The Effect of Enterprise Systems Implementation on the Firm Information Environment
Bibliographic record
Abstract
This study uses an archival research design to assess the impact of enterprise systems on a firm's internal information environment as reflected in the production of management earnings forecasts. Specifically, the authors hypothesize that, if enterprise systems improve management's access to decision‐relevant internal information, higher quality management earnings forecasts should ensue. Consistent with disclosure theory and the purported technical characteristics of enterprise systems, the authors find a positive association between enterprise system implementations and subsequent increases in the likelihood of management forecast issuance and the accuracy of the forecasts. Additional robustness tests support the argument that improvements in management forecasts are due to improvements in the firm's internal information environment rather than to enhancements in management's ability to manage earnings. Beyond accumulating financial reporting information, the authors note that such systems provide management with information to make day‐to‐day operational decisions. Moreover, the paper provides a basis for considering management forecast qualities as a measurable proxy for improvements in the firm's internal information environment that result from information technology investments.
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How this classification was reachedexpand
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 | 0.011 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".