service quality, and presents the relationship among service quality, customer satisfaction, and customer reaction. The literature supports the value of family restaurant's service quality and relation between service quality and customer reaction. Exploratory study examined customer's satisfaction with service quality components and customer's reaction with satisfaction. The survey was conducted in four phases; service quality, customer reaction(satisfaction, repurchase intention, and word of mouth), restaurant information, general profile of customer. The results of the study show that service quality(product's quality, physical character) provided family restaurant customer with the overall satisfaction, and service quality affected on customer reaction(repurchase intention, positive word of mouth). Also overall satisfaction affected on repurchase intention and positive word of mouth.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.180-184
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• 2024

Since COVID-19, many foreign tourists have visited Korea for medical tourism. When statistical data were checked from 2022, after COVID-19, the number of foreign patients visiting Korea for two years was 24.8 million, an increase of 70.1% from 2020. It was confirmed that it has achieved a 50% level compared to 2019 (Statistics Office, 2023). Therefore, to create a development plan by linking medical tourism and wellness tourism, the purpose of this study is to find the link between medical tourism and wellness tourism as big data and present a development plan. In this research method, medical tourism, and wellness tourism for two years from 2022 to 2023 from the post-COVID period as big data are set as central keywords to compare text data to find common points. When analyzing wellness tourism and medical tourism, it was confirmed that most wellness tourism had a greater frequency than medical tourism. This confirmed that wellness tourism occupies a larger pie than medical tourism. As a result, when checking the word frequency, it was confirmed that wellness tourism and medical tourism share a lot as complex tourism products, and when checking 2-gram, to attract many medical tourists, it is necessary to combine medical tourism clusters and wellness tourism according to each other's characteristics among local governments.

• International Area Studies Review
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• v.14 no.3
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• pp.363-387
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• 2010

This papers studies the causalities and effects on the relationship between inbound tourism(TOU) and the production amount of service industry in China, using the unit root test, the Granger causality test, the cointegration test, and VECM. we take their natural logarithm and define them as TOU and SGDP: these represent the distributed variable based the lagged values of the number of international tourists by continent and real production amount in service industry of China, respectively. The results of empirical study of this papers are as follows: Firstly, in the unit root test, we found that each time series was unstable one that has unit root. This result made me use 1st differenced data for this empirical study. Secondly, in the Granger casuality test, the study results show that there is unilateral casuality relation between DLSGDP-$DLTOU_i$ except DLSGDP-DLTOUL model for the same time, while no casuality relation between DLTOU-DLSGDP for all models of China. Thirdly, there is cointegration relation between all models for the period of 1980-2008.

• Culinary science and hospitality research
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• v.23 no.4
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• pp.22-32
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• 2017

The purpose of this study was to explore awareness of food tourism using big data analysis. For this, this study collected data containing 'food tourism' keywords from google web search, google news, and google scholar during one year from January 1 to December 31, 2016. Data were collected by using SCTM (Smart Crawling & Text Mining), a data collecting and processing program. From those data, degree centrality and eigenvector centrality were analyzed by utilizing packaged NetDraw along with UCINET 6. The result showed that the web visibility of 'core service' and 'social marketing' was high. In addition, the web visibility was also high for destination, such as rural, place, ireland and heritage; 'socioeconomic circumstance' related words, such as economy, region, public, policy, and industry. Convergence of iterated correlations showed 4 clustered named 'core service', 'social marketing', 'destinations' and 'social environment'. It is expected that this diagnosis on food tourism according to changes in international business environment by using these web information will be a foundation of baseline data useful for establishing food tourism marketing strategies.

• International Journal of Advanced Culture Technology
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• v.9 no.2
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• pp.80-85
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• 2021

This study is to analyze the structure of the networks of tourism marketing on Twitter, identifying the most prominent users, the flow of information about tourism marketing, and the interaction between the users posting tweets. This study employs NodeXL pro as a visualization software package for social network analysis. The number of vertices or nodes is 171, and the number of the unique edges or links is 128, but there are 101 edges with duplicates, so the total links are 229, which means that there are fewer Twitter accounts in the social network on tourism marketing, but they have a few close relationships by sharing information. The research can map the social network of communicators of tourism marketing using Twitter data. The network has a complicated pattern, including one independent network and some connected networks. Some mediators connect each network and can control the information flow of tourism marketing. More communicators are getting the information than the ones providing it, which means that there is likely to be the dependence of information among communicators that can cause an obstacle and distortion of the information flow system, especially in the independent network.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.579-586
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• 2021

This study examines the application of big data and tasks of tourism based on the case of Jeju Special Self-Governing Province, which used big data for regional tourism policy. Through the use of big data, it is possible to understand rapidly changing tourism trends and trends in the tourism industry in a timely and detailed manner. and also could be used to elaborate existing tourism statistics. In addition, beyond the level of big data analysis to understand tourism phenomena, its scope has expanded to provide a platform for providing real-time customized services. This was made possible by the cooperative governance of industry, government, and academia for data building, analysis, infrastructure, and utilization. As a task, the limitation of budget dependence and institutional problems such as the infrastructure for building personal-level data for personalized services, which are the ultimate goal of smart tourism, and the Personal Information Protection Act remain. In addition, expertise and technical limitations for data analysis and data linkage remain.