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Selection of possible scenarios for improving the quality of public transport services through the use of hybrid fuzzy-MCDM models

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Języki publikacji
EN
Abstrakty
EN
A unified calculating approach is needed for public passenger transportation. All public transport companies and other stakeholders would have additional opportunities to create a transport offer if the unified methodology was made available to them and if calculations and calculation criteria were harmonized. Thus, the main goal – improving citizen mobility – would be accomplished. For this reason, in the study, we suggested the hybrid fuzzy methods for evaluating and improving the quality of public transport service. Unreliable responses of survey participants often distort group decision-making regarding the problem of public services, negatively affecting the end of the calculation procedure. Fuzzy multicriteria decision-making approach has been used. The suggested technique has the advantage of taking into account the degree of fuzzification of respondents' judgments about the choice scenario, while also using two MCDM models to eliminate bias in the responses.
Rocznik
Tom
Strony
189--198
Opis fizyczny
Bibliogr. 20 poz.
Twórcy
  • The University of Texas at Arlington, 701 South Nedderman Drive, Arlington, TX, 76019, 817-272-2011. United States
  • Faculty of Transport and Aviation Engineering, The Silesian University of Technology, Krasińskiego 8 Street, 40-019 Katowice, Poland
  • Center for Technology and Society, Technische Universität Berlin, Kaiserin-Augusta-Allee 104, 10553 Berlin, Germany
Bibliografia
  • 1. Jacyna M., M. Wasiak, K. Lewczuk, M. Kłodawski. 2014. “Simulation model of transport system of Poland as a tool for developing sustainable transport”. Archives of Transport 31(3): 23-35.
  • 2. Our Common Future. Report of the World Commission on Environment and Development. 1987.
  • 3. Communication From The Commission To The European Parliament, The Council, The European Economic And Social Committee And The Committee Of The Regions: Clean Power for Transport: A European alternative fuels strategy. COM(2013)17. Brussels. 24.01.2013.
  • 4. Banister D. 2008. “The sustainable mobility paradigm. Transport Policy 15: 73-80. Elsevier.
  • 5. Jacyna M., J. Merkisz. 2014. “Proecological approach to modelling traffic organization in national transport system”. Archives of Transport 2(30): 43-56.
  • 6. White Paper on the Future of Europe, Reflections and scenarios for the EU27 by 2025. COM(2017)2025. 2017.
  • 7. White Paper: Roadmap to a Single European Transport Area – Towards a competitive and resource efficient transport system. COM(2011)144. 2011.
  • 8. Starowicz W. 2007. Jakość przewozów w miejskim transporcie zbiorowym. [In Polish: Quality of transport in urban collective transport]. Publishing house of the Cracow University of Technology. Cracow.
  • 9. 'Public Transport First' Strategy, Annex A of the Handbook 'Navigating Transport NAMAs'. A practical handbook. Eschborn, Germany. 2015.
  • 10. Szabolcs Duleba, Sarbast Moslem. 2019. “Examining Pareto optimality in analytic hierarchy process on real Data: An application in public transport service development”. Expert Systems with Applications 116: 21-30. ISSN: 0957-4174. DOI: https://doi.org/10.1016/j.eswa.2018.08.049.
  • 11. Fatma Kutlu Gündoğdu, Szabolcs Duleba, Sarbast Moslem, Serhat Aydın. 2021. “Evaluating public transport service quality using picture fuzzy analytic hierarchy process and linear assignment model”. Applied Soft Computing 100: 106920. ISSN: 1568-4946. DOI: https://doi.org/10.1016/j.asoc.2020.106920.
  • 12. Redman Lauren, Margareta Friman, Tommy Gärling, Terry Hartig. 2013. “Quality attributes of public transport that attract car users: A research review”. Transport Policy 25: 119-127. ISSN: 0967-070X. DOI: https://doi.org/10.1016/j.tranpol.2012.11.005.
  • 13. BEST. Benchmarking in European Service of Public Transport. Available at: http://benchmarkingpublictransport.org/.
  • 14. Kłos Marcin Jacek, Grzegorz Sierpiński. 2021. „Building a Model of Integration of Urban Sharing and Public Transport Services”. Sustainability 13(6): 3086. DOI: https://doi.org/10.3390/su13063086.
  • 15. Broniewicz E., K. Ogrodnik. 2021. “A comparative evaluation of multi-criteria analysis methods for sustainable transport”. Energies 14: 16. DOI: https://doi.org/10.3390/en14165100.
  • 16. Ziemba P. 2021. “Selection of Electric Vehicles for the Needs of Sustainable Transport under Conditions of Uncertainty – A Comparative Study on Fuzzy MCDA Methods”. Energies 14: 7786. DOI: https://doi.org/10.3390/en14227786.
  • 17. Moradi Shohreh, Grzegorz Sierpiński, Houshmand Masoumi. 2022. “System Dynamics Modeling and Fuzzy MCDM Approach as Support for Assessment of Sustainability Management on the Example of Transport Sector Company”. Energies 15(13): 4917. DOI: https://doi.org/10.3390/en15134917.
  • 18. Saaty T.L., Ozdemir M.S. 2003. “Why the magic number seven plus or minus two”. Mathematical and Computer Modelling 38: 233-244. DOI: https://doi.org/10.1016/S0895-7177(03)90083-5.
  • 19. Yan Liu, Claudia Eckert, Gwenola Yannou-Le Bris, Gaëlle Petit. 2019. “A fuzzy decision tool to evaluate the sustainable performance of suppliers in an agrifood value chain”. Computers & Industrial Engineering 127: 196-212. ISSN: 0360-8352. DOI: https://doi.org/10.1016/j.cie.2018.12.022.
  • 20. Buckley J.J. 1985. “Fuzzy hierarchical analysis”. Fuzzy sets and systems 17(3): 233-247.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-eff82874-ec1d-492c-8008-b04b4fda1a9a
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