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Performance Assessment Of Intelligent Transportation Systems Using Data Envelopment Analysis

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  • Nakanishi, Yuko J
  • Falcocchio, John C

Abstract

Data Envelopment Analysis (DEA) is a powerful, non-parametric technique that allows the comparison of diverse decision-making units (DMUs) and provides a summary measure of performance for each agency. Due to the special circumstances faced by public agencies, this mathematical programming technique is particularly suited for the assessment of public sector performance. Public agencies have multiple and frequently conflicting objectives, and difficult-to-price inputs and outputs. Also, public agencies operate in diverse environments with different service area characteristics and constraints. Other techniques that have been employed in the past include comparison of agency performance with the average agency. DEA is distinguished by the fact that it creates a best practice frontier and evaluates the performance of each agency against that frontier. This paper discusses the potential for DEA to make significant contributions to the evaluation of public sector investments in ITS technologies.

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  • Nakanishi, Yuko J & Falcocchio, John C, 2004. "Performance Assessment Of Intelligent Transportation Systems Using Data Envelopment Analysis," Research in Transportation Economics, Elsevier, vol. 8(1), pages 181-197, January.
    • Handle: RePEc:eee:retrec:v:8:y:2004:i:1:p:181-197
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    References listed on IDEAS

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    1. 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.
    2. Nozick, Linda K. & Borderas, Hector & Meyburg, Arnim H., 1998. "Evaluation of travel demand measures and programs: a data envelopment analysis approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(5), pages 331-343, September.
    3. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    4. Chu, Xuehao & Fielding, Gordon J. & Lamar, Bruce W., 1992. "Measuring transit performance using data envelopment analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 26(3), pages 223-230, May.
    5. 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.
    6. Viton, Philip A., 1997. "Technical efficiency in multi-mode bus transit: A production frontier analysis," Transportation Research Part B: Methodological, Elsevier, vol. 31(1), pages 23-39, February.
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    Cited by:

    1. Boban Djordjević & Evelin Krmac, 2019. "Evaluation of Energy-Environment Efficiency of European Transport Sectors: Non-Radial DEA and TOPSIS Approach," Energies, MDPI, vol. 12(15), pages 1-27, July.
    2. Hassan, Mohammad Nurul & Hawas, Yaser E. & Ahmed, Kamran, 2013. "A multi-dimensional framework for evaluating the transit service performance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 50(C), pages 47-61.
    3. Zhao, Y. & Triantis, K. & Murray-Tuite, P. & Edara, P., 2011. "Performance measurement of a transportation network with a downtown space reservation system: A network-DEA approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 1140-1159.

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