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Goal programming $\&$ data envelopment analysis (GoDEA) for target-based multi-level planning: Allocating central grants to the Greek local authorities. (English) Zbl 0915.90155
Summary: We develop an interface between Goal programming and Data Envelopment Analysis (GoDEA) in order to integrate target setting and resource allocation in multi-level planning problems. Data envelopment analysis (DEA) has been traditionally used for assessing the performance of individual decision making units and, therefore, necessary extensions are needed to apply DEA principles to the global organizational level without, however, losing its attractive features. The method was originally developed as an aid to the reorganization of the allocation of central funds to local authorities in Greece.

MSC:
90B50Management decision making, including multiple objectives
91B32Resource and cost allocation
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References:
[1] Anandalingam, G.: A mathematical programming model of decentralised multi-level systems. Journal of the operational research society 39, 1021-1033 (1988) · Zbl 0657.90061
[2] Athanassopoulos, A.: Decision support systems for target setting and resource allocation in multi-unit and multi-level organisations using data envelopment analysis. Ph.d. thesis (1995)
[3] Athanassopoulos, A.; Ballantine, J.: Ratio and frontier analysis for assessing corporate performance: evidence from the grocery industry in the UK. Journal of the operational research society 46, No. 4, 427-440 (1995) · Zbl 0830.90090
[4] Athanassopoulos, A.; Tatsos, N.: Econometric modelling as an aid for reorganisation policies: the case of the Greek local authorities. Econometrics Europe 2000 (1992)
[5] Bisschop, J.; Entriken, R.: AIMMS. the modelling system. (1993)
[6] Buchanan, J.; Daellenbach, H.: A comparative evaluation of interactive solution methods for multiple objective decision models. European journal of operational research 29, 353-359 (1987)
[7] Burton, R.; Obel, B.: The multilevel approach to organisational issues of the firm -- A critical review. Omega 5, 395-413 (1977)
[8] Charnes, A.; Cooper, W.; Rhodes, E.: Measuring the efficiency of decision making units. European journal of operational research 2, No. 6, 429-444 (1978) · Zbl 0416.90080
[9] Charnes, A.; Cooper, W.; Sueyoshi, T.: Least squares/ridge regression and goal programming/constrained regression alternatives. European journal of operational research 27, 146-157 (1986)
[10] Charnes, A.; Cooper, W.; Sueyoshi, T.: A goal programming/constrained regression review of the Bell system break-up. Management science 34, No. 1, 1-26 (1988)
[11] Farrell, M.: The measurement of productive efficiency. Journal of royal statistical society. Series A 120, 253-281 (1957)
[12] Forsund, F.: A comparison of parametric and nonparametric efficiency measures: the case of norwegian ferries. Journal of productivity analysis 3, 25-43 (1992)
[13] Freeland, J.; Baker, N.: Goal partitioning in a hierarchical organisation. Omega 3, 673-688 (1975)
[14] Giokas, D.: Bank branch operating efficiency: A comparative application of DEA and the loglinear model. Omega 19, No. 6, 549-557 (1991)
[15] Goreux, L.; Manne, A.: Multi-level planning: case studies in Mexico. (1973)
[16] Khorramshahgol, R.; Moustakis, V.: Delphic hierarchy process (DHP): A methodology for priority setting derived from the delphi method and analytical hierarchy process. European journal of operational research 37, 347-354 (1988) · Zbl 0652.90065
[17] Mandell, M.: Modelling effectiveness -- equity tradeoffs in public service delivery systems. Management science 37, 467-482 (1991)
[18] Nachane, D.: Optimisation methods in multilevel systems: A methodological survey. European journal of operational research 21, 25-38 (1984) · Zbl 0587.93005
[19] Nijkamp, P.; Rietveld, P.: Multi-objective multilevel policy models: an application to regional and environmental planning. European economic review 15, 63-89 (1981)
[20] Ruefli, T.: Analytical models of resource allocation in hierarchical multi-level systems. Socio-economic planning sciences 8, 353-363 (1974)
[21] Savas, E.: On equity in providing public services. Management science 24, 800-808 (1978)
[22] Schoemaker, P.; Waid, C.: An experimental comparison of different approaches to determining weights in additive utility models. Management science 28, 182-196 (1982)
[23] Sueyoshi, T.: Stochastic frontier production analysis: measuring performance of public telecommunications in 24 OECD countries. European journal of operational research 74, 466-478 (1994) · Zbl 0925.90204
[24] Sweeney, D.; Winkofsky, P.; Roy, P.; Baker, N.: Composition vs. Decomposition: two approaches to modelling organisational decision processes. Management science 24, 1491-1498 (1978)
[25] Thanassoulis, E.; Dyson, R.: Estimating preferred targets input-output levels using data envelopment analysis. European journal of operational research 56, 80-97 (1992) · Zbl 0825.90088