Wu, Yi; (2025) Driving Household Lifestyle Transition and Optimizing Interventions from a Bottom-Up Perspective. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

The issue of global climate change is increasingly deteriorating and addressing this global challenge calls for the joint efforts from all economic sectors and individual actions. Since the global emission mitigation actions failed to provide adequate compensation for pollution and sufficient emission reductions in the world. This, in turn, triggered calls to reduce global emissions through “conspicuous consumption” and “lifestyle changes”. Currently, either the theoretical or the methodological perspective on household lifestyle transition has yet been well researched and existing lifestyle initiatives and transition actions rarely address the challenges and obstacles faced by different target groups or provide actionable solutions. This thesis first lays the theoretical foundation of household lifestyle transition by defining the concept of lifestyle transition as the process through which households select available transition options to achieve synchronised emission reductions by altering their individual energy demand and behaviours. This definition is supported by extensive theoretical and methodological discussions proposed in this research. In addition, household heterogeneity, as a key driver of household lifestyle transition, is defined as unobserved individual variations in energy demand that is equivalent to an individual baseline level of unobserved energy demand and is quantified in this study. To address the methodological gaps, a holistic assessment framework is established in this work to explore ex ante analyses of the motivation of household lifestyle transition and its treatment effect on energy demand and emissions, as well as what interventions can be identified effective in guiding the transition. Fine-grained observational datasets have been organised and reshaped by integrating the external long-term population projection datasets, which covers socioeconomic and energy-related features of Chinese and Japanese households during 2015-2060 and 2017-2040. It starts with the household segmentation using a three-step machine learning approach to cluster households by multiple dimensions. Furthermore, a cutting-edge causal inference approach and a unified avoid-shift-improve framework are proposed to examine the treatment effects of lifestyle transition on household energy demand. Throughout the analysis, household heterogeneity has been quantified across household groups and countries and then constrained household capability in transition has been confirmed. This work concludes with an agent-based model that simulates a small proportion of Japanese households (1,000 samples) with behavioural data to observe how households decide to adopt lifestyle transition within interventions. It is found that households are heterogeneous in their energy demand and behaviours concerning lifestyle transition. households exhibit significant heterogeneity in both their energy demand and behaviours related to lifestyle transitions. Effective decarbonisation strategies must account for this complexity and the associated uncertainties at the household level. Household heterogeneity also influences the capacity to adopt transition options, such as energy efficiency improvements, residential solar installations, and electric vehicles. Taking account various interventions and nudges, which can be regarded complementary to the existing or future climate policies, tailored strategies and specific population targets should be highlighted for policymakers. Notably, social norm nudges have been shown to be effective in facilitating household lifestyle transitions in our simulations. However, special attention should be given to vulnerable groups, such as the elderly and single-person households, as while the transition supports the decarbonisation agenda, it may also impose additional burdens on these populations.

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