This paper examines how online complaints influence stock price crash risk and identifies the underlying mechanisms in Chinese capital markets.
Using data from China's Black Cat Complaint platform data, we employ fixed-effects regression to analyze 930 listed companies from Q2 2018 to Q4 2023 (3,843 firm-quarter observations). Crash risk is measured using negative skewness and down-to-up volatility.
Higher online complaint volumes significantly increase crash risk, with results robust across sensitivity tests. The effects are stronger for firms with lower financial distress, higher information transparency, and inadequate complaint responses. Mechanism tests reveal that complaints elevate crash risk through deteriorating revenue performance and declining disclosure quality.
Managers should prioritize complaint management and product quality to prevent information hoarding. Investors can use complaint metrics as early warning signals. Regulators may mandate complaint disclosure to enhance market transparency, especially for firms with high information asymmetry.
This study makes three contributions to behavioral finance: it pioneers the use of consumer-generated complaints as crash predictors, bridging consumer and asset pricing research; it extends stakeholder theory by demonstrating how consumer voice directly impacts market stability; and it reveals how the digitalization of complaints creates information pathways that shape investor behavior, offering guidance for proactive consumer relationship management.
