Bibliographic record
Abstract
SMEs that are adopting Internet technologies and e-business solutions often require business support services. This paper summarizes the results of a survey of New Brunswick SMEs discusses characteristics of New Brunswick SMEs in terms of “pain points” - perceived barriers to growth and desired capabilities. \nKey points are: \n• The most extensive users of Internet technologies or e-business solutions are larger SMEs. \n• However, microenterprises lead in adoption of business models relying on Internet-based sales, and small SMEs lead in matters of Internet-based exporting. \n• Two-thirds of SMEs report having plans for further investments in Internet technologies and e-business solutions. \n• New Brunswick SMEs that have adopted Internet technologies and e-business solutions in varying degrees report a broad range of benefits from their engagement in e-business. \n• Domestic market development is the principal motivation for adoption of Internet technolo-gies and e-business solutions. \n• Personalized expert services are the most highly desired support service. \nSix possible sets of drivers of demand for nine e-business support services are investigated. The six postulated influencers of demand are firm size, growth orientation, e-Business technological capabilities, desired business capabilities solutions to business problems, and intensity of competition. The nine e-buisness support services are directory of support organizartions, interactive questionnaire to help define an e-commerce strategy; online sector-specific seminars on e-commerce; classroom-based sector-specific seminars about e-commerce; personalized, expert advice on e-commerce; examples or case studies of businesses using e-commerce success-fully; recommendations about e-commerce solutions; statistics and graphics about e-commerce adoption and use among different sizes or types of companies in New Brunswick; visits to successful companies. Tests of differences of means between firms expressing interest in particular support services show that problem solving, use of e-Business technologies, and strategic development of business capabilities are much more strongly associated with demand for services than size of firm, growth orientation, or intensity of competition.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".