• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.66-77
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• 2021

Companies widely use survey to identify customer requirements, but the survey has some problems. First of all, the response is passive due to pre-designed questionnaire by companies which are the surveyor. Second, the surveyor needs to have good preliminary knowledge to improve the quality of the survey. On the other hand, text mining is an excellent way to compensate for the limitations of surveys. Recently, the importance of online review is steadily grown, and the enormous amount of text data has increased as Internet usage higher. Also, a technique to extract high-quality information from text data called Text Mining is improving. However, previous studies tend to focus on improving the accuracy of individual analytics techniques. This study proposes the methodology by combining several text mining techniques and has mainly three contributions. Firstly, able to extract information from text data without a preliminary design of the surveyor. Secondly, no need for prior knowledge to extract information. Lastly, this method provides quantitative sentiment score that can be used in decision-making.

• Culinary science and hospitality research
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• v.22 no.6
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• pp.61-70
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• 2016

The purpose of this study is to identify the effects of a company's response strategies (response type, communication style, and response sincerity) on customer's brand attitude and purchase intentions. A fictional Facebook fan page containing 6 separate scenarios was developed based on actual customer reviews and company responses observed on Facebook restaurant fan pages. Participants were recruited from Amazon's Mechanical Turk (MTurk). A total of 202 responses were obtained; 185 responses were analyzed after deleting insufficient responses. The results of MANOVA found that an accommodative response leads customers to have a more favorable attitude towards a brand and have stronger purchasing intentions. In addition, customers who perceive the company's response to a negative review as sincere are more likely to have a positive brand attitude and purchasing intentions, as compared to those who perceive it as either insincere or neutral.

• 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.

• International Commerce and Information Review
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• v.9 no.4
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• pp.91-104
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• 2007

The recent stabilization of the Internet is now driving every aspect of life into an Internet presence. In the coming years, the Internet will see growth in numbers unlike the world has ever seen. The subject of this study is the Research Study on the Products Purchase Type of On-line Shopping Mall Buyer. Also, this paper is to examine the relations between customer satisfaction and intensity of repurchase intention and complaining behavior in on-line context. On-line shopping customer depths interview it led and the online afternotes trust evaluation dimension was discovered the of useful characteristic, intention characteristic, exaggerating characteristic and on-line afternotes with or without. From these results, this paper suggests effective marketing strategy to the marketer who plans to run on-line shopping mall in the near future and also to the marketer who plans to sell products through the on-line shopping mall.

• Journal of Fashion Business
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• v.24 no.3
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• pp.69-84
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• 2020

The purpose of this study is to analyze examples of online fashion product planning of domestic fashion brands, to grasp the characteristics and step-by-step problems in product planning, and to suggest product planning methods. This study consists of a literature study and a case study. The results of th study are as follows. First, in the information analysis and product planning, product planning according to analysis and targeting of online consumers should be conducted separately from offline, and the proportion of online-only products should be expanded. Second, in the design planning and product development stages, it should be possible to secure the quantity through the pre-planning of fabrics, a to acquire the novelty of the material through the preemption of good fabrics and the pre-planning of colors to secure competitive design. Third, in the convention, a systematic review process involving company members and customer review teams should be conducted to ensure product quality and sales-ability Fourth, in the production stage, the production period must be to reduce cost. Fifth, differentiated services according to the characteristics of their products for each brand in the promotion and sales stages. Based on this analysis, a desirable approach online product planning should first run promotion phase, increasing pre-planning for the product, and organizing specialize work and manpower issues.

• The Journal of Information Systems
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• v.27 no.1
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• pp.89-110
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• 2018

Purpose There is much information in customer reviews, but finding key information in many texts is not easy. Business decision makers need a model to solve this problem. In this study we propose a multi-topic sentiment analysis approach using Latent Dirichlet Allocation (LDA) for user-generated contents (UGC). Design/methodology/approach In this paper, we collected a total of 104,039 hotel reviews in seven of the world's top tourist destinations from TripAdvisor (www.tripadvisor.com) and extracted 30 topics related to the hotel from all customer reviews using the LDA model. Six major dimensions (value, cleanliness, rooms, service, location, and sleep quality) were selected from the 30 extracted topics. To analyze data, we employed R language. Findings This study contributes to propose a lexicon-based sentiment analysis approach for the keywords-embedded sentences related to the six dimensions within a review. The performance of the proposed model was evaluated by comparing the sentiment analysis results of each topic with the real attribute ratings provided by the platform. The results show its outperformance, with a high ratio of accuracy and recall. Through our proposed model, it is expected to analyze the customers' sentiments over different topics for those reviews with an absence of the detailed attribute ratings.

• The Journal of the Korea Contents Association
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• v.13 no.10
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• pp.533-546
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• 2013

This study analyzed the contents of online hotel reviews of Benikea hotels. The results were as follows: First, the outstanding customer value were functional value, emotional value, price/value for money and epistemic value, conditional value are next. Social value was not found. Functional value was provoked by the functions of hotel room, room amenities, room view, room cleaness, restaurant service, and hotel staff friendliness as human services. Emotional value was the emotional response to the qualities of hotel's functions. Price/value for money was a perceived value of hotel user by the comparison of what to invest with what to receive. From the results, it can be proposed that hotel should maintain the basic qualities of core functions of hotel.

• Information Systems Review
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• v.20 no.4
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• pp.59-78
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• 2018

With the advent of the various device types and marketing communication, customer's search and purchase behavior have become more complex and segmented. However, extant research on multichannel marketing effects of the purchase funnel has not reflected the specific features of device User Interface (UI) and User Experience (UX). In this study, we analyzed the marketing channel effects of multi-device shoppers using a unique click stream dataset from global online retailers. We examined device types that activate online shopping and compared the differences between marketing channels that promote visits. In addition, we estimated the direct and indirect effects on visits and purchase revenue through customer's accumulated experience and channel conversions. The findings indicate that the same customer selects a different marketing channel according to the device selection. These results can help retailers gain a better understanding of customers' decision-making process in multi-marketing channel environment and devise the optimal strategy taking into account various device types. Our empirical analyses yield business implications based on the significant results from global big data analytics and contribute academically meaningful theoretical framework using an economic model. We also provide strategic insights attributed to the practical value of an online marketing manager.

• Korea Trade Review
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• v.42 no.1
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• pp.141-163
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• 2017

The purpose of this study to analyze the relationship among three characteristics of O2O commerce and extended goal-directed behavior(EGB) model(trust, desire and intention to use). From June to July in 2015, the questionnaires were sent to Chinese customers using O2O commerce. Among 494 questionnaires gathered, 433 valid ones are analyzed using SPSS and AMOS. Among ten research hypotheses derived from prior research and the research model, eight hypotheses are tenable, while the rest hypotheses are untenable. Online features of mobility and Offline features of service quality. The Online features of mobility bring consumers convenience but also has some latent customer privacy issue. On other hand, because of the untenable hypothesis, there is inconformity between online service and offline service, and customer have distrust on the O2O commerce. To achieve continuous online consumption, offline businesses need to improve their service. The perceived quality of selling company exerts a significant effect on the customers' reliability for the brand equity of open market company and selling company, such as the brand awareness of the open market, open market image, brand awareness of selling company, and the perceived quality of selling company. Thus, selling company should improve self-brand service and quality in order to improve customers' reliability. In addition, the consumer characteristics of attitude, subjective norm, and perceived behavioral control are all tenable. These results mean that O2O commerce is a favorite way of consumption by Chinese consumers.

• Information Systems Review
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• v.17 no.1
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• pp.49-64
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• 2015

Customer reviews which include subjective opinions for the product or service in online store have been generated rapidly and their influence on customers has become immense due to the widespread usage of SNS. In addition, a number of studies have focused on opinion mining to analyze the positive and negative opinions and get a better solution for customer support and sales. It is very important to select the key terms which reflected the customers' sentiment on the reviews for opinion mining. We proposed a document-level terms-based sentiment classification model by select in the optimal terms with part of speech tag. SVMs (Support vector machines) are utilized to build a predictor for opinion mining and we used the combination of POS tag and four terms extraction methods for the feature selection of SVM. To validate the proposed opinion mining model, we applied it to the customer reviews on Amazon. We eliminated the unmeaning terms known as the stopwords and extracted the useful terms by using part of speech tagging approach after crawling 80,000 reviews. The extracted terms gained from document frequency, TF-IDF, information gain, chi-squared statistic were ranked and 20 ranked terms were used to the feature of SVM model. Our experimental results show that the performance of SVM model with four POS tags is superior to the benchmarked model, which are built by extracting only adjective terms. In addition, the SVM model based on Chi-squared statistic for opinion mining shows the most superior performance among SVM models with 4 different kinds of terms extraction method. Our proposed opinion mining model is expected to improve customer service and gain competitive advantage in online store.