The impact of interactional justice on service evaluations in the banking context
Year: 2025
Type: article
Abstract: This study examines the impact of interactional justice —informational justice and interpersonal justice—on customer service evaluation in banking. Through five scenario-based experiments with 921 Chinese non-banking adults, we systematically manipulated justice levels and service agent source (human vs. AI). Findings reveal that both dimensions significantly enhance service evaluations (supported by a mini meta-analysis: Hedges' g = 0.62 for informational, g = 1.16 for interpersonal justice). Crucially, we identify a critical theoretical boundary condition for algorithm aversion: under low justice conditions, human agents received significantly lower evaluations than AI agents, yet under high justice, no significant human-AI difference emerged . This asymmetry—driven by higher expectations for humans—challenges the universality of human preference in service recovery and demonstrates that AI can achieve parity when justice is optimized. Our results advance interactional justice theory and provide actionable insights for resource allocation in AI-human hybrid service systems. • Informational and interpersonal justice are key factors influencing service evaluations in banking contexts. • Human agents receive lower evaluations than AI under low interactional justice conditions. • Five experiments and a mini meta-analysis demonstrate multi-dimensional justice impacts. • Banks should balance AI efficiency with human emotional engagement for optimal service. • Findings inform resource allocation between human and AI agents in financial services.
Source: Acta Psychologica
Authors: Jinghan Liu, Guangyao Yang, Yanqi Lyu, Qingwang Wei
Institution: Renmin University of China
Language: English
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,670
Award: G2644659014
OpenAlex ID: W4415570163