Chinese Consumer Response to AI Functions on Online Secondhand Platforms

Abstract

This study examines Chinese consumers’ perceptions of AI functions on online secondhand platforms and their impact on purchase intention. Drawing on the technology acceptance model and perceived cyber risk, the research investigates perceived usefulness (PU), perceived ease of use (PEU), perceived enjoyment (PE), perceived cyber risk (PCR), and purchase intention (PI). A quantitative survey of 200 mainland Chinese consumers with prior experience or intent to use AI functions on secondhand platforms employed correlation and multiple regression analyses. Results indicate moderate levels of PEU (M = 2.83) and PCR (M = 2.85), high PU (M = 3.08), and relatively low PI (M = 2.19). Regression findings show that only PEU and PCR significantly predict PI, with PEU emerging as the strongest positive predictor (β = 0.270) and PCR exerting a negative effect (β = −0.261). The model accounts for 30.2% of the variance in PI (adjusted R² = 0.302). These findings highlight the importance of user‑friendly AI design that minimizes consumer effort in secondhand shopping, alongside transparent and trustworthy data practices that mitigate privacy and security concerns, thereby enhancing consumer confidence in AI‑mediated secondhand commerce.