Spatial Planning
Urban Modelling
Data Analytics
Digital Cities

WORKING PAPERS

Li Wan and Ilaï Bendavid (2023)

The lack of information on trip purpose and alternative mode in micromobility service usage data remains a major analytical challenge. Conventional survey method is subject to significant sampling and stated preference biases. To overcome this challenge, this paper presents a new inference method through a case study of rental e-scooters in London. The inference method features a rule-based algorithm for matching observed rental e-scooter trips with filtered trip samples in the English National Travel Survey (NTS) series. Probability distribution of trip purposes and alternative modes are then retrieved from NTS. Inference results are validated using official data. Discrepancies, sources of biases and correction measures are investigated. Based on the inferred mode substitution pattern, we estimate greenhouse gas emissions reduction of selected rental e-scooter trips in London (36-103g CO2e per mile). It is expected that the proposed method is applicable to a wide range of micromobility studies using service usage data.

Jerry Chen and Li Wan (2023)

Causality between the built environment and subjective wellbeing has thus far been segmentally explored and partially quantified. We identify two unresolved challenges in the literature. Firstly, a reliance on cross-sectional data produces associative findings. Secondly, a reductive approach to regress aggregate subjective wellbeing on limited and disparate built environment measurements risks significant confounding effects. We address the research gaps by leveraging residential relocation as a natural experiment to investigate the causality between built environment change and subjective wellbeing (measured with composite score of negatively phrased General Health Questionnaire-12 items). Two causal inference methods (difference-in-differences and synthetic control) are applied and compared. The use of the ‘Understanding Society’ dataset (The UK Household Longitudinal Study, 2009-2019), combined with holistic locational attributes (Area Classification at the Lower Super Output Area level as per the UK Census) for exploring such causality is novel in literature. Specifically, to estimate the wellbeing effects of residential relocation, we compare movers (treatment n=773) to non-movers (control n=4,619). To estimate the effects of built environment change, we compare movers with a change of built environment type (n=506) to those moving into the same built environment type (n=267). Our research design incorporates novel extensions to the canonical forms of both causal inference methods – staggered difference-in-differences and generalised synthetic control methods – to accommodate individual-level data with multiple relocation timepoints.

Jerry Chen and Li Wan (2022)

Mental health in the UK had deteriorated compared with pre-pandemic trends. The impact of COVID-19 on the subjective wellbeing of working populations with distinct lifestyles is not yet studied. Methods: Combining time use surveys collected pre- and during COVID-19, latent class analysis was used to identify distinct lifestyles based on aggregated daily activity patterns and reported working modes. We provide qualitative pen portraits alongside pre-versus-during pandemic comparisons of intraday time use and wellbeing patterns. Lifestyle heterogeneity in wellbeing was quantified in relation to aggregated activity types. Results: COVID-19 impact on wellbeing varied significantly between usual working hours (6am-6pm) and rest of the day. The decline in wellbeing outside of usual working hours was significant and consistent across lifestyles. During usual working hours, the direction of impact varied in line with working modes: wellbeing of homeworkers decreased, remained relatively stable for commuters, and increased for certain hybrid workers. Magnitude of impact correlates strongly with lifestyle: those working long and dispersed hours are more sensitive, whereas non-work dominated lifestyles are more resilient. Conclusion: The direction and magnitude of impact from COVID-19 were not uniformly manifested across activity types, time of day, and latent lifestyles. Blurring work-life boundaries and general anxiety about the pandemic may be key determinants of the decline outside of usual working hours. During usual working hours, strong yet complex correlations between wellbeing and time-use changes suggested that policies aiming to enhance wellbeing of workers need to consider not only spatial flexibility but also provide wider support for temporal flexibility.