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Improving Pupil Transportation in North Carolina

Author

Listed:
  • Thomas R. Sexton

    (W. Averell Harriman School for Management and Policy, State University of New York at Stony Brook, Stony Brook, New York 11794-3775)

  • Sally Sleeper

    (Sleeper Associates, 7048 Edgerton Street, Pittsburgh, Pennsylvania 15208)

  • Robert E. Taggart

    (David M. Griffith and Associates, Ltd., Suite 100, 1350 Piccard Drive, Rockville, Maryland 20850)

Abstract

North Carolina uses data envelopment analysis (DEA) to produce a pupil transportation funding process that encourages operational efficiency and reduces expenditures. To do so, we extended the DEA methodology to nonhomogeneous units by integrating DEA with a regression model that adjusts the DEA output to account for variations in site characteristics and to ensure that the final funding allocations were fair. The new process has led to changes in bus routes and schedules, adjustments in school start and stop times, and reductions in the inventory of buses. Between 1990 and 1993, the state saved $25.2 million in capital costs and $27.9 million in operating costs, and it expects savings to increase.

Suggested Citation

  • Thomas R. Sexton & Sally Sleeper & Robert E. Taggart, 1994. "Improving Pupil Transportation in North Carolina," Interfaces, INFORMS, vol. 24(1), pages 87-103, February.
    • Handle: RePEc:inm:orinte:v:24:y:1994:i:1:p:87-103
    DOI: 10.1287/inte.24.1.87
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    Citations

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    Cited by:

    1. Miningou, Élisé Wendlassida & Vierstraete, Valérie, 2013. "Households' living situation and the efficient provision of primary education in Burkina Faso," Economic Modelling, Elsevier, vol. 35(C), pages 910-917.
    2. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    3. Thomas Sexton & Herbert Lewis, 2012. "Measuring efficiency in the presence of head-to-head competition," Journal of Productivity Analysis, Springer, vol. 38(2), pages 183-197, October.
    4. Haas, David A. & Murphy, Frederic H., 2003. "Compensating for non-homogeneity in decision-making units in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 144(3), pages 530-544, February.
    5. Andrea Guerrini & Giulia Romano & Bettina Campedelli, 2013. "Economies of Scale, Scope, and Density in the Italian Water Sector: A Two-Stage Data Envelopment Analysis Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(13), pages 4559-4578, October.
    6. George Halkos & Mike G. Tsionas, 2019. "Accounting for Heterogeneity in Environmental Performance Using Data Envelopment Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 54(3), pages 1005-1025, October.
    7. Ross, Anthony D., 2000. "Performance-based strategic resource allocation in supply networks," International Journal of Production Economics, Elsevier, vol. 63(3), pages 255-266, January.
    8. Wooseung Jang & Huay H. Lim & Thomas J. Crowe & Gail Raskin & Thomas E. Perkins, 2006. "The Missouri Lottery Optimizes Its Scheduling and Routing to Improve Efficiency and Balance," Interfaces, INFORMS, vol. 36(4), pages 302-313, August.
    9. Xiang Ji & Jie Wu & Qingyuan Zhu & Jiasen Sun, 2019. "Using a hybrid heterogeneous DEA method to benchmark China’s sustainable urbanization: an empirical study," Annals of Operations Research, Springer, vol. 278(1), pages 281-335, July.
    10. Chen, Chailin & Cook, Wade D. & Imanirad, Raha & Zhu, Joe, 2020. "Balancing Fairness and Efficiency: Performance Evaluation with Disadvantaged Units in Non-homogeneous Environments," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1003-1013.
    11. Herbert F. Lewis & Thomas R. Sexton & Kathleen A. Lock, 2007. "Player Salaries, Organizational Efficiency, and Competitiveness in Major League Baseball," Journal of Sports Economics, , vol. 8(3), pages 266-294, June.
    12. Mallikarjun, Sreekanth & Lewis, Herbert F. & Sexton, Thomas R., 2014. "Operational performance of U.S. public rail transit and implications for public policy," Socio-Economic Planning Sciences, Elsevier, vol. 48(1), pages 74-88.
    13. Maria Alberta Oliveira & Carlos Santos, 2005. "Assessing school efficiency in Portugal using FDH and bootstrapping," Applied Economics, Taylor & Francis Journals, vol. 37(8), pages 957-968.
    14. Malczewski, Jacek & Jackson, Marlene, 2000. "Multicriteria spatial allocation of educational resources: an overview," Socio-Economic Planning Sciences, Elsevier, vol. 34(3), pages 219-235, September.
    15. Cavaignac, Laurent & Petiot, Romain, 2017. "A quarter century of Data Envelopment Analysis applied to the transport sector: A bibliometric analysis," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 84-96.

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