Analyzing public travel demand by a fuzzy analytic hierarchy process model for supporting transport planning
Abstract
Travel demand plays an essential role in strategic transport planning. Generally, experts use either discrete methods, e.g. discrete choice models or simulation, e.g. activity-based models to estimate demand in transportation. This paper offers a different solution; instead of using the traditional approach, the demand is considered as a Multi Criteria Decision Making (MCDM) problem and surveying the citizens’ preferences provides the results for decision support. Public transport demand depends on two main issues, quality and price of the transportation. In a hierarchical model, both issues have been integrated and the well-proven Analytic Hierarchical Process (AHP) method has been applied in the current research. Further, fuzzyfication of the scores have also been conducted because of the citizen evaluator pattern. The fuzzy-AHP (FAHP) model has been tested in a real-world situation with the case study of Amman (Jordan).
First published online 17 January 2022
Keyword : public transport, travel demand, multi criteria decision making (MCDM), fuzzy-AHP (FAHP), transport planning, questionnaire survey
How to Cite
Alkharabsheh, A., Moslem, S., & Duleba, S. (2022). Analyzing public travel demand by a fuzzy analytic hierarchy process model for supporting transport planning. Transport, 37(2), 110–120. https://doi.org/10.3846/transport.2022.15881
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Chowdhury, S.; Hadas, Y.; Gonzalez, V. A.; Schot, B. 2018. Public transport users’ and policy makers’ perceptions of integrated public transport systems, Transport Policy 61: 75–83. https://doi.org/10.1016/j.tranpol.2017.10.001
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Duleba, S.; Shimazaki, Y.; Mishina, T. 2013. An analysis on the connections of factors in a public transport system by AHPISM, Transport 28(4): 404–412. https://doi.org/10.3846/16484142.2013.867282
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Gao, T.; Na, S.; Dang, X.; Zhang, Y. 2018. Study of the competitiveness of Quanzhou port on the belt and road in China based on a fuzzy-AHP and ELECTRE III model, Sustainability 10(4): 1253. https://doi.org/10.3390/su10041253
Ghorbanzadeh, O.; Moslem, S.; Blaschke, T.; Duleba, S. 2019. Sustainable urban transport planning considering different stakeholder groups by an interval-AHP decision support model, Sustainability 11(1): 9. https://doi.org/10.3390/su11010009
Grošelj, P.; Zadnik Stirn, L. 2018. Evaluation of several approaches for deriving weights in fuzzy group analytic hierarchy process, Journal of Decision Systems 27(suppl 1): 217–226. https://doi.org/10.1080/12460125.2018.1460160
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Haghighathoseini, A.; Bobarshad, H.; Saghafi, F.; Rezaei, M. S.; Bagherzadeh, N. 2018. Hospital enterprise architecture framework (study of Iranian university hospital organization), International Journal of Medical Informatics 114: 88–100. https://doi.org/10.1016/j.ijmedinf.2018.03.009
Hasnine, M. S.; Habib, K. N. 2018. What about the dynamics in daily travel mode choices? A dynamic discrete choice approach for tour-based mode choice modelling, Transport Policy 71: 70–80. https://doi.org/10.1016/j.tranpol.2018.07.011
Hatefi, S. M.; Tamošaitienė, J. 2018. Construction projects assessment based on the sustainable development criteria by an integrated fuzzy AHP and improved GRA model, Sustainability 10(4): 991. https://doi.org/10.3390/su10040991
Hine, J.; Scott, J. 2000. Seamless, accessible travel: users’ views of the public transport journey and interchange, Transport Policy 7(3): 217–226. https://doi.org/10.1016/S0967-070X(00)00022-6
Hsieh, T.-Y.; Lu, S.-T.; Tzeng, G.-H. 2004. Fuzzy MCDM approach for planning and design tenders selection in public office buildings, International Journal of Project Management 22(7): 573–584. https://doi.org/10.1016/j.ijproman.2004.01.002
Imam, R. 2014. Measuring public transport satisfaction from user surveys, International Journal of Business and Management 9(6): 106–114. https://doi.org/10.5539/ijbm.v9n6p106
John, A.; Yang, Z.; Riahi, R.; Wang, J. 2014. Application of a collaborative modelling and strategic fuzzy decision support system for selecting appropriate resilience strategies for seaport operations, Journal of Traffic and Transportation Engineering (English Edition) 1(3): 159–179. https://doi.org/10.1016/S2095-7564(15)30101-X
Kumar, A.; Pal, A.; Vohra, A.; Gupta, S.; Manchanda, S.; Dash, M. K. 2018. Construction of capital procurement decision making model to optimize supplier selection using fuzzy Delphi and AHP-DEMATEL, Benchmarking: an International Journal 25(5): 1528–1547. https://doi.org/10.1108/BIJ-01-2017-0005
Lai, W.-T.; Chen, C.-F. 2011. Behavioral intentions of public transit passengers – the roles of service quality, perceived value, satisfaction and involvement, Transport Policy 18(2): 318–325. https://doi.org/10.1016/j.tranpol.2010.09.003
Liou, J. J. H.; Chuang, M.-L. 2010. Evaluating corporate image and reputation using fuzzy MCDM approach in airline market, Quality & Quantity 44(6): 1079–1091. https://doi.org/10.1007/s11135-009-9259-2
Liou, J. J. H.; Yen, L.; Tzeng, G.-H. 2008. Building an effective safety management system for airlines, Journal of Air Transport Management 14(1): 20–26. https://doi.org/10.1016/j.jairtraman.2007.10.002
Lirn, T.-C.; Thanopoulou, H. A.; Beresford, A. K. C. 2003. Transhipment port selection and decision-making behaviour: analysing the Taiwanese case, International Journal of Logistics Research and Applications: a Leading Journal of Supply Chain Management 6(4): 229–244. https://doi.org/10.1080/13675560310001626990
Lupo, T. 2013. Handling stakeholder uncertain judgments in strategic transport service analyses, Transport Policy 29: 54–63. https://doi.org/10.1016/j.tranpol.2013.04.002
McNally, M. G. 2007. The four-step model, in D. A. Hensher, K. J. Button (Ed.). Handbook of Transport Modelling 1: 35–53. https://doi.org/10.1108/9780857245670-003
Mokonyama, M.; Venter, C. 2013. Incorporation of customer satisfaction in public transport contracts – a preliminary analysis, Research in Transportation Economics 39(1): 58–66. https://doi.org/10.1016/j.retrec.2012.05.024
Moslem, S.; Duleba, S. 2019. Sustainable urban transport development by applying a fuzzy-AHP model: a case study from Mersin, Turkey, Urban Science 3(2): 55. https://doi.org/10.3390/urbansci3020055
Moslem, S.; Ghorbanzadeh, O.; Blaschke, T.; Duleba, S. 2019. Analysing stakeholder consensus for a sustainable transport development decision by the fuzzy AHP and interval AHP, Sustainability 11(12): 3271. https://doi.org/10.3390/su11123271
Murat, Y. S.; Arslan, T.; Cakici, Z.; Akcam, C. 2016. Analytical hierarchy process (AHP) based decision support system for urban intersections in transportation planning, in E. V. Ocalir-Akunal (Ed.). Using Decision Support Systems for Transportation Planning Efficiency, 203–222. https://doi.org/10.4018/978-1-4666-8648-9.ch008
Ngossaha, J. M.; Ngouna, R. H.; Archimede, B.; Nlong, J. M. 2017. Sustainability assessment of a transportation system under uncertainty: an integrated multicriteria approach, IFACPapersOnLine 50(1): 7481–7486. https://doi.org/10.1016/j.ifacol.2017.08.1064
Pantouvakis, A.; Lymperopoulos, K. 2008. Customer satisfaction and loyalty in the eyes of new and repeat customers: evidence from the transport sector, Managing Service Quality: an International Journal 18(6): 623–643. https://doi.org/10.1108/09604520810920103
Paquette, J.; Bellavance, F.; Cordeau, J. F.; Laporte, G. 2012. Measuring quality of service in dial-a-ride operations: the case of a Canadian city, Transportation 39(3): 539–564. https://doi.org/10.1007/s11116-011-9375-4
Park, K.-S.; Seo, Y.-J.; Kim, A.-R.; Ha, M.-H. 2018. Ship acquisition of shipping companies by sale & purchase activities for sustainable growth: exploratory fuzzy-AHP application, Sustainability 10(6): 1763. https://doi.org/10.3390/su10061763
Pendyala, R. M.; Kitamura, R.; Kikuchi, A.; Yamamoto, T.; Fujii, S. 2005. Florida activity mobility simulator: overview and preliminary validation results, Transportation Research Record: Journal of the Transportation Research Board 1921: 123–130. https://doi.org/10.1177/0361198105192100114
Rasouli, S.; Timmermans, H. 2012. Uncertainty in travel demand forecasting models: literature review and research agenda, Transportation Letters: the International Journal of Transportation Research 4(1): 55–73. https://doi.org/10.3328/TL.2012.04.01.55-73
Redman, L.; Friman, M.; Garling, T.; Hartig, T. 2013. Quality attributes of public transport that attract car users: a research review, Transport Policy 25: 119–127. https://doi.org/10.1016/j.tranpol.2012.11.005
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