Disaggregate Behavioral Travel Demand's RUM Side A 30-Year Retrospective

By Daniel McFadden. 2000

274 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/78447d705b8576478a0951c72eb58f51909368af

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Affective-Symbolic and Instrumental-Independence Psychological Motives Mediating Effects of Socio-Demographic Variables on Daily Car Use (2011, methodology): “A second approach emanates from disaggregate travel-choice modeling (Ben-Akiva & Lerman, 1985; McFadden, 2001).”
Valuing the outputs of multifunctional agriculture (2002, methodology): “The random utility model (RUM) has become the travel cost model of choice (Bockstael, 1995; McFadden, 2001 ), because its systematic treatment of substitute sites allows it to characterise site quality more completely.”
Extended discrete choice models : integrated framework, flexible error structures, and latent variables (2001, methodology): “…Boccara, 1987), the literature contains only empirical applications to specific problems (for example, the case studies reviewed here) or restricted model formulations (for example, the elegant formulation for a binary probit and MIMC model presented in McFadden, 2000, and Morikawa et al., 1996).”
Subjective well-being related to satisfaction with daily travel (2011, background): “Utility-maximization theory is the dominant account of how travel-related choices of activity, destination and travel mode are made (McFadden 2001).”
Structural choice modelling: Theory and applications to combining choice experiments (2011, methodology): “Random Utility Theory (RUT) underpins the choice models used in a wide array of academic and practical situations to model choice processes (e.g., Luce 1959; McFadden 1974; McFadden 1980; Ben-Akiva and Lerman 1985; McFadden 2001).”
Discrete choice models with multiplicative error terms (2009, unknown): “In, for example, McFadden (2000), it is described how the indirect conditional utility function is separated into a systematic part and a residual term summarizing all unobserved factors.”
Modeling Micro-Level Crime Location Choice: Application of the Discrete Choice Framework to Crime at Places (2010, unknown): “Multipleindicator-multiple cause (MIMC) models integrate the discrete choice framework with structural equations modeling, by including latent variables, typically in the form of ‘stated preference’ data and psychometric data on beliefs and attitudes (McFadden 2001).”
Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software (2017, unknown): “It is natural to start with the classical multinomial logit (MNL) and its link to the random-utility model established by McFadden [22, 23].”
Meso- or micro-scale? Environmental factors influencing pedestrian satisfaction (2014, background): “…destination, and travel mode deals with travelers’ satisfaction derived from observed travelers’ choice, assuming that travelers make rational decisions to maximize their utility, mostly by minimizing travel time and costs (disutility), under given time and budget constraints (McFadden, 2001).”
Improving behavioral realism in hybrid energy-economy models using discrete choice studies of personal transportation decisions (2005, background): “Discrete choice modeling approaches have become increasingly sophisticated over the past 30 years, especially in how they account for uncertainty (McFadden, 2000), and this sophistication presents an opportunity to communicate additional information about model results.”
Foundations of Stated Preference Elicitation: Consumer Behavior and Choice-based Conjoint Analysis (2019, unknown): “There are a number of good introductions to discrete choice analysis (Ben-Akiva and Lerman, 1985; Train, 1986, 1993; McFadden, 1999, 2001, 2014; Brownstone, 2001; Boyce and Williams, 2015), and to stated preference and conjoint analysis methods and market research applications (Louvier, 1988;…”
A General and Operational Representation of Generalised Extreme Value Models (2006, background): “These results have been long known (see, for instance, McFadden, 2000 ).”