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ObjectivePotential causal relationship between the built environment and subjective wellbeing has been segmentally explored and partially quantified. We leverage household relocation as a natural experiment to investigate the causality between built environment change and subjective wellbeing.
MethodTwo 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 effects of 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 in built environment (n=506) with those moving to the same built environment type (n=267).
ResultsOur results show immediate and enduring positive causal effects of relocation, equivalent to an average improvement of 8% in subjective wellbeing level compared to non-movers. Among moves, moving to a different built environment improves subjective wellbeing by an equivalent of 13% compared with moving to the same built environment type. Without a change in built environment type, the positive causal effects become negligible. We further find the distress of relocation is transitory, and preliminary evidence that relocation decisions are formed over years and influenced by acute stressors. We hypothesise that relocation and change in built environment alleviate existing distresses but play limited roles in delivering multi-dimensional subjective wellbeing benefits.
ConclusionThis paper is one of the first studies that apply and compare two causal models (DiD and SCM) for identifying potential causal effects of built environment on subject wellbeing. It is demonstrated that recent developments in causal inference methods have untapped potential to be applied in urban planning research. The ability to robustly identify complex causal/associative effects are particularly pertinent for policymaking purposes.

PurposeThe purpose of this paper is to explore the determinants of consumer purchase intention (CPI) of cross-border e-commerce (CBEC) in the countries of the Belt and Road Initiative (BRI).Design/methodology/approachThis study proposes a research model of the antecedents of CPI on CBEC in BRI countries. Study participants were consumers with CBEC shopping experience in BRI-associated countries (n = 278). Structural equation modeling was used to test the research model.FindingsTrust has the greatest effect on CPI, while perceived security has the least effect. In addition, in BRI-associated countries, in contrast to the previous study, product presentation was found to have a significant positive influence on CPI in CBEC. Platform simplicity and logistic service have a significant positive influence on CPI. Practical implicationsThese findings offer important implications for CBEC. Consumers' trust in product providers has the greatest impact on CPI. Simplicity, timely shipment tracking and the fast delivery speed of the platform will increase CPI. The results suggest a highly successful tactic for enhancing consumers' perceptions of product authenticity and interest. Finally, this study provides insights into BRI. Originality/valueThis study contributes to the literature on CBEC. It explores the multilevel (i.e. product presentation, platform simplicity, logistic service, perceived security, and trust) determinants of CPI on CBEC. The study provides insights into the determinants of CPI in BRI countries.