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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 and forecasting the role of different players in decision-making in many areas of interest. One such example is business travel, i.e. travel for purposes connected to work (excluding commuting). Business travel accounts for 15 to 20% of total travel worldwide and like other types of travel, it has been substantially impacted by the pandemic. The stark reduction in congestion, pollution and urban temperatures in 2020, as well as the widespread acquisition of remote work skills, have created an attitude shift, with employees wishing for more flexible working conditions and businesses wondering whether some travel activities could be avoided or otherwise modified to cut costs and emissions and improve employee well-being. The current economic crisis is making this issue even more pressing, with businesses and organisations seeking ways to use their resources more efficiently.

Against this backdrop, the present project has two aims:

- From a methodological standpoint, the student will develop a new modelling framework to understand joint decision-making

- From an applied perspective, they will focus on the case study of business travel as a key under-researched example of joint decision which can have important environmental, economic and well-being consequences.

We are looking for a highly motivated student to conduct this PhD research. For more details, please see:


We are still accepting applications for fully-funded PhD positions:

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.