Adoption and Coverage of Performance‐Related Pay during Institutional Change: An Integration of Institutional and Agency Theories
Bibliographic record
Abstract
abstract Whether or not to adopt and how extensively to use a newly legitimized practice are discrete decisions made by firms undergoing institutional change. The aim of this paper is to identify the distinct effects of economic, social, and political factors on the adoption of performance‐related pay practices and their coverage (i.e. the proportion of employees covered by the practices) by integrating institutional and agency theories. An empirical analysis is performed with a unique sample of Korean firms that experienced the East Asian financial crisis of 1997. The results show that while performance‐related pay adoption was influenced by economic and social factors, performance‐related pay coverage was related to political factors as well as economic and social factors. This finding suggests that while firms adopt performance‐related pay practices in search of legitimacy, they do not blindly imitate such practices but rather proactively adapt them based on economic efficiency considerations. This study makes valuable contributions to research on institutionalism and remuneration by empirically identifying the conditions under which a pay practice adopted for social legitimacy fits or fails to fit the economic needs of the adopters.
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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 | 0.009 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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 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".