Understanding employees' reactions to supervisors' influence behaviors
Bibliographic record
Abstract
Purpose This study seeks to demonstrate that employees' reactions to their supervisors' influence behaviors are governed by meanings inferred from the behaviors. Another aim is to develop a method in which “weights” for predicting employees' reactions are assigned using mean ratings of perceptions of the features and social/organizational implications of the influence behaviors. Design/methodology/approach Employees of an energy utility completed survey questionnaires concerning the extent of their supervisors' use of specified influence tactics. Employees' organizational commitment, supervisor commitment, turnover intention, and stress also were surveyed. A separate, community sample rated the influence tactics for dimensions of meaning or implications of the tactics. Data from the two samples were combined in a novel arithmetic scoring procedure as one of several analyses looking for evidence of the specified dimensions' effects. Findings The study finds that employees' work attitudes and other outcomes were predicted to a statistically significant degree by dimensional, perceptual characterizations of the influence tactics used by their supervisors. In culminating multiple regression analyses, respectfulness was associated with supervisor commitment, turnover intention, and emotional distress; directness was associated with organizational commitment. Additional analyses indicated that other dimensions of meaning also were associated with outcomes. Research limitations/implications The meanings of supervisors' influence behaviors are somewhat culture‐specific, so the generalizability of findings to other cultures is uncertain. However, the central role of social inferences in reactions to supervisors' influence behaviors may be replicable to other cultures if culture‐specific content or ratings are substituted there. This research also has the usual limitations of cross‐sectional, correlational research. Practical implications In their interactions with employees, managers and supervisors should be aware that their influence behaviors, collectively, generate reactions that are significant for employees' motivation and well‐being. Supervisory behaviors and work contexts should be managed so that employees will infer that their supervisors are showing respect and are being honest and direct. Originality/value Processes previously assumed to intervene between supervisory influence behavior and employee reactions were operationalized and demonstrated. Novel methods were developed for this research, and these methods may also be applicable to other research domains that involve sets of behaviors that parallel existing schemes for influence behavior.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".