The influences of perceptions in bicycle demand for users with the same socioeconomic characteristics
Las influencias de las percepciones en la demanda de bicicletas para los usuarios con las mismas características socioeconómicas
Date
2017
2017
Metadata
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Abstract
Con esta investigación se analizó la demanda potencial para el uso de la bicicleta como alternativa de transporte para estudiantes universitarios y empleados en un área de la ciudad de Barranquilla, donde actualmente no se cuenta con una infraestructura para este modo. Para el análisis, se evaluó un modelo simple de elección discreta incluyendo variables de percepciones. Nuestros resultados indican que la existencia de una adecuada y suficiente infraestructura puede afectar positivamente la decisión de los individuos, y podría mejorar si se brindaran ciclo facilidades en las instalaciones, como aparcamientos y duchas o lugares donde las personas se puedan cambiar y guardar ropa de ser necesario. Además se demostró que los individuos con las mismas características socioeconómicas y con las mismas alternativas disponibles, pueden elegir distintos modos de transporte ya que sus percepciones pueden influir en su elección.
Referencias:
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Bahamonde-Birke, F., & Ortúzar, J. de D. (2012). On the variability of hybrid discrete choice models. Transportmetrica A: Transport Science, 10(1), 74–88. Cervero, R. (2005). Progressive transport and the poor-bogotas bold steps foward. Escholarship, 27, 24–30. Cervero, R., Sarmiento, O. L., Jacoby, E., Gomez, L. F., & Neiman, A. (2009). Influences of Built Environments on Walking and Cycling: Lessons from Bogotá. International Journal of Sustainable Transportation, 3(4), 203–226. Córdoba, J. E., & Jaramillo, G. P. (2012). Inclusion of the Latent Personality Variable in Multinomial Logit Models Using the 16pf Psychometric Test. Procedia - Social and Behavioral Sciences, 54(2011), 169–178. Dell’Olio L. Ibeas A, Bordagaray M & Ortúzar S., J. de D (2014). Modeling the Effects of Pro Bicycle Infrastructure and Policies Toward Sustainable Urban Mobility. 2014 American Society of Civil Engineers. Domencich, T. A., & McFadden, D. L. (1975). Urban travel demand: A behavioral analysis. North-Holland Publishing Co. http://doi.org/10.1016/0041-1647(76)90063-0 Gutiérrez-Torres, Margareth V; Cantillo V. (2014). Classic and bayesian estimation of Subjective Value of Time. DYNA, 81(187), 158–166. Hauster, J. R., & Koppelman, F. S. (1979). Alternative Perceptual Mapping Techniques: Relative Accuracy and Usefulness. Journal of Marketing Research (JMR), 16(4), 495–506. Hensher, D. A. (2006). How do respondents process stated choice experiments? Attribute consideration under varying information load. Journal of Applied Econometrics, 21(6), 861–878. Hensher, D., Louviere, J., & Swait, J. (1998). Combining sources of preference data. Journal of Econometrics, 89(1-2), 197–221. Huber, J., & Zwerina, K. (1996). The importance of utility balance in efficient choice designs. Journal of Marketing Research, 33(3), 307–317. Jiménez Serpa, J. C., Rojas Sánchez, A. E., & Salas Rondón, M. H. (2015). Tariff Integration for Public Transportation in the Metropolitan Area of Bucaramanga. INGE CUC, 11(1), 25–33. McFadden, D., & Train, K. (2000). Mixed MNL models for discrete response. Journal of Applied Econometrics, 15, 447–470. Ortúzar S., J. de D., & Willumsen, L. G. (2011). Modelling transport. Wiley-Blackwell. Ortúzar, J. D. D., & Garrido, R. (1994). A practical assessment of stated preferences methods. Transportation, 21(3), 289–305. Paulssen, M., Temme, D., Vij, A., & Walker, J. (2014). Values, attitudes and travel behavior: a hierarchical latent variable mixed logit model of travel mode choice. Transportation, 41(4), 873–888. Rose, J. M., Bliemer, M. C. J., Hensher, D. A., & Collins, A. T. (2008). Designing efficient stated choice experiments in the presence of reference alternatives. Transportation Research Part B: Methodological, 42(4), 395–406. Teschkea K., Conor C.O., Reynoldsb, F. J. Riesc, Gougec B., Wintersd M. (2012). Bicycling: Health Risk or Benefit?, 6-11. Train, K. (2009). Discret choice methods with simulation. Discrete choice methods with siimulations. Cambridge University Press. Walker, J. L. (2001). Extended Discrete Choice Models: Integrated Framework, Flexible Error Structures, and Latent Variables. Massachusetts Institute of Technology.
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