Digital channels diminish SME barriers: the case of the UK
Bibliographic record
Abstract
This article investigates the usage of digital channels by UK small- and medium-sized enterprises (SMEs) and assesses the impact caused on their strategic marketing position. The research is based on statistical analysis of 66 surveyed SMEs in the context of the digital era. Despite indications from the relevant literature about the reluctance of SMEs to adopt advances in technological communication, the research reported indicates a high level of usage of digital channels, especially social media (SM). The web 2.0 technologies that facilitate the new digital channels are standardised, interactive, ubiquitous and cheap. These features change the way how companies communicate and shift fundamental marketing and business concepts. Due to this shift, the SMEs’ barriers for technology adoption, including lack of financial resources, knowledge and skills, are diminishing. The latter, supported also by the research findings, increases the impact of SMEs bringing them closer to the large corporations in the global marketplace. The study is significant because it extends previous knowledge on technology adoption, with findings about the adoption of digital channels by SMEs, but more importantly, it opens up a novel insight into strategic literature for SMEs.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".