Beyond Usefulness: Credibility as the Driver of Consumer Trust and Satisfaction in AI Chatbot Interactions—Evidence from Moroccan E-Commerce

Abstract

AI chatbots have become central to e-commerce customer service globally, yet the trust mechanisms driving their adoption in emerging markets remain poorly understood. Existing research, grounded largely in the Technology Acceptance Model, emphasizes perceived usefulness and personalization as primary adoption drivers — constructs whose predictive validity in low AI-exposure, high uncertainty-avoidance markets cannot be taken for granted. This study proposes and tests a credibility-first framework among Moroccan e-commerce users, arguing that in high uncertainty-avoidance cultures, credibility — defined as the perceived honesty, reliability, and transparency of the chatbot — will be the primary feature activating consumer trust, while perceived usefulness, interactivity, and personalization are expected to have weak or non-significant effects. Survey data from 150 respondents were analyzed using Covariance-Based Structural Equation Modeling (CB-SEM) via the lavaan package in R, with mediation tested through 5,000 bootstrap resamples. Model fit was excellent (CFI = 0.978, RMSEA = 0.076). Results confirm that credibility is the primary significant predictor of trust (β = 0.486, p < .001), while usefulness, interactivity, and personalization are non-significant. Trust strongly predicts satisfaction (β = 0.532, p < .001), and full mediation is confirmed exclusively for the credibility–trust–satisfaction pathway (indirect β = 0.259, p < .001). These findings establish the credibility highway as the primary verified route to consumer satisfaction in this market, with direct implications for chatbot design priorities, personalization strategy, and AI governance policy in comparable emerging markets.