Moderated Multiple Regression of Absorptive Capacity Attributes and Deployment Outcomes
Bibliographic record
Abstract
In this study, the author examines organizations’ perceptions of the importance of absorptive capacity attributes in the deployment of radio frequency identification (RFID) in a supply chain and their relationships with operational efficiency and market knowledge creation as moderated by information technology infrastructure integration and supply chain process integration. Data was collected using a survey questionnaire administered online to members of the Council of Supply Chain Management Professionals (CSCMP). Four proposed hypotheses were partially supported in this study. Both variables, IT infrastructure integration and supply chain process integration, moderate the relationships between three predictor variables, business process modularity, standard electronic business interfaces, and breadth of information exchange and the two dependent variables examined in this study, operational efficiency and market knowledge creation to a considerable extent. This study has clear implications for how decision makers affecting their firm’s supply chains should make a business case for robust IT elements that support both IT infrastructure integration and supply chain process integration.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 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".