Internal Marketing Based on the Hierarchy of Effects Model for the Life Insurance Industry
Bibliographic record
Abstract
The purpose of this study is to identify the extent to which ethical climate, leader–member exchange, and role clarity can be employed as business levers in internal marketing; the relationships among them are investigated using a conceptual model based on the hierarchy of effects model. From several major life insurance firms in Taiwan, 644 life insurance salespeople formed the basis of the empirical analysis in this study. Ethical climate is not only a feasible business practice for implementing internal marketing but also a basis for other managerial activities concerning internal marketing. Managerial activities arousing salespeople's perceptions of ethical climate, leader-member exchange, and role clarity may be useful in enhancing their job satisfaction, and in strengthening the organizational identification and organizational commitment of their salespeople. This study extends the internal marketing literature both by applying the principles of the hierarchy of effects model to internal marketing, and by examining the effects of ethical climate, leader-member exchange, and role clarity on job outcomes within such a context.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".