• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.12-28
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• 2024

This study aims to identify the trend of changes in tourist floating population before and after COVID-19 in major tourist destinations in Jeju Island through spatial analysis. Seongsan-eup and Andeok-myeon in Jeju Island were selected as the research area, and the research period was set at 1 year before and 2 years after the COVID-19 outbreak. For the analysis, mobile floating population data was refined and processed to calculate floating population distribution and floating population increase/decrease data. This was converted into spatial data and an overlay analysis was performed with location data of major tourist attractions. As a result of the analysis, it was confirmed that the floating population of indoor tourist attractions and small facilities decreased immediately after COVID-19, and that in open coastal areas or large facilities, the floating population decreased less or actually increased. In conclusion, in tourism development, it is necessary to identify changes in floating population according to the characteristics of tourist facilities, and it is necessary to develop tourism facilities and strategies that can respond to risk situations such as pandemics when developing tourist destinations.

• Journal of the Korean Society of Clothing and Textiles
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• v.25 no.2
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• pp.303-314
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• 2001

The purposes of this study were 1) to identify different sub-segments of tourism market in Cheju island based on fashion image of clothing souvenir and 2) to provide manufactures with useful information for developing cultural fashion goods related to Cheju island. The data were collected via a self-administered questionnaire from 192 female tourist(20-59 years old) in Cheju and analyzed by factor analysis, cluster analysis, one-way ANOVA and $\chi$$^2$-test. Six factors of fashion image were found image were found and labeled as: Sexy/feminine, wild/mannish, easy/simple, Cheju, ecology, natural image. Four factors of benefit sought were also identified: Practicality/economic-value, fashionability/preference of design, reputation and souvenir-value. Three groups were identified based on fashion image sought: Image of primitive nature(G1: 37.7%), image of nature in the city(G2: 20.1%), sexy/feminine image(G3: 42.2%). There were significant differences among sub-groups in age, fashion innovation, benefit sought and intention of buying Gal-ot. Younger females(20-30 ages) were included more in group 1 than group 2 while older females(40-50 ages) were included more in group 2. Group 1 had a higher score of fashion innovation comparing group 3. Group 1 had the highest scores on practicality/economic-value and souvenir-value. However, group 2 placed the highest importance on reputation as well as practicality/economic-value and group 3 had the lowest scores on all types of benefit. Group 1 and group 2 had intention of buying Gal-ot more than group 1. Based on the results of this study, manufactures may implement target marketing strategies on group 1 which sought the image of primitive nature and group 2 which sought the image of nature in the city.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.271-280
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• 2017

Small islands in humid and hot climates have received less attention development due to lack of resources and difficulties for in-situ construction. This paper addresses this problem by presenting a modular system for sustainable construction of a resort hotel in accordance with the international tourism standards, in addition to, minimizing undesirable effects on nature. This has been achieved by review of literature in the scope of off-site construction and identification of the natural geographical features of Herndurabi Island. According to the information acquired, a feasibility study and design practice have been conducted to achieve a reasonable solution to equip Hendurabi Island as a sample with a self-sufficient prefabricate resort hotel. Findings indicate that the volumetric prefabricated modules would be a solution to devising a framework for design and construction in remote regions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.97-104
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• 2008

Recently the navigation service and LBS (Location based Services) using map supports much information services on mobile terminal. Also Internet Web sites support user much information. But, the user has the difficulty for acquiring the service and the various information based on map because of searching the many Internet sites. Accordingly, this paper supports a convergence information service model of various culture, education, tourism, sport and traffic for accessing synthesizing information based on map. And we design and implement this model using 공개 API. We present a convergence information service model of culture, tourism, sport and bus line information form tour destination and cultural place of Jeju province using the model. Additionally, we develop this service model using apache web server on Linux environment, PHP and JavaScript, MySQL database and Map 공개 API. As this service model supports a convenience action of culture and tourism for Jeju islanders and tourists.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.463-466
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• 2007

In this study, 3D building reconstruction and road design were performed using LiDAR data, digital map and airborne digital image. Information for tourism was extracted from digital maps (scale: 1/5,000) of Jeju Island, and then route of the road was determined for road design. Reconstructed buildings, aerial image and designed road were overlayed with tourism information for 3D simulation. In addition, landscape analysis was performed and result of the road design was visualized.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.328-338
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• 2022

This study aims to identify the influential relationship between the characteristics of tourism information of the MZ generation's SNS content, tourist destination reputation, and intentions of traveling behavior with a focus on Jeju Province. To achieve the purpose of this research, this study was conducted on 270 tourists who had recently traveled to Jeju Island after being exposed to characteristic tourism information on SNS within the last year among the MZ generation through a commissioned survey company. A total of 270 results were collected and used for empirical analysis. The results of the research are as follows. First, it was found that the reliability, usefulness, timeliness, and interactivity factors of SNS tourism information had a significantly positive (+) effect on the reputation of the tourist destination. Second, it was found that the reliability, usefulness, timeliness, and interactivity factors of SNS tourism information had a significantly positive (+) effect on the intentions of traveling behavior. Third, it was found that the tourist destination reputation has a positive (+) effect on the intentions of traveling behavior. This study discussed the future tourist destination reputation formation and future behavioral decision process of the MZ generation tourists who are constantly seeking tourist destinations. In addition, the theoretical implications presented in this study were discussed.

• International Journal of Advanced Culture Technology
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• v.11 no.3
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• pp.327-331
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• 2023

This paper proposes a tourist destination recommendation application that combines a chatbot and a recommendation system. The data to be entered into the chatbot was through big data on social media. Through TEXTOM, a total of 22,701 data were collected over a one-year period from January 2022 to January 2023. Non-terms that interfere with analysis were removed through the data purification process. Using refined data, network visualization and CONCOR analysis were used to identify the information users want to obtain about travel to Jeju Island, and categories for each cluster were organized. The content was intuitively organized so that even those who approached it for the first time could easily use it, reducing the difficulty of operating the application. In this paper, users can select their own preferences and receive information. In addition, a tool called a chatbot allows users to focus more on the process of acquiring information by gaining a sense of reality while operating the application. This suggests an application that can reach the purpose of the curator by affecting the user's desire to visit tourist attractions.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.19-30
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• 2018

The main purposes of this study are to analyze the contents and text network of online tourism information. For this purpose, Jeju Island, one of the representative tourist destinations in South Korea is selected as a study site. And this study collects the contents of both JeJu official tourism website and Sina Weibo's personal blogs which is one of the most popular Social Network Systems in China. In addition, this study analyzes this online text information using ROST Content Mining System, one of the Chinese big data mining systems. The results of the content analysis show that the formal website of Jeju includes the nouns related to natural, geographical and physical resources, verbs related to existence of resources, and adjectives related to the beauty, cleanness and convenience of resources mainly. Meanwhile, personal blogs include the nouns of Korean-wave, food, local products, other destinations and shopping, verbs related to activity and feeling in Jeju, and adjectives related to their experiences and feeling mainly. Finally, the results of text network show that there are some strong centrality and network of online tourism information at formal website, but there are weak relationships in personal blogs. The results of this study may be able to contribute to the development of demand-based marketing strategies of tourists destination.

• Knowledge Management Research
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• v.23 no.2
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• pp.277-299
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• 2022

The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.185-205
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• 2023

As the tourism industry recovers post the COVID-19 pandemic, an increasing number of tourists are utilizing various platforms to leave reviews. However, amidst the vast amount of data, finding useful information remains challenging, often leading to time and cost inefficiencies in selecting travel destinations. Despite ongoing research, there are limitations due to the absence of ratings or the presence of different rating formats across platforms. Moreover, inconsistencies between ratings and the content of reviews pose challenges in developing recommendation models. To address these issues, this study utilized 7,104 reviews of tourist spots in Jeju Island to develop a specialized satisfaction index for Jeju tourist attractions and employed this index to construct a 'Rating Prediction Model.' To validate the model's performance, we predicted the ratings of 700 experimental data points using both the developed model and an LSTM approach. The proposed model demonstrated superior performance with a weighted accuracy of 73.87%, which is approximately 4.67% higher than that of the LSTM. The results of this study are expected to resolve the discrepancies between ratings and review contents, standardize ratings in reviews without ratings or in various formats, and provide reliable rating indicators applicable across all areas of travel in different domains.