From complaints to recalls: how online linguistic cues influence product recall speed

Abstract

Purpose The study aims to examine how the linguistic content and style of online consumer defect reports, including negative affective, social, cognitive, and perceptual language, affect recall speed in the automotive industry. Design/methodology/approach Using both text mining and survival analysis, this study compiled and analyzed 166,027 vehicle customer complaints from China during 2011–2018. Findings Negative affective and social cues serve as powerful peripheral signals that heighten urgency perceptions, thus accelerating the recall speed. In contrast, cognitive and perceptual language require greater central processing effort, dilute urgency perceptions, and ultimately slow the recall process. Research limitations/implications We extend time-to-recall research by moving beyond product hazards, firm-level factors, and other macro-level contextual characteristics to emphasize the micro-linguistic mechanisms through which online consumer defect reports influence recall speed. The study also shifts the analytical focus from automakers to regulatory agencies, highlighting that under conditions of bounded rationality and capacity constraints, regulators rely on linguistic cues in consumer reports to assess urgency. Practical implications Our findings show that the language consumers use in online defect reports directly affects how regulators perceive urgency and respond. Thus, monitoring online consumer complaints requires attention not only to volume but also to linguistic features. Originality/value By integrating stakeholder salience theory and the elaboration likelihood model, we extend the recall research on online consumer defect reports by moving from macro-level reputational and media pressures to the micro-level linguistic mechanisms through which consumer complaints influence regulatory decision-making and recall speed.