The Use of Dominance Analysis to Identify Key Factors in Salespeople’s Affective Commitment Toward the Sales Manager and Organizational Commitment
Bibliographic record
Abstract
Selling in the current business environment requires dedication from various members of the organization. It is important for managers and researchers to identify key factors contributing to salesperson commitment within the organization and to the organization in order to achieve sales objectives. The purpose of this study is to identify the relative importance of variables influencing salesperson affective commitment to their sales manager and the commitment to the organization. Using social exchange theory and resource exchange theory, salesperson interaction with their manager is expected to be exchanged for commitment to that manager. On an organizational level, salesperson satisfaction with the organization is expected to be exchanged for commitment to the organization. Dominance is calculated for each of the independent variables examining affective commitment to the manager (trust, integrity, consideration) and organizational commitment (job satisfaction, promotion opportunity, needs fulfillment). Dominance analysis results show relative importance for perceived trustworthiness of the manager on salesperson commitment to the manager and promotion opportunity on salesperson commitment to the organization.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| 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".