Strategic management during the financial crisis: How firms adjust their strategic investments in response to credit market disruptions
Bibliographic record
Abstract
Abstract Research summary This study investigates how companies adjusted their investments in key strategic resources—that is, their workforce, capital expenditures, R&D, and CSR—in response to the sharp increase in the cost of credit (the “credit crunch”) during the financial crisis of 2007–2009. We compare companies whose long‐term debt matured shortly before versus after the credit crunch to obtain (quasi‐)random variation in the extent to which companies were hit by the higher borrowing costs. We find that companies that were adversely affected followed a “two‐pronged” approach of curtailing their workforce and capital expenditures, while maintaining their investments in R&D and CSR. We further document that firms that followed this two‐pronged approach performed better post‐crisis. Managerial summary We study how companies adjusted their key strategic investments during the financial crisis of 2007–2009. As financial markets collapsed—and the cost of financing skyrocketed—managers had to rethink their strategic investments. We find that, on average, managers pursued a two‐pronged approach of (i) “saving their way out of the crisis” by curtailing the company's workforce and capital expenditures and (ii) “investing their way out of the crisis” by maintaining the company's investments in R&D and CSR. Moreover, we find that firms that followed this two‐pronged approach performed better in the post‐crisis years. Overall, these findings suggest that investments in innovation and stakeholder relationships are instrumental in sustaining competitiveness during and beyond times of crisis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".