A BWS application to identify factors affecting user preferences for parking choices at university campuses

Parking around university campuses has become a major issue in recent decades because of nearby congestion impacts. Objective: To determine the factors influencing parking lot selection, which is crucial to propose adequate parking demand management strategies. Materials and Methods: We evaluate dif...

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Autores:: Orozco-Fontalvo, Mauricio
Martínez, Sheila
Arellana, Julian
Vega, Laura

Tipo de recurso:: Article of journal

Fecha de publicación:: 2020

Institución:: Corporación Universidad de la Costa

Repositorio:: REDICUC - Repositorio CUC

Idioma:: eng

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dc.title.spa.fl_str_mv	A BWS application to identify factors affecting user preferences for parking choices at university campuses
title	A BWS application to identify factors affecting user preferences for parking choices at university campuses
spellingShingle	A BWS application to identify factors affecting user preferences for parking choices at university campuses escala maxdiff logit multinomial elección de parqueaderos gestión de parqueaderobest-worst scaling multinomial logit parking choice parking management
title_short	A BWS application to identify factors affecting user preferences for parking choices at university campuses
title_full	A BWS application to identify factors affecting user preferences for parking choices at university campuses
title_fullStr	A BWS application to identify factors affecting user preferences for parking choices at university campuses
title_full_unstemmed	A BWS application to identify factors affecting user preferences for parking choices at university campuses
title_sort	A BWS application to identify factors affecting user preferences for parking choices at university campuses
dc.creator.fl_str_mv	Orozco-Fontalvo, Mauricio Martínez, Sheila Arellana, Julian Vega, Laura
dc.contributor.author.spa.fl_str_mv	Orozco-Fontalvo, Mauricio Martínez, Sheila Arellana, Julian Vega, Laura
dc.subject.spa.fl_str_mv	escala maxdiff logit multinomial elección de parqueaderos gestión de parqueaderobest-worst scaling multinomial logit parking choice parking management
topic	escala maxdiff logit multinomial elección de parqueaderos gestión de parqueaderobest-worst scaling multinomial logit parking choice parking management
description	Parking around university campuses has become a major issue in recent decades because of nearby congestion impacts. Objective: To determine the factors influencing parking lot selection, which is crucial to propose adequate parking demand management strategies. Materials and Methods: We evaluate different attributes using a best-worst scaling survey applied at Universidad de la Costa (CUC), Colombia. Using discrete choice modeling techniques, we identified the extent to which selected infrastructure attributes influence parking behavior. Results: Security and cover (roof) availability are the most relevant attributes of parking choice in the case study. Conclusions: Based on our results, we strongly recommend implementing a dynamic pricing rate, roof pricing, removing “reserved spots” and investing in security.
publishDate	2020
dc.date.issued.none.fl_str_mv	2020
dc.date.accessioned.none.fl_str_mv	2021-01-22T23:43:24Z
dc.date.available.none.fl_str_mv	2021-01-22T23:43:24Z
dc.type.spa.fl_str_mv	Artículo de revista
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dc.relation.references.spa.fl_str_mv	[1] W. Riggs, “Dealing with parking issues on an urban campus: The case of UC Berkeley,” Case Studies on Transport Policy, vol. 2, no. 3, pp. 168–176, 2014. [2] C.J. Balsas, “Sustainable transportation planning on college campuses,” Transport Policy, vol. 10(1), p. 35–49, 2003. [3] D. Shoup, Parking on smart campus: California Policy Options. Los Angeles: UCLA School of Public Affairs, 2005. [4] A. Aoun et al., “Reducing parking demand and traffic congestion at the American University of Beirut,” Transport Policy, vol. 25, pp. 52–60, 2013. [5] T. Litman, “Evaluating parking management benefits,” Transportation Research Board 2007 Annual Meeting, vol. 86, p. 14, 2007. [6] C. Miralles-Guasch y E. Domene , “Sustainable transport challenges in a suburban university: The case of the Autonomous University of Barcelona,” Transport Policy, vol. 17, pp. 454-463, 2010. [7] J. Bilbao Ubillos. and A. Fernández Sainz, “The influence of quality and price on the demand for urban transport : the case of university students,” Transportation Research Part A: Policy and Practice, vol. 38, no. 8, pp. 607–614, 2004. [8] C. Gonzáles Calderón,D. Moreno Palacio, and S. Velásquez Gallón, “Análisis de la movilidad en campus universitarios: Caso de estudio Universidad de Antioquia,” Revista Politécnica, vol. 7, no. 12, p. 4, 2011. [9] V. Cantillo, Estudio de movilidad de la Universidad del Norte. Barranquilla: Universidad del Norte, 2012. [10] A. Filipovitch, and E. Frimpong, “A systems model for achieving optimum parking eficiency on campus: The case of Minnesota State University,” Transport Policy, vol. 45, pp. 86–98, 2015. [11] L.D. Olio, “Paying for parking: improving stated-preference surveys,” Proc. of the Inst. of Civil Engineers Transport, vol. 162, no. TR1, pp. 39-45, 2009. [12] S. Sultana, “Factors associated with students’ parking-pass purchase decisions: Evidence from an American University,” Transport Policy, vol. 44, pp. 65–75, 2015. [13] X. Ma et al., “Parking choice behavior investigation: A case study at Beijing Lama Temple,” Procedia - Social and Behavioral Sciences, vol. 96, pp. 2635–2642, 2013. [14] J. Louvriere J., The best-worst or maximum difference measurment model: applications to behavioral research in marketing. Phoenix, Arizona, 1993. [15] L.H. Mielby, M. Edelenbos, and A. K. Thybo, “Comparison of rating, best-worst scaling, and adolescents’ real choices of snacks,” Food Quality and Preference, vol. 25, no. 2, pp. 140–147, 2012. [16] S. R. Jaeger, A.S. Jørgensen, M. D. Aaslyng, and W. L. Bredie, “Best–worst scaling: An introduction and initial comparison with monadic rating for preference elicitation with food products,” Food Quality and Preference, vol. 19, pp. 579-588, 2008. [17] A. Larrañaga, J. Arellana, L. Rizzi, O. Strambi and H. Cybis, “Using Best-Worst Scaling to identify barriers to walkability: a study of Porto Alegre, Brazil,” Transportation, pp. 1-33, 2018. [18] M.R. Franco et al, “Eliciting older people’s preferences for exercise programs: A best-worst scaling choice experiment,” Journal of Physiotherapy, vol. 61, no. 1, pp. 34–41, 2015. [19] C.J. Lagerkvist, “Consumer preferences for food labelling attributes: Comparing direct ranking and best-worst scaling for measurement of attribute importance, preference intensity and attribute dominance,” Food Quality and Preference, vol. 29, no. 2, pp. 77–88, 2013. [20] C. Balbontin, J.D.D. Ortuzar, and J.D. Swait, “Importance of dwelling and neighbourhood attributes in residential location modelling: best worst scaling vs . discrete choice,” Procedia - Social and Behavioral Sciences, vol. 160, pp. 92–101, 2014. [21] J. J. Cabello, M. Orozco, C. Ayala, H. Hernández, and P. Romero, “Evaluación de la calidad de vida urbana en las principales ciudades colombianas,” Revista Brasileira de Gestão e Desenvolvimento Regional, pp. 106-127, 2017. [22] D. Bostyn and A. Roets, “The morality of action: The asymmetry between judgments of praise and blame in the action–omission effect,” Journal of Experimental Social Psychology, vol. 63, pp. 19-25, 2016. [23] G. Feldman, K.F.E. Wong, and R.F. Baumeister, “Bad is freer than good: positive–negative asymmetry in attributions of free will,” Conscious. Cogn., vol. 42, 2016. [24] D.L. Hamilton and M.P. Zanna, “Differential Weighting of Favorable and Unfavorable Attributes in,” Journal of Experimental Research in Personality, vol. 6, no. 2-3, pp. 204-212, 1972. [25] A. Tversky and D. Kahneman, “Advances in prospect theory: cumulative representation of uncertainty,” Journal of Risk and Uncertainty, vol. 5, pp. 297-323, 1992. [26] I. Kittelson & Associates and P. Brinckerhoff, Transit Capacity and Quality of Service Manual, 3rd ed., Washington D.C., 2013. [27] CEPAL, ¿Solidaridad ofocalización?: la estratificación socioeconómica para el cobro de los servicios públicos domiciliarios en Colombia, Santiago, 2006. [28] T.N. Flynn, and A.A.J. Marley, Best Worst Scaling: Theory and Methods. Australia, 2007. [29] A.A.J. Marley, and J.J. Louviere, “Some probabilistic models of best, worst, and best – worst choices,” Journal of Mathematical Psychology, vol. 49, pp. 464–480, 2005. [30] M. Bierlaire, “BIOGEME: A free package for the estimation of discrete choice models,” Proc. 3rd Swiss Transportation Research Conference, Ascona, Switzerland, 2003. [31] N. Castellanos, A. Sánchez, and A. Zarate, Estudio de estacionamiento sobre la vía y en lotes privados en el área de influencia del centro expandido de Barranquilla. Barranquilla: Universidad Nacional de Colombia, 2005 [32] J. J. Soto, L. Márquez, and L. F. Macea, “Accounting for attitudes on parking choice: An integrated choice and latent variable approach,” Transportation Research, Part A, 2018. [33] M. Ben-Akiva and S. Lerman, Discrete choice analysis: theory and application to travel demand. Boston: MIT Press, 1985. [34] J. de D. Ortuzar and L. Willumsen, Modelling Transport. New York: Wiley, 2011. [35] K. Shaaban and A. Pande, “Classification tree analysis of factors affecting parking choices in Qatar,” Case Studies on Transport Policy, vol. 4, no. 2, pp. 88-95, 2016. [36] E. Barata, L. Cruz, and J. Ferreira, “Parking at the UC campus: Problems and solutions,” Cities, vol. 28, no. 5, pp. 406–413, 2011. [37] A. Ibeas, L. dell´Olio, M. Bordagaray, and J. de D. Ortúzar, “Modelling parking choices considering user heterogeneity,” Transportation Research Part A: Policy and Practice, vol. 70, pp. 41-49, 2014. [38] RACC, “Efecto de la radiación solar en la temperatura interior del vehículo,” 2015 [onlines]. Available: http://s01.s3c.es/imag/doc/2015-08-06/estudio-sol-coche-racc.pdf
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spelling	Orozco-Fontalvo, MauricioMartínez, SheilaArellana, JulianVega, Laura2021-01-22T23:43:24Z2021-01-22T23:43:24Z2020https://hdl.handle.net/11323/7756https://doi.org/10.11144/Javeriana.iyu24.aifaCorporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Parking around university campuses has become a major issue in recent decades because of nearby congestion impacts. Objective: To determine the factors influencing parking lot selection, which is crucial to propose adequate parking demand management strategies. Materials and Methods: We evaluate different attributes using a best-worst scaling survey applied at Universidad de la Costa (CUC), Colombia. Using discrete choice modeling techniques, we identified the extent to which selected infrastructure attributes influence parking behavior. Results: Security and cover (roof) availability are the most relevant attributes of parking choice in the case study. Conclusions: Based on our results, we strongly recommend implementing a dynamic pricing rate, roof pricing, removing “reserved spots” and investing in security.Orozco-Fontalvo, Mauricio-will be generated-orcid-0000-0003-0514-4647-600Martínez, SheilaArellana, Julian-will be generated-orcid-0000-0001-7834-5541-600Vega, Lauraapplication/pdfengCorporación Universidad de la CostaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Ingeniería y Universidadhttps://revistas.javeriana.edu.co/index.php/iyu/article/view/23907escala maxdifflogit multinomialelección de parqueaderosgestión de parqueaderobest-worst scalingmultinomial logitparking choiceparking managementA BWS application to identify factors affecting user preferences for parking choices at university campusesArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersion[1] W. Riggs, “Dealing with parking issues on an urban campus: The case of UC Berkeley,” Case Studies on Transport Policy, vol. 2, no. 3, pp. 168–176, 2014.[2] C.J. Balsas, “Sustainable transportation planning on college campuses,” Transport Policy, vol. 10(1), p. 35–49, 2003.[3] D. Shoup, Parking on smart campus: California Policy Options. Los Angeles: UCLA School of Public Affairs, 2005.[4] A. Aoun et al., “Reducing parking demand and traffic congestion at the American University of Beirut,” Transport Policy, vol. 25, pp. 52–60, 2013.[5] T. Litman, “Evaluating parking management benefits,” Transportation Research Board 2007 Annual Meeting, vol. 86, p. 14, 2007.[6] C. Miralles-Guasch y E. Domene , “Sustainable transport challenges in a suburban university: The case of the Autonomous University of Barcelona,” Transport Policy, vol. 17, pp. 454-463, 2010.[7] J. Bilbao Ubillos. and A. Fernández Sainz, “The influence of quality and price on the demand for urban transport : the case of university students,” Transportation Research Part A: Policy and Practice, vol. 38, no. 8, pp. 607–614, 2004.[8] C. Gonzáles Calderón,D. Moreno Palacio, and S. Velásquez Gallón, “Análisis de la movilidad en campus universitarios: Caso de estudio Universidad de Antioquia,” Revista Politécnica, vol. 7, no. 12, p. 4, 2011.[9] V. Cantillo, Estudio de movilidad de la Universidad del Norte. Barranquilla: Universidad del Norte, 2012.[10] A. Filipovitch, and E. Frimpong, “A systems model for achieving optimum parking eficiency on campus: The case of Minnesota State University,” Transport Policy, vol. 45, pp. 86–98, 2015.[11] L.D. Olio, “Paying for parking: improving stated-preference surveys,” Proc. of the Inst. of Civil Engineers Transport, vol. 162, no. TR1, pp. 39-45, 2009.[12] S. Sultana, “Factors associated with students’ parking-pass purchase decisions: Evidence from an American University,” Transport Policy, vol. 44, pp. 65–75, 2015.[13] X. Ma et al., “Parking choice behavior investigation: A case study at Beijing Lama Temple,” Procedia - Social and Behavioral Sciences, vol. 96, pp. 2635–2642, 2013.[14] J. Louvriere J., The best-worst or maximum difference measurment model: applications to behavioral research in marketing. Phoenix, Arizona, 1993.[15] L.H. Mielby, M. Edelenbos, and A. K. Thybo, “Comparison of rating, best-worst scaling, and adolescents’ real choices of snacks,” Food Quality and Preference, vol. 25, no. 2, pp. 140–147, 2012.[16] S. R. Jaeger, A.S. Jørgensen, M. D. Aaslyng, and W. L. Bredie, “Best–worst scaling: An introduction and initial comparison with monadic rating for preference elicitation with food products,” Food Quality and Preference, vol. 19, pp. 579-588, 2008.[17] A. Larrañaga, J. Arellana, L. Rizzi, O. Strambi and H. Cybis, “Using Best-Worst Scaling to identify barriers to walkability: a study of Porto Alegre, Brazil,” Transportation, pp. 1-33, 2018.[18] M.R. Franco et al, “Eliciting older people’s preferences for exercise programs: A best-worst scaling choice experiment,” Journal of Physiotherapy, vol. 61, no. 1, pp. 34–41, 2015.[19] C.J. Lagerkvist, “Consumer preferences for food labelling attributes: Comparing direct ranking and best-worst scaling for measurement of attribute importance, preference intensity and attribute dominance,” Food Quality and Preference, vol. 29, no. 2, pp. 77–88, 2013.[20] C. Balbontin, J.D.D. Ortuzar, and J.D. Swait, “Importance of dwelling and neighbourhood attributes in residential location modelling: best worst scaling vs . discrete choice,” Procedia - Social and Behavioral Sciences, vol. 160, pp. 92–101, 2014.[21] J. J. Cabello, M. Orozco, C. Ayala, H. Hernández, and P. Romero, “Evaluación de la calidad de vida urbana en las principales ciudades colombianas,” Revista Brasileira de Gestão e Desenvolvimento Regional, pp. 106-127, 2017.[22] D. Bostyn and A. Roets, “The morality of action: The asymmetry between judgments of praise and blame in the action–omission effect,” Journal of Experimental Social Psychology, vol. 63, pp. 19-25, 2016.[23] G. Feldman, K.F.E. Wong, and R.F. Baumeister, “Bad is freer than good: positive–negative asymmetry in attributions of free will,” Conscious. Cogn., vol. 42, 2016.[24] D.L. Hamilton and M.P. Zanna, “Differential Weighting of Favorable and Unfavorable Attributes in,” Journal of Experimental Research in Personality, vol. 6, no. 2-3, pp. 204-212, 1972.[25] A. Tversky and D. Kahneman, “Advances in prospect theory: cumulative representation of uncertainty,” Journal of Risk and Uncertainty, vol. 5, pp. 297-323, 1992.[26] I. Kittelson & Associates and P. Brinckerhoff, Transit Capacity and Quality of Service Manual, 3rd ed., Washington D.C., 2013.[27] CEPAL, ¿Solidaridad ofocalización?: la estratificación socioeconómica para el cobro de los servicios públicos domiciliarios en Colombia, Santiago, 2006.[28] T.N. Flynn, and A.A.J. Marley, Best Worst Scaling: Theory and Methods. Australia, 2007.[29] A.A.J. Marley, and J.J. Louviere, “Some probabilistic models of best, worst, and best – worst choices,” Journal of Mathematical Psychology, vol. 49, pp. 464–480, 2005.[30] M. Bierlaire, “BIOGEME: A free package for the estimation of discrete choice models,” Proc. 3rd Swiss Transportation Research Conference, Ascona, Switzerland, 2003.[31] N. Castellanos, A. Sánchez, and A. Zarate, Estudio de estacionamiento sobre la vía y en lotes privados en el área de influencia del centro expandido de Barranquilla. Barranquilla: Universidad Nacional de Colombia, 2005[32] J. J. Soto, L. Márquez, and L. F. Macea, “Accounting for attitudes on parking choice: An integrated choice and latent variable approach,” Transportation Research, Part A, 2018.[33] M. Ben-Akiva and S. Lerman, Discrete choice analysis: theory and application to travel demand. Boston: MIT Press, 1985.[34] J. de D. Ortuzar and L. Willumsen, Modelling Transport. New York: Wiley, 2011.[35] K. Shaaban and A. Pande, “Classification tree analysis of factors affecting parking choices in Qatar,” Case Studies on Transport Policy, vol. 4, no. 2, pp. 88-95, 2016.[36] E. Barata, L. Cruz, and J. Ferreira, “Parking at the UC campus: Problems and solutions,” Cities, vol. 28, no. 5, pp. 406–413, 2011.[37] A. Ibeas, L. dell´Olio, M. Bordagaray, and J. de D. Ortúzar, “Modelling parking choices considering user heterogeneity,” Transportation Research Part A: Policy and Practice, vol. 70, pp. 41-49, 2014.[38] RACC, “Efecto de la radiación solar en la temperatura interior del vehículo,” 2015 [onlines]. 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A BWS application to identify factors affecting user preferences for parking choices at university campuses

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