Rong Du

Visual content is central to online health communication, yet little is known about how multimodal relationships are associated with audiences’ click-through choices. Drawing on processing fluency and risk communication perspectives, this study distinguishes image–text congruence from inter-image coherence and examines their linear, nonlinear, and risk-contingent associations with click-through rate (CTR). We analyze 34,341 health-related articles published by 2184 authors. Clicks are modeled relative to impressions using beta-binomial regression with author and publication-date fixed effects. Image–text congruence is positively associated with the probability that an impression converts into a click, whereas inter-image coherence has an inverted U-shaped association with this probability. Moderate coherence is associated with the highest CTR, while excessive similarity corresponds to declining CTR. Higher topic health risk corresponds to a stronger association between image–text congruence and CTR and a weaker high-coherence decline. The results remain consistent across alternative model specifications, visual measures, outlier exclusion, and different observation windows. By distinguishing cross-modal congruence from within-modal coherence, this study clarifies their different persuasive functions and demonstrates that their associations with click-through choice depend on topic health risk. These findings inform research on digital persuasion and the design of online health content.

Purpose: Grounded in signaling theory, this study examines whether traceability information displaces or complements incumbent quality cues and contrasts the relative efficacy of blockchain-enabled traceability technologies with traditional systems. Design/methodology/approach: This study analyzes 18 months of product-level sales data from a global e-commerce platform using a staggered difference-in-differences design with robustness checks. We apply latent Dirichlet allocation topic modeling to consumer reviews and use a synthetic difference-in-differences approach to examine shifts in consumer attention after traceability implementation. Findings: Traceability information increases product sales, particularly for lower-reputation brands and diminishes the effect of electronic word-of-mouth, suggesting that diagnostic quality signals matter more than social information signals. Although blockchain-enabled traceability should enhance signal credibility, its observed impact falls short of expectations. Research limitations/implications: The sample is limited to the automotive engine oil context in China. Future research should examine other categories and national contexts. Practical implications: Platform managers and emerging brands can deploy low-cost traceability labels to boost demand. Blockchain solutions may require consumer education to justify higher implementation costs. Social implications: Augmenting supply-chain transparency and product traceability curbs counterfeit and substandard goods, improves consumer welfare, and supports regulatory and sustainability objectives. Originality/value: This study systematically assesses the substitutive and complementary roles of traceability signals in a multi-cue setting, tempers optimism about blockchain-enabled traceability and extends research on digital supply-chain transparency and signaling theory.

Purpose: Social question and answer (Q&A) systems have been rapidly developed on many e-commerce websites. The purpose of this paper is to explore how social Q&A systems influence consumers' information processing and purchase intention.Design/methodology/approach: The authors design this research based on the information adoption model (IAM). First, the auhors consider the impacts of the central route (information factor) and peripheral route (social factor) on consumers' perception of information usefulness in Q&A systems. Then, the authors verify the influence of information and social aspects on purchase intention and empirically test the model with structural equation modelling (SEM) using 428 effective data samples.Findings: On the whole, the authors prove that purchase intention is influenced by information and social aspects, which are two paths in Q&A systems. Specifically, both answer quality and social presence positively influence information usefulness. Interestingly, respondent credibility and answer consistency do not significantly impact information usefulness. Moreover, information usefulness positively affects information adoption, which positively affects consumer purchase intention.Practical implications: This paper provides insights on social Q&A system mechanism design.Originality/value: First, this paper is a useful complement to the research on social Q&A systems on e-commerce websites. Second, the authors provide a new theoretical lens through which the impacts of social Q&A systems on e-commerce websites are understood by extending the IAM. Third, the authors add answer consistency into original information process routes, which obtains a finding that is different from those of prior research.