When Pricing Backfires: The Role of Love, Betrayal, Hate, and Social Discovery in Consumer Retaliation
Description
This dataset supports a study examining how the discovery of price inequity during hospitality service consumption influences consumer emotions and vindictive retaliatory behavior. Drawing on Referent Cognitions Theory and Psychological Contract Violation logic, the study investigates how consumers interpret pricing discrepancies in ongoing service encounters. The analysis employs regression-based mediation and moderated mediation models (PROCESS Models 6 and 12) to examine the relationships between price inequity, perceived price fairness, brand betrayal, brand hate, and vindictive retaliatory behaviors, including negative word-of-mouth and complaining. The empirical findings reveal that price inequity reduces perceived price fairness, which in turn increases brand betrayal and brand hate. Additionally, price inequity may directly trigger relational responses, indicating that consumers can bypass fairness evaluations and interpret inequity as a violation of expected treatment. Across both pathways, brand hate emerges as the primary driver of vindictive retaliatory behavior, whereas brand betrayal functions as an intermediate relational appraisal that does not directly translate into behavior. The results further show that brand love attenuates emotional escalation, while the social discovery of price inequity amplifies negative emotional responses The data were collected using a scenario-based experimental design in which participants were exposed to conditions involving disadvantageous or advantageous price inequity during ongoing service consumption. The dataset includes measures of perceived price fairness, brand betrayal, brand hate, vindictive negative word-of-mouth, and complaining behavior, along with moderators such as brand love and mode of discovery of price inequity. The dataset has been fully anonymized and contains no personally identifiable information. The file also includes a detailed codebook describing all the variables.
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Steps to reproduce
The dataset used in this study is provided in this repository. To reproduce the analysis: Import the dataset into a statistical analysis software such as SPSS. Identify and code the key variables as follows: Independent Variable: Price Inequity (PIn) Mediator: Perceived Price Fairness (PPF) Mediators: Brand Betrayal (BB), Brand Hate (BH) Dependent Variables: Vindictive Negative Word-of-Mouth (NWComp), Vindictive Complaining (NCComp) Moderators: Brand Love (BL), Mode of Discovery of Price Inequity (MoD) Conduct preliminary data screening: Check for missing values Ensure scale reliability and validity Standardize variables where required Estimate the mediation model using PROCESS Model 6: Test the sequential relationships: PI → PPF → BB → BH → behavioral outcomes Estimate the moderated mediation model using PROCESS Model 12: Include Brand Love and Mode of Discovery as moderators Test interaction effects and conditional indirect effects Use bootstrapping (e.g., 5,000 resamples) to assess the significance of indirect effects. Compare direct, indirect, and conditional effects to replicate the reported findings.