How do consumers react to big data-based personalised pricing? A cognition–affect–behaviour perspective

Abstract

We explored how customers’ thoughts and feelings about big data-based personalised pricing (BDPP) impacts their reactions. We developed a conceptual model based on the cognition-affect-behaviour paradigm and tested it using data from 284 consumers in the tourism and hospitality industry (female = 56. 34%; mean age = 34. 38 years, SD = 1. 95 years). The findings of PLS-SEM analysis revealed that consumers perceived price unfairness, betrayal, and privacy concerns when confronted with BDPP. These perceptions of unfairness and betrayal led to anger, while privacy concerns resulted in worry. Both anger and worry were significantly associated with the likelihood of discontinuous usage of online booking platforms and negative word-of-mouth about the products and services offered. Our findings suggest that cognition-affect-behaviour theory can effectively guide consumer reactions to BDPP. Additionally, there is a need for customer-centric studies on big data as a source of product pricing in various industries.