Abstract
The service sector holds substantial challenges for productivity analysis because most service delivery is often heterogeneous, simultaneous, intangible, and perishable. Nevertheless, the prospects for future studies are promising as we gently push the data envelopment analysis research envelope by using more innovative research designs that may include synergistic partnerships with other methods and disciplines, as well as delve deeper into the sub-DMU network of organizations. This chapter is dedicated to providing a selection of applications in the service sector with a focus on building a conceptual framework, research design, and interpreting results. Given the expanding share of the service sector in gross domestic products of many countries, the twenty-first century will continue to provide fertile grounds for research in the service sector.
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- 1.
DEA can give meaningless results if data on a variable have a very large range. This is because DEA is an efficient frontier technique and a DMU with an extreme value on a variable can appear as efficient even though it may be performing poorly on all other variables.
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Avkiran, N.K. (2011). Applications of Data Envelopment Analysis in the Service Sector. In: Cooper, W., Seiford, L., Zhu, J. (eds) Handbook on Data Envelopment Analysis. International Series in Operations Research & Management Science, vol 164. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-6151-8_15
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