An AHP-ISM approach for considering public preferences in a public transport development decision
Abstract
Recently, there has been a transparent need to involve public in transport development decisions not only in the EU but also in other countries worldwide. Public involvement in decision-making, however, suffers from two critical issues: lack of expertise and lack of enthusiasm. This paper aims to overcome the first problem: how to amend passenger preferences related to public transport development with expert knowledge on transport systems. For this purpose, a new research methodology has been created which combines the well proven Analytic Hierarchy Process (AHP) and Interpretive Structural Modelling (ISM) methods in a novel way. ISM is used to reveal the non-hierarchical connections of the transport system elements and by this, AHP results are modified with the consideration of element interactions. The first stage of the three-stage-survey has been conducted in Yurihonjo (Japan), the second and third in an international workshop with the participation of experts. Results show that the original AHP scores – gained from passenger evaluations – are significantly modified by adding expert knowledge on factor interactions, thus new preference order is gained related to the importance of the development of public transport system elements. The introduced procedure can be applied for other public transport system improvement decision-making situations in which passenger involvement is required.
First published online 18 March 2019
Keyword : AHP, ISM, passenger preferences, MCDM, element interactions, public involvement
How to Cite
Duleba, S. (2019). An AHP-ISM approach for considering public preferences in a public transport development decision. Transport, 34(6), 662-671. https://doi.org/10.3846/transport.2019.9080
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Al-Atawi, A. M.; Kumar, R.; Saleh, W. 2016. Transportation sustainability index for Tabuk city in Saudi Arabia: an analytic hierarchy process, Transport 31(1): 47–55. https://doi.org/10.3846/16484142.2015.1058857
Barić, D.; Pilko, H.; Strujić, J. 2016. An analytic hierarchy process model to evaluate road section design, Transport 31(3): 312–321. https://doi.org/10.3846/16484142.2016.1157830
Bhushan, N.; Ria, K. 2004. Strategic Decision Making: Applying the Analytic Hierarchy Process. Springer-Verlag London. 172 p.
Burall, S.; Shahrokh, T. 2010. What the Public Say: Public Engagement in National Decision-Making. Involve Company, UK. 18 p. Available from Internet: https://www.involve.org.uk/resources/publications/project-reports/what-public-say-public-engagement-national-decision-making
Cascetta, E.; Pagliara, F. 2013. Public engagement for planning and designing transportation systems, Procedia – Social and Behavioral Sciences 87: 103–116. https://doi.org/10.1016/j.sbspro.2013.10.597
Chen, S.; Pham, V. K.; Chen, J. K. 2016. Evaluating and selecting the best outsourcing service country in East and Southeast Asia: an AHP approach, Journal of Testing and Evaluation 44(1): 89–101. https://doi.org/10.1520/JTE20140065
De Luca, S. 2014. Public engagement in strategic transportation planning: an analytic hierarchy process based approach, Transport Policy 33: 110–124. https://doi.org/10.1016/j.tranpol.2014.03.002
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.; Shimazaki, Y.; Mishina, T. 2013. An analysis on the connections of factors in a public transport system by AHP-ISM, Transport 28(4): 404–412. https://doi.org/10.3846/16484142.2013.867282
Eswarlal, V. K.; Dey, P. K.; Shankar, R. 2011. Enhanced renewable energy adoption for sustainable development in India: interpretive structural modeling approach, in Proceedings from the World Renewable Energy Congress, 8–13 May 2011, Linkoping, Sweden, 351–358. https://doi.org/10.3384/ecp11057351
Gao, L.; Hailu, A. 2013. Identifying preferred management options: an integrated agent-based recreational fishing simulation model with an AHP-TOPSIS evaluation method, Ecological Modelling 249: 75–83. https://doi.org/10.1016/j.ecolmodel.2012.07.002
Gao, L.; Hailu, A. 2012. Ranking management strategies with complex outcomes: an AHP-fuzzy evaluation of recreational fishing using an integrated agent-based model of a coral reef ecosystem, Environmental Modelling & Software 31: 3–18. https://doi.org/10.1016/j.envsoft.2011.12.002
Iyer, K. C.; Sagheer, M. 2010. Hierarchical structuring of PPP risks using interpretative structural modeling, Journal of Construction Engineering and Management 136(2): 151–159. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000127
Jen, W.; Tu, R.; Lu, T. 2011. Managing passenger behavioral intention: an integrated framework for service quality, satisfaction, perceived value, and switching barriers, Transportation 38(2): 321–342. https://doi.org/10.1007/s11116-010-9306-9
Jharkharia, S.; Shankar, R. 2007. Selection of logistics service provider: an analytic network process (ANP) approach, Omega 35(3): 274–289. https://doi.org/10.1016/j.omega.2005.06.005
Kannan, G.; Noorul Haq, A.; Sasikumar, P.; Arunachalam, S. 2008. Analysis and selection of green suppliers using interpretative structural modelling and analytic hierarchy process, International Journal of Management and Decision Making 9(2): 163–182. https://doi.org/10.1504/IJMDM.2008.017198
Li, F.; Phoon, K. K.; Du, X.; Zhang, M. 2013. Improved AHP method and its application in risk identification, Journal of Construction Engineering and Management 139(3): 312–320. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000605
Malone, D. W. 1975. An introduction to the application of interpretive structural modeling, Proceedings of the IEEE 63(3): 397–404. https://doi.org/10.1109/PROC.1975.9765
Pfohl, H.-C.; Gallus, P.; Thomas, D. 2011. Interpretive structural modeling of supply chain risks, International Journal of Physical Distribution & Logistics Management 41(9): 839–859. https://doi.org/10.1108/09600031111175816
Renn, O.; Webler, T.; Wiedemann, P. 1995. Fairness and Competence in Citizen Participation: Evaluating Models for Environmental Discourse. Springer Netherlands. 381 p. https://doi.org/10.1007/978-94-011-0131-8
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, T. L. 2013. Analytic network process, in S. I. Gass, M. C. Fu (Eds.). Encyclopedia of Operations Research and Management Science. https://doi.org/10.1007/978-1-4419-1153-7_32
Saaty, T. L. 2001. The Analytic Network Process: Decision Making with Dependence and Feedback. RWS publications. 370 p.
Saaty, T. L.; Ozdemir, M. S. 2003. Why the magic number seven plus or minus two, Mathematical and Computer Modelling 38(3–4): 233–244. https://doi.org/10.1016/S0895-7177(03)90083-5
Saleeshya, P. G.; Thampi, K. S.; Raghuram, P. 2012. A combined AHP and ISM-based model to assess the agility of supply chain – a case study, International Journal of Integrated Supply Management 7(1–3): 167–191. https://doi.org/10.1504/IJISM.2012.051050
Tudela, A.; Akiki, N.; Cisternas, R. 2006. Comparing the output of cost benefit and multi-criteria analysis: An application to urban transport investments, Transportation Research Part A: Policy and Practice 40(5): 414–423. https://doi.org/10.1016/j.tra.2005.08.002
US DoT. 2015. A Guide to Transportation Decisionmaking. 24 p. US Department of Transportation (DoT), Washington, DC, US. Available from Internet: https://www.planning.dot.gov/documents/GuidetoTransportationDecisionmaking.pdf
US Government. 2005. Safe, Accountable, Flexible, Efficient Transportation Equity Act: a Legacy for Users. Public Law 109–59. 10 August 2005. US Government Printing Office. 836 p. Available from Internet: https://www.govinfo.gov/content/pkg/PLAW-109publ59/pdf/PLAW-109publ59.pdf
Vitić-Ćetković, A.; Bauk, S. 2014. E-services and positioning of passenger ports in the context of cruise tourism promotion, Promet – Traffic & Transportation 26(1): 83–93. https://doi.org/10.7307/ptt.v26i1.1282
Yedla, S.; Shrestha, R. M. 2003. Multi-criteria approach for the selection of alternative options for environmentally sustainable transport system in Delhi, Transportation Research Part A: Policy and Practice 37(8): 717–729. https://doi.org/10.1016/S0965-8564(03)00027-2
Zhang, X.; Gao, L.; Barrett, D.; Chen, Y. 2014. Evaluating water management practice for sustainable mining, Water 6(2): 414–433. https://doi.org/10.3390/w6020414