DOI QR코드

DOI QR Code

Relationship between Business Type on Sales Orders and Major Factors in Domestic Ecommerce Markets

  • JEONG, Dong-Bin (Department of Information Statistics, Gangneung-Wonju National University)
  • Received : 2020.02.28
  • Accepted : 2020.05.26
  • Published : 2020.06.30

Abstract

Purpose: The goal of this study is to comprehensively grasp the current status of ecommerce and to use as basic data for information-related policies. In this work, we understand recent ecommerce utilization, purchasing business by main factors, and look over the association between business type on sales orders (BTSO) and three variables: region, occupation and group type. Research design, data and methodology: The resource of this research is obtained by Ministry of Science and Technology Information and Communication in 2017, and investigated about 14,000 national business samples. Two statistical methods are used to analyze the association between the three variables: chi-square test and correspondence analysis. Results: The findings show that BTSO is pairwise associated with thee categorical variables, and the association between the categories of the two variables can be visually examined on two dimensional plane. Conclusions: This study suggests 'household & individual consumers' among BTSO are closely connected with 'Chungbuk' and 'Kyungnam' for region, 'others', 'finance & insurance' and 'association, repairing & other personal service' for occupation, and 'national & local government' for group type. Additionally, 'other companies' among BTSO are, particularly, related to 'Chunnam' for region, 'manufacturing industry' for occupation, and 'company corporations' for group type.

Keywords

References

  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. https://doi.org/10.20982/tqmp.07.1.p005
  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. Hoffman, D. L., & Franke, G. R. (1986). Correspondence analysis: graphical representation of categorical data in marketing research. Journal of Marketing Research, 23, 213-227. https://doi.org/10.2307/3151480
  10. Jeong, D. B. (2015). A study on cluster and positioning of domestic electronic commerce based on purchasing motivation. Journal of Korean Data & Information Science Society, 29(4), 841-856. https://doi.org/10.7465/jkdi.2015.26.4.841
  11. Jeong, D. B. & Wang, Q. (2016). Evaluation on development performances on ecommerce for 50 major cities in China. Journal of Distribution Science, 14(1), 67-74. https://doi.org/10.15722/jds.14.1.201601.67
  12. Kang, H. W., & Chun, S. M. (2018). The current issues on domestic ecommerce regulations and global competitions: market dominance, data sovereignty, and amazon effects. Korean Journal of Law and Economics, 15(3), 355-374. https://doi.org/10.46758/kjle.2018.12.15.3.355
  13. Kim, M., Jung, H. J., & Choi, A. R. (2017). Ecommerce activation measures following the completion of Korea-China FTA. Asia Trade Risk Management, 1(2), 43-66. https://doi.org/10.22142/atrm.2017.1.2.43
  14. Steven, J. P. (2009). Applied multivariate statistics for the social sciences. New York: Lawrence Erlbaum Associates Inc.
  15. Vin, C. H., & Chun, B. J. (2019). Platform and logistics innovation for ecommerce competitiveness: the case of amazon.com. Electric Trade Review, 17(4), 1-22.
  16. Yang, B. H. (2013). Understanding multivariate analysis. Seoul: Communication books