Internet Adoption by Small and Medium-Sized Enterprises (SMEs) in Developing Countries: The Case of Travel Agents in the United Arab Emirates
Bibliographic record
Abstract
Internet technologies are commonly seen as the future for most modern businesses across industries. However, the adoption of such new technologies is often lagging in small and medium-sized enterprises (SMEs) worldwide. Because of a lack of infrastructure or institutional development, SMEs located in developing countries may struggle even more in adopting new technologies. This research investigates the factors that influence Internet adoption in SMEs in developing countries through a case study of travel agents in the United Arab Emirates (U.A.E.). A census-like database of all known travel agents in four emirates provided the basis for the survey. The findings indicate that customer demand and industry pressures are positively associated with Internet adoption by travel agents across the U.A.E. Surprisingly, internal resources appear to be less relevant. Lack of local institutional support is negatively associated with Internet adoption but has no effect on the perceived importance of Internet features,...
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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 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".