빅데이터를 활용한 이커머스 산업에 대한 국내외 소비자인식 비교 연구 - AliExpress, Temu, and Shein -
Comparative Study of Domestic and International Customer Perceptions in the E-commerce Industry Using Big Data : AliExpress, Temu, and Shein
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Purpose: The purpose of this study was to propose useful suggestions through E-commerce research, analyzed with big data about Customer Perception based on Textom. Methods: The data were pre-processed by deleting duplicated, irrelevant, and meaningless data. The derived data were analyzed using Textom and Ucinet 6.0 with analysis methods: Text Analysis, WordClould, TF-IDF, Network Analysis, and Concor Analysis. Results: This study investigated domestic and international consumer perceptions of Chinese e-commerce companies—AliExpress, Temu, and Shein—using text analysis. The findings revealed that international customers had a clearer understanding of each company’s characteristics, with Shein being particularly associated with "fashion" and "women." Domestic customers showed similar, though less specific, recognition and tended to focus more on promotional codes and discounts. Overall, positive sentiment was predominant, with AliExpress, Temu, and Shein perceived most favorably in that order. The research provides a deeper consumer- centric understanding of the e-commerce market and highlights differences in domestic and international market strategies. Future studies should include surveys and long-term data analysis to produce more com-prehensive results. Conclusion: The results indicate some differences in perceptions between domestic and international markets as well as among companies. Various strategies are being implemented to revitalize the e-commerce industry, and insights have been presented based on these efforts. Continuous research in the future is expected to yield even more diverse insights.
Abstract
Purpose: The purpose of this study was to propose useful suggestions through E-commerce research, analyzed with big data about Customer Perception based on Textom. Methods: The data were pre-processed by deleting duplicated, irrelevant, and meaningless data. The derived data were analyzed using Textom and Ucinet 6.0 with analysis methods: Text Analysis, WordClould, TF-IDF, Network Analysis, and Concor Analysis. Results: This study investigated domestic and international consumer perceptions of Chinese e-commerce companies—AliExpress, Temu, and Shein—using text analysis. The findings revealed that international customers had a clearer understanding of each company’s characteristics, with Shein being particularly associated with "fashion" and "women." Domestic customers showed similar, though less specific, recognition and tended to focus more on promotional codes and discounts. Overall, positive sentiment was predominant, with AliExpress, Temu, and Shein perceived most favorably in that order. The research provides a deeper consumer- centric understanding of the e-commerce market and highlights differences in domestic and international market strategies. Future studies should include surveys and long-term data analysis to produce more com-prehensive results. Conclusion: The results indicate some differences in perceptions between domestic and international markets as well as among companies. Various strategies are being implemented to revitalize the e-commerce industry, and insights have been presented based on these efforts. Continuous research in the future is expected to yield even more diverse insights.
참고문헌 (30)
- Choi, Sung Won, "Research on Factors Affecting Customer Experience Management(CEM) in E-commerce", M.A, pp.2022
- Ding, Yi, "A Comparative Analysis on the Development of E-commerce between China and South Korea", M.A, pp.2019
- Go, Eun Seo, "Research on Factors Affecting Customer Experience Management(CEM) in E-commerce", pp.2024
- Huh, Hyoung Jo, "A Study on the Big Data Analysis and Predictive Models for Quality Issues in Defense C5ISR", Journal of Korean Society for Quality Management, 51(4), pp.551~571 (2023)
- Hyun, Hyowon, "A Study on the Purchase Intention of Chinese Brands The Role of Consumer’s Product Knowledge", Korea Distribution Association, 2017(4), pp.139~145 (2017)
- "Worldwide Semiannual Big Data and Analytics Spending Guide" (2016)[URL]
- Jeong, Ye-Eun, "Analysis of Domestirc Research Treands on Artificail Intelligence-Based Prognostics and Health Management", Journal of Korean Society for Quality Management, 51(2), pp.223~245 (2023)
- Jiao, Bin, "Development and application of cross-border e-commerce in China", M.A, pp.2018
- Jo, Tae-Ho, "Concept and Application of Text Mining", Journal of Scientific & Technological Knowledge Infrastructure, 5, pp.76~85 (2001)
- Joo, Hye-young, "Domestic Consumers’ Perceptions of Chinese e-Commerce : A Semantic Network Anlaysis Using Big Data", International Commerce and Information Review, 26(2), pp.3~23 (2024)
- Kang, Jungmuk, "An empirical study on the factors of bigdata utilization in local government", M.A, pp.2015
- Kim, Gangwon, "Data collection, loading, processing, analysis, and machine learning" (2017), WikiBooks
- Kim, Minjun, "Understanding of the Overview of Quality 4.0 Using Text Mining", Journal of Korean Society for Quality Management, 51(3), pp.403~418 (2023)
- Kim, Sunghyun, "Consumer Trend Platform Development for Combination Analysis of Structured and Unstructured Big Data", Journal of Digital Convergence, 15(6), pp.133~143 (2017)
- Lee, Eunji, "Analysis of CSR·CSV·ESG Research Trends : Based on Big Data Analysis", Journal of the Korean Society for Quality Management, 50(4), pp.751~776 (2022)
- Lee, Eunji, "Analysis of Xiaomi Trends Using Big Data : Based on Customer Perception at Domestic and Global", Journal of the Korean society for Quality Management, 52(2), pp.323~340 (2024)
- "McKinsey Global Institute" (2020)[URL]
- Nam, HyunJeong, "Case study on e-commerce and distribution industry in the era of the 4th industrial revolution", Korean Society of Service Management conference, 2020(6), pp.83~ (2020)
- Oh, Chang-Seok, "Establishment of ITS Policy Issues Investigation Method in the Road Section applied Textmining", The Journal of The Korea Institute of Intelligent Transport Systems, 15(6), pp.10~23 (2016)
- Oh, JungShim, "Research trends and knowledge system analysis of the academic field of intangible cultural heritage through big data text-mining", Korean Journal of Intangible Heritage, (8), pp.93~127 (2020)
- Park, Jin-seok, "Network Analysis of Forest Welfare Issues Using Domestic News Articles", M.A, pp.2021
- Son, Kyung Wook, "A Case Study on Chinese E-commerce Companies' Global Entry", M.A, pp.2024
- Wang, Jinjiang, "Deep learning for smart manufacturing:Methods and applications", Journal of manufacturing systems, 48, pp.144~156 (2018)
- Wang, Yaqing, "A Study on Characteristics of Consumers in China Direct Purchase Shopping Using Big Data", M.A, pp.2023
- Xue, Jiang, "The Logistics Strategies of China’s Cross Border E-Commerce Platforms -based on a case study of AliExpress and Joybuy", Korea International Commercial Reveiw, 34(4), pp.285~305 (2019)
- Yeonjin Cho, "Trend Analysis of E-commerce Market and Logistics and Distribution Industries : Comparative Analysis of Chinese, American, and South Korean Markets", International Business Review, 25(3), pp.183~195 (2024)
- Zhu, Tai Lin, "A study on brand image of Xiaomi that korean consumers perceive using semantic network analysis", M.A, pp.2020
- "National Statistical Office"[URL]
- "Temu, Shein"[URL]
