• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2011.05a
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• pp.49-50
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• 2011

• Journal of Information Technology Services
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• v.17 no.2
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• pp.165-177
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• 2018

Recently, online commerces are becoming more common due to factors such as mobile technology development and smart device dissemination, and online review has a big influence on potential buyer's purchase decision. This study presents a set of analytical methodologies for understanding the meaning of customer reviews of products in online transaction. Using techniques currently developed in deep learning are implemented Hierarchical Attention Network for analyze meaning in online reviews. By using these techniques, we could solve time consuming pre-data analysis time problem and multiple topic problems. To this end, this study analyzes customer reviews of laptops sold in domestic online shopping malls. Our result successfully demonstrates over 90% classification accuracy. Therefore, this study classified the unstructured text data in the semantic analysis and confirmed the practical application possibility of the review analysis process.

• Journal of Korean Home Economics Education Association
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• v.22 no.3
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• pp.129-145
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• 2010

In this study, when buying fashion products through internet shopping malls, it is researched about the buying behavior, the awareness of customer review, the use and posting of customer review and the accompanying awareness. The difference of awareness on the customer review according to their involvement of clothes, are examined from high school students in Seoul. And it is examined if they experienced any dissatisfaction after their purchase and what their behavior were. The questionnaire survey was taken by 508 students from 6 high schools in Seoul. The average, the standard deviation, the frequency, the t-test, the One way ANOVA and Duncan's Multiple Test were conducted for data analysis using SPSS 17.0. In the fashion products purchase behavior of the students, The reasons of buying were mainly because of the diversity and the convenience. Some students don't shop online because screen product and actual product are not the same. The awareness of the customer review represented high in the reliability and usefulness. The awareness on the influence of the customer review represented high in the contents direction and the numbers of the customer reviews but represented low in the timeliness. As to the awareness of the customer review, the student using it represented higher in all elements such as the usefulness, the reliability, and the influence than students who not use customer review. The students posting customer review recognized higher on the usefulness and the reliability of the customer review than those who did not post it, and were highly influenced by the numbers of customer reviews. The awareness of the customer review according to the involvement of clothes was the difference only in the usefulness. As to coping actions of students experiencing dissatisfaction, the proportion of the students coping with the public action and those who do not perform any action represented high.

• 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.

• ETRI Journal
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• v.33 no.5
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• pp.720-730
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• 2011

Opinion mining involves the analysis of customer opinions using product reviews and provides meaningful information including the polarity of the opinions. In opinion mining, feature extraction is important since the customers do not normally express their product opinions holistically but separately according to its individual features. However, previous research on feature-based opinion mining has not had good results due to drawbacks, such as selecting a feature considering only syntactical grammar information or treating features with similar meanings as different. To solve these problems, this paper proposes an enhanced feature extraction and refinement method called FEROM that effectively extracts correct features from review data by exploiting both grammatical properties and semantic characteristics of feature words and refines the features by recognizing and merging similar ones. A series of experiments performed on actual online review data demonstrated that FEROM is highly effective at extracting and refining features for analyzing customer review data and eventually contributes to accurate and functional opinion mining.

• Journal of Information Technology Services
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• v.19 no.4
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• pp.85-107
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• 2020

The Internet of Things market, a technology that connects the Internet to various things, is growing day by day. Besides, various smart home services using IoT and AI (Artificial Intelligence) are being launched in homes. Related to this, existing smart home-related studies focus primarily on ICT technology, not on what service improvements should be made in customer positions. In this study, we will use smart home application customer review data to classify functional and design elements of smart home usability value and examine the ways customers think of service improvement. For this, LG Electronics and Samsung Electronics" Smart Home application, the main provider of Smart Home in Korea, customer reviews were crawled to conduct a comparative analysis between them. In this study, the review of IoT home-applications was analyzed to find service improvement insights from customer perspective, and related analysis of text mining, social network analysis and Doc2vec was used to efficiently analyze data equivalent to about 16,000 user reviews. Through this research, we hope that related companies effectively seek ways to improve smart home services that reflect customer needs and are expected to help them establish competitive strategies by identifying weaknesses and strengths among competitors.

• Journal of Korean Society for Quality Management
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• v.30 no.4
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• pp.120-136
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• 2002

The CRM is the process of integrated customer management to increase the profitability of firm as a maximizing the consumer's value and supplying the high quality product or service. The Post Information Service Headquarter was recognizing the importance of CRM and constructed the customer relationship management system that based on CRM, steadily has made an endeavor for operating to improve the job operation such as posting, banking and insurance. This research analysed the impact of service quality on the customer satisfaction in the Korea Post Office. First of all, we review the existing literature on measurement of service quality and management. As a result of this review and survey of the employer in post office, nineteen factors emerged as important to the service management of The Korea Post Office; Postal Services, Banking Services, Insurance Services. The regression analysis was utilized for analyzing the influence of service quality factors upon the customer satisfaction. Results show that service quality factors have a statistically significant impact on the customer satisfaction of the Korea Post Office.

• Journal of Information Technology Services
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• v.17 no.3
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• pp.1-16
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• 2018

There exist a number of studies pertaining to the determinants of customer satisfaction between low-cost and full-service carriers in the airline industry. Most studies measured service quality using SERVQUAL based on a survey method. This study offers a new perspective by employing a big data analytic approach using SNS data, which reflects the immediate response of customers as well as trends in real time. This study chose eight factors from TripAdvisor's customer review site as determinants of customer satisfaction and compared the differences between low-cost and full-service airlines. The factors analyzed were seat comfort, customer service, cleanliness, food and beverage, legroom, entertainment, value for money, and check-in and boarding. Additionally, ratings from domestic and foreign customers were compared. The findings show that customer service and value for money are significant factors in satisfaction with low-cost airlines while all variables except legroom and entertainment are significant for full-service airlines. The results show that SNS-based data and analysis of big data are important for improving decision-making effectiveness and increasing customer satisfaction in the airline industry.

• Journal of Korea Trade
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• v.25 no.2
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• pp.22-45
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• 2021

Purpose - This study aims to identify new attributes by analyzing reviews conducted by global automaker customers and to examine the influence of these attributes on satisfaction ratings in the U.S. automobile sales market. The present study used J.D. Power for customer responses, which is the largest online review site in the USA. Design/methodology - Automobile customer reviews are valid data available to analyze the brand personality of the automaker. This study collected 2,998 survey responses from automobile companies in the U.S. automobile sales market. Keyword analysis, topic modeling, and the multiple regression analysis were used to analyze the data. Findings - Using topic modeling, the author analyzed 2,998 responses of the U.S. automobile brands. As a result, Topic 1 (Competence), Topic 5 (Sincerity), and Topic 6 (Prestige) attributes had positive effects, and Topic 2 (Sophistication) had a negative effect on overall customer responses. Topic 4 (Conspicuousness) did not have any statistical effect on this research. Topic 1, Topic 5, and Topic 6 factors also show the importance of buying factors. This present study has contributed to identifying a new attribute, personality. These findings will help global automakers better understand the impacts of Topic 1, Topic 5, and Topic 6 on purchasing a car. Originality/value - Contrary to a traditional approach to brand analysis using questionnaire survey methods, this study analyzed customer reviews using text mining. This study is timely research since a big data analysis is employed in order to identify direct responses to customers in the future.

• Korea Trade Review
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• v.47 no.5
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• pp.253-272
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• 2022

As the digital era accelerates, traditional perspectives have limitations in explaining the success or failure of export performance. The purpose of this study is to analyze new factors affecting export performance from the perspective of customer experience, which has emerged as an important factor in securing a competitive advantage and generating organizational performance. After deriving hypotheses based on literature review and discussion, a research model is designed in which three factors of customer experience such as understanding customer's objectives, customer value creation capability, and customer journey management are the antecedents, and export performance is the dependent variable. This model also includes organizational agility and personal contact as the moderating variables. To verify the hypotheses, multiple regression analysis was conducted on the collected data drawn from 198 SME exporters. According to the analysis results, it was found that all three antecedents positively affected export performance. In particular, the organizational agility and personal contact were confirmed to have a moderating effect that creates better export performance by interacting with customer value creation capability. The theoretical significance of this study is to find that effective customer experience management can be a key factor in creating export performance. The results suggest that checking the overall customer journey, exporters should select and intervene to intensively manage key touch points that can have a decisive impact on the quality of customer experience. At the end of the paper, practical implications to be considered in creating export performance through effective customer experience management are presented.