A systematic review of agent-based modelling of residential low-carbon energy technology uptake and its integration of place-based approach

Abstract

The residential uptake of low-carbon energy technologies (LCETs) is crucial for energy transition. Emerging literature employs agent-based modelling (ABM) as an effective computational approach to study this topic. ABM is particularly valuable because it can address the multi-level dynamics, complexity and emergent phenomena in socio-technical energy transitions, simulate innovation diffusion and inform decision-making in policy and planning. However, no systematic review has yet been conducted on the growing ABM literature on residential LCET uptake. Residential LCET uptake, as a key part of the notably place-based energy transition, can benefit from a place-based approach (PBA) which explicitly considers local actors and socio-spatial contexts. The integration of PBA in this literature remains underexplored. This paper systematically analyses 22 articles from the Scopus database, focusing specifically on evaluating the application of ABM in researching residential LCET uptake and examining how PBA is embedded or reflected. We analyse key modelling aspects including model purposes, theoretical and empirical background, agent-decision making, interactions, heterogeneity, stochasticity, observation and emergence. Our findings highlight the significant potential of ABM in elucidating underlying mechanisms and emerging trends in residential LCET uptake, supporting decision-making for policymakers and stakeholders and informing policy design and evaluation. We identify a research gap concerning qualitative inputs and a research challenge of empirical validation. A common place-based focus, demonstrated through the incorporation of socio-spatial contexts and engagement with local actors and stakeholders, is also identified among the reviewed models. We further discuss potential pathways of integrating PBA to advance ABM research on residential LCET uptake.

Publication DOI: https://doi.org/10.1002/geo2.70066
Divisions: College of Business and Social Sciences
College of Business and Social Sciences > School of Social Sciences & Humanities
College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
College of Engineering & Physical Sciences > Smart and Sustainable Manufacturing
College of Engineering & Physical Sciences > Aston Advanced Materials
College of Engineering & Physical Sciences
College of Business and Social Sciences > School of Social Sciences & Humanities > Politics, History and International Relations
College of Business and Social Sciences > School of Social Sciences & Humanities > Aston Centre for Europe
Aston University (General)
Funding Information: This research is funded by the Engineering and Physical Sciences Research Council (EPSRC), UK, under Grant No. EP/V041452/1.
Additional Information: Copyright © 2026 The Author(s). Geo: Geography and Environment published by the Royal Geographical Society (with the Institute of British Geographers) and John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Uncontrolled Keywords: agent-based modelling,low-carbon energy technologies,place-based approach,residential energy decarbonisation,socio-technical energy transition
Publication ISSN: 2054-4049
Data Access Statement: The dataset associated with the interactive web-based map and searchable database of reviewed articles is publicly available. The live interactive application can be accessed at https://yuan-feng-aston-university.github.io/Interactive-map-and-searchable-database-for-reviewed-articles/. A preserved and citable version of the application, together with the underlying dataset, has been archived in Zenodo and is available under the persistent DOI: https://doi.org/10.5281/zenodo.18091170<br/>
Last Modified: 10 Mar 2026 08:11
Date Deposited: 09 Mar 2026 16:31
Full Text Link:
Related URLs: https://rgs-ibg ... 1002/geo2.70066 (Publisher URL)
PURE Output Type: Article
Published Date: 2026-03-07
Published Online Date: 2026-03-07
Accepted Date: 2026-01-29
Authors: Feng, Yuan (ORCID Profile 0000-0002-8218-3378)
Jia, Yu (ORCID Profile 0000-0001-9640-1666)
Miao, Ying (ORCID Profile 0000-0001-9405-6387)

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License: Creative Commons Attribution


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