ORGANIZATIONAL ADAPTATION AND RESILIENCE TO EXTREME WEATHER EVENTS
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».