The effect of corporate image on the formation of customer attraction
Bibliographic record
Abstract
This paper examines the relationship of corporate image with customer attraction in Irancell Telecommunications Services Company in city of Ahvaz, Iran.The study uses a sample of 384 randomly selected people who use the firm's services.Measuring tools for corporate image and customer attraction are an 18-item questionnaire of Rampersad (2001) [Rampersad, H. (2001).75 painful questions about your customer satisfaction.the TQM Magazine, 13(5), 341-347.]and a 14-item questionnaire of Geib (2005) [Geib, M. (2005).Architecture for customer relationship management to attract and retain customers approaches in financial services, IEEE, Proceedings of the 38th Hawaii International Conference on System Sciences.],respectively.Results of regression analysis showed that there was a significant relationship between corporate image and attracting customers in Irancell firm.In addition, dimensions of corporate image including experience, character, competence, quality, differentiation, cost, technology, and culture and cognition increase customer attraction to the company.On the other hand, component of culture has the most effect on attracting customers in this firm.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".