Overview of emerging literature

Note that publications are alphabetically ordered.

Alwosheel, A., van Cranenburgh, S. & Chorus, C. G. (2019).‘Computer says no’ is not enough: Using prototypical examples to diagnose artificial neural networks for discrete choice analysis. Journal of Choice Modelling, In press.

Alwosheel, A., van Cranenburgh, S. & Chorus, C. G. (2018). Is your dataset big enough? Sample size requirements when using artificial neural networks for discrete choice analysis. Journal of Choice Modelling, 28, 167-182.

Brathwaite, T. (2018). The Holy Trinity: Blending Statistics, Machine Learning and Discrete Choice, with Applications to Strategic Bicycle Planning. UC Berkeley.

Brathwaite, T., Vij, A., & Walker, J. L. (2017). Machine Learning Meets Microeconomics: The Case of Decision Trees and Discrete Choice. Cornell University.

Golshani, N., Shabanpour, R., Mahmoudifard, S. M., Derrible, S., & Mohammadian, A. (2018). Modeling travel mode and timing decisions: Comparison of artificial neural networks and copula-based joint model. Travel Behaviour and Society, 10, 21–32.


Hagenauer, J., & Helbich, M. (2017). A comparative study of machine learning classifiers for modeling travel mode choice. Expert Systems with Applications, 78, 273–282.

Hasnat, M. M., Faghih-Imani, A., Eluru, N., & Hasan, S. (2019). Destination choice modeling using location-based social media data. Journal of Choice Modelling, 31, 22–34.

Karlaftis, M. G., & Vlahogianni, E. I. (2011). Statistical methods versus neural networks in transportation research: Differences, similarities and some insights. Transportation Research Part C: Emerging Technologies, 19(3), 387–399.

Lhéritier, A., Bocamazo, M., Delahaye, T., & Acuna-Agost, R. (2018). Airline itinerary choice modeling using machine learning. Journal of Choice Modelling.

Pereira, F. C. (2019). Rethinking travel behavior modeling representations through embeddings. arXiv preprint arXiv:1909.00154

Van Cranenburgh, S. & Alwosheel, A. (2019). An artificial neural network based approach to investigate travellers’ decision rules. Transportation Research Part C: Emerging Technologies, 98, 152-166.

Van Cranenburgh, S. & Kouwenhoven, M. (2019). Using Artificial Neural Networks for Recovering the Value-of-Travel-Time Distribution. International Work-Conference on Artificial Neural Networks, Springer.

Sifringer, B., Lurkin, V., & Alahi, A. (2018). Enhancing Discrete Choice Models with Neural Networks. Swiss Transport Research Conference.