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  • E-ISSN2288-2766
  • KCI

Association between Type of Ecomerce with and Demographic variables

East Asian Journal of Business Economics / East Asian Journal of Business Economics, (E)2288-2766
2021, v.9 no.3, pp.83-100
https://doi.org/10.20498/eajbe.2021.9.3.83
Jeong, Dong Bin

Abstract

Purpose – The purpose of this study is to comprehensively understand the recent status of domestic ecommerce market and provide useful information for the revitalization of domestic on-line economy. This study looks over the association between type of ecommerce and demographic variables for each purchse ordering and sales order business. The demographics under consideration is administrative district, occupation and business organization type and type of ecommerce is B2B, B2C and B2G to deal with. Research design, data, and methodology –From January 2017 to December 2017, about 14000 samples are extracted from all businesses with experience in purchasing or selling products or services through ecommerce. The association between the two categorical variables considered by using two major statistical techniques such as chi-square test and correspondence analysis can be quantitatively and visually detected. Results – This study shows the association between the type of ecommerce with the administrative district and the occupation is completely different, but B2B and B2C are identical for organization type, with respect to both purchase and sales orders. Conclusions - the association between the type of ecommerce with the administrative district and the occupation is completely different, but B2B and B2C are identical for organization type, with respect to both purchase and sales orders

keywords
Association, Demographics, Type of Ecommerce

Reference

1.

Agresti, A. (2002). Categorical data analysis (2nd ed.). Hoboken, New Jersey: John Wiley & Sons Inc.

2.

Benzercri, J. P. (1992). Correspondence analysis handbook. New York: Marcel Decker.

3.

Brigitte, Le R. (2009). Multiple correspondence analysis. Thousand Oaks, CA: Sage Publications.

4.

Clausen, S. E. (1988). Applied correspondence analysis: an introduction. Thousand Oaks, CA: Sage Publications.

5.

Doey, L., & Kurta, J. (2011). Correspondence analysis applied to psychological research. Tutorials in Quantitative Methods for Psychology, 7(1), 5-14.

6.

Greenacre, M. J. (1984). Theory and applications of correspondence analysis. New York: Academic Press.

7.

Greenacre, M. J. (2007). Correspondence analysis in practice. Boca Raton, Florida: Taylor and Francis Group.

8.

Hair, J. F., Black, B., Babin, B., Anderson, R. E., & Tatham, R. L. (2007). Multivariate data analysis. Toronto:Prentice Hall.

9.

Ham, Y. J., & Kwak, B. H. (2019). A study on application of risk management for online Retailers. Korea International Commercial Review, 34(4), 307-326.

10.

Han, S. L., Lee, J. W., & Moon, J. H. (2015). Determinants of B2B transaction period and long-term relationships:ordered logit model analysis. Journal of Product Research, 33(6), 219-231.

11.

Hoffman, D. L., & Franke, G. R. (1986). Correspondence analysis: graphical representation of categorical data in marketing research. Journal of Marketing Research, 23, 213-227.

12.

Jeong, S. M., & Park, S. L. (2016). A study on the effect of the facilitating factors of B2C e-commerce on the online shopping and the overseas direct purchase. International Commerce and Information Review, 28(2), 27-51.

13.

Jhun, S. J. (2018). A New VAT Taxation System for Electronic Commerce in Germany. Issue Brief on Foreign Laws, 2018(5), 95-104.

14.

Lee, J. B., & Nam, K. D. (2016). B2C cross-border e-commerce export activation plan: focusing on identification of step-by-step operational difficulties of online overseas direct sales for domestic SMEs. Journal of International Trade & Commerce, 12(6), 207-228.

15.

Park, S. H., & Han, S. S. (2018). The relation among brand value, relation value, market orientation and performance in B2B. International Journal of Industrial Distribution & Business, 9(9), 53-62.

16.

Song, S. Y. (2019). An empirical study on the online export strategy and performance of B2C exporters - focusing on the differences in Export Type-. The International Commerce & Law Review, 81, 139-164.

17.

Steven, J. P. (2009). Applied multivariate statistics for the social sciences. New York: Lawrence Erlbaum Associates Inc.

18.

Yang, B. H. (2013). Understanding multivariate analysis. Seoul: Communication books.

East Asian Journal of Business Economics