DEA-based performance measurement with a centralized view on DMUs
Final Report Abstract
Standard Data Envelopment Analysis (DEA) has widely been used to evaluate the efficiency of Decision Making Units (DMUs) on the assumption that each DMU operates independently. Under the scenario of a centralized management, however, an umbrella organization strives for improving the overall performance of its DMUs. Our research addresses this scenario by modifying DEA-based benchmarking systems according to a controlling-type structure by which the central management’s preferences can be taken into account. In particular, the DFG project served to develop approaches to incorporate crucial controlling parameters into DEA with a centralized view of measurement. The purpose of the second part of the project was to bridge the gaps between the research area of the centralized view of measurement and the domain of frontier-based incentive regulation. Our studies on different aspects of this relationship has helped us produce high-quality research. Our respective findings opened up one more research avenue addressed in a further project. This has addressed the incorporation of environmental variables into the centralized view of measurement. The methods which have been applied can be subsumed under the umbrella of performance analytics, location analytics, incentive regulation and operations research. In order to achieve the objectives, research has been concentrated on developing mathematical programming models such as linear and integer programming models as well as techniques in statistics and data mining. In order to illustrate the applicability of the proposed frameworks and the corresponding mathematical models, extensive numerical experiments and simulations have also been carried out. In particular, in order to exemplify the type of real-world problems that can be addressed by our proposed models, different data sets have been generated based on the information from: maintenance units of KONE corporation, electricity transmission service operators in Brazil, German savings banks, and hospitals in the district of Braunschweig.
Publications
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Generalized DEA: An approach for supporting input/output factor determination in DEA. Benchmarking: An International Journal 23, 1892–1909
Afsharian, M., Ahn, H., Neumann, L.
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A DEA-based incentives system for centrally managed multi-Unit organisations. European Journal of Operational Research 259, 587–598
Afsharian, M., Ahn, H., Thanassoulis, E.
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Multi-period productivity measurement under centralized management with an empirical illustration to German saving banks. OR Spectrum 39, 881–911
Afsharian, M., Ahn, H.
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A linear programming approach to efficiency evaluation in nonconvex metatechnologies. European Journal of Operational Research 268, 268–280
Afsharian, M., Podinovski V.V.
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A non-convex meta-frontier Malmquist index for measuring productivity over time. IMA Journal of Management Mathematics 29, 377–392
Afsharian, M., Ahn, H., Harms, S.G.
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A frontier-based system of incentives for units in organisations with varying degrees of decentralisation. European Journal of Operational Research 275, 224–237
Afsharian, M., Ahn, H., Thanassoulis, E.
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Measuring potential sub-unit efficiency to counter the aggregation bias in benchmarking. Journal of Business Economics 89, 53–77
Ahn, H., Bogetoft, P., Lopes, A.
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Performance comparison of management groups under centralised management. European Journal of Operational Research 278, 845–854
Afsharian, M., Ahn, H., Harms, S.G.
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A metafrontier-based yardstick competition mechanism for incentivising units in centrally managed multi-Group organisations. Annals of Operations Research 288, 681–700
Afsharian, M.
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Identifying production units with outstanding performance. European Journal of Operational Research 287, 1191–1194
Afsharian, M., Bogetoft, P.
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A frontier-based facility location problem with a centralized view of measuring the performance of the network. Journal of the Operational Research Society 72, 1058–1074
Afsharian, M.
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A review of DEA approaches applying a common set of weights: The perspective of centralized management. European Journal of Operational Research 294, 3–15
Afsharian, M., Ahn, H., Harms, S.G.
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The p-efficient problem in location analytics: Definitions, formulations, applications, and future research directions. Healthcare Analytics
Afsharian, M.
