Firm-level Strategies for Climate Change Adaptation: Sectoral and Geographic Influences
Bibliographic record
Abstract
We apply the natural resource-based view (RBV) of the firm to a 17-year longitudinal data set of 117 FT500 companies to understand the influence geography and sector have on firms integrating a climate change focus into their business model. We base our analysis on information derived from the Carbon Disclosure Project (CDP). Our RBV-model captures a two-stage transformation process, which includes Walk I and Walk II. This process identifies the firm’s changes in governance, information gathering, and managerial systems as an ‘intermediate’ step, i.e., Walk I. This step often precedes firms actually investing in changing products and production processes to complete the transition towards a more proactive state, i.e., Walk II. We find that firms with a head office in Europe have initiated investments earlier along Walk I than firms with a head office in North America and this extends to Walk II as well. However, by the end of the period included in our data set, there appears to be little difference anymore in the degree to which a climate change focus has been integrated into firm-level strategy along Walk I and Walk II. The sectoral affiliation also influences firm-level strategy and the speed and depth with which a climate change focus materializes over time. For instance, energy-related firms have integrated a climate change focus earlier than firms in business-to-consumer (B2C) sectors and have made deeper changes to their business models in terms of dedicated investments. Firms in B2C sectors have also added a climate change focus, but the changes they have made typically did not require the same depth of dedicated investments. Firms not included in either of the two above groups have somewhat lagged in the start of transition and occupy an intermediate position as to the level of change required for a Walk II transformation. Keywords Resource-Based View, Dynamic capabilities, Carbon Disclosure Project, Dynamic GISTe model, Data driven climate change strategies, FT500 longitudinal data base, Walk I and Walk II model, GISTe model, geographic and sectoral influences
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".