Interdisciplinary collaboration in VUCA contexts: a conceptual review for environmental upheavals management
Bibliographic record
Abstract
Abstract Purpose Environmental upheavals increasingly challenge traditional risk management approaches. Characterized by volatility, uncertainty, complexity, and ambiguity (VUCA), this context exposes the limitations of siloed disciplines and predictive models. This conceptual review develops a new theoretical framework for interdisciplinary collaboration in VUCA contexts, redefining it as a dynamic, iterative, and integrative process aimed at fostering shared understanding, co-creation of solutions, and adaptive capacity. Design/Methodology/Approach Grounded in an integrative literature review, the article synthesizes insights from environmental governance, complexity theory, resilience thinking, and systems approaches. A broad search strategy prioritized sources that explicitly engaged with VUCA, critically addressed interdisciplinary collaboration, and/or contributed to conceptual innovation. The analysis aimed to identify core tensions, conceptual gaps, and overlooked dimensions within current models of collaboration. Findings While interdisciplinary collaboration is frequently advocated, its implementation often remains fragmented. Disciplinary silos persist, limiting the capacity to address interconnected disruptions. Moreover, current approaches tend to overemphasize uncertainty and complexity, while neglecting volatility and ambiguity, two dimensions critical to understanding rapid change and interpretive conflict. The review emphasizes the need to move beyond superficial cooperation toward genuine collaboration, characterized by plural knowledge integration, shared sensemaking, and collective adaptability. Originality/Value This article offers a novel contribution by bridging theoretical, strategic, and normative domains within a cohesive conceptual framework. It exposes the disconnect between the rhetoric and practice of collaboration and provides a clarified, operational definition tailored to VUCA environments. The proposed model serves both as a synthesis of existing knowledge and as a heuristic tool to guide future research and inform more adaptive, inclusive, and resilient approaches to environmental upheavals governance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".