• Asia Marketing Journal
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• v.15 no.4
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• pp.61-101
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• 2014

This study investigates when and how disagreements in online customer ratings prompt more favorable product evaluations. Among the three metrics of volume, valence, and variance that feature in the research on online customer ratings, volume and valence have exhibited consistently positive patterns in their effects on product sales or evaluations (e.g., Dellarocas, Zhang, and Awad 2007; Liu 2006). Ratings variance, or the degree of disagreement among reviewers, however, has shown rather mixed results, with some studies reporting positive effects on product sales (e.g., Clement, Proppe, and Rott 2007) while others finding negative effects on product evaluations (e.g., Zhu and Zhang 2010). This study aims to resolve these contradictory findings by introducing preference heterogeneity as a possible moderator and causal attribution as a mediator to account for the moderating effect. The main proposition of this study is that when preference heterogeneity is perceived as high, a disagreement in ratings is attributed more to reviewers' different preferences than to unreliable product quality, which in turn prompts better quality evaluations of a product. Because disagreements mostly result from differences in reviewers' tastes or the low reliability of a product's quality (Mizerski 1982; Sen and Lerman 2007), a greater level of attribution to reviewer tastes can mitigate the negative effect of disagreement on product evaluations. Specifically, if consumers infer that reviewers' heterogeneous preferences result in subjectively different experiences and thereby highly diverse ratings, they would not disregard the overall quality of a product. However, if consumers infer that reviewers' preferences are quite homogeneous and thus the low reliability of the product quality contributes to such disagreements, they would discount the overall product quality. Therefore, consumers would respond more favorably to disagreements in ratings when preference heterogeneity is perceived as high rather than low. This study furthermore extends this prediction to the various levels of average ratings. The heuristicsystematic processing model so far indicates that the engagement in effortful systematic processing occurs only when sufficient motivation is present (Hann et al. 2007; Maheswaran and Chaiken 1991; Martin and Davies 1998). One of the key factors affecting this motivation is the aspiration level of the decision maker. Only under conditions that meet or exceed his aspiration level does he tend to engage in systematic processing (Patzelt and Shepherd 2008; Stephanous and Sage 1987). Therefore, systematic causal attribution processing regarding ratings variance is likely more activated when the average rating is high enough to meet the aspiration level than when it is too low to meet it. Considering that the interaction between ratings variance and preference heterogeneity occurs through the mediation of causal attribution, this greater activation of causal attribution in high versus low average ratings would lead to more pronounced interaction between ratings variance and preference heterogeneity in high versus low average ratings. Overall, this study proposes that the interaction between ratings variance and preference heterogeneity is more pronounced when the average rating is high as compared to when it is low. Two laboratory studies lend support to these predictions. Study 1 reveals that participants exposed to a high-preference heterogeneity book title (i.e., a novel) attributed disagreement in ratings more to reviewers' tastes, and thereby more favorably evaluated books with such ratings, compared to those exposed to a low-preference heterogeneity title (i.e., an English listening practice book). Study 2 then extended these findings to the various levels of average ratings and found that this greater preference for disagreement options under high preference heterogeneity is more pronounced when the average rating is high compared to when it is low. This study makes an important theoretical contribution to the online customer ratings literature by showing that preference heterogeneity serves as a key moderator of the effect of ratings variance on product evaluations and that causal attribution acts as a mediator of this moderation effect. A more comprehensive picture of the interplay among ratings variance, preference heterogeneity, and average ratings is also provided by revealing that the interaction between ratings variance and preference heterogeneity varies as a function of the average rating. In addition, this work provides some significant managerial implications for marketers in terms of how they manage word of mouth. Because a lack of consensus creates some uncertainty and anxiety over the given information, consumers experience a psychological burden regarding their choice of a product when ratings show disagreement. The results of this study offer a way to address this problem. By explicitly clarifying that there are many more differences in tastes among reviewers than expected, marketers can allow consumers to speculate that differing tastes of reviewers rather than an uncertain or poor product quality contribute to such conflicts in ratings. Thus, when fierce disagreements are observed in the WOM arena, marketers are advised to communicate to consumers that diverse, rather than uniform, tastes govern reviews and evaluations of products.

• The Korean Journal of Franchise Management
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• v.9 no.3
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• pp.45-55
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• 2018

Purpose - Non-verbal Communication with customers in restaurant business can play an important role because it affects customer behavior and attitudes as a means to develop and maintain long-term relationships with customers. The purpose of this study is to analyze the effect of non-verbal communication with customers and the effect of the influence on customer satisfaction, trust, and revisit intention. Research design, data, methodology - In order to verify the research models and hypotheses of this study, questions were prepared for each variable and data were collected through questionnaires. The questionnaire survey was conducted from March 27, 2018 to April 17, 2018, for those who agreed with the citizens of the Jeju area who visited the restaurant recently. 50 out of 100 were conducted by internet survey and 50 were surveyed. Thus, a total of 100 responses were used using structural equation modeling with Smartpls 3.0. Results - The results of the study are as follows. First, non-verbal communication has a significant impact on customer emotion. Second customer emotion have a significant impact on customer trust and satisfaction. Third, Customer satisfaction had positive a significant effect on revisit intention. Fourth, Customer trust had positive a significant effect on revisit intention. Conclusions - The implications of this study are following as: The food service company should continuously provide non-verbal communication training to employees so that they can respond to customers with the right attitude and bright smile. In particular, in the case of restaurant franchises, customer response manuals should be created and distributed to the franchisees, and a regular training program for the franchisees should be implemented to provide the same service to the customer. Second, CEOs should have to worry about what kind of experience he or she has left since leaving the store. It is also necessary to constantly look at what customers experience in their stores or in their brands, and what emotions they form through their experiences. Third, the more satisfied or trusted customers are formed through the service of the employee, the more loyal the restaurant business will be, and the more likely it is to make continuous revisit and positive word-of-mouth activities..

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

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.377-388
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• 2016

The purposes of this study are; first, to supply useful suggestions for the market segmentation of the Chinese market according to individual psychological variables(self-congruence) of customers. Second, it figures out the relative importance of actual self-congruence and ideal self-congruence. Lastly, it reveals whether there are any differences in the preference of attributes according to the popular cultural involvement. According to the results, actual self-congruence had a positive influence on the contents factor evaluation while ideal self-congruence had positive effect on the human and cultural factors evaluation. Also, the human and cultural factor had a positive influence on the purchase intention, as well as content factor and cultural factor had the influence on the word-of-mouth. In addition, the group of highly interested in the involvement at the popular culture was significantly higher in the evaluation on the human and contents factor than the low group.

• Management & Information Systems Review
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• v.30 no.4
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• pp.195-227
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• 2011

There is no doubt that distribution channels and services greatly satisfy consumers' desires. Lots of products and services, stimulate consumers to purchase products to relieve their depressed feeling/stress temporarily, leading them gradually to a shopping addiction. Shopping addiction generates lots of problems, damaging not only consumers themselves but also other consumers and the entire society. Therefore, the purposes of this study were 1) to examine psychological factors that affected addictive shopping orientation of consumers, 2) to explore the effects addictive shopping orientation on the post-purchase emotions(positive emotion/negative emotion), 3) to examine the effect of post-purchase emotions on post-purchase behaviors (repurchasing/refund and exchange/negative word of mouth). 4) the study explored the differences in terms of effects of addictive shopping orientations on post-purchase emotions and behaviors, depending on the retailing channel (online and off line). The study performed a questionnaire survey for female adults older than 18 years old, living Seoul and Pusan areas. By using 404 copies for questionnaires, factor analysis, reliability analysis, and Amos 7.0 were used for the data analysis. It was found that psychological variables, self-esteem, compensatory buying and impulsiveness, had significant effects on addictive shopping orientations. Addictive shopping orientations affect both positive and negative post-purchase emotions in case of off-line shopping. Negative post-purchase emotions have higher impact on the postpurchase behaviors than positive post-purchase emotions.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.343-353
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• 2022

This study examines which factors will act as important factors for the public in designing a platform in the future to raise public awareness of the horse industry, and through this, a study on platform design factors of the horse industry to present insights on optimal platform design. For this study, structured questionnaires were distributed to 300 domestic adults who were interested in the horse industry to collect data, and the research questions set by using the statistical processing program SPSS 22.0 Ver were verified. As a result of the study, the usefulness of information in the central route and the playfulness of the information source among the peripheral routes were the most influential factors for consumer attitudes, and the up-to-dateness of information in the central route on consumer behavioral intentions. It was found that the attractiveness of the information source among the surrounding routes was the most influential factor. In addition, it was found that the positive attitude of consumers toward the horse industry platform is a factor that has a positive effect on the purchase intention and positive word of mouth intention for the horse industry in the future. Based on these results, this researcher needs to design content that can unravel useful information related to the horse industry in an interesting way to raise public awareness of the horse industry, and to provide the latest trends related to the horse industry at all times to draw real demand It should be possible and suggested that a design configuration that can make the platform feel more attractive is needed.

• Journal of Service Research and Studies
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• v.8 no.1
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• pp.123-143
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• 2018

This research examines empirically the causal relationship among service quality, CSR, trust, customer-company identification(=CCID), customer's behavioral intention as well as the mediating effect of trust and CCID on the relationship between service quality, CSR and customer's behavioral intention in insurance industry. With this background, this study conducted a statistical analysis based on survey data collected from insurance customers. The result of this empirical study is as follows. First, insurance company's CSR activity has a positive impact on customer's trust and customer-company Identification( =CCID). Second, both customer's trust and CCID have positive and significant effect on customer's behavioral intention. Third, we also find that both trust and CCID has a mediating effect on the relationship between service quality, CSR and customer's behavioral intention. This research shows that CSR activity of insurance company can enhance both customer's trust and CCID, in turn, when CSR activity and service quality is mediated by customer's trust and customer-company identification, it could be linked to customer's behavioral intention such as repurchasing, positive WOM(=word of mouth). This study is likely to contribute to CSR and service marketing research of insurance company.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.255-271
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• 2009

Since consumers have difficulty in acquiring information related to products in online, they are apt to use WOM(word-of-mouth). It seems to be more popular and acceptable methods to acquire information about products sold in online. In other words, consumers who visit the Internet shopping-mall can not make a purchase-decision immediately because they have no sufficient knowledge about products. To solve this problem, consumers make use of the service called "online review". The objective of this study is to verify how these reviews can influence attitude toward the message, product and several buying behaviors in the online. In particular, this study focus on the message's sidedness(positive or negative) and objectivity(objective or subjective), because it is expected that consumers are likely to behave differently according to the characteristics of online reviews. Thus, to measure consumer's attitude and buying behavior, this study was examined by 4 types of messages. The results of this study are as follows: First, in the positive-objective message, the message attitude has a stronger effect on purchase intention than other outcomes. Second, in the positive-subjective message, the message attitude has a stronger effect on revisiting intention than others. Third, in the negative-objective message, the message attitude has a stronger effect on purchase intention than others. Hence, it is said that online shopping-mall managers need to understand the effects of multidimensional online review.

• Journal of Korea Trade
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• v.24 no.7
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• pp.1-28
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• 2020

Purpose - This paper empirically investigates the predictors and main determinants of consumers' ratings of mobile applications in the Google Play Store. Using a linear and nonlinear model comparison to identify the function of users' review, in determining application rating across countries, this study estimates the direct effects of users' reviews on the application rating. In addition, extending our modelling into a sentimental analysis, this paper also aims to explore the effects of review polarity and subjectivity on the application rating, followed by an examination of the moderating effect of user reviews on the polarity-rating and subjectivity-rating relationships. Design/methodology - Our empirical model considers nonlinear association as well as linear causality between features and targets. This study employs competing theoretical frameworks - multiple regression, decision-tree and neural network models - to identify the predictors and main determinants of app ratings, using data from the Google Play Store. Using a cross-validation method, our analysis investigates the direct and moderating effects of predictors and main determinants of application ratings in a global app market. Findings - The main findings of this study can be summarized as follows: the number of user's review is positively associated with the ratings of a given app and it positively moderates the polarity-rating relationship. Applying the review polarity measured by a sentimental analysis to the modelling, it was found that the polarity is not significantly associated with the rating. This result best applies to the function of both positive and negative reviews in playing a word-of-mouth role, as well as serving as a channel for communication, leading to product innovation. Originality/value - Applying a proxy measured by binomial figures, previous studies have predominantly focused on positive and negative sentiment in examining the determinants of app ratings, assuming that they are significantly associated. Given the constraints to measurement of sentiment in current research, this paper employs sentimental analysis to measure the real integer for users' polarity and subjectivity. This paper also seeks to compare the suitability of three distinct models - linear regression, decision-tree and neural network models. Although a comparison between methodologies has long been considered important to the empirical approach, it has hitherto been underexplored in studies on the app market.