• Journal of Digital Convergence
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• v.15 no.10
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• pp.173-182
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• 2017

On the tourism purchasing stage, this study is focused on analyzing the relationship among tourism omnichannel selecting factor, satisfaction and purchasing intention considering the moderator effects of tourism experience and perceived risk. Based upon antecedent studies and literature about tourism omnichannel, We presented the study model and hypotheses. For the accurate analysis, we did field survey with 400 respondents. The results are as follows. First, the positive relationship are found between channel selecting factors during purchasing and tourism omnichannel satisfaction. Secondly there is a positive relationship between tourism omni-channel satisfaction and tourism purchasing intention. Thirdly tourism experience is proved as a positive moderating effect between channel selecting factors during purchasing and tourism omni-channel satisfaction. But the moderating effect of perceived risk is negative between them.

• Smart Media Journal
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• v.4 no.4
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• pp.93-100
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• 2015

Markets of e-book and app book in Korea see novel as genre literature and webtoon account for 80 percents in sales so that market share is too based towards some specific fields. In readiblily and easy-to-buy convenience, different from paper books mostly sold off-line, app books are more advantageous but it works as a weak point to take long to publicly spread them before they are generally accepted. Meanwhile, the sales of the e-book market in Korea has been steeply risen. Further, the market is not only restricted to genre literature but also has come into the stage that various experimental challenges are issued in the field of publication contents. This study is aimed at developing the sightseeing app book as a future web-mobile platform with planning and develping the first app book dealing with localized contents based on Busan tour contents, making up for its defect that it offers only current simple information and then suggesting a strategy that the travelers' app book should be available for constant utilization connected to purchase by charged download.

• Journal of Digital Convergence
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• v.16 no.4
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• pp.107-116
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• 2018

Information is very important for modern consumers, and the factors that have a great influence on product purchasing. Accordingly, elucidating factors affecting the retrieval process of information is an important. This study identifies factors that affect tourism information retrieval activities. First, it was carried out the meta analysis of tourism information, repurchase intention, attitude toward technology, and information utilization. Through the meta analysis, hypothesis model about each factor of information retrieval and repurchase of tourism products was suggested. The hypothesis model was verified by a survey of Korean and Japanese tourists. As a result, it is confirmed the relationship between the above factors. The results of this study are expected to contribute to the development of a tourists' information usage model in the future.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.31-36
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• 2018

The tourism industry has a great influence on national economy activation. The development of IT technology has enabled the collection and analysis of personal profile information, location information and activity information based on the characteristics, behavior, purchase propensity and interest of tourists. In order to realize this, the implementation of convergence smart tourism information service platform is completed by developing business model, IoT & Big Data integration management system, big data algorithm development and analysis platform in three stages. The underlying technology of the platform and algorithm needs a process of adopting open source, expanding the service element on the basis of it, and then complementing the problem through the test-bed demonstration test that connects the area. Using this platform, it is possible to develop a smart tourism environment that can provide customized services for each tourist by analyzing various information in an integrated manner. Also, it will be possible to improve the life of tourist destination residents and contribute to regional revitalization and job creation through the creation of smart tourism ecosystem focused on the region.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Journal of the Economic Geographical Society of Korea
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• v.19 no.3
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• pp.550-565
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• 2016

The size of Korean and global cosmetic industry market are consistently growing and the domestic cosmetic industry's rate of total production increase is higher than GDP in Korea. In addition, the Korean Wave has strengthened not only this phenomenon but also the increase of exports. For these reasons, the purpose of this paper is to analyze Korean cosmetic industry regarded as a new growth engine. For this study, Porter's Value Chain theory, Mudambi's Smile of Value Creation, Cosmetic GMP by ISO, and the production process on cosmetic industry are used as tools. As a result, Korean cosmetic industry comprises five nodes value chains: R&D, Raw Material Manufacture, Container Manufacture, Cosmetic Manufacture, and Marketing. And then, based on this result, the spatial analysis is conducted to identify spatial distribution characteristics of each node.

• The Journal of Bigdata
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• v.5 no.2
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• pp.1-15
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• 2020

The duty-free industry before COVID-19 has continuously grown since 2000, along with the increase of demand in tourism industry. To cope with the increased demand, the duty free companies have kept the strategies which focused on the sales volume. Therefore, they have developed the ways to increase the volume and capacity, not the efficient operations. In the most of previous research, however, authors have proposed the better strategies for marketing and supporting policies. It is very hard to find the previous research which dealt with the operations like logistics and inventory management. Therefore, in this study, it has been predicted the future demand of frequently purchased items in airport duty free shops based on the estimated number of departing passengers by the linear regression, which concluded with the appropriate inventory level. In addition, it has been analyzed the expected effects by introducing the inventory management policy considering the cost and efficiency of operations. Based on the results of this study, it may be possible to reduce total cost and improve productivity by predicting the excessive inventory problems at duty-free shops and improving cycles of supplying items.

• The Journal of the Korea Contents Association
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• v.12 no.9
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• pp.479-488
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• 2012

The purpose of this study was to determine the impact in visitors' spending on two separate local festivals, and to present the improved market strategies to attract visitors to revisit the local festivals. This study was also intended to suggest the ways to increase the competitiveness and revitalize the local festivals by improving the existing attractions and creating new attractions based on the visitors' evaluation. On the purpose of the study, we studied the visitors of two local ricefests, Icheon Rice Cultural Festival and Rice Festival in Jincheon Chungbuk, and estimated the determinants influencing the visitors' spending to the festivals by applying Tobit model. Finally, to estimate the behavioral differences in visitors of the two festivals, we compared the estimated determinants for the visitors of each festival by using Log-likelihood Ratio, and analyzed the differences in the factors influencing the visitors' spending. Summarizing the propensity of visitor's spending to local festivals, visitors of two rice festivals buy or tended to buy things on impulse. Therefore, festival industry needs to take measures to efficiently accommodate their expenditures from the stage of designing festivals.