Caught in the crossfire: Dimensions of vulnerability and foreign multinationals' exit from war‐afflicted countries
Why this work is in the frame
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Bibliographic record
Abstract
Research summary : When war occurs in a country, some foreign multinational enterprises ( MNE s) stay on, while others flee. We argue that MNE responses to external threats depend on the firm's vulnerability, which we decompose into exposure (proximity to threat), at‐risk resources (potential for loss), and resilience (capacity for coping). We test the independent and interactive effects of these dimensions using a geo‐referenced sample of 1,162 MNE subsidiaries in 20 war‐afflicted countries between 1987 and 2006. We find that highly valuable resources can become liabilities when exposed to harm, and the best way to cope with external threats may be to exit. Our findings extend the resource‐based view and real options theory by demonstrating the bounded value of resources and options in the face of environmental contingencies . Managerial summary : A recent survey of multinational enterprise ( MNE) executives revealed that 30 percent of the respondents believed that their firms were exposed to collateral damage from war, with more than 90 percent expecting risks to rise. Yet, 25 percent of the executives indicated that their firms had no continuity plan. Our study of MNE s in war‐afflicted countries highlights the costs of not having a response strategy in place. We find that, in war zones, otherwise highly valuable locations and resources can become sources of vulnerability that prompt early withdrawal from a host country. Our work further highlights the value of real options thinking—where structural solutions such as building redundancy into a portfolio of options may exist in advance of problems—for navigating hostile environments . Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it