• East Asian Journal of Business Economics (EAJBE)
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• v.4 no.4
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• pp.24-32
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• 2016

There hardly have been support policies for small wholesale vendors or any materials such as proper statistical standards and figures compared to diversity of support policies and size of budget for small and medium manufacturing business. The biggest concern coming from it is that there have never been any policies for small and medium wholesale vendors. This study proposes some ways to improve support policies through investigating the current status of those vendors as their true values haven't been properly recognized, while diverse support systems have been devised for manufacturing business thanks to the traditional industrial development process. According to the study on support policies for domestic and international small and medium wholesale vendors, I realized that those vendors need a policy to ensure them to be promptly adjusted to the rapidly changing distribution environment and to be competitive to access to the global distribution market to finally become hidden champions through systematical operations of small and medium wholesale vendors and implementing educational business through sales management. Therefore, I propose five ways to improve support policies for small and medium wholesale vendors by considering social and economic value, systematizing small wholesalers and scaling small and medium wholesale vendors, reinforcing support for wholesalers, support policies for new online market opening and offline market opening.

• Journal of Smart Tourism
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• v.3 no.4
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• pp.5-15
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• 2023

With the growing trend of online global market, customers have further technological capabilities in searching for information and online shopping on the Internet. In addition, electronic word-of-mouth (eWOM) is a significant factor that influences customer purchase intention. However, the perspective of online users on hotel websites is still in its infancy, especially in various cultural contexts. The current study examined a theoretical framework of hotel websites to understand how online users perceive the importance of hotel websites with regard to influencing purchase intention, within the content of Thai online users through an online questionnaire survey. Findings show that usability positively influences online Thai users' satisfaction. Moreover, eWOM has a significant positive influence on satisfaction, but eWOM has an indirect effect on the intention to purchase. Practical implications are further discussed.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.21-36
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• 2022

Recently, as COVID-19 has made the e-commerce market expand widely, customers who have different consumption patterns appear in the market. Because companies can obtain opinions and information of customers from reviews, they increasingly face the requirements of managing customer reviews on online platform. In this study, we analyze customers and carry out market segmentation for classifying and defining type of customers in e-commerce. Specifically, K-means clustering was conducted on customer review data collected from Wemakeprice online shopping platform, which leads to the result that six clusters were derived. Finally, we define the characteristics of each cluster and propose a customer management plan. This paper is possible to be used as materials which identify types of customers and it can reduce the cost of customer management and make a profit for online platforms.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.10 no.4
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• pp.148-154
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• 2011

This paper presents u-COEX, Ubiquitous-Collaborative Online shopping EXecution system, for small- and mediam- sized business enterprises, based on EPCglobal network. The system is taking advantage of RFID technology promises to optimize the critical processes in the Supply Chain Management. The system consists of five major functions: integrated order management, realtime monitoring and analysis system of sales and inventory, decision support system, integrating with EPCglobal and RFID technology, and u-catalog feature. The prototype implementation was developed for mass electronic market complex and the result revealed the feasibility to be applicable to real market.

• Korean System Dynamics Review
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• v.9 no.1
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• pp.143-154
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• 2008

This study has tried to suggest a new model that can effectively redistribute the tickets in the online ticket resale market, while suggesting a new allocation mechanism based on an agent negotiation. To this end, this study has analyzed and simulated the secondary ticket market through System dynamics. As a result of these simulations, it has been proved that the price stability of ticket resale market leads to an increase in revenue. An agent negotiation helps to stabilize the ticket prices that are usually inclined to rise at auction, benefiting all the participants in the negotiations, consequently showing a Pareto solution.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.2
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• pp.181-189
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• 2001

The proliferation of the Internet and related technologies and applications has led to a new form of market place known as the electronic store. In this paper, we study competition between two shopping channels, an electronic store and traditional retailers. Based on the circular spatial market model, we derive the Nash and Stackelberg equilibria as a function of the efficiency of the electronic store. The result shows that the Stackelberg equilibrium is always superior to the Nash equilibrium for both channels. It is also shown that, in some cases, the electronic store has incentive to decrease its efficiency to gain more profit.

• Journal of Industrial Convergence
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• v.10 no.1
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• pp.1-12
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• 2012

The purpose of this study firstly shows the marketing current condition and features of large discount stores playing a big change role in the Korea domestic distribution market. Secondly, I will analyze the success factors of the online marketing. And then finally, I will derive implication regarding the using solution of the effective online marketing.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.119-138
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• 2016

Since the Industrial Revolution, which made the mass production and mass distribution of standardized goods possible, machine-made (manufactured) products have accounted for the majority of the market. However, in recent years, the phenomenon of purchasing even more expensive handmade products has become a noticeable trend as consumers have started to acknowledge the value of handmade products, such as the craftsman's commitment, belief in their quality and scarcity, and the sense of self-esteem from having them,. Consumer interest in these handmade products has shown explosive growth and has been coupled with the recent development of three-dimensional (3D) printing technologies. Etsy.com is the world's largest online handmade platform. It is no different from any other online platform; it provides an online market where buyers and sellers virtually meet to share information and transact business. However, Etsy.com is different in that shops within this platform only deal with handmade products in a variety of categories, ranging from jewelry to toys. Since its establishment in 2005, despite being limited to handmade products, Etsy.com has enjoyed rapid growth in membership, transaction volume, and revenue. Most recently in April 2015, it raised funds through an initial public offering (IPO) of more than 1.8 billion USD, which demonstrates the huge potential of online handmade platforms. After the success of Etsy.com, various types of online handmade platforms such as Handmade at Amazon, ArtFire, DaWanda, and Craft is ART have emerged and are now competing with each other, at the same time, which has increased the size of the market. According to Deloitte's 2015 holiday survey on which types of gifts the respondents plan to buy during the holiday season, about 16% of U.S. consumers chose "homemade or craft items (e.g., Etsy purchase)," which was the same rate as those for the computer game and shoes categories. This indicates that consumer interests in online handmade platforms will continue to rise in the future. However, this high interest in the market for handmade products and their platforms has not yet led to academic research. Most extant studies have only focused on machine-made products and intelligent services for them. This indicates a lack of studies on handmade products and their intelligent services on virtual platforms. Therefore, this study used signaling theory and prior research on the effects of sellers' characteristics on their performance (e.g., total sales and price premiums) in the buyer-seller relationship to identify the key influencing e-Image factors (e.g., reputation, size, information sharing, and length of relationship). Then, their impacts on the performance of shops within the online handmade platform were empirically examined; the dataset was collected from Etsy.com through the application of web harvesting technology. The results from the structural equation modeling revealed that the reputation, size, and information sharing have significant effects on the total sales, while the reputation and length of relationship influence price premiums. This study extended the online platform research into online handmade platform research by identifying key influencing e-Image factors on within-platform shop's total sales and price premiums based on signaling theory and then performed a statistical investigation. These findings are expected to be a stepping stone for future studies on intelligent online handmade services as well as handmade products themselves. Furthermore, the findings of the study provide online handmade platform operators with practical guidelines on how to implement intelligent online handmade services. They should also help shop managers build their marketing strategies in a more specific and effective manner by suggesting key influencing e-Image factors. The results of this study should contribute to the vitalization of intelligent online handmade services by providing clues on how to maximize within-platform shops' total sales and price premiums.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.23-38
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• 2012

There is a large difference between purchasing patterns in an online shopping mall and in an offline market. This difference may be caused mainly by the difference in accessibility of online and offline markets. It means that an interval between the initial purchasing decision and its realization appears to be relatively short in an online shopping mall, because a customer can make an order immediately. Because of the short interval between a purchasing decision and its realization, an online shopping mall transaction usually contains fewer items than that of an offline market. In an offline market, customers usually keep some items in mind and buy them all at once a few days after deciding to buy them, instead of buying each item individually and immediately. On the contrary, more than 70% of online shopping mall transactions contain only one item. This statistic implies that traditional data mining techniques cannot be directly applied to online market analysis, because hardly any association rules can survive with an acceptable level of Support because of too many Null Transactions. Most market basket analyses on online shopping mall transactions, therefore, have been performed by expanding the co-occurrence criteria of traditional association rule mining. While the traditional co-occurrence criteria defines items purchased in one transaction as concurrently purchased items, the expanded co-occurrence criteria regards items purchased by a customer during some predefined period (e.g., a day) as concurrently purchased items. In studies using expanded co-occurrence criteria, however, the criteria has been defined arbitrarily by researchers without any theoretical grounds or agreement. The lack of clear grounds of adopting a certain co-occurrence criteria degrades the reliability of the analytical results. Moreover, it is hard to derive new meaningful findings by combining the outcomes of previous individual studies. In this paper, we attempt to compare expanded co-occurrence criteria and propose a guideline for selecting an appropriate one. First of all, we compare the accuracy of association rules discovered according to various co-occurrence criteria. By doing this experiment we expect that we can provide a guideline for selecting appropriate co-occurrence criteria that corresponds to the purpose of the analysis. Additionally, we will perform similar experiments with several groups of customers that are segmented by each customer's average duration between orders. By this experiment, we attempt to discover the relationship between the optimal co-occurrence criteria and the customer's average duration between orders. Finally, by a series of experiments, we expect that we can provide basic guidelines for developing customized recommendation systems. Our experiments use a real dataset acquired from one of the largest internet shopping malls in Korea. We use 66,278 transactions of 3,847 customers conducted during the last two years. Overall results show that the accuracy of association rules of frequent shoppers (whose average duration between orders is relatively short) is higher than that of causal shoppers. In addition we discover that with frequent shoppers, the accuracy of association rules appears very high when the co-occurrence criteria of the training set corresponds to the validation set (i.e., target set). It implies that the co-occurrence criteria of frequent shoppers should be set according to the application purpose period. For example, an analyzer should use a day as a co-occurrence criterion if he/she wants to offer a coupon valid only for a day to potential customers who will use the coupon. On the contrary, an analyzer should use a month as a co-occurrence criterion if he/she wants to publish a coupon book that can be used for a month. In the case of causal shoppers, the accuracy of association rules appears to not be affected by the period of the application purposes. The accuracy of the causal shoppers' association rules becomes higher when the longer co-occurrence criterion has been adopted. It implies that an analyzer has to set the co-occurrence criterion for as long as possible, regardless of the application purpose period.

• Journal of Korea Game Society
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• v.11 no.5
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• pp.43-52
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• 2011

This study assumed the competitive structure based on genre classification for Korean online game market, and carried out the analysis on the degree and characteristics of the competition that appear differently in each sub market classified according to the genre. Analysis result can be summarized as follows. (1) In the view of the total play time, the proportions of the online games in each genre were appeared in the order of "RPG > FPS/RTS > Sports > Arcade/Poker > Go-stop > Board/Racing". (2) In the view of the shares in the play time, the degree of competition between games in the sub market structure of the online games according to the genre was found in the order of "RTS > Racing > FPS/Sports > Go-stop > Poker > Arcade/Board > RPG". The evaluation and interpretation of the high and low of the competition degree are as follows. As the degree of competition is higher, (RTS > Racing > ${\cdots}$) the royalty and the ratio of reusing of the users for the game is lower, and on the other hand, the tendency of replacing and using appeared higher, so the market entry barrier for a new game can be evaluated to be low. Reversely, as the degree of competition is lower, (${\cdots}$ > Arcade/Board > RPG) the royalty and the ratio of reusing of the users for the game is higher, and on the other hand, the tendency of replacing and using appeared lower, so the market entry barrier for a new game can be evaluated to be high.