Skip to main content

Allocating the Subsidy Among Urban Public Transport Enterprises for Good Performance and Low Carbon Transportation: An Application of DEA

  • Conference paper
  • First Online:
Book cover LTLGB 2012

Abstract

This paper proposes a stimulating mechanism for allocating subsidies to urban public transport enterprises. The allocation method is based on data envelopment analysis and the satisfaction degrees of urban public transport enterprises. It first finds the set of subsidy allocation that can keep the Pareto efficient for both the whole urban public transit industry and each urban public transport enterprise to reflect the efficiency principle, and then yields a unique subsidy allocation scheme from the set of subsidy allocations with considering the equity of satisfaction degrees. The allocation mechanism can reflect the market competition regulation on some level and benefit to achieve the goal of Green Transport in urban public transit industry. An example of allocating the subsidy among urban public transport enterprises is illustrated.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Asmild M, Paradi JC, Pastor JT (2009) Centralized resource allocation BCC models. Omega 37:40–49

    Article  Google Scholar 

  • Avellar JVG, Milioni AZ, Rabello TN (2007) Spherical frontier DEA model based on a constant sum of inputs. JOper Res Soc 58:1246–1251

    Article  Google Scholar 

  • Beasley JE (2003) Allocating fixed costs and resources via data envelopment analysis. Eur J Oper Res 147:198–216

    Article  Google Scholar 

  • Bertsimas D, Farias VF, Trichakis N (2011) The price of fairness. Oper Res 59(1):17–31

    Article  Google Scholar 

  • Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2:429–444

    Article  Google Scholar 

  • Cook WD, Kress M (1999) Characterizing an equitable allocation of shared costs: a DEA approach. Eur J Oper Res 119:652–661

    Article  Google Scholar 

  • Cook WD, Zhu J (2005) Allocation of shared costs among decision making units: a DEA approach. Comput Oper Res 32:2171–2178

    Article  Google Scholar 

  • Gomes EG, Lins MPE (2008) Modelling undesirable outputs with zero sum gains data envelopment analysis models. J Oper Res Soc 59:616–623

    Article  Google Scholar 

  • Karlaftis MG (2004) A DEA approach for evaluating the efficiency and effectiveness of urban transit systems. Eur J Oper Res 152:354–364

    Article  Google Scholar 

  • Kolm S (1971) Justice et Equite. CEPREMAP, Paris

    Google Scholar 

  • Lao Y, Liu L (2009) Performance evaluation of bus lines with data envelopment analysis and geographic information systems. Comput Environ Urban Syst 33:247–255

    Article  Google Scholar 

  • Li YJ, Yang F, Liang L, Hua ZS (2009) Allocating the fixed cost as a complement of other cost inputs: a DEA approach. Eur J Oper Res 197:389–401

    Article  Google Scholar 

  • Li YJ, Yang M, Chen Y, Dai QZ, Liang L (2012) Allocating a fixed cost based on data envelopment analysis and satisfaction degree. Omega (in press)

    Google Scholar 

  • Lins MPE, Gomes EG, Mello JCCBS, Mello AJRS (2003) Olympic ranking based on a zero sum gains DEA model. Eur J Oper Res 148:312–322

    Article  Google Scholar 

  • Lozano SA, Villa G (2004) Centralized resource allocation using data envelopment analysis. J Prod Anal 22:143–161

    Article  Google Scholar 

  • Lozano SA, Villa G (2005) Centralized DEA models with the possibility of downsizing source. J Oper Res Soc 56(4):357–364

    Article  Google Scholar 

  • Lozano SA, Villa G, Adenso-Diaz B (2004) Centralized target setting for regional recycling operations using DEA. Omega. 32:101–110

    Article  Google Scholar 

  • Milioni AZ, Avellar JVG, Gomes EG, Mello JCCBS (2011) An ellipsoidal frontier model: Allocating input via parametric DEA. Eur J Oper Res 209:113–121

    Article  Google Scholar 

  • Rawls J (1971) A theory of justice. Harvard University Press, Cambridge

    Google Scholar 

  • Yan W, Wei Q (2011) Data envelopment analysis classification machine. Inf Sci 18:5029–5041

    Article  Google Scholar 

  • 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. Transp Res Part E 47:1140–1159

    Article  Google Scholar 

Download references

Acknowledgments

This research is supported by National Natural Science Foundation of China under Grants (No. 70901070 and 61101219), Science Fund for Creative Research Groups of the National Natural Science Foundation of China (No. 70821001) and the Funds for International Cooperation and Exchange of the National Natural Science Foundation of China (No. 71110107024).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Qianzhi Dai .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Dai, Q., Li, Y., Xie, Q., Liang, L. (2013). Allocating the Subsidy Among Urban Public Transport Enterprises for Good Performance and Low Carbon Transportation: An Application of DEA. In: Chen, F., Liu, Y., Hua, G. (eds) LTLGB 2012. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34651-4_15

Download citation

Publish with us

Policies and ethics