• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.2
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• pp.66-76
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• 2011

The Sightseeing ITS is defined as a system that gives tourists and inhabitants the information concerned with road network conditions, parking, sightseeing spots, and travel time in the relevant area. When focusing on tourists' excursion behaviors in sightseeing areas, however, it is sometimes found that they feel much annoyed with insufficient information about the area. While they also have a variety of needs to get information and make a decision about their excursions, it becomes one of important subjects to understand the actual circumstances of their information usage and to identify the causal relationship between their excursion patterns and the obtained information. This paper aims to investigate basic issues toward development of Sightseeing ITS and to modify an analytical model of tourist's excursion behavior considering information usage at Fuji five lakes Area, which is a representative sightseeing place in Japan. The relationship was analyzed using a structural equation model: information usage at the scheduling stage has an impact on tourists' individual cognition of the sightseeing area, tourists' individual cognition affects information usage at the excursion stage, and information usage at the excursion stage affects behavior during excursions. It is found that tourists' decision making behaviors on their excursion tend to depend on the information usage. This implies essential results to construct effective and customer oriented ITS.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.909-916
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• 2006

This study investigates tourists' sightseeing excursion behaviors and their information usage patterns at Fuji five lakes Area. This paper aims to empirically analyze the relationship between a sightseeing excursion behavior and use of tourist information applying a cluster analysis and a quantitative regression model. The main results are summarized as follows: (1) Tourists' information need is high about 90% of all tourists get information, 80% get the information before travel, 70% on the journey, 60% at the same time. (2) The patterns of information usage are categorized into 3 groups by the timing when tourists try to get the information.(3) There exists a difference among the time-spatial characteristics of excursion's behaviors such as the time after arriving time at sightseeing area, the time till go to home, duration time, and the total travel time between spots, the number of spots, and the size of excursion scale. (4) The quantitative regression model shows that information usage which constrained by time and space significantly determines both the number of the sightseeing spots and the duration time.

• Proceedings of the Korea Contents Association Conference
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• 2013.05a
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• pp.253-254
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• 2013

In the preceding studies, an analysis of Saga Prefectural sightseeing information by a self-organizing map (SOM) has been tried. And recent development on information and communication technology (ICT) will help us to access any results via the mobile devices easily. Then, in order to realize this basic idea, development of an application for mobile devices is investigated through some preliminary computer simulations on the standard desktop PC in this article.

• International Journal of Contents
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• v.9 no.3
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• pp.15-18
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• 2013

In the preceding studies, an analysis of Saga Prefectural sightseeing information by a Self-Organizing Map (SOM) has been tried. And recent development on Information and Communication Technology (ICT) will help us to access any results via the mobile devices easily. This is why the mobile devices, e.g., smartphones and tablet computers, have an operating system installed, and we can improve their functions by downloading any applications on the Web. Then, in order to realize this basic idea, development of an application for the mobile devices is investigated through some computer simulations on the standard desktop PC in this paper. As a result, it is found that i) a developed feature map is useful to identify some candidate topics, ii) a touchscreen is suitable to show the feature map, and iii) arrangement of the feature map can be modified based on our interests. Then, it is concluded that the proposed idea seems to be applicable, even though further consideration is required to brush it up.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.149-169
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• 2018

Korea is currently accumulating a large amount of data in public institutions based on the public data open policy and the "Government 3.0". Especially, a lot of data is accumulated in the tourism field. However, the academic discussions utilizing the tourism data are still limited. Moreover, the openness of the data of restaurants, hotels, and online tourism information, and how to use SNS Big Data in tourism are still limited. Therefore, utilization through tourism big data analysis is still low. In this paper, we tried to analyze influencing factors on foreign tourists' satisfaction in Korea through numerical data using data mining technique and R programming technique. In this study, we tried to find ways to revitalize the tourism industry by analyzing about 36,000 big data of the "Survey on the actual situation of foreign tourists from 2013 to 2015" surveyed by the Korea Culture & Tourism Research Institute. To do this, we analyzed the factors that have high influence on the 'Satisfaction', 'Revisit intention', and 'Recommendation' variables of foreign tourists. Furthermore, we analyzed the practical influences of the variables that are mentioned above. As a procedure of this study, we first integrated survey data of foreign tourists conducted by Korea Culture & Tourism Research Institute, which is stored in the tourist information system from 2013 to 2015, and eliminate unnecessary variables that are inconsistent with the research purpose among the integrated data. Some variables were modified to improve the accuracy of the analysis. And we analyzed the factors affecting the dependent variables by using data-mining methods: decision tree(C5.0, CART, CHAID, QUEST), artificial neural network, and logistic regression analysis of SPSS IBM Modeler 16.0. The seven variables that have the greatest effect on each dependent variable were derived. As a result of data analysis, it was found that seven major variables influencing 'overall satisfaction' were sightseeing spot attraction, food satisfaction, accommodation satisfaction, traffic satisfaction, guide service satisfaction, number of visiting places, and country. Variables that had a great influence appeared food satisfaction and sightseeing spot attraction. The seven variables that had the greatest influence on 'revisit intention' were the country, travel motivation, activity, food satisfaction, best activity, guide service satisfaction and sightseeing spot attraction. The most influential variables were food satisfaction and travel motivation for Korean style. Lastly, the seven variables that have the greatest influence on the 'recommendation intention' were the country, sightseeing spot attraction, number of visiting places, food satisfaction, activity, tour guide service satisfaction and cost. And then the variables that had the greatest influence were the country, sightseeing spot attraction, and food satisfaction. In addition, in order to grasp the influence of each independent variables more deeply, we used R programming to identify the influence of independent variables. As a result, it was found that the food satisfaction and sightseeing spot attraction were higher than other variables in overall satisfaction and had a greater effect than other influential variables. Revisit intention had a higher ${\beta}$ value in the travel motive as the purpose of Korean Wave than other variables. It will be necessary to have a policy that will lead to a substantial revisit of tourists by enhancing tourist attractions for the purpose of Korean Wave. Lastly, the recommendation had the same result of satisfaction as the sightseeing spot attraction and food satisfaction have higher ${\beta}$ value than other variables. From this analysis, we found that 'food satisfaction' and 'sightseeing spot attraction' variables were the common factors to influence three dependent variables that are mentioned above('Overall satisfaction', 'Revisit intention' and 'Recommendation'), and that those factors affected the satisfaction of travel in Korea significantly. The purpose of this study is to examine how to activate foreign tourists in Korea through big data analysis. It is expected to be used as basic data for analyzing tourism data and establishing effective tourism policy. It is expected to be used as a material to establish an activation plan that can contribute to tourism development in Korea in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4D
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• pp.339-349
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• 2010

The objective of this paper is to develop a structural equations model system for the purpose of tourists' excursion behaviour analysis with their information usage. A tourist' excursion behavior defined as activities in the sightseeing region between arriving and leaving time includes indexes with respect to activity' time use and the number of spots. Additionally, such indexes can be modeled as endogenous variables in the structural equation model system on the assumption that they are influenced by the degree of familarity on the sightseeing region, the degree of information usage, and individual attributes. The case study application involves excursion behaviour data such as one-day excursion activity and information usage diary that are observed in the Fuji Five Lakes, Japan. Since the models presented in the paper are available to statistically analyze the covariance among the endogenous variables, they have the advantage of effectiveness analysis on information usage in the excursion area, compared to the prior approaches such as discrete choice models.

• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.413-418
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• 2020

The travel pattern of tourists for the development of the tourist course is designed to collect and analyze tourist information based on the big data of the carrier to improve the quality of the tourist course. In particular, the analyzed data is used to derive empirical data that can estimate the effect of tourists' inflow into tourism, and to utilize the information as basic data for the development of the tourist course. In addition, the travel pattern of tourists for the development of regional tourism courses is to collect and analyze information on the route and duration of tourists' travel based on big data collected by telecom operators, credit card companies and other data to improve the quality of tourist course development, and to derive empirical data to estimate the effect of tourist inflow through the analyzed data, based on the characteristics of the tourism course and the data needed for the development of new tourist courses in the future.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.725-732
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• 2016

This study analyzes the number of Jeju-bound tourists according to travellers' purposes. We classify the travellers' purposes into three categories: "Rest and Sightseeing", "Leisure and Sport", and "Conference and Business". To see an impact of MERS outbreak occurred in May 2015 on the number of tourists, we fit seasonal ARIMA-Intervention model to the monthly arrivals data from January 2005 to March 2016. The estimation results show that the number of tourists for "Leisure and Sport" and "Conference and Business" were significantly affected by MERS outbreak whereas arrivals for "Rest and Sightseeing" were little influenced. Using the fitted models, we predict the number of Jeju-bound tourists.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.672-674
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• 2006

Information and communication technology joins in and with development the mobile service pattern which the tourist uses is various and it is changing. Jeiu area is the domestic maximum tourist resort which the annual 5 million visit. The mobile service pattern change from mobile market predition does to be possible. Research analysis against sightseeing industry which is major industry and a mobile service market it led from the research which it sees location base and the mobile fusion technology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.248-254
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• 2011

As the demands of island tourism increasing, the importance of information is considered the key success factor of island tourism. This study suggest the several factors that affecting in island tourism based on the previous studies of tourism research domain. the Important Performance Analysis(IPA) that has much popularity in tourism research is used to evaluate the information characteristic and priority of island tourism in university students of Korea. Based on the result of this study, the information of the natural landscape/scenery and the sightseeing related activity have less priority than the facilities and local foodstuff of the specific island. Considering the aspects and levels of currently serviced island tourism information, differentiated information that including the facilities and local foodstuff of island have reasonable priority for establishing effective and efficient island tourism strategy.