• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.119-125
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• 2019

The purpose of this study is to find out the relevant factors of the choice tendency of tourism users to Intelligent Tourism platform through big data analysis, which will help enterprises to make accurate positioning and improvement according to user information feedback in the tourism market in the future, so as to gain the favor of users' choice and achieve long-term market competitiveness. This study takes the Intelligent Tourism platform as the independent variable and the user choice tendency as the dependent variable, and explores the related factors between the Intelligent Tourism platform and the user choice tendency. This study make use of text mining and R language text analysis, and uses SPSS and AMOS statistical analysis tools to carry out empirical analysis. According to the analysis results, the conclusions are as follows: service quality has a significant positive correlation with user choice tendency; service quality has a significant positive correlation with tourism trust; Tourism Trust has a significant positive correlation with user choice tendency; service quality has a significant positive correlation with user experience; user experience has a significant positive correlation with user choice tendency Positive correlation effect.

• Journal of the Korean Society for Railway
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• v.10 no.3 s.40
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• pp.350-354
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• 2007

Intelligent agent is to decide what customers need on the internet and offer them accurate information. In this paper, the system which can recommend the tourism items in terms of customer‘s needs is proposed by appling the intelligent agent to railway tourism system. Most of previous agents are focused on price. But, this study proposes the Railway tourism system which offers each customer the best suitable information based on quality of information and reputation. The customer's needs are analyzed through intelligent agent and the information which is suitable for customer's needs is obtained the Artificial Neural Network Model.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.1948-1953
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• 2007

Intelligent agent is to decide what customers need on the internet and offer them accurate information. In this paper, the system which can recommend the tourism items in terms of customer's needs is proposed by appling the intelligent agent to railway tourism system. Most of previous agents are focused on price. But, this study proposes the Railway tourism system which offers each customer the best suitable information based on quality of information and reputation. The customer's needs are analyzed through intelligent agent and the information which is suitable for customer's needs is obtained the Artificial Neural Network Model.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.304-311
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• 2011

Recently, tourism is one of future promising industries having high developing possibilities, so many countries have developed tour resources and tried to attract foreign tourists using the resources. Many researches and attempts have tried to apply for tourism using various technologies such as GPS and RFID. However, the applying areas have been highly restricted to the technology providing contents on the spot for independent tourists. Therefore, this paper designed and implemented "Intelligent Tour Guide System (ITGS)" using GPS and ZigBee. The ITGS is for group tourists, and provides various functions for enjoying their tours in limited schedules.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.3
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• pp.75-89
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• 2020

This study was conducted to investigate researches related to tourism transport conducted in Korea and to discover new complementary research projects based on this. Forty cases were reflected in the study, including 28 academic papers and 12 policy studies. Based on the characteristics of tourism transport and cases of prior research, this study divided the field of tourism transport research into three ranges: traffic mode choice for tourism, information for tourist traffic and support policy for tourist traffic etc. In particular, mode choice for tourist traffic was divided into four sub-ranges, reflecting the importance of tourist traffic and the weight of research cases. As a result of the study, it was found that there were not many cases of research on tourism transport, and the research cases were concentrated on the mode choice for tourist traffic. To complement this, this study proposed 10 new research projects in 3 ranges. This is a result of reflecting changes in tourist demand and tourism trends. In addition, a new research field was proposed to seek the connection between transport facilities supply and tourist demand.

• Information Systems Review
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• v.16 no.3
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• pp.69-87
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• 2014

The integration of Tourism and Information Communication Technology (ICT) has been continued based on a drastic progress of ICT in the entire sectors of tourism industry. A variety of terminologies such as eTourism, Virtual Tourism, Smart Tourism have appeared during the last decades, however, tourism with Smartphones created a new paradigm has not discussed yet in tourism industry and academia. By investigating on the previous literature in the role of ICT in tourism, we have classified five major streams in the past such as end user perspective (tourist behaviour), Community, Multimedia and Web, Intelligent System, and Smart Tourism. At a result, we investigated the concept of smart tourism and extended to research on Smart Tourism Ecosystems. We suggest the concept of smart tourism ecosystems, which may create values by interacting among tourism players (tourist, distribution channel, supply channel, government, and local community). We propose the discussion of meaning of 'creating shared value' through 'Smart Tourism Ecosystems'.

• Journal of the Korea Society of Computer and Information
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• v.7 no.1
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• pp.161-173
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• 2002

The increasing disposable time through advancing information has come to make the tourism industry as well as the information communication industry glow in the 21st century We cannot make rational decision without proper guide information. It is impossible to anticipate tourism Products which are invisible products consisting of a variety of basic combinations of products. Tourists are getting dissatisfied with tourism experts' distorted guidance every year. A recent survey shows that the current tourism information system can't meet the need of tourists who are informative and individualized. This paper presents tourism information system that offers the most appropriate tour courses depending on the tastes of tourists by utilizing expert system, artificial intelligent applied technology. This paper is the first attempt to maximize comsumer satisfaction by developing the intelligent agent system that is able to reflect the traits of individualized customers' in the tourism industry The establishment of this system will contribute to activating the tourism industry, ultimately, by decreasing inconveniencies and tour schedules appropriate to the purpose of individual tours.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.55-64
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• 2011

This study aims to analyze of the impact of converged information with tourism and Bus Information on recreational bus travel. The research has conducted as the following process : A survey was implemented that the user preference behavior as if they were provided a converged information with tourism and bus information on bus usage. As a result, we found that able to using mobile media, having a experience visiting the tourism site, evaluate willingness to pay of the information highly, the 20s age, increasing income variables are concerned with positive relation, and the factors which are using the main mode by auto and having a auto are negative relation on bus usage actively.

• The Journal of Fisheries Business Administration
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• v.35 no.1
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• pp.57-85
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• 2004

To develop an blue tourism website(BTW) for electronic commerce(EC), information requirements of BTW are defined firstly. We defined information requirements of BTW from two aspects, i.e., front office and back office. Information requirements for front office were derived by consumer purchasing decision process. And information requirements for back office were derived by tourism value chain. Total 29 functions are identified as critical EC related functions of BTW. Among them, 25 functions were investigated into BTW. BTWs were searched by search engines - Yahoo and Empas - to Korean websites. There are 12 specialized BTWs, except one cyber museum website. For 12 websites, 25 functions were probed. By the results, in need recognition stage of blue tourism, only weather information was provided in most websites. In information search stage of blue tourism, package recommendation and various contents were provided in most websites. In consumption stage of blue tourism, traffic information were provided in most websites. And in after - sales service stage of blue tourism, bulletin board function was implemented in most websites. The rest of the functions were scarcely implemented. On the whole, it was concluded that most EC related functions of BTW in Korea were not implemented properly. To improve the status quo, it is expected in the dimension of individual website, that marketing planning, customized service, intelligent service, reinforcing purchasing assistance functions, customer relationship management, and escrow service etc. need to be implemented. And it is expected in the dimension of blue tourism industry, that standardizing product catalog, security assistance policy, information sharing by industrial database, finding referral model of BTW, elevating information mind, revising related laws etc. are needed.

• Journal of the Korean Applied Science and Technology
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• v.37 no.3
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• pp.473-483
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• 2020

This paper proposes a tourism recommendation system in intelligent cloud environment using information of tourist behavior applied with perceived value. This proposed system applied tourist information and empirical analysis information that reflected the perceptual value of tourists in their behavior to the tourism recommendation system using wide and deep learning technology. This proposal system was applied to the tourism recommendation system by collecting and analyzing various tourist information that can be collected and analyzing the values that tourists were usually aware of and the intentions of people's behavior. It provides empirical information by analyzing and mapping the association of tourism information, perceived value and behavior to tourism platforms in various fields that have been used. In addition, the tourism recommendation system using wide and deep learning technology, which can achieve both memorization and generalization in one model by learning linear model components and neural only components together, and the method of pipeline operation was presented. As a result of applying wide and deep learning model, the recommendation system presented in this paper showed that the app subscription rate on the visiting page of the tourism-related app store increased by 3.9% compared to the control group, and the other 1% group applied a model using only the same variables and only the deep side of the neural network structure, resulting in a 1% increase in subscription rate compared to the model using only the deep side. In addition, by measuring the area (AUC) below the receiver operating characteristic curve for the dataset, offline AUC was also derived that the wide-and-deep learning model was somewhat higher, but more influential in online traffic.