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

Listed author(s):
  • 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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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
DOI: 10.1080/17421770903114687
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  1. Pekka Korhonen & Sari Stenfors & Mikko Syrjänen, 2003. "Multiple Objective Approach as an Alternative to Radial Projection in DEA," Journal of Productivity Analysis, Springer, vol. 20(3), pages 305-321, November.
  2. 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.
  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. Lidia Angulo-Meza & Marcos Lins, 2002. "Review of Methods for Increasing Discrimination in Data Envelopment Analysis," Annals of Operations Research, Springer, vol. 116(1), pages 225-242, October.
  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. Doyle, J & Green, R, 1993. "Data envelopment analysis and multiple criteria decision making," Omega, Elsevier, vol. 21(6), pages 713-715, November.
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