A systematic assessment of the empirical support for transaction cost economics
Bibliographic record
Abstract
Abstract Transaction cost economics (TCE) is one of the leading perspectives in management and organizational studies, yet debate continues regarding its empirical support. In this paper, we take stock of the large body of extant research and provide a systematic assessment of empirical evidence. In all, 308 statistical tests from 63 articles, selected according to a set of clear criteria, were examined across various dimensions. We assess not only the level of empirical support for the theory, but also the degree of paradigm consensus present in the empirical literature. Our analysis shows that results are mixed: while we found support in some areas (e.g., with regard to asset specificity), we also found considerable disagreement on how to operationalize some of TCE's central constructs and propositions, and relatively low levels of empirical support in other core areas (e.g., surrounding uncertainty and performance). We conclude that a more thorough empirical grounding of the theory's foundation is crucial to its future development, and offer several strategies for doing this. Copyright © 2003 John Wiley & Sons, Ltd.
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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 | 0.114 | 0.488 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.031 | 0.028 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".