Urbanization and economic development in cities have made commuting become an important daily issue for urban residents. Expensive rentals and properties in central cities may lead workers to relocate in longer distance and commute to work with long hours. Long commuting is one of the key themes for social scientists as it imposes cost on time and social relationships for commuters and cumulatively affects quality of life. Furthermore, the emerging trends of de-centralizing business hubs in the city also result in long commuting for workers as their companies move to new areas that are farer away from what they are used to. Extensive studies showed the detrimental effects on physical health, mental health and life satisfaction. Negative health outcomes are varied by demographic and socioeconomic profiles of commuters as they have different resources and support to cope with the stress by long commuting. For example, women can be more sensitive to commuting stress than men can because working women usually have to balance between childcare and work. Commuters with lower education may have worse health outcomes caused by long commuting in comparison with those with higher education due to the differences of the employment sectors.
To investigate the effects of long commuting due to the emergence of a regional business hub on workers' well-being, students will review relevant literature on health and long commuting and develop focuses of the specific health outcomes and profiles of commuters. Then, we will build an agent-based model (ABM) to simulate workers' commuting pattern. Note that the ABM will be coded on Python in consultation with the community partner for a realistic spatial organization of residential and economic activities in Singapore. In the model, each worker is represented as an agent who travels from his/her residential location to the work place by public transport. Physical health, mental health and social well-being of interest will be modelled according to their commuting time. Here, two scenarios will be simulated: (1) firms clustered at the central business district (CBD) and (2) a substantial number of firms are relocated to a regional hub which is far from the CBD. Students are encouraged to propose and study a number of different relocation strategies. Commuters' health will be estimated through social statistics based on the simulated samples.
- List the scientific relevance of research on long commuting and health.
- Describe the potential health implications of long commuting across different demographic and socioeconomic profiles of commuters.
- Identify key mechanisms of long commuting that influences health. Use relevant theories to explain the relationship between health and commuting.
- Analyse geospatial data.
- Understand the basics of agent-based modelling and social statistics.
- Differentiate the estimated effects of long commuting on health across different demographic and socioeconomic profiles of commuters.