The Determinants of Extent of Internet/E-business Technologies Use by SMEs in Maritime Canada: An analysis
Bibliographic record
Abstract
This study examines the determinants of extent of internet/e-business technologies (IEBT) use by small- and medium-sized enterprises (SMEs) in Maritime Canada. A research model based on the Technology–Organization–Environment (TOE) framework, proposed by Tornatzky and Fleischer (1990) was used to guide this research. Such factors as relative advantage, compatibility, complexity, management support, organizational readiness, and external pressures taken from the TOE framework were used to develop relevant hypotheses. Questionnaires were mailed to key informants in SMEs in the region. Data analysis was performed using the PLS approach. The perceptions of relative advantage, compatibility, organizational readiness, and external pressures moderately impacted the main construct: extent of IEBT use in the adopting SME. The result showed that the management support factor yielded the best result with regard to the dependant variable. The implications of the result findings for research and practice are discussed.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".