Study on Customer Relationship Management in Growing Companies in Emerging Economies
Bibliographic record
Abstract
Customer Relationship Management (CRM) has a growing popularity and is fast becoming one of the hottest topic and innovative way in present day marketing because of its practicality in the business field. In fact, due to the competitive environment, CRM is crucial and has become a niche for company performance. However, there is still a huge gap between companies and customers in CRM dimensions and in growing economies because they are yet to get a real understanding of comprehensive implementation of CRM. An analysis of strategy in CRM has become a necessary part of organisations in marketing. Already existing markets need people with the technical no-how on the best way in dealing and relating with supposed customers. There is no marketing or management without customers. The study intends to show the importance of how CRM in 21st century businesses and industries, helps in serving customers better. It also will highlight problems encountered in effective CRM implementation in business field of growing economies, and offer some suggestions in bridging the gap between growing economies and already developed economies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".