• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.259-266
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• 2023

In this paper, we propose an algorithm that can improve the accuracy performance of collaborative filtering using attribute-based opinion mining (ABOM). For the experiment, a total of 1,227 online consumer review data about smartphone apps from domestic smartphone users were used for analysis. After morpheme analysis using the KKMA (Kkokkoma) analyzer and emotional word analysis using KOSAC, attribute extraction is performed using LDA topic modeling, and the topic modeling results for each weighted review are used to add up the ratings of collaborative filtering and the sentiment score. MAE, MAPE, and RMSE, which are statistical model performance evaluations that calculate the average accuracy error, were used. Through experiments, we predicted the accuracy of online customers' app ratings (APP_Score) by combining traditional collaborative filtering among the recommendation algorithms and the attribute-based opinion mining (ABOM) technique, which combines LDA attribute extraction and sentiment analysis. As a result of the analysis, it was found that the prediction accuracy of ratings using attribute-based opinion mining CF was better than that of ratings implementing traditional collaborative filtering.

• Information Systems Review
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• v.24 no.1
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• pp.157-181
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• 2022

As competition in the airline industry intensifies, effective airline service quality evaluation has become one of the main challenges. In particular, as big data analytics has been touted as a new research paradigm, new research on service quality measurement using online review analysis has been attempted. However, these studies do not use review titles for analysis, relyon supervised learning that requires a lot of human intervention in learning, and do not consider airline characteristics in classifying service quality dimensions.To overcome the limitations of existing studies, this study attempts to measure airlines service quality and to classify it into the AIRQUAL service quality dimension using online review text as well as title based on self-trainingand sentiment analysis. The results show the way of effective extracting service quality dimensions of AIRQUAL from online reviews, and find that each service quality dimension have a significant effect on service satisfaction. Furthermore, the effect of review title on service satisfaction is also found to be significant. This study sheds new light on service quality measurement in airline industry by using an advanced analytical approach to analyze effects of service quality on customer satisfaction. This study also helps managers who want to improve customer satisfaction by providing high quality service in airline industry.

• Information Systems Review
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• v.8 no.1
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• pp.101-123
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• 2006

The main purpose of this study is to conceptualize and investigate the relationship between customer satisfaction and the linking variables of customer loyalty in internet shopping mall including general merchandise and specialized online mall. To achieve this objective, the study tries to validate the structural equation model and causal relationships among the model's elements involving customer satisfaction, customer trust, customer attitude, relationship involvement, and customer loyalty. The same research model was used in analysing general merchandise and specialized internet shopping mall to reveal and compare the casual path constructs. Empirical findings are as follows: First, all the hypothesis concerned with internet merchandise shopping mall were accepted but the direct effects between satisfaction $\Rightarrow$ loyalty and satisfaction $\Rightarrow$ attitude rejected in case of specialized internet shopping mall. Second, I found out that there were direct or indirect relationships between the mediating variables(satisfaction, attitude, involvement) and site trust and customer loyalty irrespective of internet shopping site patterns. In Particular, the direct effects of on customer loyalty showed the difference each other, but the indirect effects through satisfaction, attitude, or relationship involvement were all accepted. This means that the proper management concerned with indirect path is probably more important for the success of all kinds of internet shopping mall. The implications of this research may be summarized as follows. First, click and mortar companies should clearly understand and articulate the key requirements of shopping mall trust and satisfaction. Second, online companies are encouraged to establish linkage including trust, positive attitude, relationship involvement in order to foster customer loyalty. Third, companies are not only required to differentiate the internet marketing strategy adapting to the patterns of internet shopping mall but also to customize the interaction strategy in the formation process of customer loyalty.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1153-1158
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• 2018

Online customer evaluations and social media information among a variety of information sources are critical for businesses as it influences the customer's decision making. There are limitations on the time and money that the survey will ask to identify a variety of customers' needs and complaints. The customer review data at online shopping malls provide the ideal data sources for analyzing customer sentiment about their products. In this study, we collected product reviews data on the smartphone of Samsung and Apple from Amazon. We applied five classification algorithms which are used as representative sentiment analysis techniques in previous studies. The five algorithms are based on support vector machines, bagging, random forest, classification or regression tree and maximum entropy. In this study, we proposed entropy score which can comprehensively evaluate the performance of classification algorithm. As a result of evaluating five algorithms using an entropy score, the SVMs algorithm's entropy score was ranked highest.

• Information Systems Review
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• v.8 no.3
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• pp.65-80
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• 2006

This paper proposes a new infrastructure that supports divisible card payment where a combination of multiple credit cards can be used for a single purchase. The divisible card payment infrastructure modifies the existing payment system in two ways. First, the V-Card Manager(VCM) is added to the merchant side to handle the divisible card approval process from respective credit-card issuers. Second, the V-Card Agent(VA) is added to the customer side and generates a customized divisible card, called V-Card, based on the customer's preferences. This paper provides a customizing card payment method that supports divisible payments based on profits and preferences of customers.

• Information Systems Review
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• v.23 no.3
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• pp.159-176
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• 2021

Obviating user churn is a prominent strategy to capitalize on online games, eluding the initial investments required for the development of another. Extant literature has examined factors that may induce user churn, mainly from perspectives of motives to play and game as a virtual society. However, such works largely dismiss the service aspects of online games. Dissatisfaction of user needs constitutes a crucial aspect for user churn, especially with online services where users expect a continuous improvement in service quality via software updates. Hence, we examine the relationship between a game's quality management and its user base. With text mining and survival analysis, we identify complaint factors that act as key predictors of user churn. Additionally, we find that enjoyment-related factors are greater threats to user base than usability-related ones. Furthermore, subsequent quasi-experiment shows that improvements in the complaint factors (i.e., via game patches) curb churn and foster user retention. Our results shed light on the responsive role of developers in retaining the user base of online games. Moreover, we provide practical insights for game operators, i.e., to identify and prioritize more perilous complaint factors in planning successive game patches.

• Journal of KIISE
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• v.43 no.9
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• pp.983-997
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• 2016

Many available online product reviews for any given product makes it difficult for a consumer to locate the helpful reviews. The purpose of this study was to investigate automatic helpfulness evaluation of online product reviews according to review information types based on the target of information. The underlying assumption was that consumers find reviews containing specific information related to the product itself or the reliability of reviewers more helpful than peripheral information, such as shipping or customer service. Therefore, each sentence was categorized by given information types, which reduced the semantic space of review sentences. Subsequently, we extracted specific information from sentences by using a topic-based representation of the sentences and a clustering algorithm. Review ranking experiments indicated more effective results than other comparable approaches.

• Korean Management Science Review
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• v.23 no.3
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• pp.27-39
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• 2006

Designing mobile Interfaces is fundamentally different from designing online interfaces. Not only are there differences in underlying technologies, but also in the way people use mobile Interfaces. If these differences are not taken into account in designing mobile interfaces, mobile services are likely to fail. If mobile services do not deliver what people want, these services will fail no matter how excellent the underlying technology is. The user interface design commonly used in mobile services is based on multi-layered approach, which is not very user-friendly. A well designed single layered user Interface will be more user friendly than the conventional one and it will be having edge over others. However, it is quite difficult to Provide a single layered user Interface in a small screen. This study aims at examining how design attributes of mobile interfaces affect customer preferences. In order to explore customer preferences to each design attribute of mobile interfaces, we measure and analyze customer's WTP (Willingness To Pay) toward their different interface designs. Ultimately, throughout the study, we try to answer how to design mobile interfaces in small screen of mobile devices. In addition, we propose an optimal design solution that customers likely prefer.

• Journal of Information Technology Services
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• v.16 no.2
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• pp.21-32
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• 2017

This study analyzes the variable consumer characteristics that influence the intention to use online product reviews. In online e-commerce, where purchases take place without consumers seeing the products in person, the product reviews left by other consumers who have already purchased the product are believed to be valuable information. However, when different consumers read the same product review, their responses to it may vary. This study analyzes the characteristics of consumers who utilize product reviews for their purchases. Consumer characteristics are categorized into personal information, personality, purchasing tendency, and experience related to product reviews. These factors are examined to see if they have direct or indirect effects on a consumer's intention to use product reviews when making online purchases. We surveyed a total of 240 consumers who had experience using e-commerce and knew about online product reviews. Once the data was collected, path analysis was conducted using the statistics tool AMOS. The study results reveal that consumers who are female, extroverted, and have higher price sensitivity think that product reviews left by others are useful, and that this "perceived usefulness" has a positive effect on the intention to use product reviews for making online purchasing decisions. In addition, consumers who are agreeable to others, have high brand sensitivity, and who have left numerous reviews themselves demonstrated the tendency to trust reviews left by others more. Thus, we conclude that this "perceived reliability" makes it more likely that a consumer will use product reviews when making online purchasing decisions. Future research can be done to develop this study further by analyzing whether providing online product reviews corresponding to the personal characteristics of consumers enhances the effect of product reviews on online purchasing decisions.

• Knowledge Management Research
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• v.15 no.4
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• pp.79-103
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• 2014

This research investigates whether product types moderate the relationship between e-tailer characteristics and shopping attitudes in the context of online category killer stores. To identify the antecedents of consumer attitudes for category killer stores, the product types are characterized by the two dimensions of hedonic and utilitarian. A total of 268 responses were collected from consumers who experienced online category killer stores. The results show that the quality of information contained in a website, customer review, relational benefits, and the expertise of the e-tailer are important determinants for shopping attitudes of consumers. Regarding the moderating effects of product types, hedonic value significantly moderates the relationships between shopping attitudes and relational benefits/e-tailer expertise. However, utilitarian value does not significantly moderate the relationships between shopping attitudes and any of the e-tailer characteristics. Theoretical contributions of this study are the findings of moderating effects of hedonic value on the relationships between e-tailer characteristics and shopping attitudes. In addition, this study practically implies how companies can utilize these characteristics strategically for marketing and the selection of products.