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The Journal of Economics, Marketing and Management / The Journal of Economics, Marketing and Management, (E)2288-7709
2022, v.10 no.6, pp.1-7
https://doi.org/https://doi.org/10.20482/jemm.2022.10.6.1
YANG, Hoe-Chang
LEE, Won-Dong
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Abstract

Purpose: The purpose of this study is identifying the research trends of degree papers related to the beauty industry and providing information which can contribute to the development of the domestic beauty industry and the direction of various research about beauty industry. Research design, data and methodology: This study used 154 academic papers and 189 academic papers with English abstracts out of 299 academic papers. All of these papers were found by searching for the keyword "beauty industry" in ScienceON on August 15, 2022. For the analysis, BERTopic and LDA (Latent Dirichlet Allocation) analysis were conducted using Python 3.7. Also, OLS regression analysis was conducted to understand the annual increase and decrease trend of each topic derived with trend analysis. Results: As a result of word frequency analysis, the frequency of satisfaction, management, behavior, and service was found to be high. In addition, it was found that 'service', 'satisfaction' and 'customer' were frequently associated with program and relationship in the word co-occurrence frequency analysis. As a result of topic modeling, six topics were derived: 'Beauty shop', 'Health education', 'Cosmetics', 'Customer satisfaction', 'Beauty education', and 'Beauty business'. The trend analysis result of each topic confirmed that 'Beauty education' and 'Health education' are getting more attention as time goes by. Conclusions: The future studies must resolve the extreme polarization between the structure of the small beauty industry and beauty stores. Furthermore, the researches have to direct various ways to create the performance of internal personnel. The ways to maximize product capabilities such as competitive cosmetics and brands are also needed attentions.

keywords
Beauty Industry, Research Trends, Topic Modeling, BERTopic, LDA

The Journal of Economics, Marketing and Management