The Study on Relation between Six Sigma Implemented Period and Financial Performance: Using Smoothing Spline Function

식스 시그마 도입기간이 기업의 재무적 성과에 미치는 영향 연구: 평활 스플라인 함수를 이용하여

  • Received : 2016.03.14
  • Accepted : 2016.04.05
  • Published : 2016.06.25

Abstract

Purpose: In this paper, we investigate whether the endeavors for Six Sigma quality management by a firm have positive effects on its financial performance and the length of Six Sigma implemented period affects its financial status. We find a relationship between Six Sigma implemented period and several financial performance index using a smoothing spline function. Methods: A smoothing spline function is used in order to analyze the relationship between efforts for quality management and financial performance. Specifically, the return on assets, return on equity, sales cost and business fee are investigated as dependent variables and the efforts for quality management as independent variable. Results: As a result of the analysis, the indication is that companies that put effects into the Six Sigma quality management have a positive result in its financial status. In detail, the efforts for Six Sigma quality management have positive effects on total asset turnover ratio and Six Sigma implemented period on net income to net sales ratio. Additionally, companies with longer (shorter) period of Six Sigma program have more (less) improvement in its financial status. Conclusion: It can be concluded that the company's efforts for quality management positively influence financial performance.

Keywords

References

  1. Swink, M. and Jacobs, B. W. (2012). "Six Sigma adoption: Operating performance impacts and contextual drivers of success". Journal of Operations Management, Vol. 30, No. 6, pp. 437-453. https://doi.org/10.1016/j.jom.2012.05.001
  2. Harry, M. J. and Schroeder, R. R. (2005). "Six Sigma: The breakthrough management strategy revolutionizing the world's top corporations". Broadway Business.
  3. Pande, P., Neuman, R. and Cavanagh, R. R. (2000). "The six sigma way: How GE, Motorola, and other top companies are honing their performance". McGraw Hill Professional.
  4. Rowlands, H. (2003). "Six sigma: a new philosophy or repackaging of old ideas?". Engineering Management Journal, Vol. 13, No. 2, pp. 18-21. https://doi.org/10.1049/em:20030201
  5. Kang, H. Y. and Park, H. I. (2011). "The Empirical Study that 6-Sigma has an Effect on Firms' Financial Performance". Journal of Finance and Accounting Information, Vol 11, No. 1, pp. 147-168.
  6. Klefsjo, B., Bergquist, B. and Edgeman, R. L. (2006). "Six Sigma and Total Quality Management: different day, same soup?". International Journal of Six Sigma and Competitive Advantage, Vol. 2, No. 2, pp. 162-178. https://doi.org/10.1504/IJSSCA.2006.010107
  7. Workplace Panel Survey. (2011). "The Introduce about WPS" Last accessed Feb. 9th, 2016. https://www.kli.re.kr/wps/index.do.
  8. Kim, H. I., Jeong, J. H. and Kim, C. M. (2009). "A method of an Accurate Six Sigma Financial Effect Measurement and Connecting the Financial Effect to the Corporate Income Performance". Journal of Korea Society for Quality Management, Vol. 37, No. 3, pp. 94-101.
  9. Harry, M. J. (1998). "Six Sigma: a Breakthrough Strategy for Profitability". Quality Progress, Vol. 31, No. 5, pp. 60-64.
  10. Klefsjo, B., Wiklund, H. and Edgeman, R. L. (2001). "Six Sigma seen as a methodology for total quality management". Measuring Business Excellence, Vol. 5, No. 1, pp. 31-35. https://doi.org/10.1108/13683040110385809
  11. Lee, K. C., Bong, C. and Kwon, S. J. (2004). "Empirical Analysis of the Influence of Six Sigma Management Activities on Corporate Competitiveness". Korean Management Review, Vol. 33, No. 6, pp. 1735-1756.
  12. Lee, S. H. and Park, K. T. (2007). "Literature Review of Six Sigma: Focused on Korean Research Papers". Journal of Korea Society for Quality Management, Vol. 35. No. 1, pp. 97-112.
  13. Park, J. Y., Ryu, C., Park, M., Kwon, K. M. and You, G. (2014). "The Study on Relation between Company's Efforts for Quality Management (Six Sigma) and Financial Performance". Journal of Korea Society for Quality Management, Vol. 42, No. 3, pp. 361-371. https://doi.org/10.7469/JKSQM.2014.42.3.361
  14. Goh, T. N., Low, P. C., Tsui, K. L. and Xie, M. (2003). "Impact of Six Sigma implementation on stock price performance". Total Quality and Business Excellence, Vol. 14, No. 7, pp. 753-763. https://doi.org/10.1080/1478336032000090969
  15. Antony, J., Kumar, M. and Labib, A. (2008). "Gearing Six Sigma into UK manufacturing SMEs: results from a pilot study". Journal of the Operational Research Society, pp. 482-493.
  16. Schroeder, R.G., Linderman, K., Liedtke, C. and Choo, A. S. (2008). "Six Sigma: Definition and underlying theory". Journal of operations Management, Vol. 26, pp. 536-554. https://doi.org/10.1016/j.jom.2007.06.007
  17. Mhun, Y. S. and Bae, S. J. (2011). "Project management based analysis for the enterprise 6 sigma success factors". Journal of Applied Reliability, Vol. 11, pp. 59-81.
  18. Park, J. G. and Baik, J. (2010). "DFSS case study for the automobile safety regulation FMVSS201". Journal of Applied Reliability, Vol. 10, No. 3, pp. 161-170.
  19. Foster, S. (2007). "Does Six Sigma Improve Performance?". Quality Management Journal, Vol. 14, No. 4, pp. 7-20.
  20. Yoon, Y. H., Kim, K. M. and Kim, J. T. (1998). "A Linear Smoothing Spline Estimation and Applications". Journal of Statistical Theory & Methods, Vol. 9, No. 1, pp. 29-36.
  21. Kook, C. P., Hong, G. H. and Jeong, Y. S. (2006). "Economies of Scale and Scope Analysis in Korea's Banking Industry: A Spline Cost Function Approach". The Korean Journal of Finance, Vol. 19, No. 1, pp. 119-154.
  22. Eubank, R. L. (1994). "A Simple Smoothing Spline". American Statistician, Vol. 48, No. 2, pp. 103-106.
  23. Messer, K. (1991). "A Comparison of a Spline Estimate to Its Equivalent Kernel Estimate". The Annals of Statistics, Vol. 19, No. 2, pp. 817-829. https://doi.org/10.1214/aos/1176348122
  24. Silverman, B. (1984). "Spline Smoothing: The equivalent Variable Kernel Method". The Annals of Statistics, Vol. 12, No. 3, pp. 898-916. https://doi.org/10.1214/aos/1176346710
  25. Waggoner, D. F. (1997). "Spline Methods for Extracting Interest Rate Curves from Coupon Bond Prices". Federal Reserve Bank of Atlanta Working Paper, pp. 97-10.
  26. Kimeldorf, G. and Wahba, G. (1971). "Some Results on Tchebycheffian Spline Functions". Journal of Mathematical Analysis and Applications, Vol. 33, No. 1, pp. 82-95. https://doi.org/10.1016/0022-247X(71)90184-3
  27. Wahba, G. (1985). "A Comparison of GCV and GML for Choosing the Smoothing Parameter in the Generalized Spline Smoothing Problem". The Annals of Statistics, Vol. 13, No. 4, pp. 1378-1402. https://doi.org/10.1214/aos/1176349743
  28. Green, P. J. and Silverman, B. W. (1994). "Nonparametric Regression and Generalized Linear Models". Chapman & Hall, New York.
  29. Harry, M. J. and Schroeder, R. (2000). "Six Sigma: Prozesse optimieren, Null-Fehler-Qualitat schaffen, Rendite radikal steigern;[das Erfolgsgeheimnis von Jack Welch]." Campus-Verlag.