Strengthening or Restricting? Explaining the Covid-19 Pandemic’s Configurational Effects on Companies’ Sustainability Strategies and Practices
Bibliographic record
Abstract
We explore the Covid-19 pandemic’s impact on companies’ sustainability strategies and practices. Prior research has identified a number of factors that shape such effects, including crisis severity, resource slack, and prior investments, but their interactions have not been given much attention. We thus collected qualitative data on 25 companies in four African countries, which we analyzed inductively and iteratively through cross-case comparison and with fuzzy set Qualitative Comparative Analysis. We identify two pathways associated with strengthening responses (“building on strengths” and “governance gap-filling”) and three associated with restricting responses (“hard hit,” “low-road business-as-usual,” and “bunkering down”). Our findings enhance our understanding of organizational responses to crises by attending to configurational effects, by elaborating the role of prior sustainability investments, and by foregrounding the relevance of governance contexts. We describe implications for future research and managers, investors, and sustainability initiatives such as the United Nations Global Compact.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".