Actor-network theory-based applications in sustainability: A systematic literature review
Bibliographic record
Abstract
Sustainability is a multifaceted endeavor that underscores the interdependence between society and nature. Its complexity arises from a delicate balance among four sustainability dimensions: economic, environmental, social, and durational. Achieving this equilibrium requires socio-technical changes, where actors and networks play pivotal roles. Actor-network theory is essential for addressing these aspects of sustainability, but a comprehensive overview of its contribution to sustainability literature is lacking. This paper provided the first systematic literature review of actor-network theory-based applications in sustainability, shedding light on current and future research directions. A bibliometric analysis of the literature from 1999 to 2024 using VOSviewer software and the Scopus database was conducted. The analysis of 197 relevant articles utilized performance metrics (productivity and citations) and science mapping techniques (co-citation analysis, bibliographic coupling, and co-word analysis). The findings reveal significant growth in publications, particularly in the last decade, as scholars have studied actor-network theory’s heterogeneity and symmetrical principles, along with the theory’s relational perspective in sustainability. The study specified four knowledge foundations of actor-network theory-based applications in sustainability, namely the nature-science perspective, multi-level perspective, cosmopolitan perspective, and meta-theoretical perspective, as well as four thematic clusters: urbanization, practices/tools, transitions, and industry. Future actor-network theory research in sustainability could emphasize the durational and socio-psychological dimensions, and focus on the field of social science computing. This paper significantly contributes to theory-based applications in sustainability and aids scholars in understanding actor-network theory while exploring critical unanswered questions about sustainability challenges and issues. • A bibliometric analysis using VOSviewer software and the Scopus database provides the first systematic literature review of actor-network theory-based applications in sustainability. • Consistent productivity and social dominance in publications come from three major countries, two major scientific domains, and four journals during five growth periods. • Four knowledge foundations and thematic clusters structure the actor-network theory-based applications in sustainability. • Future research in sustainability may explore the connections between actor-network theory and social sciences computing, as well as the durational dimension and aspects of social psychology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".