• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.207-218
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• 2020

Recently, due to the increase of online reviews and the development of analysis technology, the interest and demand for online review analysis continues to increase. However, previous studies have not considered the emotions contained in each vocabulary may differ from one reviewer to another. Therefore, this study first classifies the customer group according to the customer's grade, and presents the result of analyzing the difference by performing review analysis for each customer group. We found that the price factor had a significant influence on the evaluation of products for customers with high ratings. On the contrary, in the case of low-grade customers, the degree of correspondence between the contents introduced in the mall and the actual product significantly influenced the evaluation of the product. We expect that the proposed methodology can be effectively used to establish differentiated marketing strategies by identifying factors that affect product evaluation by customer group.

• The Journal of Industrial Distribution & Business
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• v.14 no.1
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• pp.21-28
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• 2023

Purpose: This study aims to analysis the difference by Michelin rating in customer satisfaction of restaurant listed in the Korea Michelin Guide. There are opinions that the Michelin Guide's rating system and evaluation criteria are somewhat ambiguous. Research design, data, and methodology: This study collected 145 actual online reviews published on TripAdvisor to examine how the effect of the content attributes of reviews on consumer satisfaction varies according to the Michelin grade. Based on this, two studies were conducted. Study 1 examined the effect of strong and weak positive reviews on consumer satisfaction according to the rating. Study 2 examined the effect of image information on consumer satisfaction. Results: The results revealed that the lower the Michelin rating, the more positive review had a significant effect on consumer satisfaction. The higher the rating, the more image information had an effect on consumer satisfaction. Expectations for Michelin three-star restaurants are higher than those of two-star restaurants, so customers are more likely to be used negatively when writing reviews. Conclusions: Accurate information on Michelin selection criteria should be delivered so as not to form high expectations and not to disappoint. For consumers to be satisfied with the name Michelin, the standards should be stricter.

• Information Systems Review
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• v.6 no.2
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• pp.243-268
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• 2004

The current e-CRM has been used in various types of e-business. Since the study of e-CRM for the promotion of online community sites are rarely studied, we attempt to analyze the case of broadcasting and suggest the promotion model focusing on the characteristic factors for a successive online community. That is, as a result of analyzing the online community cases for broadcasting, we know that the Internet community site of broadcasting has grown in the order of contents, community and then commerce. According to the case analysis, we have presented an e-CRM promotion model consisting of four phases: customer attraction, customer maintenance, customer enhancement, and customer activation. The e-CRM model suggested in this study may be used as a theoretical basis and practical guideline for further research in relation to e-CRM and e-business.

• Knowledge Management Research
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• v.24 no.4
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• pp.153-176
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• 2023

Generative AI, especially conversational AI like ChatGPT, has recently gained traction as a technological alternative for automating customer service. However, there is still a lack of research on whether current generative AI technologies can effectively replace traditional human managers in customer service automation, and whether they are advantageous in some situations and disadvantageous in others, depending on the conditions and environment. To answer the question, "Can generative AI replace human managers in customer service activities?", this study conducted experiments and surveys on customer online reviews of a food delivery platform. We applied the perspective of the elaboration likelihood model to generate hypotheses about whether there is a difference between positive and negative online reviews, and analyzed whether the hypotheses were supported. The analysis results indicate that for positive reviews, generative AI can effectively replace human managers. However, for negative reviews, complete replacement is challenging, and human managerial intervention is considered more desirable. The results of this study can provide valuable practical insights for organizations looking to automate customer service using generative AI.

• Fashion & Textile Research Journal
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• v.16 no.1
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• pp.79-90
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• 2014

With the development of modern society, not only have the Internet and e-commerce been progressed but they also made 'consumption patten' diverse. Despite the internet clothing market growth, there is critical a disadvantage, which is consumers is not able to wear the products presented via online pictures. Thus, pictures on the internet are the only information customers can get, which has caused consciousness on the importance of dealing with 'customer review'. In spite of the fact that 'customer review' has undeniably evolved to be one of customers' essential requisites, the research on this subject is very limited. Until now, the studies on the internet shopping consumers' behavior mostly has to do with the features of 'customer review' such as 'a sense of exaggeration', 'usability', 'duality', 'purity', 'professionalism', 'reliability', and the 'similarity', etc.) Therefore, this study categorizes the characteristics of online shopping reviews to 'the number of reviews', 'the article-length', 'the existence of photos', 'the rewards for reviews', 'the contents of the reviews' and 'the freshness of the reviews' and reviews the impact of an features of 'customers' reviews' affecting the internet shopping sales promotion. Moreover, it is to contribute to the marketing strategies of a shopping mall by analyzing consumers' 'purchasing satisfaction', 'the intention of repurchasing', and 'the factors of viral marketing'.

• Smart Media Journal
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• v.2 no.2
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• pp.20-27
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• 2013

The concept of social media is top of the agenda for many business executives and decision makers, as well as consultants try to identify ways where companies can make profitable use of applications such as Netflix, Flixster. The social media is playing an increasingly important role as the information sources for customers making product choices etc. With the flourish of Web 2.0 technology, customer reviews are becoming more and more useful and important information resources for people to save their time and energy on purchasing products that they want. This paper proposes the Bayesian Probabilistic Classification algorithm to mine the social media review, and evaluates it by different splits and cross validation mechanism from the real data set. The explored study experimental results show the robustness and effectiveness of proposed approach for mining the social media review.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.43-61
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• 2016

Customer reviews help potential customers make purchasing decisions. However, the prevalence of reviews on websites push the customer to sift through them and change the focus from a mere search to identifying which of the available reviews are valuable and useful for the purchasing decision at hand. To identify useful reviews, websites have developed different mechanisms to give customers options when evaluating existing reviews. Websites allow users to rate the usefulness of a customer review as helpful or not. Amazon.com uses a ratio-type helpfulness, while Yelp.com uses a count-type usefulness index. This usefulness index provides helpful reviews to future potential purchasers. This study investigated the effects of sentiment and readability on useful votes for customer reviews. Similar studies on the relationship between sentiment and readability have focused on the ratio-type usefulness index utilized by websites such as Amazon.com. In this study, Yelp.com's count-type usefulness index for restaurant reviews was used to investigate the relationship between sentiment/readability and usefulness votes. Yelp.com's online customer reviews for stores in the beverage and food categories were used for the analysis. In total, 170,294 reviews containing information on a store's reputation and popularity were used. The control variables were the review length, store reputation, and popularity; the independent variables were the sentiment and readability, while the dependent variable was the number of helpful votes. The review rating is the moderating variable for the review sentiment and readability. The length is the number of characters in a review. The popularity is the number of reviews for a store, and the reputation is the general average rating of all reviews for a store. The readability of a review was calculated with the Coleman-Liau index. The sentiment is a positivity score for the review as calculated by SentiWordNet. The review rating is a preference score selected from 1 to 5 (stars) by the review author. The dependent variable (i.e., usefulness votes) used in this study is a count variable. Therefore, the Poisson regression model, which is commonly used to account for the discrete and nonnegative nature of count data, was applied in the analyses. The increase in helpful votes was assumed to follow a Poisson distribution. Because the Poisson model assumes an equal mean and variance and the data were over-dispersed, a negative binomial distribution model that allows for over-dispersion of the count variable was used for the estimation. Zero-inflated negative binomial regression was used to model count variables with excessive zeros and over-dispersed count outcome variables. With this model, the excess zeros were assumed to be generated through a separate process from the count values and therefore should be modeled as independently as possible. The results showed that positive sentiment had a negative effect on gaining useful votes for positive reviews but no significant effect on negative reviews. Poor readability had a negative effect on gaining useful votes and was not moderated by the review star ratings. These findings yield considerable managerial implications. The results are helpful for online websites when analyzing their review guidelines and identifying useful reviews for their business. Based on this study, positive reviews are not necessarily helpful; therefore, restaurants should consider which type of positive review is helpful for their business. Second, this study is beneficial for businesses and website designers in creating review mechanisms to know which type of reviews to highlight on their websites and which type of reviews can be beneficial to the business. Moreover, this study highlights the review systems employed by websites to allow their customers to post rating reviews.

• Journal of Information Technology Applications and Management
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• v.14 no.2
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• pp.129-149
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• 2007

The purpose of this study is to examine the effect of relationship orientation factors on customer satisfaction and loyalty in Internet shopping malls. Based on previous exploratory work and a review of the literature of relationship marketing, six key factors of relationship orientation construct are identified: trust, bonding, communication. shared value. empathy and reciprocity. And a conceptual model is developed and seven research hypotheses are empirica1ly examined using structural equation modelling. The results show that bonding, shared value and reciprocity has statistically significant effect on the trust of online customers and trust has a positive influence on customer satisfaction and loyalty in Internet shopping malls. Theoretical. managerial and research implications are discussed.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.7
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• pp.761-774
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• 2011

This study investigated the consumer review information considered important by consumers when making a purchase decision to buy apparel products online. Data were collected through focus group interviews. Eleven females in their 20s and 30s, who have extensive experience in reading consumer reviews posted on online apparel stores, participated in the study. The consumer review information considered important by participants is the information related to seven product attributes (size, fabric, design, color, sewing, price, and country of origin), seven benefits (functional, financial, esthetic, emotional, social, utilitarian benefits, and product value compared to price) of the apparel product and four store attributes (return/refund, delivery, reputation/credibility, and customer service). The findings from the study can serve as an important tool in developing survey questions in order to evaluate the quality of consumer review information and help online retailers plan methods to improve the quality of reviews.

• Fashion & Textile Research Journal
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• v.25 no.4
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• pp.419-428
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• 2023

This study examines customer reviews from online stores of Korean vegan fashion brands to determine the qualities that customers value in vegan fashion items. For this purpose, we conducted a case study of online reviews-2,285 reviews were collected and analyzed. The results are as follows: The clothing evaluation criteria for vegan fashion products can be divided into four categories: aesthetics, material characteristics, affordability, and characteristics. This suggests that evaluation standards for vegan fashion items operate at multiple levels. The animal welfare aspect of the product was the most important factor, followed closely by how well the clothes fit. High-quality vegan materials and the use of recycled materials that are environmentally friendly were emphasized. The findings of this study suggest that even for vegan products, stylistic features remain an essential component of fashion items. To understand the main aspects of clothing evaluation criteria in the current vegan fashion market, this study differs from other studies in that it examined online reviews of vegan fashion brands. This comprehensive analysis contributes to a deeper understanding of customer preferences and highlights the importance of ethical considerations alongside style in the evaluation of vegan fashion items, providing valuable insights for the industry. Moving forward, this study is significant in suggesting that vegan fashion brands should develop their products as well as their brands, capitalizing on the demand for ethically conscious and stylish options.