Typology of B-to-B e-commerce initiatives and related benefits in manufacturing SMEs
Bibliographic record
Abstract
Empirical research into business-to-business e-commerce issues involving manufacturing small- and medium-sized enterprises (SMEs) is still embryonic. In an attempt to partially fill this gap, this paper presents empirical data from an electronic survey conducted among 96 manufacturing SMEs to investigate e-commerce initiatives and their perceived benefits for adopting firms. E-commerce initiatives are assessed in this study using a set of 36 business processes that can be executed using e-commerce tools. These processes were classified according to their focus: customer (downstream), supplier (upstream) or in-house. The research findings point to four main profiles for manufacturing SMEs with different e-commerce focuses. The first group seems to lack any focus or may still be exploring e-commerce opportunities. The second and third groups are supplier-and customer-focused, respectively. The fourth group consists of the more involved SMEs that have leveraged their e-commerce initiatives with both their customers and their suppliers. The results also suggest the existence of a close alignment between e-commerce focus and the related benefits.
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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 | 0.000 | 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 | 0.000 |
| 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".