• Informatization Policy
• /
• v.20 no.3
• /
• pp.3-17
• /
• 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
• /
• v.16 no.3
• /
• pp.93-112
• /
• 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.

• 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.

• Information Systems Review
• /
• v.23 no.3
• /
• pp.25-50
• /
• 2021

Though there have been a lot of studies about online product review, the effects of highlighted reviewhave not been examined enough. Highlighted review is a type of review that the platform designer changes its size or position in order to highlight without any sponsorship or incentive. The main subject of this study is about how highlighted review type affects consumer's perception and behavior in online information acquisition. We collected data from 171 subjects to test hypotheses. Using three different types of screen captures, we compared three groups - general review group, positive highlighted review only group, and both positive and negative highlighted review group. As a result, disclosing both of positiveand negative highlighted review was perceived more useful than disclosing only positive highlighted review. However, correlation between highlighted review type and review skepticism was not statistically significant. The impacts of review usefulness and skepticism on platform credibility were statistically significant, and the correlation between platform credibility and usage intention was also significant. All of results is almost similar across two product types, search goods and experiential goods. This research provides practical implications to online shopping platform designers when they design review systems to make people use their platforms.

• The Journal of the Korea Contents Association
• /
• v.21 no.11
• /
• pp.1-10
• /
• 2021

This study analyzes the use and meaning of consumer personality implication words in the review text of the Used Transaction Application . From of May 2021, the data were collected for the past six months by our Web crawler in Seoul and Gyeonggi Province, and a total of 1368 cases were collected first by random sampling, and finally 570 cases were preprocessed. The results are as follows. First, 48.2% of review texts were related to the personality of consumers even though it was a commercial platform of products. Second, the review text is mainly positive, which formed a text network structure based on the keyword 'gratitude'. Third, the review text, which implies consumer character, was divided into two groups: 'extrovert personality' and 'introvert personality' of consumers. And the individuality of the two groups worked together on the platform. In conclusion, we would like to suggest that consumer personality plays an important role in the platform transaction process, that consumer personality will play a role in the services of the platform in the future, and that consumer personality should be studied from various perspectives.

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

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

• The Journal of Society for e-Business Studies
• /
• v.26 no.4
• /
• pp.95-118
• /
• 2021

As the AI speaker business has risen significantly in recent years, the potential for numerous uses of AI speakers has gotten a lot of attention. Consumers have created an environment in which they can express and share their experiences with products through various channels, resulting in a large number of reviews that leave consumers with a variety of candid opinions about their experiences, which can be said to be very useful in analyzing consumers' thoughts. Using this review data, this study aimed to examine the factors driving the continued use of AI speakers. Above all, it was determined whether the seven characteristics associated with the intention to adopt AI identified in prior studies appear in consumer reviews. Based on customer review data on Amazon.com, text mining and social network analysis were utilized to examine Amazon eco-products. CONCOR analysis was used to classify words with similar connectivity locations, and Connection centrality analysis was used to classify the factors influencing the continuous use of AI speakers, focusing on the connectivity between words derived by classifying review data into positive and negative reviews. Consumers regarded personality and closeness as the most essential characteristics impacting the continued usage of AI speakers as a result of the favorable review survey. These two parameters had a strong correlation with other variables, and connectedness, in addition to the components established from prior studies, was a significant factor. Furthermore, additional negative review research revealed that recognition failures and compatibility are important problems that deter consumers from utilizing AI speakers. This study will give specific solutions for consumers to continue to utilize Amazon eco products based on the findings of the research.

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

• The Journal of the Korea Contents Association
• /
• v.20 no.7
• /
• pp.316-330
• /
• 2020

The study analyzes reviews of hardware products, customer service products, and products that take the form of a convergence of hardware and cloud services in ICT using text mining. We derive keywords of each review and find the differentiation of words that are used to derive topics. A cluster analysis is performed to categorize reviews into their respective clusters. Through this study, we observed which keywords are most often used for each product type and found topics that express the characteristics of products and services using topic modeling. We derived keywords such as "professional" and "technician" which are topics that suggest the excellence of the service provider in the review of service products. Further, we identified adjectives with positive connotations such as "favorite", "fine", "fun", "nice", "smart", "unlimited", and "useful" from Amazon Eco review, an integrated product and service. Using the cluster analysis, the entire review was clustered into three groups, and three product type reviews exclusively resulted in belonging to each different cluster. The study analyzed the differences whereby consumer needs are expressed differently in reviews depending on the type of product and suggested that it is necessary to differentiate product planning and marketing promotion according to the product type in practice.