• Asia pacific journal of information systems
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• v.31 no.4
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• pp.491-526
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• 2021

Airlines can employ a variety of quality monitoring procedures. In this study, we employ a content analysis of 8 years of online reviews for Korean airlines in contrast to other international airlines. Online airline reviews are infrequent, relative to the total number of passengers - the number of reviews is multiple orders of magnitude lower than passenger volumes - and online airline reviews are, therefore, not representative of passenger attitudes overall. Nevertheless, online reviews may be indicative of specific service issues, and draw attention to aspects that require further study by airline operators. Furthermore, significant words and phrases used in these airline reviews may help airline operators to rapidly automate filtering, partitioning, and analysis of incoming passenger comments via other channels, including email, social media posts, and call center transcripts. The current study provides insights into the contents of online reviews of Korean vs Other-International airlines, and opportunities for service enhancement. Further, we provide a set of marker words and phrases that may be helpful for management dashboards that require automated partitioning of passenger comments.

• Asia pacific journal of information systems
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• v.27 no.4
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• pp.216-232
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• 2017

This study's objective is to use the construal-level theory (CLT) to explore the effect of the utility of online travel reviews on tourists' perception. To accomplish this goal, online travel reviews are divided into two different categories based on concreteness, and the usefulness of each review is compared with the temporal dimension of psychological distance. The results show that close future tourists are more influenced by concrete reviews than abstract reviews; however, the far future tourists are more influenced by abstract reviews than concrete reviews. Based on these results, theoretical and practical implications are discussed, and suggestions are made for future research.

• Asia pacific journal of information systems
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• v.31 no.4
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• pp.472-490
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• 2021

The detection of products with manipulated reviews has received widespread research attention, given that a truthful, informative, and useful review helps to significantly lower the search effort and cost for potential customers. This study proposes a method to recognize products with manipulated online customer reviews by examining the sequence of each review's sentiment, readability, and rating scores by product on randomness, considering the example of a Russian online retail site. Additionally, this study aims to examine the association between brand awareness and existing manipulation with products' reviews. Therefore, we investigated the difference between well-known and unknown brands' products online reviews with and without manipulated reviews based on the average star rating and the extremely positive sentiment scores. Consequently, machine learning techniques for predicting products are tested with manipulated reviews to determine a more useful one. It was found that about 20% of all product reviews are manipulated. Among the products with manipulated reviews, 44% are products of well-known brands, and 56% from unknown brands, with the highest prediction performance on deep neural network.

• Knowledge Management Research
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• v.23 no.2
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• pp.229-251
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• 2022

Online reviews are useful for other consumers to make reasonable purchase decisions by providing previous buyers' experiences. However, when online reviewers are biased, online reviews do not accurately reflect the true quality of the product. Therefore, we investigated the characteristics of reviewers with underreporting bias to cope with the problem of declining reliability of online reviews. In this context, this study attempted to examine the characteristics of reviewers with underreporting bias using 14,165 reviews of Steam, an online game platform. As a result of the analysis, reviewers with underreporting bias mainly write reviews positively, write reviews within a short period from the game release date, but tend to write reviews after playing games for longer time, and write reviews when purchasing high-priced games. Since this study has explored the characteristics of reviewers showing underreporting bias, it will be meaningful as a basic study to cope with the problem caused by underreporting bias.

• Korea Journal of Hospital Management
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• v.27 no.3
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• pp.1-14
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• 2022

Purposes: This purpose of this study was to check how much the online word of mouth influences on customer's hospital selection according to Kano's model. Methodology: Kano classified the attributes that affect customer's satisfaction into attractive, one-dimensional, indifferent, must-be, and reverse attributes. Among them, attractive and one-dimensional attributes make up the largest portion in hospital selection. Based on this, the influence of positive or negative online reviews on the selection of hospitals was investigated. Differentiated service was selected as the attractive attributes, and a kind, sufficient explanation was selected as the one-dimensional attributes. Then a questionnaire was conducted how much the positive or negative online reviews influence on hospital selection, respectively. It was conducted from August 7 to September 7, 2021 for medical consumers in their 20s and older who have used medical services for the past 3 years, and the final 142 questionnaires were analyzed. All data was analyzed by chi-square and two-way ANOVA using SPSS ver 25.0. Findings: The results showed that, in one-dimensional attributes, the difference between positive and negative reviews was not statistically significant, but in attractive attributes, positive and negative reviews showed a statistically significant difference. It suggests that positive reviews on attractive attributes had a greater influence on hospital selection. In terms of hospital selection, when the experimental participants were exposed to the positive reviews, the hospital selection ratio did not differ by Kano's attributes, but to the negative reviews it differed. The hospital selection ratio, even after they were exposed to negative reviews, was higher in the attractive attributes than in the one-dimensional attributes. Practical Implication: This study confirmed that hospital selection is influenced differently depending on the Kano's attributes and the direction of the reviews, and suggests that marketers should respond differently to each Kano's attributes when they deal with online reviews of hospitals.

• Journal of the Korean Society of Clothing and Textiles
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• v.36 no.3
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• pp.282-296
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• 2012

This study identified the types of motives for reading consumer reviews of apparel products for online stores and classified shoppers into the groups based on motives. Data were collected from eleven Korean women by a focus group interview and from 313 females by an online survey. Respondents were in their 20s' and 30s' with significant experience reading consumer reviews of apparel products for online stores. The seven motives found by interviews were reduced to four types of motives by factor analysis: Right product choice and judgment of product value, risk reduction, saving time and money, and fun/killing time. The motive for the right product choice and judgment of product value was the highest and the motive for fun/killing time was the lowest. Consumers were classified into four groups based on motives: Utilitarian shoppers (25.8%), shopping-task oriented shoppers (36.8%), multiple-motive shoppers (19.7%), and moderate-motive shoppers (17.7%). There were significant differences among age groups and the amount of reading reviews posted on a product and the duration of reading reviews for online stores. In addition, managerial implications were developed.

• Asia pacific journal of information systems
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• v.25 no.4
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• pp.763-783
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• 2015

Online customer reviews (i.e., electronic word-of-mouth) has gained considerable interest over the past years. However, a knowledge gap exists in explaining the mechanisms among the factors that determine the product sales in online retailing environment. To fill the gap, this study adopts a principal-agent perspective to investigate the effect of customer reviews and customer incentives on product sales in online retail stores. Two customer review factors (i.e., average review ratings and the number of reviews) and two customer incentive factors (i.e., price discounts and special shipping offers) are used to predict product sales in regression analysis. The sales ranking data collected from the video game titles at Amazon.com are used to analyze the direct effects of the four factors and the interaction effects between customer review and customer incentive factors to product sales. Result reveals that most relationships exist as hypothesized. The findings support both the direct and interaction effects of customer reviews and incentive factors on product sales. Based on the findings, discussions are provided with regard to the academic and practical contributions.

• Asia pacific journal of information systems
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• v.25 no.4
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• pp.746-762
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• 2015

This study developed a conceptual model that integrated psychological and physical reactions resulting from online tourism reviews through a longitudinal trust-satisfaction model (LSTM) developed based on the extended valence framework and expectation-confirmation theory. Online reviews are essential factor of consumer's purchase decision. This phenomenon is well applied in a tourism context. However, investigations on online reviews in a longitudinal approach in a tourism context are quite limited. Therefore, this study suggests a conceptual model based on LTSM and several propositions about how online tourism reviews, which are divided into factual and experiential reviews, influence the future travelers' perceptions and attitudes, such as expectation, confirmation, and destination loyalty, in a longitudinal format by examining previous related studies. Finally, expected results were discussed and several implications were described theoretically and practically.

• Journal of Smart Tourism
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• v.3 no.3
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• pp.5-15
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• 2023

Given the increasing information overload among users of online review websites, understanding the manner in which cognitive costs are reduced and efficient information is made reliable has become increasingly important. This study targets a unique consumer review design and explores how reviews from an external peer-to-peer site embedded in an online travel agency (OTA) website influence subsequent evaluation behaviors. The empirical results indicate that (1) embedded external reviews with a high average valence tend to strengthen the influence of the positive evaluation ratio while diminishing the effect of the review volume, and (2) embedded external reviews with a large variance strengthen the positive effect of the review volume while weakening the effect of the positive evaluation ratio on subsequent positive evaluations. The findings provide practical insights for consumers and online platforms.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.47-54
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• 2022

The development of the Internet of Things led to new services that did not exist before. This required a change to the existing network. This study aims to verify the service quality, satisfaction, repurchase intention relationship, and the moderating effect of online reviews of Chinese consumers using fashion shopping malls. The results of the study showed that from the perspective of consumers in their 20s and 30s in China, the type, reliability, convenience, and interaction of service quality had a positive effect on customer satisfaction and repurchase intention. In addition, negative reviews among online reviews had a great influence on repurchase intention. Based on the results of the study, it will help improve the effect on online product reviews and in-depth understanding of the acceptance of online product reviews for online fashion shopping malls, and establish strategies for fashion companies to effectively manage online product reviews information.