E-Commerce in Serbia: Where Roads Cross Electrons Will Flow
Bibliographic record
Abstract
A qualitative exploration into conditions for diffusing e-commerce in Serbia was conducted by using a multidimensional model. Serbia is a country located at an important geographical location in southeast Europe, which descended on a path of political and economic changes after a decade of stagnation. Our main finding is that the process of diffusing e-commerce in Serbia resembles a car hesitating at a traffic light because all lights are flashing at the same time. Dynamics within the areas of software industry, e-payment/e-banking, and legislation support e-commerce. In contrast, the telecommunications infrastructure and ownership as well as customer beliefs and behaviors halt it. The ambivalent yellow light is triggered by the state of traffic/delivery and education. Research contributions of the study refer to advancing the understanding of trust as a major enabler of e-commerce and to filling the void in the literature on a potentially important country. Practical contributions refer to creating a country profile along with development prospects that can be useful to other developing countries and global e-commerce players.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".