Analyzing key performance indicators of e-commerce using balanced scorecard
Bibliographic record
Abstract
E-commerce as one of the most significant aspects of innovation in business processes is what takes place in companies across the world.The gap between information and communications technology and e-business application is called the digital divide.It is necessary to understand the reasons for the failure of commercial sites.Here the objective is to assess the commercial sites of Iran.Different methods are adopted to evaluate sites and electronic stores.The balanced scorecard is a rarely adopted method of concern to evaluate these sites in Iran.The survey methodology and Delphi technique are applied in building the research tools, which led to the development of a questionnaire.Through applying the BSC approach, the numbers of indicators in each of the four perspectives of BSC were identified.The DEMATEL technique is applied to determine the importance of different perspectives and to identify the causal correlations among the four perspectives.The results generated by SMART PLS graphics, the Structural Equation Modeling software, confirm the adequacy of this proposed model for websites.The findings here indicate that the growth and learning perspective have the greatest impact on the other perspectives while the other perspectives mostly affect the financial perspective.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".