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.
best-worst scaling, multinomial logit, parking choice, parking managementescala maxdiff, logit multinomial, elección de parqueaderos, gestión de parqueadero
 C.J. Balsas, “Sustainable transportation planning on college campuses,” Transport Policy, vol. 10(1), p. 35–49, 2003.
 D. Shoup, Parking on smart campus: California Policy Options. Los Angeles: UCLA School of Public Affairs, 2005.
 A. Aoun et al., “Reducing parking demand and traffic congestion at the American University of Beirut,” Transport Policy, vol. 25, pp. 52–60, 2013.
 T. Litman, “Evaluating parking management benefits,” Transportation Research Board 2007 Annual Meeting, vol. 86, p. 14, 2007.
 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.
 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.
 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.
 V. Cantillo, Estudio de movilidad de la Universidad del Norte. Barranquilla: Universidad del Norte, 2012.
 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.
 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.
 S. Sultana, “Factors associated with students’ parking-pass purchase decisions: Evidence from an American University,” Transport Policy, vol. 44, pp. 65–75, 2015.
 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.
 J. Louvriere J., The best-worst or maximum difference measurment model: applications to behavioral research in marketing. Phoenix, Arizona, 1993.
 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.
 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.
 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.
 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.
 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.
 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.
 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.
 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.
 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.
 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.
 A. Tversky and D. Kahneman, “Advances in prospect theory: cumulative representation of uncertainty,” Journal of Risk and Uncertainty, vol. 5, pp. 297-323, 1992.
 I. Kittelson & Associates and P. Brinckerhoff, Transit Capacity and Quality of Service Manual, 3rd ed., Washington D.C., 2013.
 CEPAL, ¿Solidaridad ofocalización?: la estratificación socioeconómica para el cobro de los servicios públicos domiciliarios en Colombia, Santiago, 2006.
 T.N. Flynn, and A.A.J. Marley, Best Worst Scaling: Theory and Methods. Australia, 2007.
 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.
 M. Bierlaire, “BIOGEME: A free package for the estimation of discrete choice models,” Proc. 3rd Swiss Transportation Research Conference, Ascona, Switzerland, 2003.
 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.
 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.
 M. Ben-Akiva and S. Lerman, Discrete choice analysis: theory and application to travel demand. Boston: MIT Press, 1985.
 J. de D. Ortuzar and L. Willumsen, Modelling Transport. New York: Wiley, 2011.
 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.
 E. Barata, L. Cruz, and J. Ferreira, “Parking at the UC campus: Problems and solutions,” Cities, vol. 28, no. 5, pp. 406–413, 2011.
 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.
 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