Developing a step-by-step effectiveness assessment model for customer-oriented service organizations

Brissimis, Sophocles and Zervopoulos, Panagiotis (2011): Developing a step-by-step effectiveness assessment model for customer-oriented service organizations.

Abstract

Effectiveness involves more than simple efficiency, which is limited to the production process assessment of peer operational units. Effectiveness incorporates both endogenous and exogenous variables. It is a fundamental driver for the success of an operational unit within a competitive environment in which either the liquidity of money in the market and the customers are considered to be scarce sources, or the New Public Management (NPM) is citizen/customer and goal-oriented. Additionally, with respect to short-run production constraints, the resources available and controllable by the operational units, as well as the legal status, we go beyond the traditional effectiveness assessment techniques by developing a modified or “rational” Quality-driven – Efficiency-adjusted DEA (MQE-DEA) model. This particular model provides a feasible effectiveness attainment path for every disqualified unit in order to meet high-perceived quality and high-efficiency standards. The input-output mix restructuring targets estimated by the original QE-DEA model are provided on a step-by-step basis in order to have realistic managerial implications.

• Item Type: MPRA Paper
• Language: English
• Keywords: Effectiveness; Efficiency; Perceived Quality; Data Envelopment Analysis (DEA); context-dependent DEA
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General; C - Mathematical and Quantitative Methods > C0 - General > C02 - Mathematical Methods; C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C61 - Optimization Techniques ; Programming Models ; Dynamic Analysis

References

Anderson, E. and Fornell, C., 1994. A Customer Satisfaction Research Prospectus. In Rust, R. and Oliver, R., Service Quality: New Directions in Theory and Practice, Sage, California, USA, pp. 241-268.

Athanassopoulos, A., 1997. Service Quality and Operating Efficiency Synergies for Management Control in the Provision of Financial Services: Evidence from Greek Bank Branches. In European Journal of Operational Research, Vol. 98, pp. 300-313.

Banker, R.D. et al, 1984. Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. In Management Science, Vol. 30, No. 9, pp. 1078-1092.

Charnes, A. et al, 1978. Measuring Efficiency of Decision Making Units. In European Journal of Operational Research, Vol. 2, pp. 429-444.

Coelli, T. et al, 2005. An Introduction to Efficiency and Productivity Analysis (2nd ed.). Srpinger, New York, USA.

Cooper, W.W. et al, 2004. Handbook on Data Envelopment Analysis. Kluwer Academic Publishers, London, UK.

Cooper, W.W. et al, 2007. Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software (2nd ed.). Springer, New York, USA.

De Bruijn, H., 2007. Managing Performance in the Public Sector (2nd ed.). Routledge, Oxon, UK.

Hayes, B., 2008. Measuring Customer Satisfaction and Loyalty: Service Design, Use and Statistical Analysis Method (3rd ed.). ASQ, Wisconsin, USA.

Paradi, J. et al, 2004. Assessing Bank and Bank Branch Performance: Modeling Considerations and Approaches. In Cooper, W. et al., Handbook on Data Envelopment Analysis. Kluwer Academic Publishers, London, UK, pp. 349-400.

Parasuraman, A. et al, 1988. SERVQUAL: A Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality. In Journal of Retailing, Vol. 64, No. 1, pp. 12-40.

Perelman, S. and Santín, D., 2009. How to Generate Regularly Behaved Production Data? A Monte Carlo Experimentation of DEA Scale Efficiency Measurement. In European Journal of Operational Research, Vol. 99, pp. 303-310.

Seiford, L.M. and Zhu, J., 2003. Context-Dependent Data Envelopment Analysis: Measuring Attractiveness and Progress, In OMEGA, Vol. 31, No. 5, pp. 397-480.

Sherman, D. and Zhu, J., 2006. Benchmarking with Quality-Adjusted DEA (Q-DEA) to Seek Lower-Cost High-Quality Service: Evidence from a U.S. Bank Application. In Annals of Operations Research, Vol. 145, pp. 301-319.

Worthington, A. and Dollery, E., 2000. Measuring Efficiency in Local Governments Planning and Regulatory Function. In Public Productivity & Management Review, Vol. 23, No. 4, pp. 469-485.

Zervopoulos, P. and Palaskas, T., 2011. Applying Quality-Driven, Efficiency-Adjusted DEA (QE-DEA) in the Pursuit of High-Efficiency – High-Quality Service Units: An Input-Oriented Approach. In Emrouznejad, A. et al., Performance Management and Measurement with Data Envelopment Analysis. Proceedings of DEA2010, Beirut, Lebanon, pp. 239.

Zhu, J., 2003. Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets and DEA Excel Solver. Springer, New York, USA.

Zhu, J., 2009. Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets. Springer, New York, USA.