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A Study on Development of Balanced Scorecard for Management Evaluation Using Multiple Attribute Decision Making

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DOI: 10.4236/jsea.2010.33032    5,871 Downloads   11,712 Views   Citations

ABSTRACT

Recently, most businesses have introduced a system for improving their responsibility to the customers in terms of job improvement. For example, small-quantity batch production increases cost but improve efficiency of management. Companies have been introduced the balanced scorecard to evaluate their management as part of improvement, while they suffer from many trials and errors. Many businesses still have difficulty in introducing balance scorecard concept in their process, but we suggest a method to successfully introduce the balance scorecard. This study aims to suggest a new performance measurement model reflecting relative importance of the key performance indicators for each factor. Our model is applied to several companies in real-world to validate the new model. Also, our study proposes a methodology for an adequate performance measurement using multiple attribute decision making.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

K. Yang, Y. Cho, S. Choi, J. Park and K. Kang, "A Study on Development of Balanced Scorecard for Management Evaluation Using Multiple Attribute Decision Making," Journal of Software Engineering and Applications, Vol. 3 No. 3, 2010, pp. 268-272. doi: 10.4236/jsea.2010.33032.

References

[1] R. S. Kaplan and D. P. Norton, “Transforming the balanced scorecard from performance measurement to strategy,” Accounting Horizons, Vol. 15, No. 2, pp. 87–104, 2001.
[2] K.-M. Yang, Y.-W. Wook, and J.-H. Park, “A study on evaluation method for process safety using multiple attribute decision making,” 38th International Conference on CIE, Las Vegas, USA, pp. 2274–2278, 3–6 August 2008.
[3] Y.-W. Cho, “Selecting the optimal preferred facilities with multiple characteristics using Loss Function,” Korea Safety Management & Science, Vol. 2, No. 2, pp. 127–135, 2002.
[4] H. Barron and C. P. Schmidt, “Sensitivity analysis of additive multi-attribute value models,” Operations Research, Vol. 36, pp. 122–127, 1988.
[5] J. S. Dyer and R. K. Sarin, “Measurable multi-attribute value functions,” Operations Research, Vol. 27, No. 4, pp. 810–822, 1979.
[6] S. French, “Decision theory: An introduction to the mathematics of rationality,” Ellis Horwood Series in Mathematics and its Applications, pp. 448, 1986.
[7] Y. Y. Haimes and V. Changkong, “Decision making with multiple objectives,” Lecture Notes in Economics and Mathematical Systems, Springer-Verlag, New York, No. 242, pp. 388–399, 1985.
[8] L. C. Lawrence and C. Dong, “On the efficacy of modeling multi-attribute decision problems using AHP and Sinarchy,” Eurpean Journal of Operational Research, Vol. 132, No. 1, pp. 39–49, 2001.
[9] T. L. Saaty, “A scaling method for priorities in hierarchical structures,” Journal of Mathematical Psychology, Vol. 15, No. 3, pp. 234–281, 1977.
[10] P. T. Harker and L. G. Vargas, “The theory of ratio scale estimation: Saaty’s analytic hierarchy process,” Management Science, Vol. 33, No. 11, pp. 1383–1403, 1987.
[11] K.-M. Yang, S.-H. Choi, J.-H. Park, and K.-S. Kang, “Development of correlation weight customer lifetime value using analytic hierarchy process,” 36th International Conference on CIE, Taipei, Taiwan, pp. 5461–5465, 20–23 June 2006.

  
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