• Fashion & Textile Research Journal
• /
• v.18 no.1
• /
• pp.15-26
• /
• 2016

Many brands are attempting to use consumers as a part of their marketing strategies, due to the fashion industry's sensitive response to consumers' reaction. In addition, due to the popularity of e-WOM(electronic Word-Of-Mouth), fashion brands are highly sensitive to their supporters' online reviews. Amid this background, the main objectives of this study are as follows: 1) to analyze the effect of online reviews' attributes and valences on forming an impression about a fashion brand; 2) to examine the online re-WOM(word-of-mouth) effect of online reviews by fashion brand supporters on brand attitude; and 3) to measure the moderating effect of fashion involvement in online re-WOM intention. In order to verify the research model and to test the proposed hypotheses, a 2 (utilitarian vs. hedonic review attributes) by 2 (positive vs. negative review valences) model is constructed and gathers 215 respondents. The results demonstrate that consumers form the highest reliable impression based on utilitarian and negative online reviews. However, there is no relationship between the types of online reviews and the formation of a favorable impression. Findings also reveal that the impression formed by online reviews has a positive effect on re-WOM intention, contributing to brand attitude. In addition, the hypothesis about the moderating effect produced by fashion involvement on re-WOM is supported. In conclusion, these results suggest that online reviews by fashion brand supporters have a powerful effect on forming a consumer's impression towards a fashion brand, affecting re-WOM intention and brand attitude.

• Smart Media Journal
• /
• v.9 no.2
• /
• pp.69-77
• /
• 2020

Unlike the past, which was limited to terrestrial broadcasts, many dramas are currently being broadcast on cable channels and the Internet web. After watching the drama, viewers actively express their opinions through reviews and studies related to the analysis of these reviews are actively being conducted. Due to the nature of the drama, the genre is not clear, and due to the various age groups of viewers, reviews and ratings from other viewers help to decide which drama to watch. However, since it is difficult for viewers to check and analyze many reviews individually, a data analysis technique is required to automatically analyze them. Accordingly, this paper classifies the topics of reviews that have an important influence on drama selection and reclassifies them into semantic topics according to the similarity of words. In addition, we propose a model that classifies reviews into sentences according to semantic topics and sentiment analysis through sentiment words.

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

• Knowledge Management Research
• /
• v.20 no.2
• /
• pp.25-42
• /
• 2019

AI speakers which are wireless speakers with smart features have released from many manufacturers and adopted by many customers. Though smart features including voice recognition, controlling connected devices and providing information are embedded in many mobile phones, AI speakers are sitting in home and has a role of the central en-tertainment and information provider. Many surveys have investigated the important factors to adopt AI speakers and influ-encing factors on satisfaction. Though most surveys on AI speakers are cross sectional, we can track customer attitude toward AI speakers longitudinally by analyzing customer reviews on AI speakers. However, there is not much research on the change of customer attitude toward AI speaker. Therefore, in this study, we try to grasp how the attitude of AI speaker changes with time by applying text mining-based analysis. We collected the customer reviews on Amazon Echo which has the highest share of AI speakers in the global market from Amazon.com. Since Amazon Echo already have two generations, we can analyze the characteristics of reviews and compare the attitude ac-cording to the adoption time. We identified all sub topics of customer reviews and specified the topics for smart features. And we analyzed how the share of topics varied with time and analyzed diverse meta data for comparisons. The proportions of the topics for general satisfaction and satisfaction on music were increasing while the proportions of the topics for music quality, speakers and wireless speakers were decreasing over time. Though the proportions of topics for smart fea-tures were similar according to time, the share of the topics in positive reviews and importance metrics were reduced in the 2nd generation of Amazon Echo. Even though smart features were mentioned similarly in the reviews, the influential effect on satisfac-tion were reduced over time and especially in the 2nd generation of Amazon Echo.

• Information Systems Review
• /
• v.23 no.1
• /
• pp.115-134
• /
• 2021

Recently, the amount of money that foreigners buy from online shopping sites in Korea has been increasing, especially by Chinese consumers. In this study, we researched the effects of Chinese consumers' reviews, inquiries, and bargains on loyalty, and how these effects differ by gender so that Korean online sellers can take advantage of these opportunities. In order to verify the research model, a survey was conducted on Chinese consumers with online purchasing experience and 231 valid samples were collected and analyzed. As results, reviews, inquiries, and bargaining had the positive impacts on the loyalty of Chinese consumers. The impact of reviews on loyalty was higher in women, and the impact of inquiries and bargains on loyalty was higher in men. This study can help Korean online sellers effectively respond to Chinese consumers' reviews, inquiries, and bargains needs. This study, also, can help they understand and deal with the difference between the effect on reviews to women and the effect of inquiries and bargaining to men.

• The Journal of Society for e-Business Studies
• /
• v.16 no.4
• /
• pp.125-137
• /
• 2011

Product reviews in online shopping sites can serve as a useful guideline to buying decisions of customers. However, due to the massive amount of such reviews, it is almost impossible for users to read all the product reviews. For this reason, e-commerce sites provide users with useful reviews or statistics of ratings on products that are manually chosen or calculated. Opinion mining or sentiment analysis is a study on automating above process that involves firstly analyzing users' reviews on a product to tell if a review contains positive or negative feedback, and secondly, providing a summarized report of users' opinions. Previous researches focus on either providing polarity of a user's opinion or summarizing user's opinion on a feature of a product that result in relatively low usage of information that a user review contains. Actual user reviews contains not only mere assessment of a product, but also dissatisfaction and flaws of a product that a user experiences. There are increasing needs for effective analysis on such criteria to help users on their decision-making process. This paper proposes a model that stores various types of user reviews in a data warehouse, and analyzes integrated reviews dynamically. Also, we analyze reviews of an online application shopping site with the proposed model.

• Information Systems Review
• /
• v.23 no.1
• /
• pp.45-68
• /
• 2021

As the influence of online reviews on consumer decision-making increases, concerns about review manipulation are also increasing. Fake reviews or review manipulations are emerging as an important problem by posting untrue reviews in order to increase sales volume, causing the consumer's reverse choice, and acting at a high cost to the society as a whole. Most of the related prior studies have focused on predicting review manipulation through data mining methods, and research from a consumer perspective is insufficient. However, since the possibility of manipulation of reviews perceived by consumers can affect the usefulness of reviews, it can provide important implications for online word-of-mouth management regardless of whether it is false or not. Therefore, in this study, we analyzed whether there is a difference between the review evaluated by the consumer as being manipulated and the general review, and verified whether the manipulated review negatively affects the review usefulness. For empirical analysis, 34,711 online book reviews on the LibraryThing website were analyzed using multilevel logistic regression analysis and Poisson regression analysis. As a result of the analysis, it was found that there were differences in product level, reviewer level, and review level factors between reviews that consumers perceived as being manipulated and reviews that were not. In addition, manipulated reviews have been shown to negatively affect review usefulness.

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

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.7 no.1
• /
• pp.247-262
• /
• 1994

This study is concerned with analysis of all the reviews published by the reviewing periodicals, The Book Review Culture and The Korean Publishing Journal, from 1991 to 1993. The result of analysis for 736 reviews are followed： 1) The percentage of reviews in the field of philosophy & religion, literature ＆ language, science ＆ technology is lower than the percent-age of books published. But in the field of history and social science the reviewing is proportionately higher than the publishing. 2) Book reviews are prepared by professors, literary reviewers, researchers, and experts in the particular subject field except librarian. 3) Basic elements of reviewing are the career and view point of author, trends of suject field, content, value, omissions, limitations, and format of book, reader's level, etc. Ideal method of book criticism may be summarized as follows： 1) The criterion of book selection are the book's value, the social . demand, and the proportion of titles published. 2) For the unbiased criticism, it should be written by the experienced librarian rather than the experts of particular subject field. 3) Book criticism need to provide not only guide to new books but also interpretation and evaluation about each book for its reader.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.44 no.2
• /
• pp.273-294
• /
• 2020

Considering the complex relationship between fashion curating and the critical approach of fashion exhibition reviews, this study explores the current state of fashion criticism in museology, focusing on fashion designer exhibition reviews of Fashion Theory. The author selected eighteen exhibition reviews of individual fashion designers' works from 1997 on to the current 2020 issues of Fashion Theory, which provides an interdisciplinary forum to analyze fashion as a cultural construction. The author performed a systematic review that qualitatively summarizes and/or synthesizes the findings of the studies on the topic with the process of a systematic review, such as key question formulation, analytic framework building, evidence mapping, critical appraisal, and evidence synthesis. The results of this study are as follows. First, the exhibition reviews included almost all stages of the inclusive fashion criticism model, based on an artifact study. Second, they reflected various critical discourses that offered current interpretations of historical and contemporary fashion. Third, they showed that fashion criticism in the museum context is the result of an interdisciplinary collaboration of various fashion agents. Finally, they offered a bridge for crossing the boundaries of various scholarly fields, as they combine multidisciplinary scholarship with object-based methods.