Changing Commutes? Exploring the uptake of cycling to work through an agent-based model focusing on social interactions and social norms

This project stands to deliver high impact policy and practitioner relevant research on how to achieve a step-change in cycle commuting in the UK, through a novel use of existing data. Climate change necessitates a move towards a sustainable transport system, with around a quarter of transport's carbon dioxide emissions coming from the commute. Cycling could make a significant contribution to reducing these emissions, while simultaneously increasing the population's physical activity, thereby improving physical and mental health and well-being. Other benefits could include reduced congestion, air pollution, and noise pollution.

Government seeks to increase cycling with current initiatives including the Local Sustainable Transport Fund and the previous government's Cycling City and Towns programme. There are big variations in cycle commuting between cities in the UK, with evidence of an increase in cycling in some areas. However, there is limited evidence for the effectiveness of interventions and, where that exists, the population impact is small.

Improving our understanding of how behaviours change is an ESRC strategic priority area. Social science insights can direct attention to how locally specific cultures, social identities, and changing social processes, shape transport behaviours. Instead of focusing on discrete interventions in isolation, social science can help us look at transport systems and their dynamics.

Agent based modelling (ABM) is increasingly used in social science, but is underused in this area. ABMs have been used to show how complex and recognisable social systems can be generated from small scale interactions. In ABM agents, usually individual people, behave according to specified rules but can also learn and change how they respond to events. Agents interact with other agents in geographical space and/or in social networks. They act based on the information available to them about their environment and what other agents are doing.

ABMs are mathematical models but their rules can be constructed using qualitative data. Currently most ABMs used in transport look at route choice, rather than social relations. However, commuting behaviour is strongly driven by habits, social norms, and social interactions. People may be influenced by seeing different kinds of people cycling or not cycling, and learn from talking with neighbours, friends and colleagues. In the workplace, organisations (e.g. Bicycle User Groups) might affect behaviour. We will examine policy measures from the Visions 2030 Walking and Cycling Project to see how these might influence, and by influenced by, social interactions.

We will use qualitative studies to develop rules around how people make commuting choices. We have chosen to develop the model focusing on cycling and commuting in 3 English urban areas (Chester, Bristol and Cambridge). The first two have seen an increase in cycling but still have considerable untapped potential. The third, Cambridge, has the highest level of cycling in the UK. The choice of areas will allow us to consider how behaviours might change as cycling becomes more normal. We will use workshops and a Delphi approach with academics and practitioners to investigate how the rules might be generalised to other areas.

Our populations will be diverse with differences in age, gender, workplace, socio-economic position, and environmental attitudes (using DEFRA's sustainable lifestyles framework). We will use data from quantitative studies to represent these populations and test the model's predictions.

This project will build knowledge about how and why commuting behaviours change. We will develop outputs for practitioners, policy-makers, and academics, including academic articles, a project blog, and a final report. An online model will allow users to explore likely potential changes in cycling levels in relation to policy or other changes, using the three cities as examples.

Our project will generate multiple Research Councils UK-identified economic and societal impacts:
-Improving health and well-being
-Evidence based policy making and influencing public policies
-Enhancing the effectiveness and sustainability of organisations
-Environmental sustainability, protection and impact
-Increasing public engagement with research and related societal issues

We have identified the following impact objectives to achieve these:
1. Build awareness of the project among practitioners and policy-makers whose work involves or is affected by transport modelling
2. Make transport modelling more pluralistic by using an innovative approach starting from social interactions
3. Contribute to a new generation of transport modelling focused on transition and achieving shift to active and sustainable modes
4. Build knowledge among 'behaviour change' practitioners about how socio-cultural factors shape responses to interventions

Immediate beneficiaries fall into two groups:
1. Policy-makers and practitioners who use, or whose activities are affected by, transport modelling
2. Practitioners interested in how our project can contribute to travel planning and behaviour change initiatives, particularly at a workplace level.

Increasing cycling could bring substantial population health benefits, reducing the burden of diseases including cardiovascular disease, diabetes, dementia and depression. Modal shift away from motorised transport can bring multiple environmental benefits (e.g. reducing local air and noise pollution). Increasing understanding of how a step-change in cycling could occur will generate significant benefits for those with responsibility for public health (including now Local Authorities) and environmental sustainability.

Our research can increase the effectiveness of public services and policy at a local and national level. Our first core user group centrally includes transport planners and engineers, and also groups such as public health professionals seeking to promote active travel and policy-makers with responsibility for meeting greenhouse gas reduction targets. DEFRA and DfT have expressed interest in our research (particularly our development of the Sustainable Lifestyles Framework to explore social factors shaping behaviour change).

Many within this user group recognise the limitations of traditional transport modelling approaches for addressing questions of transition and transport modal shift. We seek to build awareness of alternative and emerging approaches to modelling that encourage and enable progress towards such objectives. Our approach brings to the foreground social interactions and cultural change, and how these shape follow-on and longer-term effects of policy. This focus is in line with ongoing shifts within academic modelling, but as of yet has had limited practical impact on policy. Therefore, our second objective is to provide an example of an alternative approach that can be used to inform policy.

Our second key user group includes employers seeking to reduce their carbon footprint, and deciding upon travel plans, and considering how to evaluate these plans. Beyond the individual employer are local organisations promoting sustainable travel such as the Cambridgeshire Travel for Work Partnership (also a data provider). This organisation and others like it will benefit from the development of knowledge about interventions and behaviour change.

For similar reasons the research is relevant to cycling industries, including the growing number of organisations planning delivery of cycling infrastructure or training (e.g. Sustrans, Cycle Training UK) and other 'soft measures' (such as 'travel champions' at work). In developing interventions and their own business plans, these organisations can learn from our examination of how behaviour change is affected by context, shaped by interpersonal interactions, and how it might dissipate or continue over time.