Benchmarking with quality-adjusted DEA (Q-DEA) to seek lower-cost high-quality service: Evidence from a U.S.bank application |
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Authors: | H David Sherman Joe Zhu |
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Institution: | (1) Northeastern University, 404 Hayden Hall, Boston, MA, 02468, U.S.A;(2) Department of Management, Worcester Polytechnic Institute, Worcester, MA, 01609, U.S.A |
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Abstract: | Benchmarking is a widely cited method to identify and adopt best-practices as a means to improve performance. Data envelopment
analysis (DEA) has been demonstrated to be a powerful benchmarking methodology for situations where multiple inputs and outputs
need to be assessed to identify best-practices and improve productivity in organizations. Most DEA benchmarking studies have
excluded quality, even in service-sector applications such as health care where quality is a key element of performance. This
limits the practical value of DEA in organizations where maintaining and improving service quality is critical to achieving
performance objectives. In this paper, alternative methods incorporating quality in DEA benchmarking are demonstrated and
evaluated. It is shown that simply treating the quality measures as DEA outputs does not help in discriminating the performance.
Thus, the current study presents a new, more sensitive, quality-adjusted DEA (Q-DEA), which effectively deals with quality
measures in benchmarking. We report the results of applying Q-DEA to a U.S. bank's 200-branch network that required a method
for benchmarking to help manage operating costs and service quality. Q-DEA findings helped the bank achieve cost savings and
improved operations while preserving service quality, a dimension critical to its mission. New insights about ways to improve
branch operations based on the best-practice (high-quality low-cost) benchmarks identified with Q-DEA are also described in
the paper. This demonstrates the practical need and potential benefits of Q-DEA and its efficacy in one application, and also
suggests the need for further research on measuring and incorporating quality into DEA benchmarking.
The review process of this paper was handled by the Edit-in-Chief Peter Hammer. |
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Keywords: | Data envelopment analysis (DEA) Efficiency Quality Benchmarking Performance Bank |
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