Mastery of operational competencies in the context of supply chain management
Bibliographic record
Abstract
Purpose According to the most recent theories, the competitiveness of organizations is based on the development of competencies. Core competencies result from greater mastery than competitors of organizational abilities valued by customers. This paper seeks to investigate how a more thorough integration of the supply chain may be associated with greater mastery of operational competencies. Design/methodology/approach The study is based on a mail survey carried out among Canadian manufacturing companies. Findings The statistical analyses identified four clusters of respondents with regard to their supply chain management practices. These practices may be either distant or integrated with upstream or downstream partners. The other component of the study made it possible to identify four operational competencies – i.e. cost, delivery, logistic services, and design. It was observed that the group with the most highly integrated supply practices mastered an operational competency in logistic services. Research limitations/implications The limited size of the sample and its regional character may limit the generalization of results. The study will therefore be reproduced in other regions of the world. Originality/value Very little research has been done on the impact of supply chain management on operational competencies. Using the results of an empirical study, the paper provides a better understanding of the relationship between supply chain management practices and the development of operational competencies. It also offers a somewhat different view of the concept of supply chain 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".