Improving efficiency of decision making units through BSC-DEA technique


Amir Reza Khaki, Seyed Esmaeel Najafi and Sadra Rashidi


Performance evaluation is one of the most important techniques to prioritize different decision making units. Data envelopment analysis (DEA), as a non-parametric method, plays an important role for measuring relative efficiency. Balanced score card, on the other hand, is another method to evaluate a business plan based on non-financial perspectives. The integrated BSC-DEA takes advantage of the advantages of both methods' features. In this paper, we propose a BSC-DEA method to rank different decision making units. We consider different financial criteria such as profit-margin, return on assets along with non-financial criteria such as customer satisfaction, advanced services, employee skills to compare the performance of different banks. The results are analyzed and discussed, which could be used for making better decisions.


DOI: j.msl.2011.08.016

Keywords: BSC-DEA ,Efficiency ,Decision making groups ,Data envelopment analysis ,Balanced score card

How to cite this paper:

Khaki, A., Najafi, S & Rashidi, S. (2012). Improving efficiency of decision making units through BSC-DEA technique.Management Science Letters, 2(1), 245-252.


References

Abran A., & Buglione L. (2003). A multidimensional performance model for consolidating Balanced Scorecards, Advances in Engineering Software, 34, 339–349.

Adler N., & Golany B. (2002). Evaluation of deregulated airline network using data envelopment analysis combined with an application to Western Europe, European Journal of Operational Research, 132, 260-273.

Andersen P., & Petersen N. C. (1993). A procedure for ranking efficient units in data envelopment analysis, Management Science, 39, 1261-1264.

Asosheh A., Nalchigar S., & Jamporazmey M. (2010). Information technology project evaluation: An integrated data envelopment analysis and balanced scorecard approach, Expert Systems with Applications, 37, 5931–5938.

Banker R.D, Charnes A., & Cooper W.W. (1984). Some models for estimating technical and scale inefficiencies in DEA, Management Science, 32,1078-92.

Banker R.D., Chang H., Janakiraman S.N., & Constantine Konstans. (2004). A balanced scorecard analysis of performance metrics, European Journal of Operational Research, 154, 423–436.

Bergendahl G., & Lindblom T. (2008). Evaluating the performance of Swedish savings banks according to service efficiency, European Journal of Operational Research ,185, 1663–1673.

Charnes A., Cooper W. W., & Rhodes E. (1978). Measuring the efficiency of decision making units, European Journal of Operational Research, 6, 429-44.

Chen T., Chen C., & Peng S. (2008). Firm operation performance analysis using data envelopment analysis and balanced scorecard. A case study of a credit cooperative bank, International Journal of Productivity and Performance Management, 57, 523-539.

Dimitris I. G., (2008). Assessing the efficiency in operations of a large Greek bank branch network: adopting different economic behaviors, Economic Modeling, 25, 559–574.

Davis S., & Albright T. (2004). An investigation of the effect of Balanced Scorecard implementation on financial performance, Management Accounting Research, 15, 135–153.

Eilat H., Golany B., & Shtub A. (2006). Constructing and evaluating balanced portfolios of R&D projects with interactions: A DEA based methodology, European Journal of Operational Research, 172, 1018–1039.

Eilat H., Golany B., & Shtub A. (2008). R&D project evaluation: An integrated DEA and balanced scorecard approach, The International Journal of Management Science, 36, 895 – 912.

García-Valderrama T., Mulero-Mendigorri E., & Revuelta-Bordoy D. (2009). Relating the perspectives of the balanced scorecard for R&D by means of DEA, European Journal of Operational Research, 196, 1177–1189.

Greatbanks R., & Tapp D. (2007). The impact of balanced scorecards in a public sector environment: empirical evidence from Dunedin city council, New Zealand, International Journal of Operations & Production Management, 27, 846-873.

Huang H.C. (2009). Designing a knowledge-based system for strategic planning: A balanced scorecard perspective, Expert Systems with Applications, 36, 209–218.

Hung-Yi .W, Tzeng G., & Chen Y. (2009). A fuzzy MCDM approach for evaluating banking performance based on Balanced Scorecard, Expert Systems with Applications, 36, 10135–10147.

Hwang, K.C. (2008). Efficency decomposition in two-stage data envelopment analysis:an application to non-life insurance companies in Taiwan, European Journal of Operational Research, 185, 418-429.Kaplan, R. S. & Norton, D. P. (1992). The balanced scorecard – measures that drive performance, Harvard Business Review, 70(1), 71-79.

Kaplan, R.S. & Norton, D.P. (1996). The balanced scorecard: translating strategy into action, Harvard Business School Press, Boston, MA.

Kaplan, R. S. & Norton, D. P. (2001). The strategy-focused organization: how balanced scorecard companies thrive in the new business environment, Harvard Business School Publishing Corporation.

Littler J., Aisthorpe P., Hudson R., & Keasey K. (2000). A new approach to linking strategy formulation and strategy implementation: an example from the UK banking sector, International Journal of Information Management, 20, 411-428

McPhail R., Heringtonb C., & Guilding C. (2008). Human resource managers’ perceptions of the applications and merit of the balanced scorecard in hotels, International Journal of Hospitality Management, 27, 623–631.

Ramanathan R. (2007). Performance of banks in countries of the Gulf Cooperation Council, International Journal of Productivity and Performance Management, 56, 137-154.

Roghanian, E. & Foroghi, A. (2010). An empirical study of Iranian regional airports using robust data envelopment analysis, International Journal of Industrial Engineering Computations, 1, 65-72.

Sadjadi, S. J. & Omrani, E. (2008). Data envelopment analysis with uncertain data: An application for Iranian electricity distribution companies, Energy Policy, 36(11), 4247-4254.

Sadjadi, S. J. & Omrani, E. (2010). A bootstrapped robust data envelopment analysis model for efficiency estimating of telecommunication companies in Iran, Telecommunications Policy, 34(4), 221-232.