Share:


Analyzing public travel demand by a fuzzy analytic hierarchy process model for supporting transport planning

    Ahmad Alkharabsheh Affiliation
    ; Sarbast Moslem Affiliation
    ; Szabolcs Duleba Affiliation

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
Published in Issue
Jun 7, 2022
Abstract Views
894
PDF Downloads
678
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Abastante, F.; Corrente, S.; Greco, S.; Ishizaka, A.; Lami, I. M. 2018. Choice architecture for architecture choices: evaluating social housing initiatives putting together a parsimonious AHP methodology and the Choquet integral, Land Use Policy 78: 748–762. https://doi.org/10.1016/j.landusepol.2018.07.037

Arslan, T. 2009. A hybrid model of fuzzy and AHP for handling public assessments on transportation projects, Transportation 36(1): 97–112. https://doi.org/10.1007/s11116-008-9181-9

Balaji, M.; Santhanakrishnan, S.; Dinesh, S. N. 2019. An application of analytic hierarchy process in vehicle routing problem. Periodica Polytechnica Transportation Engineering 47(3): 196–205. https://doi.org/10.3311/PPtr.10701

Bhat, C. R. 2018. A new flexible multiple discrete–continuous extreme value (MDCEV) choice model, Transportation Research Part B: Methodological 110: 261–279. https://doi.org/10.1016/j.trb.2018.02.011

Bilişik, O. N.; Erdoğan, M.; Kaya, İ.; Baraclı, H. 2013. A hybrid fuzzy methodology to evaluate customer satisfaction in a public transportation system for Istanbul, Total Quality Management & Business Excellence 24(9–10): 1141–1159. https://doi.org/10.1080/14783363.2013.809942

Bowman, J. L.; Ben-Akiva, M. E. 2001. Activity-based disaggregate travel demand model system with activity schedules, Transportation Research Part A: Policy and Practice 35(1): 1–28. https://doi.org/10.1016/S0965-8564(99)00043-9

Chen, Y.; Wang, S.; Yao, J.; Li, Y.; Yang, S. 2018. Socially responsible supplier selection and sustainable supply chain development: a combined approach of total interpretive structural modeling and fuzzy analytic network process, Business Strategy and the Environment 27(8): 1708–1719. https://doi.org/10.1002/bse.2236

Chiou, Y.-C.; Chen, Y.-H. 2012. Service quality effects on air passenger intentions: a service chain perspective, Transportmetrica 8(6): 406–426. https://doi.org/10.1080/18128602.2010.548837

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

Del Castillo, J. M.; Benitez, F. G. 2012. A methodology for modeling and identifying users satisfaction issues in public transport systems based on users surveys, Procedia – Social and Behavioral Sciences 54: 1104–1114. https://doi.org/10.1016/j.sbspro.2012.09.825

DoS. 2017. Statistical Yearbook of Jordan 2017. Department of Statistics (DoS), Amman, Jordan. 324 p. Available from Internet: http://dosweb.dos.gov.jo/databank/Yearbook2017/YearBook2017.pdf

Duleba, S.; Mishina, T.; Shimazaki, Y. 2012. A dynamic analysis on public bus transport’s supply quality by using AHP, Transport 27(3): 268–275. https://doi.org/10.3846/16484142.2012.719838

Duleba, S.; Moslem, S. 2018. Sustainable urban transport development with stakeholder participation, an AHP–Kendall model: a case study for Mersin, Sustainability 10(10): 3647. https://doi.org/10.3390/su10103647

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

Eboli, L.; Mazzulla, G. 2008. A stated preference experiment for measuring service quality in public transport, Transportation Planning and Technology 31(5): 509–523. https://doi.org/10.1080/03081060802364471

Eboli, L.; Mazzulla, G. 2007. Service quality attributes affecting customer satisfaction for bus transit, Journal of Public Transportation 10(3): 21–34. https://doi.org/10.5038/2375-0901.10.3.2

Farooq, D.; Moslem, S.; Duleba, S. 2019. Evaluation of driver behavior criteria for evolution of sustainable traffic safety, Sustainability 11(11): 3142. https://doi.org/10.3390/su11113142

GAM. 2010. Transport and Mobility Master Plan for Amman. Final Report. Greater Amman Municipality (GAM), Amman, Jordan. 156 p. Available from Internet: http://www.ammanbrt.jo/contents/Articles/2020/4/20/%D8%A7%D9%84%D9%85%D8%AE%D8%B7%D8%B7%D8%A7%D9%84%D8%B4%D9%85%D9%88%D9%84%D9%8A%D9%84%D9%84%D9%86%D9%82%D9%84%D9%88%D8%A7%D9%84%D8%AD%D8%B1%D9%83%D9%87%D9%81%D9%8A%D9%85%D8%AF%D9%8A%D9%86%D8%A9%D8%B9%D9%85%D8%A7%D9%86160322.pdf

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

Gupta, V. 2018. Comparative performance of contradictory and non-contradictory judgement matrices in AHP under qualitative and quantitative metrics, International Journal of Decision Support System Technology 10(1): 21–38. https://doi.org/10.4018/IJDSST.2018010102

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

Rohani, M. M.; Wijeyesekera, D. C.; Karim, A. T. A. 2013. Bus operation, quality service and the role of bus provider and driver, Procedia Engineering 53: 167–178. https://doi.org/10.1016/j.proeng.2013.02.022

Ruiz-Padillo, A.; Pasqual, F. M.; Larranaga Uriarte, A. M.; Bettella Cybis, H. B. 2018. Application of multi-criteria decision analysis methods for assessing walkability: a case study in Porto Alegre, Brazil, Transportation Research Part D: Transport and Environment 63: 855–871. https://doi.org/10.1016/j.trd.2018.07.016

Saaty, T. L. 1977. A scaling method for priorities in hierarchical structures, Journal of Mathematical Psychology 15(3): 234–281. https://doi.org/10.1016/0022-2496(77)90033-5

Saaty, Т. L. 1980. The Analytic Hierarchy Process. McGraw-Hill.

Sun, C.-C. 2010. A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods, Expert Systems with Applications 37(12): 7745–7754. https://doi.org/10.1016/j.eswa.2010.04.066

Tan, R. R.; Aviso, K. B.; Huelgas, A. P.; Promentilla, M. A. B. 2014. Fuzzy AHP approach to selection problems in process engineering involving quantitative and qualitative aspects, Process Safety and Environmental Protection 92(5): 467–475. https://doi.org/10.1016/j.psep.2013.11.005

Taskin Gumus, A. 2009. Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology, Expert Systems with Applications 36(2): 4067–4074. https://doi.org/10.1016/j.eswa.2008.03.013

Teng, J.-Y.; Huang, W.-C.; Lin, M.-C. 2010. Systematic budget allocation for transportation construction projects: a case in Taiwan, Transportation 37(2): 331–361. https://doi.org/10.1007/s11116-009-9239-3

Yayla, A. Y.; Oztekin, A.; Gumus, A. T.; Gunasekaran, A. 2015. A hybrid data analytic methodology for 3PL transportation provider evaluation using fuzzy multi-criteria decision making, International Journal of Production Research 53(20): 6097–6113. https://doi.org/10.1080/00207543.2015.1022266