Impacts from climate change on organizations: a conceptual foundation
Bibliographic record
Abstract
Abstract Physical impacts from climate change already pose major challenges for organizations, and the trend is rising. Organization theorists, however, have barely begun to systematically consider the organizational impacts of more and increasingly intense storms, floods, droughts, fires, sea level rise or changing growing seasons as part of their domain of study. Eight organizationally relevant dimensions of climate impacts are identified: severity, temporal scale, spatial scale, predictability, mode, immediacy, state change potential and accelerating trend potential. Combined, their scale, scope and systemic uncertainty suggest future conditions of systemic hyperturbulence in organizational environments, defined here as ‘massive discontinuous change’ (MDC). To build a conceptual foundation for organizations to respond and adapt to MDC, the paper examines contributions from literatures on the management of sustainability, crisis, risk, resilience and adaptive organizational change. It highlights gaps for addressing both business challenges and opportunities from MDC, and suggests avenues for future research. Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.020 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".