• Informatization Policy
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• v.20 no.3
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• pp.3-17
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• 2013

As electronic marketplaces grow and a large number of consumers exchange their opinions on products and services on the Internet, many studies have been conducted in the area of online consumer reviews. This paper analyzes the research trend of the online consumer reviews by investigating those studies in an attempt to provide future research directions. Many researchers have focused on the effects of online reviews on consumer behaviors as well as the usefulness of the online reviews. In particular, review contents, characteristics of reviewers/consumers and features of products/services have been identified as influencing factors on the effects of the online consumer reviews. For the review contents, the number and the volume of the contents have increasing effects on the online reviews, while the direction (positive vs. negative) of the contents has resulted in conflicting effects of the review. The reputation and trustfulness of reviewers, consumers' prior knowledge on the products, consumers' product involvement, and types of the products were investigated as these factors influence the effectiveness of the online consumer reviews. Social media (such as Facebook and Twitter) nowadays play an important role to disseminate online reviews among consumers. Thus, it is necessary to study how social media influence the effects of online reviews on consumers. Since some firms abuse the online reviews for their own sakes, we recognize the necessity for empirical studies on the side effects of the online reviews.

• The Journal of Society for e-Business Studies
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• v.16 no.3
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• pp.93-112
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• 2011

For the success of an online retail market, it is important to allow consumers to get more helpful reviews by figuring out the factors determining the helpfulness of online reviews. On the basis of elaboration likelihood model, this study analyzes which factors determine the helpfulness of reviews and how the factors affecting the helpfulness of an online consumer review differ for product price. For this study, 75,226 online consumer reviews were collected from Amazon.com. Furthermore, additional information on review messages was also gathered by carrying out a content analysis on the review messages. This study shows that both of peripheral cues such as review rating and reviewer's credibility and central cues such as word count of review message and the proportion of negative words influence the helpfulness of review. In addition, the result of this study reveals that each consumer focuses on different information sources of reviews depending on the product price.

• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.139-148
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• 2024

In the post-pandemic era, the demand for online education platforms has surged, leading to increased consumer reliance on online reviews for decision-making. This study investigates the impact of Chinese online customer reviews on consumer purchase behavior in online education. By examining the role of trust, review sentiment, and the quantity and timeliness of reviews, the research aims to understand how these factors influence consumer decisions. By using regression model, findings reveal that negative reviews, timely feedback, and a higher volume of reviews positively affect consumer purchase decisions, while course pricing demonstrates an inverse relationship. Furthermore, cognitive and affective trust mediate the relationship between reviews and purchase behavior, highlighting a reverse U-shaped effect on consumer decision inclination. These insights provide valuable implications for online education providers, emphasizing the need to manage and leverage online reviews to foster consumer trust and improve sales performance.

• Proceedings of the Korean DIstribution Association Conference
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• 2005.05a
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• pp.41-58
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• 2005

본 연구는 eWOM(온라인 구전) 효과에 영향을 미치는 요인을 문화권(국가), 소비자특성(소비자 수용성), 그리고 온라인 경험 (인터넷 사용기간, 이용시간, 온라인 쇼핑횟수)로 나누어 살펴보았다. 문헌연구들을 통해 연구문제를 도출하고 이를 비교 문화적으로 실증하기 위해 총 1,176(한국 615명, 미국 561명)명의 온라인 리뷰 사용자를 대상으로 설문조사를 실시하였다. 그 결과 개인주의적인 미국보다는 집단주의적인 한국에서 eWOM의 효과는 더 큰 것으로 나타나 문화적 영향은 유의한 것으로 나타났다. 또한 소비자 수용성이라는 소비자 특성도 eWOM 효과(온라인 리뷰의 구매 직접영향정도)에 유의한 영향을 미치는 것으로 나타났다. 그리고 온라인 경험도 유의한 영향을 미쳤는데, 인터넷 사용기간 보다는 현재의 인터넷 이용시간이나 보다 관련이 있는 온라인 쇼핑횟수와 같은 변수가 eWOM 효과에 유의한 영향을 미치는 것으로 나타났다.

• The Journal of Society for e-Business Studies
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• v.16 no.4
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• pp.241-256
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• 2011

The present study examines the impact of eWOM on consumer decision making process by viewing eWOM as the product information supplier. We employ the concept of information entropy which was proposed in the information theory to explain different consumer responses to various types of product information in eWOM. Information entropy is the degree of uncertainty associated with the information in the message. In eWOM, a variety of information with different levels of entropy is available, and these different entropy levels result in different impacts on consumer behavior. The preliminary hypotheses are formulated to examine the impact of eWOM on consumer behavior, at the product attribute level and the purchase action level separately. An experiment was conducted to online shopping mall users and the analysis gives valuable insights into our future research.

• Knowledge Management Research
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• v.23 no.2
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• pp.253-276
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• 2022

Online reviews attract much attention because they play an essential role in consumer decision-making. Therefore, it is necessary to investigate the review attributes that affect the perceived helpfulness of consumers. However, most previous studies on the helpfulness of online reviews mainly focus on quantitative factors such as review volume and reviewer attributes. Recently, some studies have investigated the impact of review content and linguistic style matching on consumers' purchase decision-making. Those studies show that consumers consider additional review attributes when evaluating reviews in decision-making. To fill the research gap with existing literature, we investigated the impact of review content and linguistic style matching on review helpfulness. Moreover, this study investigated how the reviewers' expertise moderates the effect of the review content and linguistic style matching on the review helpfulness. The empirical results show that positive affective content has a negative effect on the review helpfulness. The negative affective content and linguistic style matching positively affect review helpfulness. Review expertise relieved the impact of negative affective content and linguistic style matching on review helpfulness. According to the mechanism confirmed in this study, online e-commerce companies can achieve corporate sales growth by identifying factors affecting review helpfulness and reflecting them in their marketing strategies.

• Science of Emotion and Sensibility
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• v.25 no.3
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• pp.63-76
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• 2022

Consumers of web novels read online reviews in order to decrease uncertainty when purchasing a web novel. This study examines the types of messages (factual or evaluative) that consumers find more useful and verifies the moderating effect of individual analytical decision-making style levels on differences in usefulness evaluation. Based on the tendency to acquire objective information, the usefulness of factual online reviews was expected to be higher in the context of buying experience goods, such as a web novel. Levels of analytical decision-making styles, which were classified based on individual perception, are also expected to affect the usefulness evaluation of reviews. Experiments 1 and 2 were repeatedly conducted to examine whether consumers think factual reviews are more useful than evaluative reviews. In particular, Experiment 2 was conducted to simulate the circumstance of selecting a romance web novel and demonstrated that reviews have a significant effect on messages and decision-making styles. The interaction effect between analytical decision-making style levels and review message types was also confirmed in Experiment 2. The results of this study can help researchers and marketers comprehend the behavioral patterns of web novel readers when evaluating reviews and consuming experience goods.

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

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.171-189
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• 2022

Online reviews play an essential role in the consumer's purchasing decision-making process, and thus, providing helpful and reliable reviews is essential to consumers. Previous online review helpfulness prediction studies mainly predicted review helpfulness based on the consistency of text and rating information of online reviews. However, there is a limitation in that representation capacity or review text and rating interaction. We propose a CNN-RHP model that effectively learns the interaction between review text and rating information to improve the limitations of previous studies. Multi-channel CNNs were applied to extract the semantic representation of the review text. We also converted rating into independent high-dimensional embedding vectors representing the same dimension as the text vector. The consistency between the review text and the rating information is learned based on element-wise operations between the review text and the star rating vector. To evaluate the performance of the proposed CNN-RHP model in this study, we used online reviews collected from Amazom.com. Experimental results show that the CNN-RHP model indicates excellent performance compared to several benchmark models. The results of this study can provide practical implications when providing services related to review helpfulness on online e-commerce platforms.

• Knowledge Management Research
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• v.22 no.1
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• pp.243-267
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• 2021

Sentiment represents one's own state through the process of change to stimulus, and emotion represents a simple psychological state felt for a certain phenomenon. These two terms tend to be used interchangeably, but their meaning and usage are different. In this study, we try to find out how it affects the helpfulness of reviews by classifying sentiment and emotion through online reviews written by online consumers after purchasing and using various products and services. Recently, online reviews have become a very important factor for businesses and consumers. Helpful reviews play a key role in the decision-making process of potential customers and can be assessed through review helpfulness. The helpfulness of reviews is becoming increasingly important in practice as it is utilized in marketing strategies in business as well as in purchasing decision-making issues of consumers. And academically, the importance of research to find the factors influencing the helpfulness of reviews is growing. In this study, Yelp.com secured reviews on restaurants and conducted a study on how the sentiment and emotion of online reviews affect the helpfulness of reviews. Based on the prior research, a research model including sentiment and emotions for online reviews was built, and text mining analyzes how the sentiment and emotion of online reviews affect the helpfulness of online reviews, and the difference in the effects on emotions It was verified. The results showed that negative sentiment and emotion had a greater effect on review helpfulness, which was consistent with the negative bias theory.