- E-ISSN2233-5382
- KCI
E-ISSN : 2233-5382
A Note on Association for Korean Markets Using Correspondence Analysis
Abstract
Purpose - In this paper, we consider more segmented types of markets than conventional version of ones in South Korea and explore the degree of relations between these markets and the related factors with them. In this case, ten attributes of types of markets mentioned above will be considered. To be more specific, the numerical strength is evaluated and graphical approach is expressed on two-dimensional plane, if the association exists between the considered variables. Research design, data, and methodology - This work is done by the 2013 report on the commercial building lease offered by Small Businessmen Promotion Institute (May/2013~August/2013) and exploited by statistical analyses such as correspondence analysis and a chi-squared test in IBM SPSS 23.0. Results - Findings of this paper indicate that a variable Korean market, including traditional markets, are closely connected with variables administrative district, sales and occupation instead of company, age group and business duration and the detailed associations between variables can be obtained by inspecting results of correspondence analysis. Conclusions - We can understand where the status of the Korean markets stands now through this work and also government authority and local autonomy can take advantage of these findings to enhance the revitalization of Korean markets and other markets.
- keywords
- Association, Attribute, Chi-squared Test, Correspondence Analysis, Types of Markets
Reference
Anderson, T. W. (1958). An Introduction to multivariate analysis. New York: Wiley.
Benzercri, J. P. (1992). Correspondence analysis handbook. New York: Marcel Decker.
Brigitte, Le R. (2009). Multiple correspondence analysis. Thousand Oaks, CA: Sage Publications.
Choo, Myung-Jo (2015). Effects of Traditional Market Service Quality Factors on Customer Value, Relational Quality, and Behavioral Intention. Journal of Distribution Science, 13(11), 79-92.
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. (1983). 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.
Jeong, Dong-Bin (2016). The degree of association between traditional markets and related major factors in Korea. Journal of Distribution Science, 14(7), 5-14.
Johnson, R. A., & Wichern, D. W. (2007). Applied multivariate statistical analysis (6th ed.). Pearson: Prentice Hall.
Kim, Dae-Yun, & Kwon, Seung-Gu (2013). A Study on the Korea Distribution Promotion Policy and Adjustment Policy. Journal of Distribution Science, 11(4), 89-97.
Lee, Kyu-Hyun, & Kim, Young-Jae (2015). The Policy Effects on Traditional Retail Markets Supported by the Korean Government. Journal of Distribution Science, 13(11), 101-109.
Muirhead, R. J. (2014). Aspects of multivariate statistical theory. New York: Wiley.
Seo, Jung-Suk, Yang, Jae-Jang, & Lee, Yong-Gi (2014). Effects of Perceived Benefits and Costs of Traditional Market Support on Relationship Quality and Support. Journal of Distribution Science, 12(12), 43-54.
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:Communication books.
- Downloaded
- Viewed
- 0KCI Citations
- 0WOS Citations