The operational impact of e-business on SMEs performance in Saudi Arabia
Bibliographic record
Abstract
The study aimed at investigating the impact of e-business on small and medium enterprises (SMEs) operational performance in terms of business flexibility, business quality, and business costs. Research data was harvested via an online questionnaire developed based on previous related works and administered to a sample consisting of 500 owners and managers of industrial and commercial SMEs in Saudi Arabia. Using SmartPLS software, the results pointed out that e-business exerts a significant positive impact on the overall SMEs operational performance. Particularly, the results revealed that e-business results in positive effects on business flexibility, business quality, and business costs. It was observed that the greater impact of e-business was on business flexibility while the impact of e-business on business quality and business costs is roughly similar. These findings suggest that the current SMEs are highly concerned with customer-oriented issues such as marketing channels, customer needs and communications, and on-time delivery. Based on these results, it was concluded that SMEs can use e-business solutions to boost their business operational capabilities with reference to flexibility, quality, and cost.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".