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- E-ISSN2233-5382
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E-ISSN : 2233-5382
Association between business switch or liquidation, and the demographics of Small and Medium Enterprises in South Korea
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Abstract
Purpose - In this study, we consider and examine relationships between reasons for business switch or liquidation (BSL), and the demographics of small and medium enterprises (SMEs) in South Korea. The related five variables are occupations, administrative districts, age of employer, firm age and foundation motivation. In addition, eleven levels in association with reasons for BSL visualize the corresponding demographics by measuring their similarity on the dimensional planes assuming that the association exists between variables under consideration. Research design, data, and methodology - This study is done by the Ministry of SMEs and Startups in 2016 and examines 20,307 small and medium enterprises. For examining the distinct relationships among variables under consideration, both chi-squared test and correspondence analysis as main statistical tools are used. Results - The results show that among levels of reasons for BSL the three levels -weakening profitability, poor sales and economic depression- are main ones for the five demographics variables mentioned above, and we can obtain the detailed associations between attributes of corresponding variables by inspecting the two dimensional plane. Conclusions - This study suggests reasons for BSL are closely associated with the five different demographics variables - Administrative districts, Firm age, Occupations, Age of employer and Foundation motivation-by looking over results.
- keywords
- Association, Business Switch and Liquidation, Correspondence Analysis
Reference
Agresti, A. (2002). Categorical Data Analysis (2nd ed.). Hoboken, New Jersey: John Wiley & Sons Inc.
Benzercri, J. P. (1992). Correspondence Analysis Handbook. New York: Marcel Decker.
Brigitte, Le R. (2009). Multiple Correspondence Analysis. Thousand Oaks, CA: Sage Publications.
Clausen, S. E. (1988). Applied Correspondence Analysis:An Introduction. Thousand Oaks, CA: Sage Publications.
Doey, L., & Kurta, J. (2011). Correspondence analysis applied to psychological research. Tutorials in Quantitative Methods for Psychology, 7(1), 5-14.
Greenacre, M. J. (1984). Theory and Applications of Correspondence Analysis. New York: Academic Press.
Greenacre, M. J. (2007). Correspondence Analysis in Practice. Boca Raton, Florida: Taylor and Francis Group.
Hair, J. F., Black, B., Babin, B., Anderson, R. E., & Tatham, R. L. (2007). Multivariate Data Analysis. Toronto:Prentice Hall.
Hoffman, D. L., & Franke, G. R. (1986). Correspondence analysis: Graphical representation of categorical data in marketing research. Journal of Marketing Research, 23, 213-227.
Kang, J. S., Chun, H. B., & Cho, J. H. (2017). Entry, exit and productivity growth in the service sector: evidence from industries with the restriction of excessive entry. The Korean Economic Review, 65(4), 19-157.
Kim, H. J., & Chung, S. H. (2016). Effects of the public venture capital syndication with the private venture capital on corporate performance. Journal of Small Business Studies, 38(2), 87-115.
Suh, G. H., Lee, Y. T., Noh, H. B., & Ryu, J. S. (2014). Study on the imfluence of excessive competition among small enterprises on rate of entry and discontinuance of business. Journal of Small Business Studies, 17(2), 13-32.
Steven, J. P. (2009). Applied Multivariate Statistics for the Social Sciences. New York: Lawrence Erlbaum Associates Inc.
Yang, B. H. (2013). Understanding Multivariate Analysis. Seoul, Korea: Communication books.
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