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  • P-ISSN1738-3110
  • E-ISSN2093-7717
  • SCOPUS, ESCI

Retail Outlet Clustering of the Imported Automobile Distributors in Korea

The Journal of Distribution Science / The Journal of Distribution Science, (P)1738-3110; (E)2093-7717
2018, v.16 no.5, pp.45-59
https://doi.org/https://doi.org/10.15722/jds.16.5.201805.45
Park, Koo-Woong

Abstract

Purpose - This paper aims to analyze the distinct pattern of clustering of imported automobile distributors and provide evidence for the phenomenon using Korean data. Research design, data, and methodology - In this paper, we use data from Korea Automobile Importers & Distributors Association of 23 foreign automobile brands to evaluate the degree of concentration of showrooms using locational Gini index. We identify possible causes for the high level of clustering from two perspectives; 1) on the distributors' side and 2) on the customers' side. Results - We find a very strong locational concentration of imported automobile showrooms within close vicinity in the major cities and districts in Korea. Locational Gini coefficients are 0.1024 at the national level, 0.1836~0.3763 at city level, and 0.3941~0.4311 at district level on a [0,0.5] scale. Conclusions - Luxury foreign automobile customers tend to shop extensively around multiple brands prior to their ideal model selection. Accordingly, the imported automobile distributors cluster together close to their direct competitors in order to give a good comparison opportunity for the potential customers. This will maximize the probability of the visits of potential customers and lead to successful sales performance.

keywords
Imported Automobile Distributors, Locational Gini Coefficient, Optimal Retail Location, Clustering, Conspicuous Consumption

Reference

1.

Berry, B. J. L., & Garrison, W. L. (1958). The Functional Bases of the Central Place Hierarchy. Economic Geography, 34(2), 145-154.

2.

Drezner, T., Drezner, Z., & Kalczynski, P. (2011). A Cover-based Competitive Location Model. Journal of the Operational Research Society, 62(1), 100-113.

3.

Drezner, T., Drezner, Z., & Kalczynski, P. (2012). Strategic Competitive Location: Improving Existing and Establishing New Facilities. Journal of the Operational Research Society, 63(12), 1720-1730.

4.

Gauri, D. K., Pauler, J. G., & Trivedi, M. (2009). Benchmarking Performance in Retail Chains: An Integrated Approach. Marketing Science, 28(3), 502-515.

5.

Ghosh, A., & Craig, C. S. (1986). An Approach to Determining Optimal Locations for New Services. Journal of Marketing Research, 23(4), 354-362.

6.

Huff, D. L. (1963). A Probabilistic Analysis of Shopping Center Trade Areas. Land Economics, 39(1), 81-90.

7.

Huff, D. L. (1964). Defining and Estimating a Trading Area. Journal of Marketing, 28(3), 34-38.

8.

Jensen-Butler, C. (1972). Gravity Models as Planning Tools: A Review of Theoretical and Operational Problems. Geografiska Annaler, 54B(1), 68-78.

9.

Kireyeva, A. A. (2016). The Formation of Information Technology Clusters in Kazakhstan: System and Structured Approaches. Journal of Asian Finance, Economics and Business, 3(2), 51-57.

10.

Kireyeva, A. A., & Nurlanova, N. K. (2014). The Formation of Innovative Clusters in Kazakhstan: Analysis and Methods for Identifying Specialization. Journal of Asian Finance, Economics and Business, 1(1), 23-30.

11.

Korea Automobile Importers & Distributors Association (2018). Market Share by Year of Passenger Car. Retrieved March 7, 2018 from https://www.kaida.co.kr/en/index.do?language=en.

12.

Korea Automobile Importers & Distributors Association (2018). Showroom & Service Center. Retrieved March 7, 2018 from https://www.kaida.co.kr/en/ index.do?language=en.

13.

Krugman, P. (1991). Geography and Trade. Cambridge, Massachusetts: MIT Press.

14.

Krugman, P. (2009). The Increasing Returns Revolution in Trade and Geography. American Economic Review, 99(3), 561-571.

15.

Lakshmanan, J. R., & Hansen, W. G. (1965). A Retail Market Potential Model. Journal of the American Institute of Planners, 31(2), 134-143.

16.

Lewis, J. P., & Traill, A. L. (1968). The Assessment of Shopping Potential and the Demand for Shops. The Town Planning Review, 38(4), 317-326.

17.

Ministry of the Interior and Safety (2018). Residents Registration and Population Statistics. Retrieved April 7, 2018 from http://www.mois.go.kr/frt/sub/a05/totStat/ screen.do.

18.

Nariu, T., & Torii, A. (2008). Long-Term Manufacturer- Distributor Relationships. The Japanese Economy, 35(2), 87-117.

19.

Naver (2018). Map. Retrieved March 14, 2018 from http://map.naver.com/.

20.

Pacione, M. (1974). Measures of the Attraction Factor: A Possible Alternative. The Royal Geographical Society, Area, 6(4), 279-282.

21.

Potluri, R. M., Ansari, R., Challa, S. K., & Puttam, L. (2014). A Treatise on the Cross-Cultural Analysis of Indian Consumers' Conspicuous Consumption of Veblen Products. International Journal of Industrial Distribution & Business, 5(3), 35-43. doi: http://dx.doi.org/10.13106

22.

Quan, Z. X., & Youn, M. K. (2016). Analysis on Preceding Study of Consumer’s Store-Choice Model: Focusing on Commercial Sphere Analysis Theories. International Journal of Industrial Distribution & Business, 7(4), 11-16. doi: http://dx.doi.org/10.13106

23.

Su, S., & Youn, M. K. (2011). Using Huff Model for Predicting the Potential Chinese Retail Market. East Asian Journal of Business Management, 1(1), 9-12.

24.

Sung, J. H., & Woo, S. H. (2017). An Analysis Regarding Trends of Dualism in Korean Agriculture. International Journal of Industrial Distribution & Business, 8(6), 87-95. doi:http://dx.doi.org/10.13106

25.

Vasiliauskas, A. V., Vilkelis, A., Zinkevičiūte, V., & Batarliene, N. (2010). Development of Automobile Distribution Networks on the Basis of Multi-Criteria Evaluation of Distribution Channels. Transport, 25(4), 361-367.

26.

Veblen, T. (1899). The Theory of the Leisure Class: An Economic Study in the Evolution of Institutions. New York: Macmillan.

The Journal of Distribution Science