Supply chain process collaboration and Internet utilization: an international perspective of business to business relationships
Bibliographic record
Abstract
This paper compiles the findings of an international study which primary objective was to investigate the relationships between Internet utilization in business-to-business relationships, collaborative efforts and their impact over supplier and customer-oriented processes performance. It highlights the Internet as an important enhancer of collaboration in supply chains and addresses the effects of such efforts on companies’ overall performance. As a conclusive-descriptive and quantitative study, data from a survey of 788 companies from the USA, China, Canada, United Kingdom, and Brazil were analyzed with the use of descriptive statistics, reliability evaluation of the research model’s internal scales, path analysis and structural equation modeling to evaluate supply chain processes collaboration, both up- and down-stream. Internet utilization in supplier and customer-oriented processes was found positively related to collaborative practices in business-to-business relationships. Collaborative practices in supplier and customer-oriented processes, in turn, showed potential effects on performance. Also, supplier-oriented processes performance was found positively associated with customer-oriented process performance. Both internet use and collaborative practices are even more important in a high-context country like Brazil. The paper helps clarify the impact of internet use on business-to-business collaborative relationships. In this sense, practitioners can take this impact to redraw the organizational landscape and business processes amongst supply chain participants.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.000 | 0.003 |
| 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".