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Cited by 277

The DOI matches its Crossref record; 144 of the 144 references it cites were found in a registry or an index.

A review of socio-technical energy transition (STET) models

Open access
Li, Francis G.N., Trutnevyte, Evelina, Strachan, Neil·2015·Technological Forecasting and Social Change
DOI 10.1016/j.techfore.2015.07.017
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Abstract

Many existing technical feasibility and modelling studies in the energy field are criticised for their limited treatment of societal actors and socio-political dynamics, poor representation of the co-evolving nature of society and technology, and hence an inability to analyse socio-technical change. At the same time, prominent conceptual frameworks of socio-technical transitions that address these elements are often found to be difficult to operationalize in quantitative energy analyses that meet policy development requirements. However a new energy modelling paradigm has started to emerge for integrating both quantitative modelling and conceptual socio-technical transitions. This paper provides a taxonomy for this new model category: ‘socio-technical energy transition’ (STET) models. A review of existing STET models and their applications to the energy supply, buildings and transport sectors is provided. Following this review, the paper reflects on the extent to which these existing quantitative models captured the variety of factors covered in socio-technical transitions theory, highlights the challenges associated with their theoretical and behavioural validation, and proposes future development priorities for STET models.

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Metadata

Authors
Li, F. G. N., Trutnevyte, E., & Strachan, N.
Venue
Technological Forecasting and Social Change
Publisher
Elsevier BV
Published
2015-11
Volume
100
Pages
290-305
ISSN
0040-1625 (ISSN-L)
DOI
10.1016/j.techfore.2015.07.017
OpenAlex
W1099966519
Cited by
277
References
144
FWCI
10.21
Type
journal article
Language
en
Open access
green

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.