ESTIMATION OF VALUE OF TRAVEL-TIME SAVINGS USING MIXED LOGIT MODELS

By Stephane Hess, Michel Bierlaire, John W. Polak. 2005

459 citations recorded by the source corpus.

Subfields: Economics and Econometrics, General Decision Sciences, Transportation

View Paper: https://www.semanticscholar.org/paper/e6b5073ed737c5e3f7a27bc8cadadfa173b77b51

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Citations in the corpus

How Much Is a Reduction of Your Customers' Wait Worth? An Empirical Study of the Fast-Food Drive-Thru Industry Based on Structural Estimation Methods (2011, unknown): “However, the maximum-likelihood estimations typically employed are challenged by the abovementioned endogeneity problems; see Hess et al. (2005) for a recent example , estimating the implicit cost associated with travel time to be in excess of $100/hour.”
Urban freight, parking and pricing policies: An evaluation from a transport providers’ perspective (2015, background): “The typical way of allowing for variations in behavior across respondents is to incorporate taste heterogeneity via the systematic component of utility assuming either continuous or discrete mixture structure (e.g. Greene and Hensher, 2003; Hess et al., 2005).”
MIXED LOGIT MODELLING OF AIRPORT CHOICE IN MULTI-AIRPORT REGIONS (2005, methodology): “However, in the case of coefficients with an a priori sign assumption, the use of the Normal distribution should be avoided, as it leads to a positive probability of wrongly signed coefficients (Hess et al., 2004b).”
On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice (2006, methodology): “For a discussion of the risks involved, and on guidance for which approach should be used, see for example Train and Sonnier (2003), Hensher and Greene (2001), Hess and Polak (2004) and Hess et al. (2004) .”
Assuring finite moments for willingness to pay in random coefficient models (2009, unknown): “The bound can be set by the analyst (which entails a degree of arbitrariness that may be deemed unacceptable, cf. Hess et al. 2005) or it can be treated as an additional parameter to estimate.”
On the Asymmetric User Perception of Transit Service Quality (2011, background): “In the case of coefficients with an a priori sign assumption, the use of the normal distribution should be avoided, as it leads to a positive probability of wrongly signed coefficients (Hess, Bierlaire, and Polak 2004).”
A pooled RP/SP mode, route and destination choice model to investigate mode and user-type effects in the value of travel time savings (2019, background): “Hess et al. (2010) argue that if non-trading is a result of utility maximizing behavior with extreme 20 preferences, such respondents should not be excluded, and in absence of further information on respondents’ 21 consideration set, the best one can do is a dedicated treatment of such preferences.”
Handling respondent uncertainty in Choice Experiments: Evaluating recoding approaches against explicit modelling of uncertainty (2009, background): “This is done to avoid a number of potentially severe problems associated with specifying a random price parameter (see e.g. Meijer and Rouwendal 2006; Hensher et al. 2005; Hess et al. 2005; Train and Sonnier 2005; Hensher and Greene 2003; Train 2003; Train and Weeks 2005).”
Route choice modeling: past, present and future research directions (2009, background): “Different discrete choice applications introduce bounded distributions for coefficients of variables with an expected sign (see, e.g., Train and Sonnier, 2005; Hess et al., 2005), but literature in the route choice context does not report the investigation of these distributions.”
Deriving Willingness-to-Pay Estimates of Travel-Time Savings from Individual-Based Parameters (2006, unknown): “In this paper we, in part, respond to the comment in the last sentence of Hess et al (2004) in which they speculate that individual-based parameters may be preferable to population-based estimates.”
Spatial preference heterogeneity in forest recreation (2013, background): “…to avoid a number of severe problems associated with specifying a random price parameter (Train, 2001; Hensher and Greene, 2003; 2003; Hensher et al., 2005; Hess et al., 2005; Train and Sonnier, 2005; Train and Weeks, 2005; Campbell et al., 2006; Meijer and Rouwendal, 2006; Rigby and Burton, 2006).”