“Give me one but not the other”: the substitution effects of supervisor’s organizational status and salesperson internal networking on performance growth trajectories
Bibliographic record
Abstract
Despite recent attention from scholars, internal networking remains underexplored in the sales literature, particularly with respect to its effect on longitudinal measures of performance. The current research addresses this notable omission by examining the interactive effect of salespeople’s internal networking ability and their supervisor’s organizational status on performance growth trajectories. Utilizing 20 quarters of individual, financial performance data from 113 salespeople at a warehousing equipment manufacturer, we find that both internal networking and a supervisor’s organizational status drive a salesperson’s performance growth trajectory. However, the interaction of these two variables has a negative – and counterintuitive – effect on performance growth trajectory. That is, supervisors with high organizational status attenuate (buttress) the performance growth of their high (low) networking salespeople. Taken together, these results reveal an important boundary condition regarding the efficacy of internal networking, and underscore the importance of sales managers in shaping the effectiveness of their salespeople’s internal networking efforts.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".