Retail Karma: How Our Shopping Sins Influence Evaluation of Service Failures
Bibliographic record
Abstract
Abstract Consumers have an intuitive belief in “karma” which dictates that bad (good) actions lead to bad (good) outcomes. Consequently, consumers perceive a causal connection between their own wrongdoing toward a company and a subsequent service failure that they experience in their interactions with another company. Eight experiments employing different contexts consistently show that consumers who have previously wronged a company (compared to those in a control group) evaluate another unrelated company more positively in response to a service failure by this company. We argue that this more positive evaluation is due to the greater blame consumers assign to themselves as dictated by the “karmic beliefs” held by consumers whereby the subsequent poor service by a different firm is seen as a karmic payback for their own prior transgression. The proposed effect is mitigated when a person’s karmic belief is reduced. We also examine a number of alternative explanations (e.g., negative experiences, moral balancing, and immanent justice reasoning) and find that our observed effect is more consistent with a karma-based account.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".