Compensating Service Failures: The Moderating Role of Customers’ Political Ideology
Bibliographic record
Abstract
When service failure occurs, the service provide often dispenses compensation to manage customer relations. However, little research has studied who accepts larger or smaller compensation amounts. Presently, we use political ideology as a basis to segment customers. Drawing on prior work on System Justification Theory, we hypothesize that politically conservative customers accept a lower amount of compensation than liberals as conservative customers more likely believe that whatever amount the service provider offers is just and fair. Importantly, we propose that the effects are specific to economic conservatives, not social conservatives. The findings are consistent with our predictions, with (economic) conservatives’ customers’ system justification beliefs serving as a mechanism. Theoretically, our work is the first to examine who accepts different levels of compensation while also broadly suggesting that political ideology is an important customer segmentation basis in the tourism and hospitality sectors. Our work also contributes to the literature on political ideology by being one of the first to empirically tease apart the distinct effects of economic and social conservatism.
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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 | 0.002 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".