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Online Shopping Research Trend Analysis Using BERTopic and LDA

융합경영연구 / The Journal of Economics, Marketing and Management, (E)2288-7709
2023, v.11 no.1, pp.21-30
https://doi.org/https://doi.org/10.20482/jemm.2023.11.1.21
Yoon-Hwang, JU (Department of Online Shopping, Jangan University)
Woo-Ryeong, YANG (Dept. of Business Informatics, Hanyang University)
Hoe-Chang, YANG (Dept. of Distribution Management, Jangan University)
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Abstract

Purpose: As one of the ongoing studies on the distribution industry, the purpose of this study is to identify the research trends on online shopping so far to propose not only the development of online shopping companies but also the possibility of coexistence between online and offline retailers and the development of the distribution industry. Research design, data and methodology: In this study, the English abstracts of 645 papers on online shopping registered in scienceON were obtained. For the analysis through BERTopic and LDA using Python 3.7 and identifying which topics were interesting to researchers. Results: As a result of word frequency analysis and co-occurrence analysis, it was found that studies related to online shopping were frequently conducted on factors such as products, services, and shopping malls. As a result of BERTopic, five topics such as 'service quality' and 'sales strategy' were derived, and as a result of LDA, three topics including 'purchase experience' were derived. It was confirmed that 'Customer Recommendation' and 'Fashion Mall' showed relatively high interest, and 'Sales Strategy' showed relatively low interest. Conclusions: It was suggested that more diverse studies related to the online shopping mall platform, sales content, and usage influencing factors are needed to develop the online shopping industry.

keywords
Research Trend, Retail Industry, Online Shopping, BERTopic, LDA (Latent Dirichlet allocation)

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