Till death do us part – customer commitment after negative publicity: the role of relational variables and cognitive dissonance
Bibliographic record
Abstract
Purpose The purpose of this study is to study the impact of relationship marketing orientation (RMO) and relationship quality on customers' commitment and pro-marketer behavior (positive word of mouth and external attribution) after negative brand publicity by using the combined lens of relationship marketing theory and the theory of cognitive dissonance. Design/methodology/approach A survey was conducted among banking customers in India using an online questionnaire. Data were analyzed using structural equation modeling and the bootstrapping procedure using the SPSS process macro. Findings Contrary to conventional wisdom, findings of this study suggest that RMO and relationship quality are positively correlated to commitment even after negative publicity. The path between RMO, relationship quality and pro-provider behavior is found to be mediated by commitment. This indirect path is moderated by customers' cognitive dissonance arising out of the negative publicity. Originality/value The study establishes the combined roles of RMO and relationship quality in pre-empting the detrimental effects of negative brand publicity. Further, it establishes interactions of cognitive dissonance with these relationship variables, thereby bringing together literature from relationship marketing theory and cognitive dissonance theory.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".