Knowledge About AI and Online Purchase Intention Among Gen Z: a Multi-Group Gender Analysis

Abstract

Background: The rapid integration of artificial intelligence (AI) into e-commerce has transformed how consumers interact with online shopping platforms, particularly among Generation Z, who exhibit high digital literacy and strong acceptance of emerging technologies. Despite the growing adoption of AI-driven features, empirical findings regarding how AI knowledge influences purchase intention remain inconclusive, especially when perceptual factors and gender differences are considered.
Purpose: This study aims to examine the effect of knowledge about artificial intelligence on Generation Z’s online purchase intention, with perceived usefulness and perceived ease of use of AI as mediating variables, and to investigate the moderating role of gender in these relationships.
Design/methodology/approach: A quantitative, cross-sectional research design was employed, employing purposive sampling. Data were collected from 200 Generation Z consumers in Indonesia through an online questionnaire. The measurement items were assessed using a five-point Likert scale. Data analysis was conducted using Partial Least Squares–Structural Equation Modeling (PLS-SEM), including mediation testing and multi-group analysis to evaluate gender moderation.
Findings/Results: The results indicate that knowledge of AI significantly influences perceived usefulness and perceived ease of use. Both perceived usefulness and perceived ease of use have positive and significant effects on purchase intention and function as mediators in the relationship between AI knowledge and purchase intention. However, the multi-group analysis reveals that gender differences were not significant in this study.
Conclusion: The findings suggest that AI knowledge influences purchase intention both directly and indirectly through perceived usefulness and perceived ease of use. Strengthening AI literacy and designing user-friendly, value-oriented AI features are therefore essential to enhance Generation Z’s purchase intention in online shopping environments.
Originality/value (State of the art): This study extends the Technology Acceptance Model (TAM) by positioning AI knowledge as a cognitive antecedent of purchase intention through perceptual mediators, while simultaneously testing gender dynamics using multi-group analysis. The research provides novel insights into AI-driven consumer behavior among Generation Z in an emerging market context.

Keywords:   artificial intelligence, knowledge about ai, perceived usefulness, perceived ease of use, purchase intention