• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.412-422
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• 2009

With the development of the Internet, online community has been made possible to buy a product in hotel industry. It is expanded gradually the customers buy various banquet services as well as guest rooms or restaurant use. From the 1950s, research has been conducted on trust and various study is achieved in connection with in social psychology or industry marketing. But there is much to be desired on research on trust in on/off-line company and customer's repurchase intention. Verifying the study model and hypothesis established through proceeding research, we would like to know that whether trust in on-line basis can be connected with the trust that already formed about the hotel in off-line basis. Furthermore, how on-line and off-line trust made in hotel industry can affects to customer's repurchase intention. The trust between on-line basis and off-line basis in hotel industry is mutually related. The trust based on off-line hotel company also affects to customer's repurchase intention. But, on-line trust in hotel industry is not related to the customer's repurchase intention.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.118-127
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• 2013

The purpose of this study was to know about the influence of consumers' knowledge level(expert vs novice) on their behavioral intentions by the storytelling about local foods. Reviewing previous storytelling studies related to local foods containing each region's traditional food culture in Korea, it can identify that most studies focused on the necessity of storytelling, the discovery of story materials, the importance of storytelling for food tour. Therefore, this study tried to know about how the storytelling about local foods influenced on the consumers' behavioral intentions, and set the attributes of storytelling and the consumers' local food-purchasing region as adjustable variances. Finally, in case that the consumers' knowledge level was low and their food-purchasing regions were not same, this study suggested the attributes of most preferred storytelling by consumers. By doing so, this study tried to discover the storytelling skills of local foods representing each region or to suggest a method to increase the cultural values of each local food in case of creating a story about the local food.

• The Journal of the Korea Contents Association
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• v.10 no.10
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• pp.389-397
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• 2010

This study is to find out influences of IT innovations factors on e-commerce diffusion, management performance. To research and analyze, from August 15th to September 15th in 2009, the questionary distributed 150 working employees at Purchasing Team & Finance Team in five star hotel in Seoul Metropolitan Area, then used for data analysis 135. The results come up with; Firstly, the factors of Information Techonology impacted on e-commerce diffusion & management performance. Secondly, e-commerce diffusion within company only had effect on management performance. The implication of this study is that if IT innovation factors were improved, hotels would have competitive achievement.

• The Journal of the Korea Contents Association
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• v.18 no.7
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• pp.74-83
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• 2018

This study analyzed the differences in effectiveness between celebrity and consumer endorsers by type of story in storytelling ads. A $2{\times}2$ factorial design experiment was conducted: the type of advertising endorser (celebrity, consumer) and the type of story (life experience, brand myth). 200 women in their 30s and 40s participated in an online survey. Study shows that for a life-experience ad, the consumer model has higher advertising effectiveness than the celebrity endorser for all three dependent variables : ad attitude, brand attitude, and purchase intent. In the case of brand-myth ad, the celebrity endorser had more favorable ad attitude than the consumer endorser did, while there was no difference in brand attitude and purchase intent. The theoretical and practical implications of the study were discussed in the conclusion.

• The Journal of the Korea Contents Association
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• v.6 no.10
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• pp.163-173
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• 2006

It is frequent to develop the fashion product through predict purchasing needs of consumers in Textile and Fashion Industry. If failed in its prediction, that is, if consumers would not purchase the product, there comes some problems that big sale is inevitable or stock increase tremendously. Otherwise, Quick Response System allows that the company observe the consumer's needs consistently and design products and establish manufacture schedule rapidly so that they could prohibit the products unnecessarily stocked. Consumer's preference is collected and analyzed through the data generated by POS system, and this is provided to the related manufacturer through network in realtime, so that the manufactures could merchandise, produce and provide the products according to the consumer's need. Thus, this study developed POS system-education program, that is, the merchandising of apparel product, product by prediction, retailer, purchase behavior, reduction in stock inventory and product lead time, cooperative system between apparel company and retailer, and conformation to the consumer's needs are included in this program, through binding the new technology in textile and fashion industry for the purpose of Quick Response system.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.535-546
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• 2015

Using mobile bookstore application is increasing in accordance with the proliferation of internet and mobile devices. In this circumstances, the purpose of this study is to explore the factors regarding to mobile bookstore application quality evaluation are effecting to customer satisfaction and reuse intention. Thus information, transaction, design, communication, ubiquitous access, personalization, safety are set as a quality evaluation factor. And it is analyzed the effect of these factors to customer satisfaction and reuse intention with path analysis method. As the result, transaction, ubiquitous access, personalization, safety factors effected customer satisfaction and customer satisfaction effected reuse intention. These results show that user mainly access mobile bookstore application for purchasing book. Thus it is important for mobile bookstore operator to keep the application accessed anytime, and serve personalized information, and simplify transaction process, and intensify security for protecting personal or transaction information.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.733-741
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• 2012

In recent, many consumers visit the online shopping malls or price comparison sites to collect the information on the product category that they are interested in. However, the volumes of the data provided by such web sites are often too enormous, and significant number of consumers have trouble in making purchase decision based on the plethora of products and sellers. In this context, modern online shopping agents need to process the retrieved information in more intelligent way before providing them to the users. This paper proposes a novel approach for identifying the main price ranges hidden in a single product category. To this end, the price of an item in the category is represented as a row vector and k-means clustering analysis is applied to the price vectors to produce the clusters that consists of the product items with similar price vectors. Then, the main price ranges of the product category can be identified from the result of clustering analysis. In general, the price is one of the most important factors in the consumers' purchase decision, and the identified main price ranges will be helpful for the online shoppers to find appropriate items effectively.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.372-380
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• 2010

Generally, data mining is the process of analyzing data from different perspectives and summarizing it into useful information that can be used to increase revenue, cuts costs, or both. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. Data mining is one of the fastest growing field in the computer industry. Because of According to computer technology has been improving, Massive customer data has stored in database. Using this massive data, decision maker can extract the useful information to make a valuable plan with data mining. Data mining offers service providers great opportunities to get closer to customer. Data mining doesn't always require the latest technology, but it does require a magic eye that looks beyond the obvious to find and use the hidden knowledge to drive marketing strategies. Automotive market face an explosion of data arising from customer but a rate of increasing customer is getting lower. therefore, we need to determine which customer are profitable clients whom you wish to hold. This paper builds model of customer loyalty detection and analyzes customer buying patterns in automotive market with data mining using decision tree as a quinlan C4.5 and basic statics methods.

• The Journal of the Korea Contents Association
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• v.16 no.4
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• pp.195-203
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• 2016

This study examined customer's purchase decision-making processes in a coffee chain context. We posit customer satisfaction, brand image, and perceive value as key drivers of forming customer's repurchase intention. From the perspective of multidimensional perceived value concept, the effects of utilitarian, hedonic, and social value on customer's decision-making processes were investigated. The proposed model was empirically tested by using survey data collected from 232 university students who often visit several coffee chains. LISREL has been used to perform these analysis. The proposed theoretical model accounts for 67% of the variance in repurchase intention and 73% of the variance in customer satisfaction. The analysis results indicate that customer satisfaction and brand image play an important role in forming customer's repurchase intention. Further, utilitarian and hedonic values significantly affect customer's repurchase intention, whereas social value negatively influences it.

• Journal of Digital Contents Society
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• v.15 no.6
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• pp.711-719
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• 2014

Along with the advent of ubiquitous computing environment, it is becoming a part of our common life style that the demands for enjoying the wireless internet using intelligent portable device such as smart phone and iPad, are increasing anytime or anyplace without any restriction of time and place. The recommending service becomes a very important technology which can find exact information to present users, then is easy for customers to reduce their searching effort to find out the items with high purchasability in e-commerce. Traditional mining association rule ignores the difference among the transactions. In order to do that, it is considered the importance of type of merchandise or service and then, we suggest a new recommending service using mining sequential pattern based on weight to reflect frequently changing trends of purchase pattern as time goes by and as often as customers need different merchandises on e-commerce being extremely diverse. To verify improved better performance of proposing system than the previous systems, we carry out the experiments in the same dataset collected in a cosmetic internet shopping mall.