Institute for Transport Studies (ITS)

Staff photo

Samuel Bennett

Research Assistant - Smart Travel Behaviour

Room: 1.04
Email: S.D.Bennett@leeds.ac.uk_
Research Group: Choice Modelling

Sam is a transport researcher with a background in psychology. His primary interests are in the reasons why people travel with a particular focus on developing effective ways to communicate the benefits of reducing car use. His research mainly focuses on:

- Effective argumentation

- Individual differences in motivations for reducing car use

- The psychology of decision-making regarding travel choices

- The links between active travel and mental health

Sam has experience in quantitative research methods and experimental design but is interested in expanding his research focus towards natural experimental studies, qualitative research and big data analytics.

Prior to joining ITS in September 2017, Sam worked as a mental health researcher in the NHS supporting NIHR portfolio studies and evaluating mental health services. He still maintains this interest through work with Leeds & York Partnership NHS Foundation Trust where he works as a research assistant alongside his role at ITS.

Qualifications

MSc Psychological Research Methods - University of Sheffield - 2015

BSc Psychology - Sheffield Hallam University - 2011

 

Sam is currently working as a research assistant on the ADAPT project led by Kate Pangbourne. The project will be drawing from computer science, transport studies, social sciences and psychology to investigate effective ways to encourage people to take voluntary action and mitigate climate change through sustainable transport usage. This will involve:

- An investigation into the current argumentation styles used in travel behaviour change campaigns.

- Understanding what constitutes effective argumentation around sustainable transport usage.

- Exploring the interpersonal factors that mediate the effective of travel behaviour campaigns.

- Developing a model to explain and quantify the effects of these interpersonal factors.

- Utilising these models to predict the most effective forms of argumentation and behavour change strategies for a given person.

- Exploring the feasibility of automating these predictions for use in persuasive transport technology (e.g. smartphone apps)

This page will be updated from our publications database.

Search site