Are users willing to walk more to access a better transit service? Application of best-worst scaling and stated preference survey
DOI:
https://doi.org/10.14295/transportes.v29i3.2647Keywords:
Willingness to walk, Public transport, Stated preference, Best-worst, Integrated choice and latent modelAbstract
The study analyzes users' willingness to walk to obtain a more frequent public transport service. Best-worst, stated preference (SP) and attitudinal data were collected in Porto Alegre, Brazil. Integrated choice and latent variable (ICLV) models allowed combining the classical discrete choice models with the structural equation model to address the attitudinal variables. The contributions are fourfold: quantification of the trade-off between these attributes, the inclusion of attitudinal and urban characteristics, study context, and a new methodological approach through the use of best-worst for PD search attribute selection. The results showed that users are willing to walk 520 m to reduce waiting time by 10 minutes, 375 m to reduce vehicle crowded by 50%, 98m to increase the number of police officers by 1 unit, and 100 m to increase quality sidewalk pavement (bad to good state). Also, users are willing to wait 7,2 minutes to reduce vehicle capacity by 50%.
Downloads
References
Adamsen, JM e Whitty, J.A.(2013) Best-Worst scaling reflections on presentation, analysis, and lessons learnt from case 3.Market & Social Research, v.21, n.1. Available at: http://hdl.handle.net/10072/58108. Accessed on 25/06/2021.
Agrawal, A., Schlossberg, M., e Irvin, K., (2008) How far, by which route and why? A spatial analysis of pedestrian preference. Journal of Urban Design, 13(1), 81-98. doi.org/10.1080/13574800701804074
Alshalalfah, B.; Shalaby, Amer Said. Case Study: Relationship of Walk Access Distance to Transit with Service, Travel, and Personal Characteristics. Journal of Urban Planning and Development, Canada, p. 1-27, jun. 2007. doi.org/10.1061/(ASCE)0733-9488(2007)133:2(114)
ANTP (2020) Sistema de informações da mobilidade urbana da Associação Nacional de Transportes Público (Simob/ANTP): Relatório geral 2017. Associação Nacional de Transportes Públicos, São Paulo.
Arellana, J.; Saltarin,M; Larranaga, A.M. ; Alvarez,V.; Henao, C.A.(2020)Urban walkability considering pedestrians? perceptions of the built environment: a 10-year review and a case study in a medium-sized city in Latin America. TRANSPORT REVIEWS. doi.org/10.1080/01441647.2019.1703842
Baran, P; Rodríguez, D.A. e Khattak AJ (2008) Space Syntax and Walking in a New Urbanist and Suburban Neighborhoods. Journal of Urban Design, 13(1), 5-28. doi.org/10.1080/13574800701803498
Ben-Akiva, M.; Walker, J.; Bernardino, A.T.; Gopinath DA; Morikawa, T. E Polydoropoulou, A. Integration of choice and latent variable models. Massachusetts Institute of Technology. Cambridge, MA, 1999. doi.org/10.1016/B978-008044044-6/50022-X
Burke, M. e Brown, A. (2007) Distances people walk for transport, Road and Transport Research 16 (3), 16-29. Available at: http://hdl.handle.net/10072/17867. Accessed on 25/06/2021.
Cao, X., Handy, S. e Mokhtarian, P. (2¬¬¬¬006) The Influences of the Built Environment and Residential Self-Selection on Pedestrian Behavior, Tx. Transportation 1(1), 20-33. doi.org/10.1007/s11116-005-7027-2
Chaug-Ing, H., Yau-Ching, T. (2014) An energy expenditure approach for estimating walking distance, Environment and Planning B: Planning and Design, 41(1), 289-306. doi.org/10.1068/b37169
Choice Metrics (2013) Ngene 1.1 User Manual and Reference Guide. Choice Metrics.
Currie, G.; Stanley, J. e Stanley, J. (2007). No way to go: Transport and social disadvantage in Australian communities.Melbourne: Monash University ePress.
Currie, G. e Wallis, I. (2008). Effective ways to grow urban bus markets - a synthesis of evidence. Journal of Transport Geography, 16(1), 419-429. doi.org/10.1016/j.jtrangeo.2008.04.007
Daniels, R. e Mulley, C. (2011) Explaining walking distance to public transport: the dominance of public transport supply. World Symposium on Transport and Land Use Research, Whistler Canada. doi.org/10.5198/jtlu.v6i2.308
Daniels, R. e Mulley, C. (2013) Explaining walking distance to public transport: the dominance of public transport supply. Journal of Transport and Land Use 6(2), 5-20.doi.org/10.5198/jtlu.v6i2.308
El-Geneidy, A. M., Tetreault, P., e Surprenant-Legault, J. (2010) Pedestrian access to transit: Identifying redundancies and gaps using a variable service area analysis. Proceedings of the 89th Annual Meeting of Transportation Research Board. Available at: https://www.researchgate.net/publication/228389395. Accessed on 25/06/2021.
Ewing, R.; Greenwald, M.J.; Zhang, M.; Walters, J. e Feldman, M. (2009) Measuring the Impact of Urban Form and Transit Access on Mixed Use Site Trip Generation Rates -- Portland Pilot Study. Washington, DC: US Environmental Protection Agency
Ewing, R. e Cervero R. (2001) Travel and the Built Environment: A Synthesis. Transportation Research Record: Journal of the Transportation Research Board, 1780, 87-114. doi.org/10.3141/1780-10
Ewing, R. e Cervero, R. (2010) Travel and the built environment: a meta-analysis. Journal of the American Planning Association, 76(3), 265-294. doi.org/10.1080/01944361003766766
Flynn, T.N. (2010) Using conjoint analysis and choice experiments to estimate quality adjusted life year values: issues to consider. Pharmacoeconomics v.28, p.711-722. doi.org/10.2165/11535660-000000000-00000
Frank, L.D.; Kavage, S.; Greenwald, M.; Chapman, J. e Bradley, M. (2009). I-PLACE3S health & climate enhancements and their application in King County. Seattle, WA: King County HealthScape.
Gutiérrez, J. e García-Palomares, J. C. (2008) Distance-measure impacts on the calculation of transport service areas using GIS. Environment and Planning B: Planning and Design, 35(3), 480-503. doi.org/10.1068/b33043
Hess, S. e Palma, D. 2019; Apollo: a flexible, powerful and customizable freeware package for choice model estimation and application, Journal of Choice Modelling, Volume 32, September 2019, 100170. doi.org/10.1016/j.jocm.2019.100170
Hsiao,S.; Lu, J.; Sterling, J. e Weatherford, M. (1997) Use of geographic information system for analysis of transit pedestrian access. Transportation Research Record, 1604, 50-59. doi.org/10.3141/1604-07
Ker, I. e Ginn, S. (2003) Myths and realities in walkable catchments: the case of walking and transit. Road and Transport Research, 12(2), 69-80.
Kimpel, T.; Dueker, K. e El-Geneidy, A. (2007) Using GIS to measure the effect of overlapping service areas on passenger boardings at bus stops. Urban and Regional Information Systems Association Journal, 19(1), p.5-11. Available at: https://tram.mcgill.ca/Research/Publications/overlapping_service_area.pdf. Accessed on 25/06/2021.
Kitamura, R., Mokhtarian, P. L., e Laidet, L. (1997) A micro-analysis of land use and travel in five neighborhoods in San Francisco Bay Area. Transportation, 24(2), 125-158. doi.org/10.1023/A:1017959825565
Larranaga, A.M.; Rizzi, L.I.; Arellana, J.; Strambi, O.; Cybis, H.B (2014) The Influence of Built Environment and Travel Attitudes on Walking: A Case Study of Porto Alegre, Brazil. International Journal of Sustainable Transportation. doi.org/10.1080/15568318.2014.933986
Larranaga, A.M; Arellana, J.; Rizzi, L. I.; Strambi,O.; Cybis, H. B. B.(2018) Using best-worst scaling to identify barriers to walkability: a study of Porto Alegre, Brazil. Transportation (Dordrecht. Online). doi.org/10.1007/s11116-018-9944-x
Lee, C. e Moudon, A.V. (2006) Correlates of Walking for Transportation or Recreation Purposes, Journal of Physical Activity and Health, 3(1), 77:98. doi.org/10.1123/jpah.3.s1.s77
Louviere, J.; Lings, I.; Islam, T.; Gudergan, S.; Flynn, T.(2013)An introduction to the application of (case 1) best-worst scaling in marketing research Intern Journal of Research in Marketing no.30 p.292-303. DOI: doi.org/10.1016/j.ijresmar.2012.10.002
Lucas, K. (2005) Providing transport for social inclusion within a framework for environmental justice in the UK. Papers of 28th Australasian Transport Research Forum, Sydney. DOI: 10.1016/j.tra.2005.12.005. DOI: doi.org/10.1016/j.tra.2005.12.005
Lucas, K. 2010. Transport and social exclusion: Where are we now? Paper presented to the 12th World Conference on ANTP, 2015). Transport Research, July 11-15, Lisbon, Portugal. DOI:10.1016/j.tranpol.2012.01.013.
Luce,R.e Suppes,P.(1965).Preference, utility, and subjective probability.InR.D.Luce,R.R.Bush,&E. Galanter (Eds.), Handbook of mathematical psychology (Vol. III, pp. 249-410). New York, NY: Wiley.
Lucchesi, S.T.; Larranaga, A. M; Cybis, H. B. B; Abreu e Silva, J.A de; Arellana, J.. Are people willing to pay more to live in a walking environment? A multigroup analysis of the impact of walkability on real estate values and their moderation effects in two Global South cities. Research in Transportation Economics, v. 86, p. 100976, 2021. DOI: doi.org/10.1016/j.retrec.2020.100976
Lucchesi, S.T.; Larranaga, A. M; Arellana, J; Samios, A.A.B. ; Cybis, H. B. B. The role of security and walkability in subjective wellbeing: A multigroup analysis among different age cohorts. RESEARCH IN TRANSPORTATION BUSINESS & MANAGEMENT, 2020. doi.org/10.1016/j.rtbm.2020.100559
McFadden D. Conditional logit analysis of qualitative choice behavior In: Zarembka P, ed. Frontiers in Econometrics. New York: Academic Press; 1973.
Mulley, C., Ho, C., Ho, L., Hensher, D., e Rose, J. (2018). Will bus travellers walk further for a more frequent service? An international study using a stated preference approach. Transport Policy,Vol. 69, p. 88-97. DOI: doi.org/10.1016/j.tranpol.2018.06.002
Murray, A., e Wu, X. (2003) Accessibility trade-offs in public transit planning. Journal of Geographical Systems, 5(1), 93-107. doi.org/10.1007/s101090300105
Neilson, G. e Fowler, W. (1972) Relation between transit ridership and walking distances in a low density Florida retirement area. Highway Research Record, 403(1), 26-34. Available at: http://onlinepubs.trb.org/Onlinepubs/hrr/1972/403/403-004.pdf. Accessed on 25/06/2021.
Nelson, J. D.; Mulley, C.; Tegnér, G.; Lind, G., e Lange, T. (2005) Public transport - Planning the networks. HiTrans. Available at: http:/hitrans.org. Accessed on 17/10/2015.
O'O'NeillW.; Ramsey, D. e Chou, J. (1992) Analysis of transit service areas using geographic information systems. Transportation Research Record, 1364, 131-139. Available at: http://onlinepubs.trb.org/Onlinepubs/trr/1992/1364/1364-015.pdf. Accessed on 25/06/2021.
Ortúzar, J. D.e Willumsen, L. G. (2011) Modelling Transport. 4th ed. Chichester: Wiley.
O'O'SullivanS. e Morrall, J. (1996) Walking distances to and from light-rail transit stations. Transportation Research Record, 1539, 19-26. doi.org/10.1177/0361198196153800103
Páez, A. Anjum, Z. Dickson-Anderson,S.Schuster-Wallace, C.; Belén, M.Higgins,C.(2020). Comparing distance, time , and metabolic energy cost functions for walking accessibility in infrastructure-poor regions. Journal of Transport Geography, v. 82, n. p. 102564. doi.org/10.1016/j.jtrangeo.2019.102564
Prefeitura de Porto Alegre (2019). Tabelas horárias. Available at: https://www2.portoalegre.rs.gov.br/eptc/default.php?p_secao=158. Accessed on March 7, 2019.
Rajamani, J., Bhat, C.R., Handy, S., Knaap, G. e Song, Y. (2003) Assessing the impact of urban form measures in nonwork trip mode choice after controlling for demographic and level-of-service effects. Transportation Research Record, 1831, 158-165. doi.org/10.3141/1831-18
Rose, J.; Mulley, C.; Tsai, C. e Hensher, D. (2013) Will bus travellers walk further for a more frequent service? A Stated preference investigation. Proceedings of the 36th Australasian Transport Research Forum ATRF 2013 - Transport and the New World City, vol.N/A, 1-15. Available at: https://www.australasiantransportresearchforum.org.au/sites/default/files/2013_rose_mulley_tsai_hensher.pdf. Accessed on 25/06/2021.
Rose, J.M.e Bliemer,M.C.(2009)Constructing Efficient Stated Choice Experimental Designs. Transport Reviews, v.5, n.29, p.587-617. doi.org/10.1080/01441640902827623
Ruiz-Padillo, A.;Pasqual, F.M.; Larranaga,A. M.;Cybis H.B. 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. doi.org/10.1016/j.trd.2018.07.016
Zhao, F.; Chow, L.; Li, M.; Ubaka, I. e Gan, A. (2003) Forecasting transit walk accessibility: Regression model alternative to buffer. Transportation Research Record, 1835, 34-41.doi.org/10.3141/1835-05
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 Ana Margarita Larranaga, Julián Arellana, Luis Garzón, Bárbara Jansson Almeida, Shanna Trichês Lucchesi
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who submit papers for publication by TRANSPORTES agree to the following terms:
- Authors retain copyright and grant TRANSPORTES the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors may enter into separate, additional contractual arrangements for the non-exclusive distribution of this journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in TRANSPORTES.
- Authors are allowed and encouraged to post their work online (e.g., in institutional repositories or on their website) after publication of the article. Authors are encouraged to use links to TRANSPORTES (e.g., DOIs or direct links) when posting the article online, as TRANSPORTES is freely available to all readers.
- Authors have secured all necessary clearances and written permissions to published the work and grant copyright under the terms of this agreement. Furthermore, the authors assume full responsibility for any copyright infringements related to the article, exonerating ANPET and TRANSPORTES of any responsibility regarding copyright infringement.
- Authors assume full responsibility for the contents of the article submitted for review, including all necessary clearances for divulgation of data and results, exonerating ANPET and TRANSPORTES of any responsibility regarding to this aspect.
