FACTORS AFFECTING CONSUMER PURCHASE INTENTION IN AI-DRIVEN LIVE-STREAMING COMMERCE: A MULTIPLE REGRESSION ANALYSIS OF DIGITAL CONSUMERS IN SHANGQIU CITY, HENAN PROVINCE
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This research article aims to: 1) examine the descriptive levels of AI streamer attributes (Anthropomorphism, Perceived Interactivity, Consumer Trust, and Information Quality) and consumer Purchase Intention in AI-driven live-streaming commerce in Shangqiu City; 2) compare differences in Purchase Intention across demographic groups; and 3) identify which factor exerts the greatest predictive influence on Purchase Intention. It is a quantitative, cross-sectional study collecting data from 385 valid respondents who are active users of live-streaming platforms (Douyin, Taobao Live, and Kuaishou) in Shangqiu City, analyzed using Multiple Regression Analysis (MRA), supported by t-test, One-Way ANOVA, and Pearson Correlation.
The research results found that: 1) The integrated four-factor model explained 61.2% of the variance in Purchase Intention (R² = .612, F(4,380) = 149.851, p < .001), and all four hypotheses were supported. 2) Purchase Intention differed significantly by age group (F = 3.245, p = .022), with consumers aged 18–25 (the “Digital Natives”) reporting the highest intention, while no significant differences were found by gender or platform preference. 3) Perceived Interactivity was the strongest predictor (β = .345), followed by Anthropomorphism (β = .282), Consumer Trust (β = .214), and Information Quality (β = .176), indicating that agentic commerce success depends on a strategic synergy of “approachable realism” and synchronous responsiveness, prioritizing low-latency dialogue over pure visual fidelity.
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