Needs Versus Wants: The Mental Accounting and Effort Effects of Tangible Rewards
Bibliographic record
Abstract
ABSTRACT The use of tangible rewards to motivate employees is common in North American organizations. However, there is considerable variation regarding the nature of tangible rewards used with some firms offering hedonic items (e.g., wants) and others offering utilitarian items (e.g., needs). We use two studies to examine the effects of tangible reward nature on employee mental accounting and effort. In Study 1, consistent with predictions, we find that hedonic tangible rewards are mentally accounted for separately from utilitarian tangible rewards, and that hedonic tangible rewards are more likely categorized separately from regular earnings than are utilitarian tangible rewards. In Study 2, as predicted, we find hedonic tangible rewards lead to greater effort than utilitarian tangible rewards. Collectively, results from our two studies demonstrate the motivational benefits of offering performance-based hedonic tangible rewards rather than utilitarian tangible rewards and offer new insights regarding the mental accounting mechanisms underlying these effects. Data Availability: Data are available on request. JEL Classifications: C91; M41; M52.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".