Relational Contracts and Managerial Delegation: Evidence from Foreign Entrepreneurs in Russia
Bibliographic record
Abstract
We examine the managerial delegation decisions of foreign entrepreneurs and assess how these decisions are shaped by characteristics of the local product and labor market environment. We argue that actual or perceived home bias in court proceedings leads foreign entrepreneurs to place little reliance on formal contracts in their dealings with local agent-managers. Adopting the lens of relational contract theory, we develop hypotheses linking managerial delegation decisions to market conditions associated with stable self-enforcing agreements and test the hypotheses in the context of post-Soviet Russia. Consistent with our arguments, we find that foreign entrepreneurs are more likely to hire an agent-manager in local markets where industry growth creates a substantial “shadow of the future,” where managers’ outside employment options are relatively limited, and where competition and the variability of returns are not so high as to induce defection from an informal agreement. Similar observations on a sample of Russian-owned entrepreneurial firms suggest that these delegation decisions are relatively insensitive to local market conditions but that they are influenced by the density of local reputation networks. Our study thus contributes to understanding of the distinctive features of foreign entrepreneurs’ managerial delegation decisions and reinforces the view that contracting impediments constitute one important aspect of the “liability of foreignness” for entrepreneurial firms.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".