• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.67-88
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• 2019

Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.

• The KIPS Transactions:PartB
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• v.19B no.4
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• pp.231-236
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• 2012

According to consumer behavior theory, human propensity can be divided into two regulatory focus types: promotion and prevention. These two types have much influence on the consumer's decision in many diverse areas. In this research, we apply regulatory focus theory to personalized recommendation to minimize the cold start problem and to improve the performance of recommendation algorithms. To achieve this goal, we extract the consumer behavior variables and information exploration activity index from web shopping logs. We then use them for classifying regulatory focus of the consumer. This research has the contribution to show the possibility of systematization of consumer behavior theory as an interdisciplinary research tool of social science and information technology. Based on this attempt, we will extend the research to IT services adapting theories on other areas.

• Information Systems Review
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• v.25 no.4
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• pp.67-87
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• 2023

Many online shopping sites now offer personalized recommendation systems to improve consumers' shopping experiences by lowering costs (time, cost, etc.), catering to consumers' tastes, and stimulating consumers' potential shopping needs. So far, domestic and foreign research on the personalized recommendation system has mainly focused on the field of computer science, which is advantageous for obtaining accurate personalized recommendation results for users but difficult to continuously track the users' psychological states or behavioral intentions. This study attempted to investigate the effect of the characteristics of the personalized recommendation system in the online shopping environment on consumer perception and purchase intention for consumers using the Stimulus-Organism-Response (S-O-R) model. The analysis results adopted all hypotheses on the effect of the quality of the personalized recommendation system and information quality on trust and perceived value. Through the empirical results of this study, the factors influencing consumers' use of personalized recommendation system can be identified. In order to increase more purchase, online shopping companies need to understand consumers' tastes and improve the quality of the personalized system by improving the recommendation algorithm thus to provide more information about products.

• The Journal of the Korea Contents Association
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• v.10 no.7
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• pp.23-30
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• 2010

It is important for the strategy of cosmetic sales to investigate the sensibility and the preference degree in the environment that the makeup style has been changed focusing on the consumer center. We proposed the human sensibility ergonomics makeup recommendation system (MakeupRS) using the context sensor information applying the collaborative filtering technique as one of methods in the makeup style development centered on the consumer's sensibility and the preference. In the collaborative filtering technique, the Pearson correlation coefficient applying to the case amplification is used to calculate similarity weights between the users. To investigate the sensibility according to the effect of makeup styles, the makeup styles were analyzed in terms of 6 style factors, such as, the foundation, the color lens, the eye shadow, the eye lash, the cheek brusher, and the lipstick. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the human sensibility ergonomics makeup recommendation system.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.7
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• pp.816-827
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• 2011

There is an increasingly fierce competition in the current fashion industry due to equalized technology, a shortened fashion cycle and changing lifestyle; however, it is not easy to map out successful marketing strategies that influence the outcome of business administration. This study discussed the importance of changing environments for the fashion industry and of CSR activities. The findings of the study were as follows. First, consumers who found the fashion company to perform more appropriate CSR activities rated its CSR activities more favorably. Second, consumers who considered the company's CSR activities more suitable for themselves viewed the CSR activities more favorably. Third, consumers who rated a fashion company's CSR activities more favorably showed a more favorable attitude to the company. Fourth, consumers who viewed a fashion company's CSR activities more favorably had a greater intention to recommend the company. Fifth, consumers who viewed a fashion company's CSR activities more favorably had a more buying intention for the company. Sixth, the consumers who took a more favorable attitude to a fashion company had a stronger recommendation intention for that fashion company. Seventh, the consumers who showed a more favorable attitude to a fashion company had a bigger buying intention. Eighth, the consumers who had a greater recommendation intention for a fashion company had an increased buying intention as well.

• 전자공학회논문지 IE
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• v.43 no.1
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• pp.67-72
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• 2006

According to the growth of wireless networks, and the spread of mobile devices, the provision of recommender services to help consumers find items to purchase with the use of the suited contexts is an important issue in mobile commerce. In this paper, we propose a proactive mobile commerce service that enables a consumer to obtain relevant information efficiently by using differentiated recommendation in context-aware environment. This paper describes the recommendation method and presents grocery shopping application prototype that implement the method. Several experiments are performed and the results verify that the proposed method's recommendation performance is better than other existing methods.

• Fashion & Textile Research Journal
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• v.23 no.2
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• pp.200-211
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• 2021

This study examines the effects of fashion influencers' body types (realistic versus ideal body types) on self-expression, self-representation, and recommendation intentions, as mediated by familiarity toward influencers. Although fashion influencers lead to a positive consumer response compared to traditional advertisements, previous research on the effects of fashion influencers on consumers is limited. Thus, this study tests the role of consumers' socio-psychological aspects in understanding how and why fashion influencers affect consumers' behavioral intentions associated with self-expression, self-representation, and influencer recommendation. A total of 180 women in their 20s and 30s participated in the survey. The responses were collected after showing them stimuli featuring fashion influencers with either ideal or realistic body shapes. The data were analyzed using SPSS18.0 for descriptive statistics, and AMOS 18.0 for confirmatory factor analysis and structural equation modeling. The results showed that participants who were shown realistic body types perceived familiarity, which generated positive effects on self-expression, self-representation, and recommendation intentions. Hence, the effects of influencers' body types on recommendation intention are mediated by familiarity. Self-expression and self-representation intentions also increase influencer recommendation intention. Comparatively, participants who were shown ideal body types only induced higher self-representation intention, which increased their recommendation intention. The current findings can help fashion marketers select the appropriate influencers who fit their target customers as promotional models, as well as to induce changes in consumers' behavioral intention.

• Journal of the Korea Fashion and Costume Design Association
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• v.24 no.2
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• pp.59-72
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• 2022

The online fashion market in the 21st century has shown rapid growth. Against this backdrop, using consumer activity data to provide customized customer services has emerged as a viable business model that draws attention. Algorithm-based personalized recommendation services are a good example. But their application in fashion products has clear limitations. It is not easy to identify consumers' perceptions of the attributes of fashion, which are various, hard to define, and very sensitive to trends. So there is a need to compile data on consumers' underlying awareness and to carry out defined research to increase the utilization of such services in the fashion industry and further engage consumers. This research aims to classify the attributes and types of fashion products and to identify consumers' perceptions of a given situation where a recommendation service is offered. To find out consumers' perceptions of and satisfaction with recommendation services, an online and mobile survey was conducted on women in their 20s and 30s, a group that uses recommendation services frequently. A total of 455 responses were used for analysis. SPSS 28.0 was used, combined with Conjoint Analysis and multiple regression, to analyze data. The study results could provide insights into a better understanding of recommendation services and be used as basic data for companies to identify consumers' preferences and draw up a detailed strategy for market segmentation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.93-97
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• 2002

In this paper, we propose personalized recommendation techniques based on multidimensional scaling (MDS) method for Business to Consumer Electronic Commerce. The multidimensional scaling method is traditionally used in marketing domain for analyzing customers' perceptional differences about brands and products. In this study, using purchase history data, customers in learning dataset are assigned to specific product categories, and after then using MDS a positioning map is generated to map product categories and alternative advertisements. The positioning map will be used to select personalized advertisement in real time situation. In this paper, we suggest the detail design of personalized recommendation method using MDS and compare with other approaches (random approach, collaborative filtering, and TOP3 approach)

• Agribusiness and Information Management
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• v.5 no.2
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• pp.27-37
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• 2013

Referral marketing plays an important role in promoting new products. When it comes to innovative agricultural products, early adopter's review or recommendation has a more critical impact on follower's purchase decision making. Hence, understanding of consumer's characteristics and needs play more important role in success of innovation. More particularly, other researchers pay attention to the role of consumer innovativeness. This study attempts to fill this gap in knowledge between innovative propensity of consumer and her/his intention to generate positive word of mouth about new agricultural products. Furthermore, in this paper, we adopt Vandecasteele and Geunes' motivated consumer innovativeness model to investigate consumer innovativeness in extrinsic motive and intrinsic motive level, and examine the moderating role of referral efficacy. For empirical verification, survey method is used for data collection. Partial least square (PLS) is adopted to analyze the data. Finally, several theoretical contributions and practical implications are discussed.