What do we know about climate change and multinational enterprises?: A systematic review and an integrated theoretical framework for future research
Bibliographic record
Abstract
Multinational enterprises’ (MNEs) strategy and actions to deal with climate change have increasingly attracted research and practical attention since the 2000s, although the literature is rather fragmented. Based on a systematic review of 182 articles published between January 1976 and January 2024, we provide a comprehensive review to identify the theories used in research on climate change and the role of MNEs. It is recognized that much of the literature on business and climate change remains concentrated in specialized journals, many of which are relatively modestly ranked according to various journal guides. We offer an integrated framework for future research on climate change and MNEs, underpinned by a contextual approach and legitimacy theory, and indicate several research themes for future investigations. We call for more research on the topic from the international business and management field. Our review study contributes to the United Nations’ Sustainable Development Goal 1—Take urgent action to combat climate change and its impacts—by generating research insights and challenging the status quo that have policy implications and societal relevance.
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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 | 0.020 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".