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MCDM approaches for evaluating urban and public transportation systems: a short review of recent studies

    Mehdi Keshavarz-Ghorabaee Affiliation
    ; Maghsoud Amiri Affiliation
    ; Edmundas Kazimieras Zavadskas Affiliation
    ; Zenonas Turskis Affiliation
    ; Jurgita Antuchevičienė Affiliation

Abstract

Studies related to transportation planning and development have been in the center of activities of many researchers in the past decades. Road congestions issues, economic problems, health problems and environmental problems are some examples of complex problems that can be caused by urban and public transportation in big cities. Evaluating urban and public transportation systems could help to reach effective solutions to overcome these issues. This article presents a short bibliographic review of some recent studies on Multi-Criteria Decision-Making (MCDM) approaches for evaluating urban and public transportation systems. To this aim, Scopus was chosen as the database for making a search on journal articles. Scopus is trusted by major institutions in the world, and all journals covered in this database are inspected for sufficiently high quality each year. The search was made on the journal articles from 2017 to 2022 (July). The analyses presented in this study show that the Analytic Hierarchy Process (AHP) method is the most used method, which has been applied to different studies in the field of urban and public transportation systems based on MCDM approaches. According to the analysis of the number of articles, Turkey is ranked 1st among different countries, and “Budapest University of Technology and Economics” (Hungary) is 1st in the ranking of institutions. Moreover, most of the articles have been published within the “social sciences” subject area. The recent trend in different studies on urban and public transportation systems shows the importance of using MCDM approaches in this field. Moreover, noticeable employment of fuzzy sets in several studies is a point that can shows the significant role of uncertainty in dealing with this type of problems.

Keyword : public transportation, urban transportation, decision-making, MCDM, MADM, review, fuzzy, AHP, TOPSIS

How to Cite
Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antuchevičienė, J. (2022). MCDM approaches for evaluating urban and public transportation systems: a short review of recent studies. Transport, 37(6), 411–425. https://doi.org/10.3846/transport.2022.18376
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Dec 31, 2022
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References

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

Alkharabsheh, A.; Moslem, S.; Oubahman, L.; Duleba, S. 2021. An integrated approach of multi-criteria decision-making and grey theory for evaluating urban public transportation systems, Sustainability 13(5): 2740. https://doi.org/10.3390/su13052740

Aydin, N.; Seker, S.; Özkan, B. 2022. Planning location of mobility hub for sustainable urban mobility, Sustainable Cities and Society 81: 103843. https://doi.org/10.1016/j.scs.2022.103843

Baç, U. 2020. An integrated SWARA-WASPAS group decision making framework to evaluate smart card systems for public transportation, Mathematics 8(10): 1723. https://doi.org/10.3390/math8101723

Barauskas, A.; Jakovlevas-Mateckis, K.; Palevičius, V.; Antuchevičienė, J. 2018. Ranking conceptual locations for a P&R parking lot using EDAS method, Građevinar 70(11): 975–983. https://doi.org/10.14256/JCE.1961.2016

Bastida-Molina, P.; Ribó-Pérez, D.; Gómez-Navarro, T.; Hurtado-Pérez, E. 2022. What is the problem? The obstacles to the electrification of urban mobility in Mediterranean cities. Case study of Valencia, Spain, Renewable and Sustainable Energy Reviews 166: 112649. https://doi.org/10.1016/j.rser.2022.112649

Bivina, G. R.; Parida, M. 2020. Prioritizing pedestrian needs using a multi-criteria decision approach for a sustainable built environment in the Indian context, Environment, Development and Sustainability 22(5): 4929–4950. https://doi.org/10.1007/s10668-019-00381-w

Bruun, E. C. 2013. Better Public Transit Systems: Analyzing Investments and Performance. Routledge. 400 p. https://doi.org/10.4324/9781315882918

Büyüközkan, G.; Feyzioğlu, O.; Göçer, F. 2018. Selection of sustainable urban transportation alternatives using an integrated intuitionistic fuzzy Choquet integral approach, Transportation Research Part D: Transport and Environment 58: 186–207. https://doi.org/10.1016/j.trd.2017.12.005

Canbulut, G.; Köse, E.; Arik, O. A. 2022. Public transportation vehicle selection by the grey relational analysis method, Public Transport 14(2): 367–384. https://doi.org/10.1007/s12469-021-00271-3

Cavone, G.; Dotoli, M.; Epicoco, N.; Seatzu, C. 2018. Efficient resource planning of intermodal terminals under uncertainty, IFAC-PapersOnLine 51(9): 398–403. https://doi.org/10.1016/j.ifacol.2018.07.065

Chau, K. W.; Ng, F. F. 1998. The effects of improvement in public transportation capacity on residential price gradient in Hong Kong, Journal of Property Valuation and Investment 16(4): 397–410. https://doi.org/10.1108/14635789810228204

Chen, Y.; Zhang, D. 2020. Evaluation of city sustainability using multi-criteria decision-making considering interaction among criteria in Liaoning province China, Sustainable Cities and Society 59: 102211. https://doi.org/10.1016/j.scs.2020.102211

Çelikbilek, Y.; Moslem, S.; Duleba, S. 2022. A combined grey multi criteria decision making model to evaluate public transportation systems, Evolving Systems (online first). https://doi.org/10.1007/s12530-021-09414-0

De Cea, J.; Fernández, E. 1993. Transit assignment for congested public transport systems: an equilibrium model, Transportation Science 27(2): 133–147. https://doi.org/10.1287/trsc.27.2.133

Dehghani, A.; Kheirkhah, A. S.; Ahadi, H. R. 2017. A hierarchical TOPSIS method based on type-2 fuzzy sets to evaluate service quality of public transportation, International Journal of Industrial Engineering: Theory, Applications and Practice 24(5): 505–525. https://doi.org/10.23055/ijietap.2017.24.5.3163

Demir, G.; Damjanović, M.; Matović, B.; Vujadinović, R. 2022. Toward sustainable urban mobility by using fuzzy-FUCOM and fuzzy-CoCoSo methods: the case of the SUMP Podgorica, Sustainability 14(9): 4972. https://doi.org/10.3390/su14094972

Dinulescu, R.; Bugheanu, A.-M. 2020. Improving users’ satisfaction by implementing the analytic hierarchy process in the public transportation system, Environmental Engineering and Management Journal 19(6): 957–968. https://doi.org/10.30638/eemj.2020.090

Duleba, S.; Alkharabsheh, A.; Gündoğdu, F. K. 2022a. Creating a common priority vector in intuitionistic fuzzy AHP: a comparison of entropy-based and distance-based models, Annals of Operations Research 318(1): 163–187. https://doi.org/10.1007/s10479-021-04491-5

Duleba, S.; Çelikbilek, Y.; Moslem, S.; Esztergár-Kiss, D. 2022b. Application of grey analytic hierarchy process to estimate mode choice alternatives: a case study from Budapest, Transportation Research Interdisciplinary Perspectives 13: 100560. https://doi.org/10.1016/j.trip.2022.100560

Dutta, J.; Barma, P. S.; Mukherjee, A.; Kar, S.; De, T.; Pamučar, D.; Šukevičius, Š.; Garbinčius, G. 2022. Multi-objective green mixed vehicle routing problem under rough environment, Transport 37(1): 51–63. https://doi.org/10.3846/transport.2021.14464

Elmansouri, O.; Almhroog, A.; Badi, I. 2020. Urban transportation in Libya: an overview, Transportation Research Interdisciplinary Perspectives 8: 100161. https://doi.org/10.1016/j.trip.2020.100161

Erdogan, M.; Kaya, I. 2019. Prioritizing failures by using hybrid multi criteria decision making methodology with a real case application, Sustainable Cities and Society 45: 117–130. https://doi.org/10.1016/j.scs.2018.10.027

Farkas, A. 2009. Route/site selection of urban transportation facilities: an integrated GIS/MCDM approach, in MEB 2009 – 7th International Conference on Management, Enterprise and Benchmarking, 5–6 June 2009, Budapest, Hungary, 169–184.

Fierek, S.; Zak, J. 2012. Planning of an integrated urban transportation system based on macro-simulation and MCDM/A methods, Procedia – Social and Behavioral Sciences 54: 567–579. https://doi.org/10.1016/j.sbspro.2012.09.774

Friese, S. 2019. Qualitative Data Analysis with ATLAS.ti. SAGE Publications Ltd. 344 p.

Gao, Y.; Wang, J. W. 2021. A resilience assessment framework for urban transportation systems, International Journal of Production Research 59(7): 2177–2192. https://doi.org/10.1080/00207543.2020.1847339

Garcia-Ayllon, S.; Hontoria, E.; Munier, N. 2022. The contribution of MCDM to SUMP: the case of Spanish cities during 2006–2021, International Journal of Environmental Research and Public Health 19(1): 294. https://doi.org/10.3390/ijerph19010294

Gershon, R. R. M. 2005. Public transportation: advantages and challenges, Journal of Urban Health 82(1): 7–9. https://doi.org/10.1093/jurban/jti003

Ghosh, A.; Dey, M.; Mondal, S. P.; Shaikh, A.; Sarkar, A.; Chatterjee, B. 2021. Selection of best e-rickshaw-a green energy game changer: an application of AHP and TOPSIS Method, Journal of Intelligent & Fuzzy Systems 40(6): 11217–11230. https://doi.org/10.3233/JIFS-202406

González-Gil, A.; Palacin, R.; Batty, P. 2013. Sustainable urban rail systems: Strategies and technologies for optimal management of regenerative braking energy, Energy Conversion and Management 75: 374–388. https://doi.org/10.1016/j.enconman.2013.06.039

Görçün, Ö. F. 2021. Evaluation of the selection of proper metro and tram vehicle for urban transportation by using a novel integrated MCDM approach, Science Progress 104(1): 1–18. https://doi.org/10.1177/0036850420950120

Güner, S. 2018. Measuring the quality of public transportation systems and ranking the bus transit routes using multi-criteria decision making techniques, Case Studies on Transport Policy 6(2): 214–224. https://doi.org/10.1016/j.cstp.2018.05.005

Hahn, D.; Munir, A.; Behzadan, V. 2021. Security and privacy issues in intelligent transportation systems: classification and challenges, IEEE Intelligent Transportation Systems Magazine 13(1): 181–196. https://doi.org/10.1109/mits.2019.2898973

Hajduk, S. 2022. Multi-criteria analysis in the decision-making approach for the linear ordering of urban transport based on TOPSIS technique, Energies 15(1): 274. https://doi.org/10.3390/en15010274

Hamurcu, M.; Eren, T. 2019. An application of multicriteria decision-making for the evaluation of alternative monorail routes, Mathematics 7(1): 16. https://doi.org/10.3390/math7010016

Hashemkhani Zolfani, S.; Ecer, F.; Pamučar, D.; Raslanas, S. 2020. Neighborhood selection for a newcomer via a novel BWM-based revised MAIRCA integrated model: a case from the Coquimbo-La Serena conurbation, Chile, International Journal of Strategic Property Management 24(2): 102–118. https://doi.org/10.3846/ijspm.2020.11543

Jasti, P. C.; Ram, V. V. 2019a. Integrated and sustainable benchmarking of metro rail system using analytic hierarchy process and fuzzy logic: a case study of Mumbai, Urban Rail Transit 5(3): 155–171. https://doi.org/10.1007/s40864-019-00107-1

Jasti, P. C.; Ram, V. V. 2019b. Sustainable benchmarking of a public transport system using analytic hierarchy process and fuzzy logic: a case study of Hyderabad, India, Public Transport 11(3): 457–485. https://doi.org/10.1007/s12469-019-00219-8

Kalifa, M.; Özdemir, A.; Özkan, A.; Banar, M. 2022. Application of Multi-Criteria Decision analysis including sustainable indicators for prioritization of public transport system, Integrated Environmental Assessment and Management 18(1): 25–38. https://doi.org/10.1002/ieam.4486

Keshavarz-Ghorabaee, M. 2021. Assessment of distribution center locations using a multi-expert subjective–objective decision-making approach, Scientific Reports 11: 19461. https://doi.org/10.1038/s41598-021-98698-y

Keshavarz-Ghorabaee, M.; Amiri, M.; Hashemi-Tabatabaei, M.; Ghahremanloo, M. 2021. Sustainable public transportation evaluation using a novel hybrid method based on fuzzy BWM and MABAC, The Open Transportation Journal 15: 31–44. https://doi.org/10.2174/1874447802115010031

Keshavarz-Ghorabaee, M.; Amiri, M.; Zavadskas, E. K.; Turskis, Z.; Antuchevičienė, J. 2018. Ranking of bridge design alternatives: a TOPSIS-FADR method, The Baltic Journal of Road and Bridge Engineering 13(3): 209–237. https://doi.org/10.7250/bjrbe.2018-13.413

Keshavarz-Ghorabaee, M.; Govindan, K.; Amiri, M.; Zavadskas, E. K.; Antuchevičienė, J. 2019. An integrated type-2 fuzzy decision model based on WASPAS and SECA for evaluation of sustainable manufacturing strategies, Journal of Environmental Engineering and Landscape Management 27(4): 187–200. https://doi.org/10.3846/jeelm.2019.11367

Kiciński, M.; Solecka, K. 2018. Application of MCDA/MCDM methods for an integrated urban public transportation system – case study, city of Cracow, Archives of Transport 46(2): 71–84. https://doi.org/10.5604/01.3001.0012.2107

Kumar, C.; Ganguly, A. 2018. Travelling together but differently: comparing variations in public transit user mode choice attributes across New Delhi and New York, Theoretical and Empirical Researches in Urban Management 13(3): 54–73. Available from Internet: http://um.ase.ro/no133/4.pdf

Lee, D.-J. 2018. A multi-criteria approach for prioritizing advanced public transport modes (APTM) considering urban types in Korea, Transportation Research Part A: Policy and Practice 111: 148–161. https://doi.org/10.1016/j.tra.2018.02.005

Lee, T.-Y.; Jeong, M.-H.; Jeon, S.-B.; Cho, J.-M. 2020. Location optimization of bicycle-sharing stations using multiple-criteria decision making, Sensors and Materials 32(12): 4463–4470. https://doi.org/10.18494/SAM.2020.3125

Liao, H.; Liu, Z.; Banaitis, A.; Zavadskas, E. K.; Zhou, X. 2022. Battery supplier development for new energy vehicles by a probabilistic linguistic UTASTAR method, Transport 37(2): 121–136. https://doi.org/10.3846/transport.2021.14710

Lin, M.; Huang, C.; Xu, Z. 2020. MULTIMOORA based MCDM model for site selection of car sharing station under picture fuzzy environment, Sustainable Cities and Society 53: 101873. https://doi.org/10.1016/j.scs.2019.101873

Lin, S.-H.; Hsu, C.-C.; Zhong, T.; He, X.; Li, J.-H.; Tzeng, G.-H.; Hsieh, J.-C. 2021. Exploring location determinants of Asia’s unique beverage shops based on a hybrid MADM model, International Journal of Strategic Property Management 25(4): 291–315. https://doi.org/10.3846/ijspm.2021.14796

Lu, M.-T.; Hsu, C.-C.; Liou, J. J. H.; Lo, H.-W. 2018. A hybrid MCDM and sustainability-balanced scorecard model to establish sustainable performance evaluation for international airports, Journal of Air Transport Management 71: 9–19. https://doi.org/10.1016/j.jairtraman.2018.05.008

Luan, X.; Cheng, L.; Song, Y.; Sun, C. 2019. Performance evaluation and alternative optimization model of light rail transit network projects: a real case perspective, Canadian Journal of Civil Engineering 46(9): 836–846. https://doi.org/10.1139/cjce-2018-0505

Ma, F.; Shi, W.; Yuen, K. F.; Sun, Q.; Guo, Y. 2019. Multi-stakeholders’ assessment of bike sharing service quality based on DEMATEL–VIKOR method, International Journal of Logistics Research and Applications: a Leading Journal of Supply Chain Management 22(5): 449–472. https://doi.org/10.1080/13675567.2019.1568401

Maitra, B.; Sadhukhan, S. 2013. Urban public transportation system in the context of climate change mitigation: emerging issues and research needs in India, in A. Khare, T. Beckman (Eds.). Mitigating Climate Change: the Emerging Face of Modern Cities, 75–91. https://doi.org/10.1007/978-3-642-37030-4_5

Marleau Donais, F.; Abi-Zeid, I.; Waygood, E. O. D.; Lavoie, R. 2019. Assessing and ranking the potential of a street to be redesigned as a complete street: a multi-criteria decision aiding approach, Transportation Research Part A: Policy and Practice 124: 1–19. https://doi.org/10.1016/j.tra.2019.02.006

Mei, Y.; Xie, K. 2019. An improved TOPSIS method for metro station evacuation strategy selection in interval type-2 fuzzy environment, Cluster Computing 22(2): 2781–2792. https://doi.org/10.1007/s10586-017-1499-7

Moslem, S.; Çelikbilek, Y. 2020. An integrated grey AHP-MOORA model for ameliorating public transport service quality, European Transport Research Review 12: 68. https://doi.org/10.1186/s12544-020-00455-1

Moslem, S.; Duleba, S.; Esztergár-Kiss, D. 2022. Comparative mode choice analysis of university staff commuting travel preferences, European Journal of Transport and Infrastructure Research 22(2): 83–107. https://doi.org/10.18757/ejtir.2022.22.2.5949

Munjal, R.; Liu, W.; Li, X.; Gutierrez, J.; Chong, P. H. J. 2022. Multi-attribute decision making for energy-efficient public transport network selection in smart cities, Future Internet 14(2): 42. https://doi.org/10.3390/fi14020042

Murray, A. T.; Davis, R.; Stimson, R. J.; Ferreira, L. 1998. Public transportation access, Transportation Research Part D: Transport and Environment 3(5): 319–328. https://doi.org/10.1016/s1361-9209(98)00010-8

Nadafianshahamabadi, R.; Tayarani, M.; Rowangould, G. M. 2017. Differences in expertise and values: Comparing community and expert assessments of a transportation project, Sustainable Cities and Society 28: 67–75. https://doi.org/10.1016/j.scs.2016.08.027

Norouzian-Maleki, P.; Izadbakhsh, H.; Saberi, M.; Hussain, O.; Jahangoshai Rezaee, M.; Ghanbar Tehrani, N. 2022. An integrated approach to system dynamics and data envelopment analysis for determining efficient policies and forecasting travel demand in an urban transport system, Transportation Letters: the International Journal of Transportation Research 14(2): 157–173. https://doi.org/10.1080/19427867.2020.1839716

Ogrodnik, K. 2020. Multi-criteria analysis of smart cities in Poland, Geographia Polonica 93(2): 163–181. https://doi.org/10.7163/GPol.0168

Ortega, J.; Moslem, S.; Palaguachi, J.; Ortega, M.; Campisi, T.; Torrisi, V. 2021. An integrated multi criteria decision making model for evaluating P&R facility location issue: a case study for Cuenca city in Ecuador, Sustainability 13(13): 7461. https://doi.org/10.3390/su13137461

Ortega, J.; Tóth, J.; Moslem, S.; Péter, T.; Duleba, S. 2020. An integrated approach of analytic hierarchy process and triangular fuzzy sets for analyzing the P&R facility location problem, Symmetry 12(8): 1225. https://doi.org/10.3390/SYM12081225

Oubahman, L.; Duleba, S. 2022. A comparative analysis of homogenous groups’ preferences by using AIP and AIJ group AHP-PROMETHEE model, Sustainability 14(10): 5980. https://doi.org/10.3390/su14105980

Öztürk, F. 2021. A hybrid type-2 fuzzy performance evaluation model for public transport services, Arabian Journal for Science and Engineering 46(10): 10261–10279. https://doi.org/10.1007/s13369-021-05687-4

Pamucar, D.; Deveci, M.; Canıtez, F.; Bozanic, D. 2020. A fuzzy full consistency method – Dombi-Bonferroni model for prioritizing transportation demand management measures, Applied Soft Computing 87: 105952. https://doi.org/10.1016/j.asoc.2019.105952

Pamucar, D.; Iordache, M.; Deveci, M.; Schitea, D.; Iordache, I. 2021. A new hybrid fuzzy multi-criteria decision methodology model for prioritizing the alternatives of the hydrogen bus development: a case study from Romania, International Journal of Hydrogen Energy 46(57): 29616–29637. https://doi.org/10.1016/j.ijhydene.2020.10.172

Pamučar, D.; Petrović, I.; Ćirović, G.; Stević, Ž. 2022. An extension of the MABAC and OS model using linguistic neutrosophic numbers: selection of unmanned aircraft for fighting forest fires, Transport 37(2): 73–95. https://doi.org/10.3846/transport.2022.16645

Peng, K.; Shen, Y. 2018. A variable iterated greedy algorithm based on grey relational analysis for crew scheduling, Scientia Iranica: Transactions E: Industrial Engineering 25(2): 831–840. https://doi.org/10.24200/sci.2017.4434

Porru, S.; Misso, F. E.; Pani, F. E.; Repetto, C. 2020. Smart mobility and public transport: opportunities and challenges in rural and urban areas, Journal of Traffic and Transportation Engineering 7(1): 88–97. https://doi.org/10.1016/j.jtte.2019.10.002

Qing, S. X.; Abdullah, L. 2017. A case study of coastal community on application of fuzzy analytic network process for determining weights of quality of life, Journal of Sustainability Science and Management 12(3): 119–129.

Rivero Gutiérrez, L.; De Vicente Oliva, M. A.; Romero-Ania, A. 2021. Managing sustainable urban public transport systems: an AHP multicriteria decision model, Sustainability 13(9): 4614. https://doi.org/10.3390/su13094614

Romero-Ania, A.; Rivero Gutiérrez, L.; De Vicente Oliva, M. A. 2021. Multiple criteria decision analysis of sustainable urban public transport systems, Mathematics 9(16): 1844. https://doi.org/10.3390/math9161844

Santos, J. B. D.; Lima, J. P. 2021. Quality of public transportation based on the multi-criteria approach and from the perspective of user’s satisfaction level: a case study in a Brazilian city, Case Studies on Transport Policy 9(3): 1233–1244. https://doi.org/10.1016/j.cstp.2021.05.015

Saplıoğlu, M.; Aydın, M. M. 2018. Choosing safe and suitable bicycle routes to integrate cycling and public transport systems, Journal of Transport & Health 10: 236–252. https://doi.org/10.1016/j.jth.2018.05.011

Seker, S.; Aydin, N. 2020. Sustainable public transportation system evaluation: a novel two-stage hybrid method based on IVIF-AHP and CODAS, International Journal of Fuzzy Systems 22(1): 257–272. https://doi.org/10.1007/s40815-019-00785-w

Shabani, Am.; Shabani, Al.; Ahmadinejad, B.; Salmasnia, A. 2022. Measuring the customer satisfaction of public transportation in Tehran during the COVID-19 pandemic using MCDM techniques, Case Studies on Transport Policy 10(3): 1520–1530. https://doi.org/10.1016/j.cstp.2022.05.009

Shekhovtsov, A.; Kozlov, V.; Nosov, V.; Sałabun, W. 2020. Efficiency of methods for determining the relevance of criteria in sustainable transport problems: a comparative case study, Sustainability 12(19): 7915. https://doi.org/10.3390/SU12197915

Simic, V.; Gokasar, I.; Deveci, M.; Karakurt, A. 2022. An integrated CRITIC and MABAC based type-2 neutrosophic model for public transportation pricing system selection, Socio-Economic Planning Sciences 80: 101157. https://doi.org/10.1016/j.seps.2021.101157

Smith, P. 2019. Exploring public transport sustainability with neutrosophic logic, Transportation Planning and Technology 42(3): 257–273. https://doi.org/10.1080/03081060.2019.1576383

Stanković, M.; Gladović, P.; Popović, V. 2019. Determining the importance of the criteria of traffic accessibility using fuzzy AHP and rough AHP method, Decision Making: Applications in Management and Engineering 2(1): 86–104.

Stanković, M.; Gladović, P.; Popović, V.; Lukovac, V. 2018. Selection criteria and assessment of the impact of traffic accessibility on the development of suburbs, Sustainability 10(6): 1977. https://doi.org/10.3390/su10061977

Tirachini, A.; Hensher, D. A.; Rose, J. M. 2013. Crowding in public transport systems: effects on users, operation and implications for the estimation of demand, Transportation Research Part A: Policy and Practice 53: 36–52. https://doi.org/10.1016/j.tra.2013.06.005

Tumsekcali, E.; Ayyildiz, E.; Taskin, A. 2021. Interval valued intuitionistic fuzzy AHP-WASPAS based public transportation service quality evaluation by a new extension of SERVQUAL Model: P-SERVQUAL 4.0, Expert Systems with Applications 186: 115757. https://doi.org/10.1016/j.eswa.2021.115757

Türk, S.; Deveci, M.; Özcan, E.; Canıtez, F.; John, R. 2021. Interval type-2 fuzzy sets improved by Simulated Annealing for locating the electric charging stations, Information Sciences 547: 641–666. https://doi.org/10.1016/j.ins.2020.08.076

Vincent, D. S.; Pitchipoo, P.; Rajakarunakaran, S. 2017. Hybrid optimisation model for blind spot reduction in heavy vehicles, International Journal of Computer Aided Engineering and Technology 9(2): 145–153. https://doi.org/10.1504/IJCAET.2017.083388

Vincent, D. S.; Pitchipoo, P.; Rajini, N.; Rajakarunakaran, S. 2018. Reduction of blind spots in heavy transport vehicles through the optimisation of driver seat design, International Journal of Computer Aided Engineering and Technology 10(1–2): 3–14. https://doi.org/10.1504/IJCAET.2018.088823

Vulevic, A. 2016. Accessibility concepts and indicators in transportation strategic planning issues: theoretical framework and literature review, Logistics & Sustainable Transport 7(1): 58–67. https://doi.org/10.1515/jlst-2016-0006

Wang, X.; Gou, X.; Xu, Z. 2022. A continuous interval-valued double hierarchy linguistic GLDS method and its application in performance evaluation of bus companies, Applied Intelligence 52(4): 4511–4526. https://doi.org/10.1007/s10489-021-02581-2

Wei, M.; Sun, B.; Wang, H.; Xu, Z. 2019. A multi-attribute decision-making model for the evaluation of uncertainties in traffic pollution control planning, Environmental Science and Pollution Research 26(18): 17911–17917. https://doi.org/10.1007/s11356-017-0631-9

Wołek, M.; Jagiełło, A.; Wolański, M. 2021. Multi-criteria analysis in the decision-making process on the electrification of public transport in cities in Poland: a case study analysis, Energies 14(19): 6391. https://doi.org/10.3390/en14196391

Yaliniz, P.; Ustun, O.; Bilgic, S.; Vitosoglu, Y. 2022. Evaluation of P&R application with AHP and ANP methods for the city of Eskisehir, Turkey, Journal of Urban Planning and Development 148(1): 04021066. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000781

Yannis, G.; Kopsacheili, A.; Dragomanovits, A.; Petraki, V. 2020. State-of-the-art review on multi-criteria decision-making in the transport sector, Journal of Traffic and Transportation Engineering 7(4): 413–431. https://doi.org/10.1016/j.jtte.2020.05.005

Yatskiv, I.; Kopytov, E.; Casellato, D.; Luppino, G.; McDonald, R. 2013. Benchmarking and assessment of good practices in public transport information systems, Transport and Telecommunication 14(4): 325–336. https://doi.org/10.2478/ttj-2013-0028