Integral evaluation as the basis of analytical support for managing the competitiveness of socially-oriented retailers
Bibliographic record
Abstract
The advantages of an integral approach to assessing the competitiveness of retailers are substantiated, which allows obtaining a more thorough and versatile informative base for making further managerial decisions to ensure the development of trading business. A new approach to the integral evaluation of the competitiveness of retailers is developed. The list of functional and structural components of competitiveness was substantiated: marketing,financial and investment, material and technical, intellectual and personnel,innovation, logistic and social. It is proposed to use the methodological sequence of competitiveness assessment, which involves the alternate passage of the following stages: construction of an evaluation hierarchy, identification of the levels of the criterion importance, definition of a set of “local vectors” by evaluation criteria, conducting comparative evaluation of competing enterprises, hierarchical synthesis of alternative options for ensuring competitiveness. The methods of an expert survey are used to form an information and analytical base. Using the Saaty’s analytic hierarchy process and the Delphi method of an expert survey, a matrix of pairwise comparisons of the criteria of the retailers’ competitiveness is formed. The Gallup Institute methodology is used to form the sample of enterprises. A matrix of rating positions of the socially-oriented retailers is developed to enable evaluation.On the basis of the obtained results – analytical support of the policy(regarding the competitiveness level, state of security and coefficients of weight of its functional and structural components), the strategic principles of managing the competitiveness of socially-oriented retailers. A matrix of strategic decisions on managing the competitiveness of socially-oriented retailers is developed.
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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 | 0.033 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".