Consumers as creative agents: How required effort influences willingness to engage
Bibliographic record
Abstract
Abstract Consumers often engage with brands by participating in activities such as co‐creating products and contributing ideas about product promotion. Such engagement enables consumers to be creative agents rather than mere end‐users. However, it also places a burden on them, as it inevitably requires effort on the consumer part. This study investigates the impact of expected effort level (low vs. high) on consumers' inclination toward engagement, and its underlying mechanisms. Three experiments find that higher expected effort leads to lower intention to engage. This effect is mediated by the perceived probability of success and perceived value of engagement, and the two mediators operate in tandem. Effort levels negatively affect the perceived probability of success, which exerts a positive impact on the perceived value of engagement and then on willingness to engage. We also examine the moderating effect of consumer mindsets and find that chronic and situational consumer mindsets work differently. Specifically, primed mindsets have a significant effect, but enduring mindsets do not. This study contributes to the literature on engagement and expectancy–value theory by exploring consumer effort in a context where effort aids in implementing creativity.
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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 | 0.015 |
| 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 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".