Show them the money? The role of pay, managerial need support, and justice in a self‐determination theory model of intrinsic work motivation
Bibliographic record
Abstract
The link between money and motivation has been a debated topic for decades, especially in work organizations. However, field studies investigating the amount of pay in relation to employee motivation is lacking and there have been calls for empirical studies addressing compensation systems and motivation in the work domain. The purpose of this study was to examine outcomes associated with the amount of pay, and perceived distributive and procedural justice regarding pay in relation to those for perceived managerial need support. Participants were 166 bank employees who also reported on their basic psychological need satisfaction and intrinsic work motivation. SEM-analyses tested a self-determination theory (SDT) model, with satisfaction of the competence and autonomy needs as an intervening variable. The primary findings were that amount of pay and employees' perceived distributive justice regarding their pay were unrelated to employees' need satisfaction and intrinsic work motivation, but procedural justice regarding pay did affect these variables. However, managerial need support was the most important factor for promoting need satisfaction and intrinsic work motivation both directly, indirectly, and as a moderator in the model. Hence, the results of the present organizational field study support earlier laboratory experiments within the SDT framework showing that monetary rewards did not enhance intrinsic motivation. This seems to have profound implications for organizations concerned about motivating their employees.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 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".