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A data envelopment analysis based for evaluating efficiency of bus public routes

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The public transport service is highly essential to meet the demand due to a rapidly growing population and mobility. Thus providing public service and improve its service becomes an urgent need in recent years. In Iraq, the Bus system represents the backbone in public transportation, which is based mainly on highway infrastructure. To meet the growing mobility needs, enhancing public service provided only by bus routes is essential. Measuring bus route performance represents one of the crucial transit research topics in the last recent years. The current study tries to investigate the urban public route's efficiency utilizing the "data envelopment analysis (DEA)" technique. To analyze route performance, DEA is using, and performance measures include route design, cost, service, operation, and comfort efficiency are selected and calculated for different routes. Efficiency and effectiveness are the output of this process. Bus company owners can also use the results of this study to improve their services, attract new customers, and better manage their resources.
Rocznik
Strony
303--323
Opis fizyczny
Bibliogr. 31 poz., il., tab.
Twórcy
autor
  • Mustansiriyah University, College of Engineering, Highway and Transportation Engineering Department, Baghdad, Iraq
autor
  • University of Technology, Civil Engineering Department, Baghdad, Iraq
Bibliografia
  • [1] N. M. Asmael and N. G. A. Alkawaaz, “The Influence Change of Private Car Ownership on Patterns of Mode Choice in Baghdad city,” in IOP Conference Series: Materials Science and Engineering, 2019, vol. 518, no. 2, p. 22025.
  • [2] G. Georgiadis, I. Politis, and P. Papaioannou, “Measuring and improving the efficiency and effectiveness of bus public transport systems,” Res. Transp. Econ., vol. 48, pp. 84-91, 2014.
  • [3] M. P. Boilé, “Estimating technical and scale inefficiencies of public transit systems,” J. Transp. Eng., vol. 127, no. 3, pp. 187-194, 2001.
  • [4] A. S. Shalaby, “Simulating performance impacts of bus lanes and supporting measures,” J. Transp. Eng., vol. 125, no. 5, pp. 390-397, 1999.
  • [5] M. G. Karlaftis, “A DEA approach for evaluating the efficiency and effectiveness of urban transit systems,” Eur. J. Oper. Res., vol. 152, no. 2, pp. 354-364, 2004.
  • [6] S. Ngamchai and D. J. Lovell, “Optimal time transfer in bus transit route network design using a genetic algorithm,” J. Transp. Eng., vol. 129, no. 5, pp. 510-521, 2003.
  • [7] V. M. Tom and S. Mohan, “Transit route network design using frequency coded genetic algorithm,” J. Transp. Eng., vol. 129, no. 2, pp. 186-195, 2003.
  • [8] A. Shalaby and A. Farhan, “Prediction model of bus arrival and departure times using AVL and APC data,” J. Public Transp., vol. 7, no. 1, p. 3, 2004.
  • [9] N. Eluru, V. Chakour, and A. M. El-Geneidy, “Travel mode choice and transit route choice behavior in Montreal: insights from McGill University members commute patterns,” Public Transp., vol. 4, no. 2, pp. 129-149, 2012.
  • [10] W. Fan and R. B. Machemehl, “Optimal transit route network design problem with variable transit demand: genetic algorithm approach,” J. Transp. Eng., vol. 132, no. 1, pp. 40-51, 2006.
  • [11] M. Carvalho and T. Syguiy, “Efficiency and Effectiveness Analysis of Public Transport of Brazilian Cities,” J. Transp. Lit., vol. 9, no. 3, pp. 40-44, 2015.
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  • [13] A. Bandyopadhayay, A. Banerjee, and N. Abidi, “RETRACTED ARTICLE: Measuring Routes Efficiency of Kolkata Bus Transport: A Modified DEA Approach,” Ann. Data Sci., vol. 3, no. 3, p. 305, 2016.
  • [14] J. Hahn, H. Kim, and S. Kho, “A DEA Approach for Evaluating the Efficiency of Bus Routes,” J. East. Asia Soc. Transp. Stud., vol. 8, pp. 1217-1229, 2010.
  • [15] J.-S. Hahn, H.-R. Kim, and S.-Y. Kho, “Analysis of the efficiency of Seoul Arterial Bus routes and its determinant factors,” KSCE J. Civ. Eng., vol. 15, no. 6, pp. 1115-1123, 2011.
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  • [17] A. Charnes, W. W. Cooper, and E. Rhodes, “Measuring the efficiency of decision making units,” Eur. J. Oper. Res., vol. 2, no. 6, pp. 429-444, 1978.
  • [18] R. D. Banker, “Estimating most productive scale size using data envelopment analysis,” Eur. J. Oper. Res., vol. 17, no. 1, pp. 35-44, 1984.
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  • [20] W. W. Cooper, L. M. Seiford, and K. Tone., Data Envelopment Analysis. Kluwer Academic Publishers, Boston, 2004.
  • [21] R. Färe and S. Grosskopf, “Productivity and intermediate products: A frontier approach,” Econ. Lett., vol. 50, no. 1, pp. 65-70, 1996.
  • [22] R. Ramanathan, “A holistic approach to compare energy efficiencies of different transport modes,” Energy Policy, vol. 28, no. 11, pp. 743-747, 2000.
  • [23] W. D. Cook and L. M. Seiford, “Data envelopment analysis (DEA)–Thirty years on,” Eur. J. Oper. Res., vol. 192, no. 1, pp. 1-17, 2009.
  • [24] W. W. Cooper, “Seiford. LM and Tone, K.(2000) Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software.” Boston: Kluwer Academic Publishers, 2007.
  • [25] K. Sarıca and I. Or, “Efficiency assessment of Turkish power plants using data envelopment analysis,” Energy, vol. 32, no. 8, pp. 1484-1499, 2007.
  • [26] D. T. Barnum, S. Tandon, and S. McNeil, “Comparing the performance of bus routes after adjusting for the environment using data envelopment analysis,” J. Transp. Eng., vol. 134, no. 2, pp. 77-85, 2008.
  • [27] N. Asmael and M. Waheed, “Demand estimation of bus as a public transport based on gravity model,” in MATEC Web of Conferences, 2018, vol. 162, p. 1038.
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-183b2e02-a68a-4377-b4bc-640ee62d8f5f
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