DOI QR코드

DOI QR Code

Analyzing the Operational Efficiency of South Korea Wholesalers and Retailers during COVID-19 period (Q1 to Q2 2020)

우리나라 도소매기업의 운영효율성에 대한 실증분석: 코로나19 기간(2020년 1~2분기)을 중심으로

  • Received : 2020.11.03
  • Accepted : 2020.11.30
  • Published : 2020.12.31

Abstract

We analyze the performance of South Korea wholesalers and retailers during the period when COVID-19 emerged and began to spread in South Korea. Specifically, we choose operational efficiency as a proxy variable for reflecting corporate performance and apply stochastic frontier analysis for estimating operational efficiency. Importantly, in order to examine the impact of the COVID-19 period (Q1 to Q2 2020) on operational efficiency, we consider the quarterly fixed effect corresponding to the COVID-19 period. Our findings include: (ⅰ) the average level of operational ffficiency is approximately 0.7138 during the analysis period (Q1 2019 to Q2 2020); (ⅱ) the fixed effect of the COVID-19 period on operational efficiency is not significant; and (ⅲ) operational efficiency is positively correlated with the scale of the company. Moreover, from an academic perspective, we make a contribution by examining the relationship between the operational efficiency as a firm-level variable and the COVID-19 period as a macroeconomic variable.

본 연구의 목적은 코로나19가 국내에 유입되고 확산되는 기간 동안 국내 도소매기업의 성과를 분석하는 것이다. 기업성과에 대한 변수로는 운영효율성 (Operational efficiency)을 선택하였으며, 확률변경분석 (Stochastic frontier analysis)을 통해 운영효율성을 추정하였다. 이후 운영효율성에 미치는 코로나19 기간 (2020년1~2분기)의 효과를 살펴보기 위해 해당 기간의 분기별 고정효과 (Quarterly fixed effect)를 회귀분석을 통해 검토하였다. 본 연구의 주요 결과는 다음과 같다. 첫째, 분석 기간 (2019년 1분기~2020년 2분기) 동안 운영효율성의 평균적 수준은 대략 0.7138이었다. 둘째, 운영효율성에 대한 코로나 19 기간 (2020년 1분기~2분기)의 고정효과는 유의미하지 않았다. 셋째, 운영효율성과 기업규모 사이의 정의 결과를 확인하였다. 한편 본 연구는 운영효율성이라는 기업차원의 성과변수와 코로나19 기간이라는 거시경제적 변수의 관련성을 검토하였다는 점에서 의미가 있다고 볼 수 있다.

Keywords

References

  1. Battes, G. E., and Coelli, T. J. (1988). Prediction of Firm-level Technical Efficiencies with a Generalized Frontier Production Function and Panel Data, Journal of Econometrics, 38(3), 387-399. https://doi.org/10.1016/0304-4076(88)90053-X
  2. Chang, Y. B., and Gurbaxani, V. (2013). An Empirical Analysis of Technical Efficiency: The Role of IT Intensity and Competition, Information System Research, 24(3), 561-578. https://doi.org/10.1287/isre.1120.0438
  3. Chari, M. D., Devaraj, S., and David, P. (2008). Research Note-the Impact of Information Technology Investments and Diversification Strategies on Firm Performance, Management Science, 54(1), 224-234. https://doi.org/10.1287/mnsc.1070.0743
  4. Chuang, H.H-C., Oliva, R., and Heim, G. R. (2019). Examining the Link between Retailer Inventory Leanness and Operational Efficiency: Moderating Roles of Firm Size and Demand Uncertainty, Production and Operations Management, 28(9), 1-27. https://doi.org/10.1111/poms.12911
  5. Cin, B-C., and Lee, E-Y. (2010). Effects of R&D and Exports on Technical Efficiency Using Stochastic Frontier Approach, Korean Corporation Management Review, 17(1), 1-21.
  6. Diaz, M. A., and Sanchez, R. (2007). Firm Size and Productivity in Spain: a Stochastic Frontier Analysis, Small Business Economics, 30(3), 315-323. https://doi.org/10.1007/s11187-007-9058-x
  7. Dutta, S., Narasimhan, O., and Rajiv S. (2005). Conceptualizing and Measuring Capabilities: Methodology and Empirical Application, Strategic Management Journal, 26, 277-285. https://doi.org/10.1002/smj.442
  8. Eroglu, C., and Hofer, C. (2011). Lean, Leaner, too Lean? The Inventory-performance Link Revisited, Journal of Operations Management, 29(4), 356-369. https://doi.org/10.1016/j.jom.2010.05.002
  9. Gaur, V., Fisher, M.L., and Raman, A. (2005). An Econometric Analysis of Inventory Turnover Performance in Retail Services, Management Science, 51(2), 181-194. https://doi.org/10.1287/mnsc.1040.0298
  10. Greene, W. H. (2005). Fixed and Random Effects in Stochastic Frontier Models, Journal of Productivity Analysis, 23(1), 7-23. https://doi.org/10.1007/s11123-004-8545-1
  11. GRI. (2020). Post-Corona 19, New Normal-Industry-Strategy in the Era, Gyeonggi Research Institute: Issue and Diagnosis.
  12. Heo, Y., and Cin, B-C. (2004). Technical Efficiencies of World's Major Steel Firms Using Stochastic Frontier Function, Korea Trade Review, 29(2), 31-51.
  13. Huh, K-S., and Kim, J. R. (2007). Analyzing the Determinants of Technical Efficiency in World Steel Industry with Stochastic Frontier Production Function, Journal of Industrial Economics and Business, 20(5), 1785-1801.
  14. Jondrow, J., Lovell, C. K., Materov, I. S., and Schmidt, P. (1982). On the Estimation of Technical Inefficiency in the Stochastic Frontier Production Function Model, Journal of Econometrics, 19(2-3), 233-238. https://doi.org/10.1016/0304-4076(82)90004-5
  15. Kesavan, S., and Kushwaha, T. (2014). Differences in Retail Inventory Investment Behavior During Macroeconomic Shocks: Role of Service Level, Production and Operations Management, 23(12), 2118-2136. https://doi.org/10.1111/poms.12048
  16. Kesavan, S., Kushwaha, T., and Gaur, V. (2016). Do High and Low Inventory Turnover Retailers Respond Differently to Demand Shocks? Manufacturing & Service Operations Management, 18(2), 198-215. https://doi.org/10.1287/msom.2015.0571
  17. KIEP. (2020). Economic Impact of the International Spread of Coronavirus Infectious Disease (COVID)-19, Korea Institute for International Economic Policy: Today's World Economy, 20(10), 11
  18. Kim, G. (2020). Impact of Inventory Management Performance on Technical Efficiency of Korean Steel Companies, Journal of the Korean P roduction and Operations Management Society, 31(1), 71-93. https://doi.org/10.32956/kopoms.2020.31.1.71
  19. Kim, G., Lin, W. T., and Simpson, N. C. (2015). Evaluating the performance of US manufacturing and service operations in the presence of IT: a Bayesian stochastic production frontier approach, International Journal of P roduction Research, 53(18), 5500-5523. https://doi.org/10.1080/00207543.2015.1026616
  20. Kim. Y-D., and Kwak, D-C. (2017). Analysis of Relationship between Profitability and Efficiency of Social Enterprise using the Stochastic Frontier Translog Function, Social Enterprise Studies, 11(1), 75-93.
  21. Kolias, G. D., Dimelis, S. P., and Filios, V. P. (2011). An Empirical Analysis of Inventory Turnover Beaviour in Greek Retail Sector: 2000-2005, International Journal of P roduction Economics, 143(1), 143-153.
  22. Kumbhakar, S. C., Wang, H., and Horncastle, A. P. (2015). A Practitioner's Guide to Stochastic Frontier Analysis using Stata, Cambridge University Press.
  23. Lam, H. K. S., Yeung, A. C., and Cheng, T. C. E. (2016). The Impact of Firms' Social Media Initiatives on Operational Efficiency and Innovativeness, Journal of Operations Management, 47(48), 28-43.
  24. Lee, C, Y., and Johnson, A. L. (2013). Operational Efficiency. A.B. Badiru, (ed.) Handbook of Industrial and System Engineering, CRC Press, Boca Raton, FL, 17-44.
  25. Lieberman, M. B., and Dhawan, R. (2005). Assessing the Resource Base of Japanese and US Auto Producers: A Stochastic Frontier Production Function Approach, Management Science, 51(7), 1060-1075. https://doi.org/10.1287/mnsc.1050.0416
  26. Lin, T., and Shao, B. B. M. (2006). The Business Value of Information Technology and Inputs Substitution: The Productivity Paradox Revisited, Decision Support Systems, 42(2), 493-507. https://doi.org/10.1016/j.dss.2005.10.011
  27. Maeil Daily Newspaper. (2020). The Biggest Damage to Wholesale and Retail Business caused by COVID-19, 2020.2.11. Maeil Daily Newspaper Article
  28. Miller, S., and Parkhe, A. (2001). Is there a Liability of Foreignness in Global Banking? An Empirical Test of Banks' X-efficiency, Strategic Management Journal, 23(1), 55-75. https://doi.org/10.1002/smj.212
  29. Roh, J-W. (2011). Measuring the Effects of ICT on Productivity and Technical Efficiency in Manufacturing Industry by Using Stochastic Frontier Model, The e-Business Studies, 11(2), 273-293.
  30. Samil Industry View. (2020). The Changes in Consumer Behavior Accelerated by COVID-19, Samil PWC, 2020.8.
  31. Saranga, H. (2009). The Indian Auto Component Industry-estimation of Operational Efficiency Determinants using DEA, European Journal of Operation Research, 196(2), 707-718. https://doi.org/10.1016/j.ejor.2008.03.045
  32. Sarkis, J. (2000). An Analysis of the Operational Efficiency of Major Airports in the United States, Journal of Operations Management, 18(3), 155-171. https://doi.org/10.1016/S0272-6963(99)00032-7
  33. Shan, J., and Zhu, K. (2013). Inventory Management in China: An Empirical Study, Production and Operations Management, 22(2), 302-313. https://doi.org/10.1111/j.1937-5956.2012.01320.x
  34. Shin, H-G. (2007). Measuring the Efficiency, Technological Change and TFP of Global Steel Industry using the Stochastic Frontier Approach, Journal of Industrial Economics and Business, 20(4), 1319-1343.
  35. Sung, S., and Kang, S. (2011). The Comparison of Efficiency for Busan Warehousing Firms using DEA and SFA, Korea Logistics Review, 21(3), 157-180.
  36. Tabak, B. M., and Tecles P. L. (2010). Estimating a Bayesian Stochastic Frontier for the Indian Banking System, International Journal of Production Economics, 125(1), 96-110. https://doi.org/10.1016/j.ijpe.2010.01.008
  37. Tecles, P. L., and Tabak, B. M. (2010). Determinants of Bank Efficiency: The Case of Brazil, European Journal of Operation Research, 18(3), 1587-1598. https://doi.org/10.1016/j.ejor.2010.06.007
  38. The Bank of Korea. (2020). The Impact of the Global Spread of COVID-19 on the Global Economy, International Economy Review, 2020(9), 96-110.
  39. Wooldridge, J. M. (2016). Introductory Econometrics: A Modern Approach, Nelson Education.
  40. Yu, W., and Ramanathan, W. (2008). An Assessment of Operational Efficiencies in the UK Retailer Sector, International Journal of Retail Distribution Management, 36(11), 861-882. https://doi.org/10.1108/09590550810911656