- P-ISSN1738-3110
- E-ISSN2093-7717
- SCOPUS, ESCI
ISSN : 1738-3110
A Study on How General Super Markets Affect Traditional Markets Performance
Kim, Soon-Hong
Abstract
Purpose - In Korea, general super markets have a great impact on the market performance of traditional markets. We propose a modified two stage DEA model for evaluating the performance of traditional markets in Incheon, Korea by identifying the influence of external environmental factors including the presence of general super markets as non-discretionary variables in DEA. Research design, data, and methodology - After obtaining bias-corrected estimates of original DEA efficiency scores using the input and output data of 49 traditional markets, we regress them on several external environmental factors by bootstrap-truncated regression. Results - We obtain bias-corrected efficiency scores from the original DEA efficiency scores by bootstrap and among the five environmental factors, the residential population and the presence of general super markets or SSMs can be considered as the driving forces influencing bias-corrected efficiency scores, positively and negatively, respectively. Conclusions - When DEA efficiency scores tend to be overestimated, we need to use a biased-corrected efficiency score by bootstrap. It is important to note that the efficiency of traditional markets can be largely influenced by external environmental factors such as the presence of general super markets or SSMs that traditional markets can not control. Therefore, it is desirable to consider such environmental factors appropriately for a reasonable performance evaluation.
- keywords
- Traditional Markets, General Super Markets, Two Stage DEA, Environmental Factors, Simar and Wilson's Bootstrap
Reference
Athanassopoulos, A. D., & Ballantine, J. A. (1995). Ratio and frontier analysis for assessing corporate performance: Evidence from the grocery industry in the UK. The Journal of the Operational Research Society, 46(4), 427-440.
Banker, R. D., & Morey, R. C. (1986). Efficiency analysis for exogenously fixed inputs and outputs. Operations Research, 34(4), 513-521.
Barros, C. P., & Alves, C. (2004). An empirical analysis of productivity growth in a Portuguese retail chain using Malmquist productivity index. Journal of Retailing and Consumer Services, 11(5), 269–278.
Bogetoft, P. (1997). DEA-based yardstick competition: The optimality of best practice regulation. Annals of Operations Research, 73(0), 277-298.
Bogetoft, P., & Otto, L. (2011). Benchmarking with DEA, SFA, and R. New York, NY: Springer.
Bradley, S., Johnes, G., & Millington, J. (2001). The effect of competition on the efficiency of secondary schools in England. European Journal of Operational Research, 135(3), 545-68.
Charnes, A., Cooper, W. W., & Rhodes, E. L. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
Charnes, A., Cooper, W. W., & Rhodes, E. L. (1981). Evaluating program and managerial efficiency: An application of DEA to program follow through. Management Science, 27(6), 668-697.
Choi, D. R., & Suh, G. H. (2017). A study on the effects of small business management result by the Korean government: Focus on SEMAS. The East Asian Journal of Business Management, 7(3), 33-43.
Chun, D. Y., & Chae, M. S. (2003). Small and mediumsized stores' competitive strategies, marketing capabilities, and retail performance: Competing against mass merchandisers. Journal of Channel and Retailing, 8(1), 91-116.
Coelli, T. J., Rao, D. S., O'Donnell, C. J., & Battese, G. E. (2005). An Introduction to efficiency and productivity analysis. New York: Springer.
Cook, W. D., & Zhu, J. (2008). Data envelopment analysis: Modeling operational processes and measuring productivity. New York: Springer.
Jeong, D. B. (2016). A note on association for Korean markets using correspondence analysis. Journal of Industrial Distribution & Business, 7(3), 5-13.
Kirjavainen, T., & Loikkanen, H. A. (1998). Efficiency differences of Finnish senior secondary schools: An application of DEA and Tobit analysis. Economics of Education Review, 17(4), 377-94.
Lau, K. H. (2013). Measuring distribution efficiency of a retail network through data envelopment analysis. International Journal of Production Economics, 146(2), 598-611.
Nam, S. J. (2017). Exploring success factors of night markets: Utilizing the diamond model. Journal of Industrial Distribution & Business, 8(2), 33-38.
Park, C. R. (2017). Issues of policies for activating traditional markets. National Assembly Research Service Publications.
Park, S. Y. (2003). A Study on the retail competitive structure when a general super market enters small cities. Journal of Channel and Retailing, 7(2), 21-44.
Perrigot, R., & Barros, C. P. (2008). Technical efficiency of French retailers. Journal of Retailing and Consumer Services, 15(4), 296-305.
Podinovski, V. V., & Thanassoulis, E. (2007). Improving discrimination in data envelopment analysis: Some practical suggestions. Journal of Productivity Analysis, 28(1), 117-126.
Ray, S. C. (1991). Resource use efficiency in public schools: A study of Connecticut data. Management Science, 37(12), 1620-1628.
Simar, L., & Wilson, P. E. (1998). Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models. Management Science, 44(1), 49-61.
Simar, L., & Wilson, P. E. (2007). Estimation and Inference in Two-stage, Semi-parametric Models of Production Processes. Journal of Econometrics, 136(1), 31-64.
SMBA (2014). A Basic Plan to Activate Traditional Markets and Shopping Centers. Research Report, Small and Medium Business Administration.
Xavier, J. M., Moutinho, V. M., & Moreira, C. (2015). Efficiency and convergence analysis in a women’s clothing retail store chain Evidence from Portugal. International Journal of Retail & Distribution Management, 43(9), 796-814.
Yu, W., & Ramanathan, R. (2008). An Assessment of Operational Efficiencies in the UK Retail Sector. International Journal of Retail & Distribution Management, 36(11), 861-882.
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