activity
20172022
most citedChoice modelling in the age of machine learning -- discussion paper

140 citations · 280 across the 10 of their papers we have counts for

collaborators

10 papers

physics.soc-ph2022★ 1 cited

A flexible and scalable single-level framework for OD matrix inference using multiple sources of transport information

Wei Sun, Akshay Vij, Nicolas Kaliszewski

This study proposes a flexible and scalable single-level framework for origin-destination matrix (ODM) inference using data from IoT (Internet of Things) and other sources. The fra…

econ.EM2021★ 140 cited

Choice modelling in the age of machine learning -- discussion paper

S. Van Cranenburgh, S. Wang, A. Vij +2

Since its inception, the choice modelling field has been dominated by theory-driven modelling approaches. Machine learning offers an alternative data-driven approach for modelling…

econ.GN2019

Semi-Parametric Hierarchical Bayes Estimates of New Yorkers' Willingness to Pay for Features of Shared Automated Vehicle Services

Rico Krueger, Taha H. Rashidi, Akshay Vij

In this paper, we contrast parametric and semi-parametric representations of unobserved heterogeneity in hierarchical Bayesian multinomial logit models and leverage these methods t…

econ.GN2019

Understanding consumer demand for new transport technologies and services, and implications for the future of mobility

Akshay Vij

The transport sector is witnessing unprecedented levels of disruption. Privately owned cars that operate on internal combustion engines have been the dominant modes of passenger tr…

econ.GN2019

A lifestyle-based model of household neighbourhood location and individual travel mode choice behaviours

Ali Ardeshiri, Akshay Vij

Issues such as urban sprawl, congestion, oil dependence, climate change and public health, are prompting urban and transportation planners to turn to land use and urban design to r…

econ.EM2018

Random taste heterogeneity in discrete choice models: Flexible nonparametric finite mixture distributions

Akshay Vij, Rico Krueger

This study proposes a mixed logit model with multivariate nonparametric finite mixture distributions. The support of the distribution is specified as a high-dimensional grid over t…

stat.AP2018★ 9 cited

A Dirichlet Process Mixture Model of Discrete Choice

Rico Krueger, Akshay Vij, Taha H. Rashidi

We present a mixed multinomial logit (MNL) model, which leverages the truncated stick-breaking process representation of the Dirichlet process as a flexible nonparametric mixing di…

stat.AP2017★ 15 cited

Machine Learning Meets Microeconomics: The Case of Decision Trees and Discrete Choice

Timothy Brathwaite, Akshay Vij, Joan L. Walker

We provide a microeconomic framework for decision trees: a popular machine learning method. Specifically, we show how decision trees represent a non-compensatory decision protocol…

stat.AP2017★ 8 cited

Modeling and Forecasting the Evolution of Preferences over Time: A Hidden Markov Model of Travel Behavior

Feras El Zarwi, Akshay Vij, Joan Walker

Literature suggests that preferences, as denoted by taste parameters and consideration sets, may evolve over time in response to changes in demographic and situational variables, p…

stat.AP2017★ 107 cited

A Discrete Choice Framework for Modeling and Forecasting The Adoption and Diffusion of New Transportation Services

Feras El Zarwi, Akshay Vij, Joan Walker

Current travel demand models are unable to predict long-range trends in travel behavior as they do not entail a mechanism that projects membership and market share of new modes of…