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A Generalized Goals-achievement Model in Data Envelopment Analysis: an Application to Efficiency Improvement in Local Government Finance in Japan


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  • Peter Nijkamp
  • Soushi Suzuki


Abstract Data envelopment analysis (DEA) has become an established benchmark tool in efficiency strategies in both the public and the private sectors. The aim of this paper is to present and apply a newly developed, emerging from a blend of a Distance Friction Minimization (DFM) and a Goals Achievements (GA), model in DEA. The above-mentioned DFM-GA model is illustrated empirically by using a data set of efficiency indicators for cities in Hokkaido prefecture in Japan. In summary, this paper presents a practical policy instrument that may contribute to efficient decision making of both public and private actors. Modèle généralisé de réalisation des objectifs dans l'analyse par la méthode d'enveloppe: application dans l'augmentation du rendement dans les finances des administrations régionales au Japon RÉSUMÉ La méthode d'enveloppe [data envelopment analysis (DEA)] est un étalon bien établi pour les stratégies d'efficacité tant dans le secteur public que dans le secteur privé. L'objectif de la présente communication est de présenter et d'appliquer un modèle de méthode d'enveloppe nouveau et ajusté. Le modèle DFM-GA susmentionné est illustré de façon empirique au moyen d'un ensemble d'indicateurs d'efficacité pour des villes de la préfecture d'Hokkaido, au Japon. En résumé, la présente communication présente un instrument de politique pratique qui pourrait contribuer à des prises de décision efficaces par des acteurs tant publics que privés. Un modelo generalizado de logro de objetivos en el análisis envolvente de datos: aplicación a la mejora de la eficiencia en las finanzas de gobiernos locales de Japón RÉSUMÉN El análisis envolvente de datos (DEA) se ha convertido en una herramienta de referencia establecida en las estrategias de eficiencia, tanto en el sector público como privado. El objetivo de este trabajo es presentar y aplicar un modelo DEA ajustado y recién desarrollado. El modelo DFM-GA mencionado anteriormente se ilustra empíricamente utilizando un conjunto de datos de indicadores de eficiencia relacionados con ciudades de la prefectura de Hokkaido, Japón. En resumen, este trabajo presenta un instrumento práctico de política que puede contribuir a una toma de decisiones eficiente tanto de actores públicos como privados.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Spatial Economic Analysis.

Volume (Year): 4 (2009)
Issue (Month): 3 ()
Pages: 249-274

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Handle: RePEc:taf:specan:v:4:y:2009:i:3:p:249-274

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Keywords: Distance friction minimization; goals achievement; data envelopment analysis (DEA); efficiency-improving projection; local government finance; H79; R50;

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  1. Doyle, J & Green, R, 1993. "Data envelopment analysis and multiple criteria decision making," Omega, Elsevier, vol. 21(6), pages 713-715, November.
  2. P. Korhonen, 1998. "Multiple Objective Programming Support," Working Papers ir98010, International Institute for Applied Systems Analysis.
  3. Merja Halme & Tarja Joro & Pekka Korhonen & Seppo Salo & Jyrki Wallenius, 1999. "A Value Efficiency Approach to Incorporating Preference Information in Data Envelopment Analysis," Management Science, INFORMS, vol. 45(1), pages 103-115, January.
  4. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
  5. Thanassoulis, E. & Dyson, R. G., 1992. "Estimating preferred target input-output levels using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 56(1), pages 80-97, January.
  6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
  7. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
  8. M. Halme & T. Joro & P. Korhonen & S. Salo & J. Wallenius, 1998. "Value Efficiency Analysis for Incorporating Preference Information in Data Envelopment Analysis," Working Papers ir98054, International Institute for Applied Systems Analysis.
  9. Tarja Joro & Pekka Korhonen & Jyrki Wallenius, 1998. "Structural Comparison of Data Envelopment Analysis and Multiple Objective Linear Programming," Management Science, INFORMS, vol. 44(7), pages 962-970, July.
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Cited by:
  1. Peter Bönisch & Peter Haug & A. Illy & L. Schreier, 2011. "Municipality Size and Efficiency of Local Public Services: Does Size Matter?," IWH Discussion Papers 18, Halle Institute for Economic Research.
  2. Karima Kourtit & Daniel Arribas-Bel & Peter Nijkamp, 2012. "High performers in complex spatial systems: a self-organizing mapping approach with reference to The Netherlands," The Annals of Regional Science, Springer, vol. 48(2), pages 501-527, April.
  3. Laura Carosi & Giovanna D’Inverno & Letizia Ravagli, 2014. "Global public spending efficiency in Tuscan municipalities," Discussion Papers 2014/175, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.


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