Complexity and the companies' informatization: Case EDI Tunisian companies
Bibliographic record
Abstract
Complexity is a recent phenomenon, characterized by incompleteness and unpredictability. With the globalization of business and technological changes, companies are not immune to the complexity. To control the inevitable growth of complexity, they are increasingly adopting more Information and Communication Technology ICT, such as EDI. It is then necessary to consider the impact of the use of EDI on the performance of complex transactions. A study was conducted among 32 Tunisian companies using EDI technology. Linear regression is used to test our model of dependence relation between exogenous variables (using EDI, product complexity, process complexity) and endogenous variable (delivery performance). Thus, we used the MRA (Moderated Regression Analysis ), followed by the subgroup analysis to analyze the moderating effect of product complexity on the relationship between the use of EDI and delivery performance. The results show the positive effect of the use of EDI by personnel on delivery performance and the moderating effect of product complexity on the relationship between the number of partners using EDI and delivery performance.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".