The Interplay of Formal Institutional and Cultural Distances and the Financial Performance of Foreign Subsidiaries in Latin America
Bibliographic record
Abstract
We investigate how formal institutional distance (FID) moderates the cultural distance (CD) and financial performance relationships of foreign subsidiaries of firms. Following recent research, we estimate the asymmetric effects of CD by considering its size and direction towards host countries on the opposite poles of each cultural dimension’s scale. We propose that a limited understanding of the formal institutions in the host country, as measured by the magnitude and direction of the FID, can positively moderate the CD–performance relationship. This is mainly because foreign subsidiary firms may be more reliant on their capacity to navigate the less formal (and more implicit) aspects of the host country’s institutional environment, such as their ability to cope with the CD. We use foreign subsidiary data from the Orbis database, which includes 22 developed and 22 developing home countries and over 1400 foreign subsidiaries operating in 10 of Latin America’s largest economies (host countries) from 2012 to 2015 (a period of 3 years). Findings confirm the asymmetric effects of CD; however, by considering the direction of FID, our findings reveal that the more FID is directed towards host countries that are less developed, the more significant the effects of CD on financial performance. These findings contribute to our knowledge of how formal and informal institutional distances interact by showing that the greater the FID towards less developed host countries, the more pronounced the effects of CD.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".