• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Asia Marketing Journal
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• v.12 no.4
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• pp.27-54
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• 2011

This research attempted to present the efficiency of culture marketing to the organizations producing culture-art products and to the companies utilizing art and suggest the practical viewpoints to the culture and art policy agencies. The methodology used was to take an in-depth look at the consumer value cognition and benefits of culture-art products in contemporary consumption culture from a social context by conducting a total of 12 Focus Group Interviews, consisting of 58 males and females in their 10s~50s who can represent culture-art product consumers. The culture-art products refer to the artist's spiritual, actual act of creating or to the end products with economic exchange value. They are also sense goods and merit goods that affect the mental state of consumers. By looking at culture-art products as consumer merit goods, this research examined consumer value cognition of culture-art products based on the characteristics culture-art products. As a result, this research determined that consumers view culture-art products largely as 'aesthetic and sensuous merit goods', 'actual and individual merit goods', and 'social public property'. As 'aesthetic and sensuous merit goods', culture-art products are considered as the products of an artist's creative activities; as 'social public property', culture-art products have a public value in terms of ownership; and as 'actual and individual merit goods', culture-art products act on the spirit and reality of a consumer in terms of consumption. As a result of analyzing the benefits of culture-art products based on the above-mentioned consumer value cognition, it was observed that the benefits of culture-art-product consumption are chiefly divided into 'aesthetic character-oriented', 'social relationships-oriented', and 'individual benefits-oriented' depending on how consumers see culture-art products. A 3-conceptional structures model was constructed according to the relationship between consumer value cognition of culture-art products and the benefits. This research revealed that consumers who pursue the aesthetic value or sense of beauty as the central reason experience culture-art products themselves, enjoy intellectual quests, and pursue their satisfaction by expressing affection for and interests in culture-art products. On the other hand, consumers who pursue social value as the central reason as a means of communication by perceiving culture-art products as a public property of society, pursue sympathy with people close to them through the symbolic power of culture-art product consumption or the joy of self-display. Consumers who perceive art products as spiritual and actual merit goods and pursue consumer value as a central reason want to express their own personality, develop themselves, and differentiate themselves or identify themselves with others in the context of social relations for the ultimate goal of living a happy and satisfied life while pursuing to satisfy imminent and actual necessities as emotional stability and rest. The fact that culture-art product benefits could vary according to how a consumer perceives them implies that consumer value cognition of culture-art products and their benefits significant affect consumers' decision in choosing and consuming various culture-art products. It turned out that such benefits from the consumption of culture-art products reflect the complex contemporary consumption culture of rational consumption, symbolic consumption, experiential consumption, and social reflective consumption. This research identified conceptional structures of consumer value cognition on culture-art products and benefits that can be used for studying and understanding culture-art products consumers who pursue a variety of consumption values. They can also be used by private companies in utilizing art, as well as by national agencies in enhancing the population's quality of life. However, since this research could only conceptually grasp consumer perception of culture-art products and reveal the dimension of classification due to its own limitations arising from characteristic investigation, quantitative data on the benefits of culture-art product consumers should be measured in future studies through a quantitative investigation, while using the value cognition of culture-art products and the individual characteristics of consumers as variables based on this research.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.12 s.138
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• pp.1583-1595
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• 2004

Simon and Sullivan(l993) estimated that clothing and textile related brand equity had the highest magnitude comparing any other industry category. It reflects that fashion brands reinforce the symbolic, social values and emotional characteristics being different from generic brands. Recently, Kim and Lim(2002) developed a fashion brand equity scale to measure a brand's psychometric properties. However, they suggested that additional psychometric tests were needed to compare the relative magnitude of each brand's equity. The purpose of this study was to recognize the psychometric constructs of fashion brand equity and validate Kim and Lim's fashion brand equity scale using the measurement invariance test of cross-group comparison. First, we identified the constructs of fashion brand equity using confirmatory factor analysis through structural equation modeling. Second, we compared the relative magnitude of two brands' equity using the measurement invariance test of multi-group simultaneous factor analysis. Data were collected at six major universities in Seoul, Korea. There were 696 usable surveys for data analysis. The results showed that fashion brand equity was comprised of 16 items representing six dimensions: customer-brand resonance, customer feeling, customer judgment, brand imagery, brand performance and brand awareness. Also, we could support the measurement invariance of two brands' equities by configural and metric invariance tests. There were significant differences in five constructs' mean values. The greatest difference was in customer feeling; the smallest, in customer judgment.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.93-110
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• 2015

The recommender system is a system which recommends products to the customers who are likely to be interested in. Based on automated information filtering technology, various recommender systems have been developed. Collaborative filtering (CF), one of the most successful recommendation algorithms, has been applied in a number of different domains such as recommending Web pages, books, movies, music and products. But, it has been known that CF has a critical shortcoming. CF finds neighbors whose preferences are like those of the target customer and recommends products those customers have most liked. Thus, CF works properly only when there's a sufficient number of ratings on common product from customers. When there's a shortage of customer ratings, CF makes the formation of a neighborhood inaccurate, thereby resulting in poor recommendations. To improve the performance of CF based recommender systems, most of the related studies have been focused on the development of novel algorithms under the assumption of using a single profile, which is created from user's rating information for items, purchase transactions, or Web access logs. With the advent of big data, companies got to collect more data and to use a variety of information with big size. So, many companies recognize it very importantly to utilize big data because it makes companies to improve their competitiveness and to create new value. In particular, on the rise is the issue of utilizing personal big data in the recommender system. It is why personal big data facilitate more accurate identification of the preferences or behaviors of users. The proposed recommendation methodology is as follows: First, multimodal user profiles are created from personal big data in order to grasp the preferences and behavior of users from various viewpoints. We derive five user profiles based on the personal information such as rating, site preference, demographic, Internet usage, and topic in text. Next, the similarity between users is calculated based on the profiles and then neighbors of users are found from the results. One of three ensemble approaches is applied to calculate the similarity. Each ensemble approach uses the similarity of combined profile, the average similarity of each profile, and the weighted average similarity of each profile, respectively. Finally, the products that people among the neighborhood prefer most to are recommended to the target users. For the experiments, we used the demographic data and a very large volume of Web log transaction for 5,000 panel users of a company that is specialized to analyzing ranks of Web sites. R and SAS E-miner was used to implement the proposed recommender system and to conduct the topic analysis using the keyword search, respectively. To evaluate the recommendation performance, we used 60% of data for training and 40% of data for test. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. A widely used combination metric called F1 metric that gives equal weight to both recall and precision was employed for our evaluation. As the results of evaluation, the proposed methodology achieved the significant improvement over the single profile based CF algorithm. In particular, the ensemble approach using weighted average similarity shows the highest performance. That is, the rate of improvement in F1 is 16.9 percent for the ensemble approach using weighted average similarity and 8.1 percent for the ensemble approach using average similarity of each profile. From these results, we conclude that the multimodal profile ensemble approach is a viable solution to the problems encountered when there's a shortage of customer ratings. This study has significance in suggesting what kind of information could we use to create profile in the environment of big data and how could we combine and utilize them effectively. However, our methodology should be further studied to consider for its real-world application. We need to compare the differences in recommendation accuracy by applying the proposed method to different recommendation algorithms and then to identify which combination of them would show the best performance.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.2
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• pp.125-137
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• 2018

Credit unions organized and operated by the members of communities, work-places or groups are co-operative entities where customers act as owners not just transaction partners. The foregoing organizational characteristic of credit unions exerts beneficial effects on their customer relationship, and underscores the need for diversifying their relationship marketing strategies. This study sheds light on the structural relationship of credit unions in terms of principal variables of relationship marketing, i.e. relationship benefits, customer satisfaction and long-term relationship orientation. Specifically, we classify the relationship benefits into three sub-dimensions, i.e. confidence benefits, social benefits and special treatment benefits, and structuralize a causal model involving the customer satisfaction and long-term relationship orientation. From December 26, 2017 to January 26, 2018, A total of 360 questionnaires was collected. Of these, 346 were selected as the final samples, excluding 14, which are difficult to use in statistics. The reliability analysis, exploratory factor analysis, and regression analysis was performed by using the 'SPSS 24.0'. And confirmatory factor analysis, structural equation model analysis was performed by using 'AMOS 24.0'. The findings highlight the following. First, confidence benefits directly impact on the long-term relationship orientation, and indirectly influence the latter by the medium of customer satisfaction. Second, social benefits directly influence the long-term relationship orientation, without exerting any indirect effects on the latter via customer satisfaction. Third, special treatment benefits do not directly impact on the long-term relationship orientation but have indirect effects on the latter by the medium of customer satisfaction. Fourth, customer satisfaction has positive effects on the long-term relationship orientation. The findings suggest credit unions should establish a long-term relationship with their customers by providing them with confidence benefits to earn their trust and confidence, with social benefits to build a relationship of affinity and friendship, and with special treatment benefits to meet their needs in the long, not short and temporary, term.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.301-308
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• 2018

This study explores an analytical mathematical model designed to estimate the optimal debt ratio of the Korean automobile industry, which has a more significant effect on the national economy than that of other industries, and attempts to estimate the optimal debt ratio based on objective data. The analytical model is based on ROA and ROE which uses the debt ratio as an independent variable and employs ROS, TAT, and NFCL as the related parameters. Regarding the NFCL, the optimal debt ratio is usually defined as the debt ratio that maximizes the ROA and ROE and is calculated using analytical procedures, such as by adding an equation that considers the debt ratio and the linearity relationship to the analytical model. This is because the optimal debt ratio can be calculated reliably by making use of an estimated value within a certain range, which is derived from more than two calculations rather than a single estimation starting from one calculation formula. In this study, for the estimation of the optimal debt ratio, the ROA and ROE are expressed as a quadratic equation with the debt ratio as the independent variable. Using this analysis procedure, the optimal debt ratio obtained using the data from the Korean automobile industry over a sixteen year period, which would optimize the profitability of the Korean automobile industry, was found to be 188% of the debt ratio in the ROA and 213% of the debt ratio in the ROE. This result was obtained by overcoming the problem of the reliability of the estimation value in spite of the limitations of the logical theory of this study, and can be interpreted as meaning that maintaining a debt ratio of 188% to 213% can enhance the profitability and reduce the risks in the Korean automobile industry. Furthermore, this indicates that the existing debt ratio of the Korean automobile industry is lower than the optimal value within the estimated range. Consequently, it is necessary for corporations to change their future debt ratio policies, given that the purpose of debt ratio management is to maintain safety and increase profitability, and to take into account the characteristics of the specific industry.

• Archives of design research
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• v.18 no.1 s.59
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• pp.91-104
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• 2005

In the past, the design education focused on the technique and skill to satisfy the production and consumption activities of a corporation based on beauty and practicality in the industrial age. Now, it's time to switchover to a life-quality enhancing education by harmonizing and meeting the public's physical and mental needs because design education is a character education which enhances the quality of life by uplifting people's aesthetic sense. This paper has emphasized on the importance of public education of design through the theoretical investigation on social environmental changes caused by the emergence of information society,,education problems, public education, and the necessity of design education. The reason why this study should be done has been suggested by investigating the necessity of this research and bringing up the issue. Furthermore, the current status and problems of public education on design have been analyzed. Then, based on the result, the development direction of design education has been suggested. This study can be concluded as follows: First, the design education should change from its vertical structure to a horizontal one. It should be widely spread to the public, getting off from its privatization for a certain group. Second, designers and the public should correct their way of thinking about design. The ordinary people as well as the designers should cultivate their capability to find and take care of design related issues in their everyday lives. Third, all people should be the subject of design education for the public. As a part of cultural education on the public's aesthetic sense, design education should be reborn as a field of study in which a sound public culture can be developed by the integration of human life and culture, exceeding the limit of school curriculum.

• Cartoon and Animation Studies
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• s.44
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• pp.85-116
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• 2016

This is the in-depth research dealing with Animatoon, the only animation-specialized magazine in Korea. By examining articles provided under the 'Animatoon Report' category, which is one of article categories set by the publisher, this research tries to find out the topic of articles and examine the tendency of topic. 'Animatoon Report' is chosen because the category title does not clearly show characteristics of articles, but has the second largest number of articles among all categories. First, the articles of the first ten years (1995-2005) has the largest number of pages as well as images, which means each article of this period tries to enrich its contents. Second, the role of magazine reporters are not critical considering the number of articles written by reporters are smaller than those made by the editorial department. Third, articles tries to deal with diverse issues and are mostly placed in front of the magazine. Fourth, in early days, articles used to provide the 3~5 lines of introductory summaries, but changed into provide the lead, the Korean and English subtitle, and so on. Fifth, articles mostly focus on issues of animation and Korea rather than other areas and countries. The results on the basis of article type are as follows. Among the types of people, work, organization/company, event, policy/industry, and etc, the policy/industry type has the largest amount of articles, and articles on the policy and those on the industry shows similar number of articles. Second, the event type has the second largest number of articles even though there are several separate categories only for the event. Third, articles in the et cetera type are often seen in early days because Animatoon who did not systemize the company itself focused on animation history and production techniques. Fourth, articles both on the people and the work type are consistently seen through the whole time period, but those on organization/company and event has more and more articles as time passes. In conclusion, it is possible to mention that the 'Animatoon Report' type shows more interest in policy and industry, and its interest on both issues are consistently seen from 2001 to 2015.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.1-17
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• 2012

Personalized smart devices such as smartphones and smart pads are widely used. Unlike traditional feature phones, theses smart devices allow users to choose a variety of functions, which support not only daily experiences but also business operations. Actually, there exist a huge number of applications accessible by smart device users in online and mobile application markets. Users can choose apps that fit their own tastes and needs, which is impossible for conventional phone users. With the increase in app demand, the tastes and needs of app users are becoming more diverse. To meet these requirements, numerous apps with diverse functions are being released on the market, which leads to fierce competition. Unlike offline markets, online markets have a limitation in that purchasing decisions should be made without experiencing the items. Therefore, online customers rely more on item-related information that can be seen on the item page in which online markets commonly provide details about each item. Customers can feel confident about the quality of an item through the online information and decide whether to purchase it. The same is true of online app markets. To win the sales competition against other apps that perform similar functions, app developers need to focus on writing app descriptions to attract the attention of customers. If we can measure the effect of app descriptions on sales without regard to the app's price and quality, app descriptions that facilitate the sale of apps can be identified. This study intends to provide such a quantitative result for app developers who want to promote the sales of their apps. For this purpose, we collected app details including the descriptions written in Korean from one of the largest app markets in Korea, and then extracted keywords from the descriptions. Next, the impact of the keywords on sales performance was measured through our econometric model. Through this analysis, we were able to analyze the impact of each keyword itself, apart from that of the design or quality. The keywords, comprised of the attribute and evaluation of each app, are extracted by a morpheme analyzer. Our model with the keywords as its input variables was established to analyze their impact on sales performance. A regression analysis was conducted for each category in which apps are included. This analysis was required because we found the keywords, which are emphasized in app descriptions, different category-by-category. The analysis conducted not only for free apps but also for paid apps showed which keywords have more impact on sales performance for each type of app. In the analysis of paid apps in the education category, keywords such as 'search+easy' and 'words+abundant' showed higher effectiveness. In the same category, free apps whose keywords emphasize the quality of apps showed higher sales performance. One interesting fact is that keywords describing not only the app but also the need for the app have asignificant impact. Language learning apps, regardless of whether they are sold free or paid, showed higher sales performance by including the keywords 'foreign language study+important'. This result shows that motivation for the purchase affected sales. While item reviews are widely researched in online markets, item descriptions are not very actively studied. In the case of the mobile app markets, newly introduced apps may not have many item reviews because of the low quantity sold. In such cases, item descriptions can be regarded more important when customers make a decision about purchasing items. This study is the first trial to quantitatively analyze the relationship between an item description and its impact on sales performance. The results show that our research framework successfully provides a list of the most effective sales key terms with the estimates of their effectiveness. Although this study is performed for a specified type of item (i.e., mobile apps), our model can be applied to almost all of the items traded in online markets.

• 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.