ORGANIZATIONAL ADAPTATION AND RESILIENCE TO EXTREME WEATHER EVENTS
Bibliographic record
Abstract
Impacts from climate change already pose major challenges for organizations and industrial systems, and vulnerabilities are expected to increase in the future, particularly in vulnerable sectors and locations. Findings by the Intergovernmental Panel on Climate Change (IPCC) suggest that climate change related vulnerabilities of organizations and industries, but also of settlement and society as a whole, are mainly related to changes in the intensity and/or frequency of extreme weather, rather than to gradual climate change impacts. Organization researchers and managers, however, have not yet systematically considered the organizational implications of changes in trends of weather extremes, such as changes to the intensity and/or frequency of storms, floods, and droughts. While companies in the reinsurance industry (e.g., Munich Re, Swiss Re) have begun to undertake research into changes in trends of extremes, most current debates on climate change and corporate response are mainly focused on adaptation – that is, longer-term adjustments that organizations can take in response to policy and legislative changes and the observed gradual warming trend. The question of how organizations can cope with more frequent and/or intense weather extremes has largely remained outside of these debates. The thesis advances the notion that the resilience concept which originated in disciplines such as ecology and engineering may provide insights into dealing with new types of environmental change arising from changes in patterns of weather extremes. It emphasizes that organizational adaptation and resilience potentials are context-specific and related to the characteristics of particular climate change impacts. While organizations may be able to undergo steady adaptations to gradual climate change (such as gradual increases in mean temperatures), they might not be able to handle disruptions that go beyond this gradual trend and are related to changes in extremes. Included in this thesis are five papers that seek to provide a foundation for understanding, assessing and evaluating organizational responses to more frequent and/or intense weather extremes. The first paper serves as an introduction to the thesis, assesses the literatures on organizational adaptation and resilience, and proposes an initial model that draws together the different streams of literature on climate change, adaptation and resilience. The second paper extends on the themes of the first paper and provides a discussion of the concepts of adaptation and resilience, as well as their applicability to different types of climate change impacts. The third paper serves as a method paper and discusses assessment methods and pathway to study organizational resilience. The key difficulties identified in this paper are the uncertainties about future climate change outcomes across temporal and spatial scales and a lack of insight into what leads to organizational resilience, or which variables should be measured in a given study. The fourth paper is an empirical study about the 2009 Victorian Bushfires. While individual extreme events cannot be directly linked to climate change impacts, this study highlights that part of the problem in drawing out the resilience of organizations to an unprecedented and ‘more-severe-than-expected’ extreme event is that a range of contingent variables across organizational and societal and ecological levels are potentially relevant. The last paper discusses the potential inability of organization to adjust to changes in climate and weather, and implications in terms of a necessity of a geographical shift of organizational and industrial activities. The thesis highlights gaps in our understanding of organizational challenges and suggests avenues for future research.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".