• Title/Summary/Keyword: 인터넷기업

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Effect a Presentation Product has on the Repurchase Action (증정상품이 소비자의 재구매행동에 미치는 영향)

  • Yun, Gi-Seon;Kim, Hong
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.1 no.2
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    • pp.193-224
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    • 2006
  • When we look into the market economy of our country recently, we learn that the mind of consumption after IMF crisis is very shrunk and the market is led into a serious slump of consumption. For an approach to survive the contraction of the market and the market competition, enterprises command a variety of sales promotion strategy, out of which presentation is a sales promotion strategy to give the same product. The price-discounted strategy through the provision of donation commodity may induce the temporarily-discounted commodity not to be sold to the consumers or make a damage of the images of the brand, or arouse the price war against other companies, or lower the sense of the quality of the commodity. Therefore, it is necessary for a company to meet the end users' demand and also maintain the evaluation of the quality on the consumers' products highly. Therefore, in this study, we have attempted to study and analyze the consumers' satisfaction level and reliability on the donation goods in order to suggest the orientation of the presentation promotion strategy in accordance with the changes of the sales market. In addition, we tried to understand how the recognition, consumers' satisfaction level and reliability on the presentation goods had on the repurchase. With such objectives in this study, we could make an analogy of the following significance and suggestion of study. Firstly, in order to survive a serious competition market, enterprises must execute the product presentation along with diverse events instead of commanding the sales promotion strategy through a simple product presentation. This strategy can be an alternative to lower the danger a person-to-person product presentation may bring about. That is to say, we shall not lower the quality and value of the products but enhance a new image to customers through a product donation occasion together with an event as a new marketing pioneering method. Secondly, during the period of the current economic depression, if a company provides the consumers with an opportunity free of charge through the present special event period and the practical events, it will affect the advertising effect of the goods, the introduction of the customers and customers' repurchase. For this purpose, the company has to heighten customers' preferences by selecting the items customers are liable to prefer and closely analyze the consumers' response and market for such an objective. Thirdly, with the internet age, as the market has a tendency to increase In the number of consumers who do shopping in the internet, the marketing strategy has to build up the strategy of the presentation product instead of a simple offline strategy. For example, a company shall have to draw attention or attraction from end users who intend to do shopping through the online by a product planning expo or a presentation product corner. Fourthly, the excessive sale promotion strategy of presentation products may bring about even a reverse effect on the value of the goods or consumers' attitude as seen above. Therefore, a company has to relay' the value as to the price' to the consumers instead of the sales promotion strategy of donation products just for a temporary sales volume. Conclusively, even if we put the value with a reasonable price through the presentation product strategy in the past, we shall have construct the strategy by providing some plus factors in the price such as the provision of the upgraded products or services instead of just presentation, or the invitation of the events related to diverse events or culture arts from now on.

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Personification of On-line Shopping Mall -Focusing on the Social Presence- (온라인 쇼핑몰의 의인화 전략 -사회적 실재감을 중심으로-)

  • Park, Ju-Sik
    • Management & Information Systems Review
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    • v.31 no.2
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    • pp.143-172
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    • 2012
  • While e-commerce market(B2C) grows rapidly, many experts argue that EC(B2C) transactions have not reached its full potential. A notable difference between online and offline consumer markets that is suppressing the growth of EC(B2C) is the decreased presence of human and social elements in the online shopping environments. Generally online shopping lacks human warmth and sociability. In this study, social presence in online shopping mall was proposed as a substitute for face-to-face social interaction in the traditional commerce and author explored what variables affect social presence(human warmth and sociability) on online shopping malls and how human warmth and sociability can influence on online store loyalty. To achieve research objectives, we reviewed literatures related with marketing, psychology and communication research areas. Based on literature review, we proposed a research model on the online shopping mall. To examine the proposed research model, we gathered data by using a self-report questionnaire. Respondents consists of online shoppers with at least five or more times of purchase experience in online shopping malls. Because social presence is a feeling which needs frequent contacts with malls to experience, respondents must have enough purchase experiences. The empirical results are as follows : First, shopping mall's customization efforts influence perceived social presence on the mall significantly. Second, shopping mall's responsiveness influences perceived social presence significantly. Third, perceived activity of community of online shopping mall influences perceived social presence significantly. Mall managers have to activate their customer community to reinforce social presence, resulting in trust building. Finally, perceived social presence influences trust and enjoyment on the mall significantly. And then trust and enjoyment on the mall affect store loyalty significantly. From these findings it can be inferred that perceived social presence appears determinant which is critical to the formation of core variables(trust and loyalty) in existing online shopping papers.

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A Study on the Influence of Information Security on Consumer's Preference of Android and iOS based Smartphone (정보보안이 안드로이드와 iOS 기반 스마트폰 소비자 선호에 미치는 영향)

  • Park, Jong-jin;Choi, Min-kyong;Ahn, Jong-chang
    • Journal of Internet Computing and Services
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    • v.18 no.1
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    • pp.105-119
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    • 2017
  • Smartphone users hit over eighty-five percentage of Korean populations and personal private items and various information are stored in each user's smartphone. There are so many cases to propagate malicious codes or spywares for the purpose of catching illegally these kinds of information and earning pecuniary gains. Thus, need of information security is outstanding for using smartphone but also user's security perception is important. In this paper, we investigate about how information security affects smartphone operating system choices by users. For statistical analysis, the online survey with questionnaires for users of smartphones is conducted and effective 218 subjects are collected. We test hypotheses via communalities analysis using factor analysis, reliability analysis, independent sample t-test, and linear regression analysis by IBM SPSS statistical package. As a result, it is found that hardware environment influences on perceived ease of use. Brand power affects both perceived usefulness and perceived ease of use and degree of personal risk-accepting influences on perception of smartphone spy-ware risk. In addition, it is found that perceived usefulness, perceived ease of use, degree of personal risk-accepting, and spy-ware risk of smartphone influence significantly on intention to purchase smartphone. However, results of independent sample t-test for each operating system users of Android or iOS do not present statistically significant differences among two OS user groups. In addition, each result of OS user group testing for hypotheses is different from the results of total sample testing. These results can give important suggestions to organizations and managers related to smartphone ecology and contribute to the sphere of information systems (IS) study through a new perspective.

Effect a Presentation Product has on the Repurchase Action (증정상품이 소비자의 재구매행동에 미치는 영향)

  • Yun, Gi-Seon;Kim, Hong
    • 한국벤처창업학회:학술대회논문집
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    • 2007.04a
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    • pp.375-404
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    • 2007
  • When we look into the market economy of our country recently, we learn that the mind of consumption after IMF crisis is very shrunk and the market is led into a serious slump of consumption. For an approach to survive the contraction of the market and the market competition, enterprises command a variety of sales promotion strategy, out of which presentation is a sales promotion strategy to give the same product. The price-discounted strategy through the provision of donation commodity may induce the temporarily-discounted commodity not to be sold to the consumers or make a damage of the images of the brand, or arouse the price war against other companies, or lower the sense of the quality of the commodity. Therefore, it is necessary for a company to meet the end users' demand and also maintain the evaluation of the quality on the consumers' products highly. Therefore, in this study, we have attempted to study and analyze the consumers' satisfaction level and reliability on the donation goods in order to suggest the orientation of the presentation promotion strategy in accordance with the changes of the sales market. In addition, we tried to understand how the recognition, consumers' satisfaction level and reliability on the presentation goods had on the repurchase. With such objectives in this study, we could make an analogy of the following significance and suggestion of study. Firstly, in order to survive a serious competition market, enterprises must execute the product presentation along with diverse events instead of commanding the sales promotion strategy through a simple product presentation. This strategy can be an alternative to lower the danger a person-to-person product presentation may bring about. That is to say, we shall not lower the quality and value of the products but enhance a new image to customers through a product donation occasion together with an event as a new marketing pioneering method. Secondly, during the period of the current economic depression, if a company provides the consumers with an opportunity free of charge through the present special event period and the practical events, it will affect the advertising effect of the goods, the introduction of the customers and customers' repurchase. For this purpose, the company has to heighten customers' preferences by selecting the items customers are liable to prefer and closely analyze the consumer's response and market for such an objective. Thirdly, with the internet age, as the market has a tendency to increase in the number of consumers who do shopping in the internet, the marketing strategy has to build up the strategy of the presentation product instead of a simple offline strategy. For example, a company shall have to draw attention or attraction from end users who intend to do shopping through the online by a product planning expo or a presentation product corner. Fourthly, the excessive sale promotion strategy of presentation products may bring about even a reverse effect on the value of the goods or consumers' attitude as seen above. Therefore, a company has to relay 'the value as to the price' to the consumers instead of the sales promotion strategy of donation products just for a temporary sales volume. Conclusively, even if we put the value with a reasonable price through the presentation product strategy in the past, we shall have construct the strategy by providing some plus factors in the price such as the provision of the upgraded products or services instead of just presentation, or the invitation of the events related to diverse events or culture arts from now on.

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A Study on Netwotk Effect by using System Dynamics Analysis: A Case of Cyworld (시스템 다이내믹스 기법을 이용한 네트워크 효과 분석: 싸이월드 사례)

  • Kim, Ga-Hye;Yang, Hee-Dong
    • Information Systems Review
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    • v.11 no.1
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    • pp.161-179
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    • 2009
  • Nowadays an increasing number of Internet users are running individual websites as Blog or Cyworld. As this type of personal media has a great influence on communication among people, business comes to care about Network Effect, Network Software, and Social Network. For instance, Cyworld created the web service called 'Minihompy' for individual web-logs, and acquired 2.4milion users in 2007. Although many people assumed that the popularity of Minihompy, or Blog would be a passing fad, Cyworld has improved its service, and expanded its Network with various contents. This kind of expansion reflects survival efforts from infinite competitions among ISPs (Internet Service Provider) with focus on enhancing usability to users. However, Cyworld's Network Effect is gradually diminished in these days. Both of low production cost of service vendors and the low searching/conversing costs of users combine to make ISPs hard to keep their market share sustainable. To overcome this lackluster trend, Cyworld has adopted new strategies and try to lock their users in their service. Various efforts to improve the continuance and expansion of Network effect remain unclear and uncertain. If we understand beforehand how a service would improve Network effect, and which service could bring more effect, ISPs can get substantial help in launching their new business strategy. Regardless many diverse ideas to increase their user's duration online ISPs cannot guarantee 'how the new service strategies will end up in profitability. Therefore, this research studies about Network effect of Cyworld's 'Minihompy' using System-Dynamics method which could analyze dynamic relation between users and ISPs. Furthermore, the research aims to predict changes of Network Effect based on the strategy of new service. 'Page View' and 'Duration Time' can be enhanced for the short tenn because they enhance the service functionality. However, these services cannot increase the Network in the long-run. Limitations of this research include that we predict the future merely based on the limited data. We also limit the independent variables over Network Effect only to the following two issues: Increasing the number of users and increasing the Service Functionality. Despite of some limitations, this study perhaps gives some insights to the policy makers or others facing the stiff competition in the network business.

A Study on the Strategic Use of an IMC Planning Model for the Distribution Industry (유통업 IMC 기획모델의 전략적 활용에 관한 연구)

  • Mo, Sun-Jong;Song, In-Am
    • Journal of Global Scholars of Marketing Science
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    • v.18 no.2
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    • pp.113-145
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    • 2008
  • Marketing for the distribution industry is making an ongoing progress in the changes of customers, the competitive environment, and the internal marketing environment. Integrated marketing communication activities are required for the enhancement of efficiency in the market.oriented activities. In this study, IMC is defined as "a notion that a market oriented business integrated marketing communication means, conducting and evaluating marketing activities with consistent messages in order to communicate with customers based on databases." In this study, an IMC planning model for the improvement of marketing efficiency in the distribution industry was derived from a pilot study. This model may be broken down into the following phases: IMC goals setting, situational analysis (customer analysis, competition analysis and company analysis), customer data analysis, contact management, budgeting, the establishment of an IMC strategy, the IMC mix and execution, an evaluation system, and feedback. In consideration of the characteristics of the distribution industry, this study was accompanied by a vocational study on IMC means employed by, in particular, department stores and other distributors such as: advertising, sales promotion, sales promotion advertising, direct marketing, public relations, personal selling, the Internet, mobile, visual merchandising, words of mouth. In addition, this study also covered the correlation among variables such as IMC activities of distributors, the process of forming customer's brand attitudes, brand loyalty and repurchase intention. This research would enhance the utilization of IMC. The analysis on customer's brand attitudes toward the IMC activities of distributors requires the simultaneous consideration of how they are linked to purchase as well as their attitudes toward both distributors and stores. The formation of brand loyalty and repurchase intention is related to the integration of marketing communication and the maintenance of consistency in contents, which requires integrated brand communication (IBC) strategies. IBC is a concept of using IMC means to manage the brand in a continuing and consistent manner and measuring their effect, which is a process to establish enterprise.level brand identity and maximize brand loyalty and repurchase intention by integrating IMC means. For an empirical analysis in this study, an online questionnaire survey was conducted among those department store customers from 20's to 50's who reside either in the Seoul and Gyeonggi areas and have made purchase at department stores. In this study, the research model consisted of four theoretical variables: IMC activities, IMC attitudes, brand loyalty, and repurchase intention, on which variables a pilot study was conducted. A number of hypotheses were constructed on the relations between IMC activities and IMC attitudes, between IMC attitudes and repurchase intention, and between brand loyalty and repurchase intention. The test of the hypotheses may be summarized as follows: Firstly, the test of the hypothesis concerning the relation between IMC attitudes and IMC activities - advertising, sales promotion, direct marketing, public relations, personal selling, the Web, mobile, visual merchandising, and word of mouth - indicates that advertising, sales promotion, direct marketing, public relations, personal selling, mobile, visual merchandising, and word of mouth have significant impact on IMC activities. In addition to the result similar to those of previous studies that such marketing communication means as word of mouth, advertising, personal selling and sales promotion, in particular, play very important roles, a notable finding of this study is that visual merchandising performed by department stores is shown to have very significant impact on IMC activities. On a separate note, it is also noteworthy that Internet marketing activities engaged by department stores are not shown to have significant impact on IMC attitudes. Secondly, the test of the hypothesis on the relation between IMC attitudes and brand loyalty attests that IMC attitudes for the distribution industry significantly affect brand loyalty. Thirdly, the test of the hypothesis concerning the relation between IMC attitudes and repurchase intention confirms that IMC attitudes for the distribution industry significantly affect repurchase intention. Fourthly, the test of the hypothesis concerning the relation between brand loyalty and repurchase intention indicates that brand loyalty significantly affect repurchase intention. A comprehensive view of these findings points to the conclusion that the IMC activities for the distribution industry do affect IMC attitudes, brand loyalty, and repurchase intention.

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A Study on E-mail Campaigns and Feedback Analysis as Marketing Tools of Internet Fashion Shopping Malls - With Focus on Specialized Fashion Shopping Malls - (인터넷 패션쇼핑몰의 이메일 마케팅 활용과 반응 - 패션 전문몰을 중심으로 -)

  • Han, Ji-Sook
    • Archives of design research
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    • v.19 no.2 s.64
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    • pp.53-62
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    • 2006
  • E-mail has indeed developed from 'a means of instant communication' to an indispensable part of online marketing. Therefore, companies need to implement consistent customer management. Communication with customers and marketing through e-mail is a powerful way of communication and adapting one-to-one marketing strategies to customer trends, habits and taste preferences. Since setting accurate targets is especially important in the fashion industry, e-mail marketing is the most effective way to communicate with customers and one-to-one marketing constitutes a very important strategy. In this study, I will analyze this powerful one-on-one marketing tool, particularly actual e-mail messages sent by an Internet Shopping Mall from June 12 to July 30, 2005, examine the effect of these messages on sales growth and analyze actual feedback received. Regarding e-mail read rates broken down by age and gender, 1 found that females in their late twenties recorded the highest rate at 21.66% and their contribution to sales growth was recorded at 3.5% From actual sales records, found that 28.10% of total sales were attributable to people in their late twenties, showing that the age group that reads e-mails the most also buys the most. Regarding feedback by e-mail title, e-mails from the 'Casual' category seemed to be the most effective, in that most of these e-mails were read. Also, messages sent on Tuesdays were read the most, according to the feedback analysis by weekday. Section e-mails were read more often than regular e-mails. Regarding the view rate according to the time e-mails were sent, messages sent to females in their late twenties at two o'clock in the afternoon were read by 20.93% of recipients, recording the highest read rate. By offering informative content and practical tips, visitors will be attracted to the site and generate site traffic. Therefore, we can conclude that sending e-mail messages can greatly contribute to sales growth and e-mail marketing is very effective. Also, in order to make e-mail campaigns more effective and improve marketing results, we need to analyze actual results and apply our findings in future e-mail campaigns. With this, we get successful marketing results.

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The Research on Recommender for New Customers Using Collaborative Filtering and Social Network Analysis (협력필터링과 사회연결망을 이용한 신규고객 추천방법에 대한 연구)

  • Shin, Chang-Hoon;Lee, Ji-Won;Yang, Han-Na;Choi, Il Young
    • Journal of Intelligence and Information Systems
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    • v.18 no.4
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    • pp.19-42
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    • 2012
  • Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.

Emoticon by Emotions: The Development of an Emoticon Recommendation System Based on Consumer Emotions (Emoticon by Emotions: 소비자 감성 기반 이모티콘 추천 시스템 개발)

  • Kim, Keon-Woo;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.24 no.1
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    • pp.227-252
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    • 2018
  • The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.

Resolving the 'Gray sheep' Problem Using Social Network Analysis (SNA) in Collaborative Filtering (CF) Recommender Systems (소셜 네트워크 분석 기법을 활용한 협업필터링의 특이취향 사용자(Gray Sheep) 문제 해결)

  • Kim, Minsung;Im, Il
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.137-148
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    • 2014
  • Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used

    . Past studies to improve CF performance typically used additional information other than users' evaluations such as demographic data. Some studies applied SNA techniques as a new similarity metric. This study is novel in that it used SNA to separate dataset. This study shows that performance of CF can be improved, without any additional information, when SNA techniques are used as proposed. This study has several theoretical and practical implications. This study empirically shows that the characteristics of dataset can affect the performance of CF recommender systems. This helps researchers understand factors affecting performance of CF. This study also opens a door for future studies in the area of applying SNA to CF to analyze characteristics of dataset. In practice, this study provides guidelines to improve performance of CF recommender systems with a simple modification.


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