Development of methodology for classification of user experience (UX) in online customer review |
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| Institution: | 1. Department of Industrial and Systems Engineering, Dongguk University - Seoul, Seoul, 04620, South Korea;2. Data Science Laboratory (DSLAB), Dongguk University - Seoul, Seoul, 04620, South Korea;3. Division of Future Convergence (HCI Science Major), Dongduk Women''s University, Seoul, 02748, South Korea;1. College of Business Administration, Shanghai Business School, Shanghai, 201400, China;2. School of Economics and Management, Tongji University, Shanghai, 200092, China;3. Business School, Changshu Institute of Technology, Changshu, Jiangsu, 215500, China;1. Department of Industrial and Management Engineering, Incheon National University, 119 Academy-Ro, Yeonsu-Gu, Incheon 22012, South Korea;2. Department of Industrial and Systems Engineering, Dongguk University – Seoul, 30 Pildong-Ro 1-Gil, Jung-Gu, Seoul 04620, South Korea;1. PricewaterhouseCoopers Private Limited, India;2. Enterprise and Innovation Group, DCU Business School, Dublin City University, Ireland;3. Operations Management Area, Indian Institute of Management, Ranchi, India;4. AIM Research Center on Artificial Intelligence in Value Creation, EMLYON Business School, Ecully, France;5. Department of Information Systems, Supply Chain Management & Decision Support, NEOMA Business School, Reims, France;1. Department of Production Engineering, Federal University of São Carlos, Rod. Washington Luis km 235, Caixa Postal 676, São Carlos, SP, CEP 13.565-905, Brazil;2. INESC TEC and Faculty of Engineering, University of Porto, s/n, R. Dr. Roberto Frias, 4200-465, Porto, Portugal |
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| Abstract: | In e-commerce, customer feedback has become an essential source of insight into a product or service's user experience (UX). The study of UX helps to integrate customers' potential needs into the product's design. Because customer reviews in e-commerce are not structured and categorized, it is necessary to analyze UX based on customer opinions systematically. This study tries to structure UX in a product's positive/negative context through a neural network-based self-organizing map (SOM). As a result of analyzing 10,482 reviews on wireless earbuds in BestBuy, an electronic product e-commerce platform, it was confirmed that it is a suitable method for categorizing user experiences between reviews and deriving important factors. In particular, the difference in core UX elements by positive/negative context of the product was verified based on the star rating. The results of this study are expected to contribute to product improvement and business improvement that reflect customer needs by companies or designers who design products for end-users. |
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| Keywords: | User experience Online reviews Text mining Self-organizing map |
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