Enterprise Resource Planning Diffusion: Measuring the Impact of Network Exposure and Power
Why this work is in the frame
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Bibliographic record
Abstract
Observations in industrial sectors indicate that companies that evolve in an industry in which a specific ERP system has been adopted by a number of members are more likely to adopt the same software. In this paper, we investigate two main effects influencing this diffusion pattern: the exposure of a firm in the network to its neighbours and the power of a firm within the network. To perform this analysis, we propose two models: a direct model that characterized the influence of immediate related ties, as well as an indirect model that characterized the influence of ties of ties. Network ties are here defined by interlock between board directorates. The statistical analysis of Canadian firm?s data suggests that network ties, especially indirect exposure, influence the diffusion of ERP systems. The influence of direct and indirect exposure and firm power also appear to differ significantly from one ERP system to another.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it