How do post content and poster characteristics affect the perceived usefulness of user-generated content?

Abstract

This study, guided by the elaboration likelihood model, explores the impact of user-generated content features, including argument quality and source credibility, on perceived usefulness. Analyzing social media posts in finance and health, the study’s econometric analysis reveals that these features influence perceived usefulness through central and peripheral cues. Newly identified features, domain relevance, and domain specificity are significantly associated with perceived usefulness. Specifically, domain relevance positively impacts perceived usefulness, while a U-shaped relationship exists for domain specificity. Subsequently, the study discusses the implications for user-generated content and management practices.