The Multiplicity of Performance Management Systems: Heterogeneity in Multinational Corporations and Management Sense‐Making
Bibliographic record
Abstract
ABSTRACT This field study examines the workings of multiple performance measurement systems (PMSs) used within and between a division and Headquarters (HQ) of a large European corporation. We explore how multiple PMSs arose within the multinational corporation. We first provide a first‐order analysis which explains how managers make sense of the multiplicity and show how an organization's PMSs may be subject to competing processes for control that result in varied systems, all seemingly functioning, but with different rationales and effects. We then provide a second‐order analysis based on a sense‐making perspective that highlights the importance of retrospective understandings of the organization's history and the importance of various legitimacy expectations to different parts of the multinational. Finally, we emphasize the role of social skill in sense‐making that enables the persistence of multiple systems and the absence of overt tensions and conflict within organizations.
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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 | 0.023 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.023 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| 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 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".