From consumer concerns to market returns: research on agricultural product quality credit based on online rice reviews

Abstract Agricultural product quality and safety is important to public health and economic stability. Traditional supervision methods are likely to suffer from inefficiency and lagged responses. Relevant studies tend to be limited to static administrative records or small-scale questionnaires, making them vulnerable to time lags and subjective biases. In contrast, the vast number of consumer reviews on e-commerce platforms provides valuable data for establishing a dynamic and intelligent regulatory system. Therefore, the BERTopic model is employed to extract consumers’ topics of concern from online reviews and identify corresponding enterprise-related variables to examine their relationship with a proxy for product sales using an OLS model. The results indicate that information transparency and enterprise quality certification are positively associated with review-based market activity through the channel of agricultural product quality credit, and advanced packaging technology positively moderates this association by mitigating quality loss and enhancing perceived credibility. Furthermore, Fuzzy-Set Qualitative Comparative Analysis (fsQCA) shows that high market performance in enterprises is closely associated with configurations that involve either comprehensive standardization or advanced packaging, while low market performance is primarily associated with a lack of agricultural product quality credit. The findings suggest that agricultural product quality credit is a major path for enterprises to transform management input into market returns. This study illustrates core correlation patterns observed among agricultural enterprises in market competition, provides direction for data-driven intelligent supervision, and establishes an effective connection between consumer market perception and enterprise objective credit.