Home

We are looking for PhD students!

Unravelling joint decision processes: the case of business travel Many decisions involve multiple parties. From a couple choosing which car to buy, to business partners agreeing on a strategy, to employer and employee jointly planning annual leave. Most statistical models used to represent decision-making only consider an individual perspective, limiting the potential for truly understanding...

Tuesday 7 November, 2023

We are looking for PhD students!

We are looking for highly motivated students to conduct PhD research in the field of choice modelling. See the following opportunities: Understanding preferences and modelling ‘difficult’ choices through virtual reality experiences. Developing new behavioural models at the intersection of psychology and econometrics. Developing new behavioural models at the intersection of econometrics and machine learning.

Thursday 2 November, 2023

We are hiring!

Academic positions: Do you have research expertise in Choice Modelling, Machine Learning and/or Mathematical Psychology? Are you interested in conducting methodological research to bridge these disciplines? Would you like to implement novel methodologies to advance the state-of-the-art in behavioural modelling and make a real-world impact? The Choice Modelling Centre at the Institute for Transport Studies...

Monday 12 June, 2023

Capurso, M., Hess, S. & Dekker, T. (2019)

Modelling the role of consideration of alternatives in mode choice: An application on the Rome-Milan corridor.
In this paper, we investigate the role consideration of the alternatives plays in mode choice models. On the Rome-Milan corridor, in Italy, where seven alternative modes of transport are available, we administered a stated choice (SC) experiment. Responses to supplementary questions on consideration of the different modes of transport and the presence of thresholds for the travel time attribute indicate travellers are less likely to consider the slower modes. Two model specifications, in which consideration for the slower alternatives is measured using both sets of supplementary questions, are proposed and contrasted against a model which assumes all alternatives are considered. Our results suggests that some of the unobserved preference heterogeneity could potentially be due to consideration effects. Accounting for consideration of alternatives also has direct impacts on choice probabilities, parameter estimates and willingness-to-pay measures.
Capurso, M., Hess, S. & Dekker, T. (2019), Modelling the role of consideration of alternatives in mode choice: An application on the Rome-Milan corridor. Transportation Research Part A, 129, November 2019, Pages 170-184.

Friday 1 November, 2019

Calastri, C., Borghesi, S., & Fagiolo, G. (2019)

How do people choose their commuting mode? An evolutionary approach to travel choices.
A considerable amount of studies in the transport literature is aimed at understanding the behavioural processes underlying travel choices, like mode and destination choices. In the present work, we propose the use of evolutionary game theory as a framework to study commuter mode choice. Evolutionary game models work under the assumptions that agents are boundedly rational and imitate others’ behaviour. We examine the possible dynamics that can emerge in a homogeneous urban population where commuters can choose between two modes, private car or public transport. We obtain a different number of equilibria depending on the values of the parameters of the model. We carry out comparative-static exercises and examine possible policy measures that can be implemented in order to modify the agents’ payoff, and consequently the equilibria of the system, leading society towards more sustainable transportation patterns.
Calastri, C., Borghesi, S., & Fagiolo, G. (2019). How do people choose their commuting mode? An evolutionary approach to travel choices. Economia Politica, 36(3), 887-912.
 

Tuesday 1 October, 2019

Bwambale, A., Choudhury, C. F., & Sanko, N. (2019)

 Car Trip Generation Models in the Developing World: Data Issues and Spatial Transferability.
In many countries of the developing world, it is difficult to conduct large-scale household travel surveys to collect data for travel behaviour model estimation and application. This paper focuses on two candidate solutions to the problem: (1) developing models that can be applied for prediction using secondary data collected for other purposes and include socio-demographic information but do not include transport specific information such as the car and/or transit pass ownership (e.g. census, public health records, etc.), (2) ‘borrowing’ a model developed using data from a similar city within the same region. In the first approach, we investigate the feasibility of developing car trip generation models which imputes the car ownership variable with estimated car ownership propensities. The proposed framework is applied in two East African cities, Nairobi and Dar-es-Salaam. The estimation results indicate that for both cities the proposed approach outperforms the models that exclude the car ownership variable. In the second approach, we investigate the spatial transferability of the models developed in the first approach between the two cities to evaluate if it is justified to apply models from one developing country to another in the absence of local models. Results indicate that though some of the estimated parameters are not significantly different from each other between the two cities, statistical tests do not support direct transferability of all the models from Nairobi to Dar-es-Salaam or vice versa. However, interestingly, the simpler model (which excludes car-ownership) outperforms the model with imputed car ownership propensity in terms of transferability. These findings provide useful insights into the development of trip generation models under data constraints which can practically be very useful for developing countries.
Bwambale, A., Choudhury, C. F., & Sanko, N. (2019). Car Trip Generation Models in the Developing World: Data Issues and Spatial Transferability. Transportation in Developing Economies, 5(2), 10.
 

Tuesday 1 October, 2019