• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.362-367
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• 2009

온라인상의 쇼핑에서 사용후기에 관한 많은 연구가 진행 중이지만, 사용후기를 보는 원인에 관한 분석에 대해서는 아직 부족함으로 연구를 진행하였다. 온라인상이기 때문에 가지는 위험 중에서도 사용후기를 통해서 어떤 위험을 가장 많이 가지고 있는지에 대해 우선 알아볼 필요성이 있을 것 같다. 이의 연구결과 기능적 위험을 가장 크게 지각하고 있었기 때문에 사용후기를 보는 이유로서의 근거가 될 수 있을 것이다. 둘째, 의류에 관련된 논문들을 보면 온라인상에서 구매를 꺼려하는 이유가 직접 눈으로 보고 만질 수 없다는 기능적 위험을 가장 크게 가지고 있었다. 그렇기 때문에 대리 시용구매를 할 수 있는 사용후기를 이용하여 의류제품을 온라인상에서 구매하는 것이 영향을 미치는 것인지에 대해 알아보고자 한다. 본 연구 결과, 긍정적인 후기를 보고 구매하려는 의도가 나타났었고 부정적인 후기를 보고 구매하지 않으려하므로 사용후기가 구매함에 있어 영향을 미치고 있음을 알 수 있었다. 마지막으로 사용후기를 중심으로 메시지를 보고 메시지에 대한 태도와 제품에 대한 태도, 그리고 구매의도 뿐만 아니라 메시지의 유형에 따라서 구전 의도나 사이트 재방문 의도라는 구매 행동에도 차이가 날 것이라고 추측했다. 연구 결과를 보면 유형별로 각각 다르게 영향을 미치고 있었으며, 부정적인 메시지로 인해 제품에 대한 좋지 않은 태도를 가지게 됨으로써 제품을 구입하려는 사이트 재방문 의도는 나타나지 않았다.

• Management & Information Systems Review
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• v.33 no.4
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• pp.49-62
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• 2014

The current study extends previous research by investigating the role of shopping experience and product type within the direction of online reviews and information reliability and product attitude. To test the hypotheses, this study conducted experimental designs. Direction of online reviews and product type were manipulated as between-subject factors. Then participants were classified into high or low group based on their shopping frequency. Dependent variable was information reliability and product attitude. The results indicate that direction of online reviews have a significant effect on both information reliability and product attitude. In addition, consumers' shopping experience also shows a moderating effect between the direction of online reviews and the dependent variables. Furthermore, product type also shows a moderating effect on the information reliability, yet not on the product attitude. The results of this study contribute to the literature as a new attempt to examine the direction of online reviews in the online shopping area. We also indicated the limitations of this study, and suggested the future research directions.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.255-271
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• 2009

Since consumers have difficulty in acquiring information related to products in online, they are apt to use WOM(word-of-mouth). It seems to be more popular and acceptable methods to acquire information about products sold in online. In other words, consumers who visit the Internet shopping-mall can not make a purchase-decision immediately because they have no sufficient knowledge about products. To solve this problem, consumers make use of the service called "online review". The objective of this study is to verify how these reviews can influence attitude toward the message, product and several buying behaviors in the online. In particular, this study focus on the message's sidedness(positive or negative) and objectivity(objective or subjective), because it is expected that consumers are likely to behave differently according to the characteristics of online reviews. Thus, to measure consumer's attitude and buying behavior, this study was examined by 4 types of messages. The results of this study are as follows: First, in the positive-objective message, the message attitude has a stronger effect on purchase intention than other outcomes. Second, in the positive-subjective message, the message attitude has a stronger effect on revisiting intention than others. Third, in the negative-objective message, the message attitude has a stronger effect on purchase intention than others. Hence, it is said that online shopping-mall managers need to understand the effects of multidimensional online review.

• Asia Marketing Journal
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• v.13 no.3
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• pp.209-231
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• 2011

Internet is having strong impact on the consumer's decision making process. Information search has been done actively through internet today. The online reviews can be crucial information cue to evaluate the alternarive products. The online WOM(Word-Of-Mouth) effect depends on the characteristics of information sender, receiver, and WOM. This study is to examine the influence of the online word of mouth on the consumer purchase intention and the moderating role of product involvement, consumer regulatory focus and self-efficacy. Positive customer reviews on the products influence the purchase intention positively and negative customer reviews influence it negatively. Moderating role of involvement in the causal relation between the valence of online reviews and purchase intention is tested. In case of positive WOM, it is predicted that purchase intention for high involvement products is higher than that of low involvement. In case of negative WOM, purchase intention for high involvement product is lower than that of low involvement product. And this study invetigate the moderating role of regulatory focus. In case of positive WOM, it is predicted that promotion focus oriented consumers have higher purchase intention than prevention focus oriented consumers. In case of negative WOM, prediction is that prevention focus oriented consumers have lower purchase intention than promotion focus oriented consumers. Then we examine the moderating role of self efficacy in the causal relation between the valence of online reviews and purchase intention. In case of positive WOM, it is predicted that consumers with low self efficacy have higher purchase intention than consumers with high self efficacy. In case of negative WOM, it is predicted that consumers with low self efficacy have lower purchase intention than consumers with high self efficacy. Emprical results support our prediction and four hypotheses derived from our conceptual framework are all accepted. This study suggest that the level of product involvement, consumer regulatory focus and the level of self-efficacy influence the consumer responses of the valence of online reviews. Therefore marketers need to manage online reviews based on the level of product involvement, regulatory focus orientation and the level of self-efficacy of target consumers.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• International Commerce and Information Review
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• v.17 no.3
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• pp.3-27
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• 2015

As hostile online reviews can have a negative impact on a company's reputation, it is not surprising that online reviewers and business owners often get involved in conflicts which sometimes evolve into legal disputes. This research examines the legal dispute case in which the business owner charges an online reviewer for a defamation. Further, this research compares the supreme court's decision with general public's view on this defamation case, using a survey method. From the legal point of view, an online reviewer's primary motive determines whether the online reviews are defamatory statements or not. Specifically, if an online reviewer's primary motive is to increase the overall benefits for the public society, the online review does not bear any legal liability. According to our survey, consumers' view aligns with the final decision of the supreme court. They believe that online reviews should bear a minimum level of legal liability as online reviews often contain useful and valuable information which can enhance overall public benefits.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.265-267
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• 2009

디지털 제품 구매자는 일반적으로 온라인을 통하여 제품 웹사이트에서 제품의 특징이나 사용 후기를 충분히 보고 제품을 구입한다. 그리고 제품을 구입 후에 사용자는 온라인에서 제품의 매뉴얼을 통하여 익힌다. 이러한 과정에서 본 연구자는 사용자들의 온라인상에서 제품 구매 전, 후에서 문제점을 발견하고 확실히 어떠한 요구사항이 존재할 것이라는 의문을 가졌다. 따라서 다양한 일반인 연령대를 구성한 340명을 대상으로 디지털 제품의 전달 매체 사용에 대한 온라인 설문조사를 실시하였다. 설문문항 내용에서 우선적 대안으로 예상한 것들은 '데스크탑 가상현실'과 '멀티미디어 동영상' 매체들이다. 그리고 사용자들이 이것들을 새로운 매체로서 가장 요구하는 사항일 것이라는 추측을 하고 현황을 파악한다. 최종적으로는 사용자가 요구하는 제품에서 매체의 기능과 만족도를 조사하고 개선점을 파악하며 문제점에 대한 해결 대안의 기초 자료로서 제시하고자 한다.

• Korean Journal of Human Ecology
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• v.18 no.5
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• pp.1063-1075
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• 2009

This study intends to provide foundational data for enhancing the welfare of customers purchasing digital products through analyzing the notes from written on-line reviews. The data used for the analysis are 6,342 on-line reviews for cell phones and digital cameras released from November, 2007 until April, 2008, which was posted on Naver Knowledge Shopping from November, 2007 until June, 2008. Through the on-line reviews, this article analyzed the evaluations on the digital products' hardware, software, design, service, price, and other criteria and the customers' emotional experience in the process of purchase, use, and possession. According to the results of the analysis, negative evaluation and emotional experience were originated from the company's information provision methods and purchase process. In addition, insufficient information searches in the process of online purchases, consumers' low right consciousness, and impolite on-line reviews were also problematic. Customers' evaluations and emotional experiences on digital products were conducted in a complex way. Based on that, this research makes suggestions in the company's marketing, customer education, and theoretical aspect.

• Information Systems Review
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• v.17 no.3
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• pp.95-111
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• 2015

The recommendation system automatically provides the predicted items which are expected to be purchased by analyzing the previous customer behaviors. This recommendation system has been applied to many e-commerce businesses, and it is generating positive effects on user convenience as well as the company's revenue. However, there are several limitations of the existing recommendation systems. They do not reflect specific criteria for evaluating products or the factors that affect customer buying decisions. Thus, our research proposes a collaborative recommendation model algorithm that utilizes each customer's online product reviews. This study deploys topic modeling method for customer opinion mining. Also, it adopts a kernel-based machine learning concept by selecting kernels explaining individual similarities in accordance with customers' purchase history and online reviews. Our study further applies a multiple kernel learning algorithm to integrate the kernelsinto a combined model for predicting the product ratings, and it verifies its validity with a data set (including purchased item, product rating, and online review) of BestBuy, an online consumer electronics store. This study theoretically implicates by suggesting a new method for the online recommendation system, i.e., a collaborative recommendation method using topic modeling and kernel-based learning.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.763-766
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• 2019

최근 사람들의 삶의 질이 향상됨에 따라 기호품인 와인의 수요가 늘어나고 있다. 그러나 와인은 생산하는데 길게는 수십 년이 걸리는 고가의 제품이므로 소비자가 와인과 잘못 구매했을 때의 기회비용이 크다. 본 논문에서는 전문 와인 테이스터 들의 후기 빅 데이터를 활용하여 딥러닝 기반 추천시스템을 개발을 다룬다. 테이스터 들의 후기 빅 데이터에 대해 Apache Pig와 자연어 처리를 통한 전 처리 과정을 수행해 리뷰 별로 특징 벡터를 구성하고, 하이퍼 매개변수 최적화와 조기 종료 기법을 사용해 데이터에 대하여 최적의 딥러닝 분류기를 구성하였다. 마지막으로, 구성된 시스템의 신뢰도를 검증하기 위해서 딥러닝의 정확도와 오차율을 확인하였고 시스템이 추천한 와인을 시각화 이미지와 비교하여 성능을 검증하였다.