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Modelling departure time choices by a Heteroskedastic Generalized Logit (Het-GenL) model: An investigation on home-based commuting trips in the Greater Toronto and Hamilton Area (GTHA)

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  • Sasic, Ana
  • Habib, Khandker Nurul

Abstract

The paper presents an econometric model for departure time choice modelling. The proposed model is a discrete choice model with latent choice sets. As per the formulation of the mode, the model falls in the general category of Generalized Extreme Value (GEV) models with choice set formation, which is also known as a Generalized Logit (GenL) model. However, the proposed modelling framework uses a scale parameterization approach to capture heteroskedasticity in departure time choices. Hence, the model presented in the paper is a Heteroskedastic Generalized Logit (Het-GenL) model in general or specifically a heteroskedastic Paired Combinatorial Logit Model (Het-PCL). Empirical models are developed for the departure time choices for home-based commuting trips in the Greater Toronto and Hamilton Area (GTHA). The datasets from the Transportation Tomorrow Survey, a 5 percent household based trip diary survey conducted in 2006 is used for empirical model estimation. Separate models are estimated for private car and transit users’ departure time choices. It becomes evident that transportation level-of-service attributes enter into the systematic utility function as well as the scale parameter function with significant coefficients. The proposed econometric approach captures the normalization effect of different variables in terms of simultaneously influencing systematic utility as well as the scale parameter and thereby correctly explains the elasticity of corresponding variables.

Suggested Citation

  • Sasic, Ana & Habib, Khandker Nurul, 2013. "Modelling departure time choices by a Heteroskedastic Generalized Logit (Het-GenL) model: An investigation on home-based commuting trips in the Greater Toronto and Hamilton Area (GTHA)," Transportation Research Part A: Policy and Practice, Elsevier, vol. 50(C), pages 15-32.
    • Handle: RePEc:eee:transa:v:50:y:2013:i:c:p:15-32
    DOI: 10.1016/j.tra.2013.01.028
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    References listed on IDEAS

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    Cited by:

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    2. Peiyu Jing & Ravi Seshadri & Takanori Sakai & Ali Shamshiripour & Andre Romano Alho & Antonios Lentzakis & Moshe E. Ben-Akiva, 2023. "Evaluating congestion pricing schemes using agent-based passenger and freight microsimulation," Papers 2305.07318, arXiv.org.
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    4. Haiyan Zhu & Hongzhi Guan & Yan Han & Wanying Li, 2020. "Can Road Toll Convince Car Travelers to Adjust Their Departure Times? Accounting for the Effect of Choice Behavior under Long and Short Holidays," Sustainability, MDPI, vol. 12(24), pages 1-29, December.

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