In view of the significant role project success plays for all parties in the crowdfunding market, a wealth of research has extensively explored its vastly diverse antecedents. Drawing on the elaboration likelihood model as an overarching theoretical basis, our meta-analysis examines the aggregated effects of widely investigated antecedents (as central and peripheral cues) and moderating roles of research contexts (referring to the elaboration likelihood). It reveals a stronger link with soft information–related factors, weaker ties with backer-related factors, and varied effects of project factors. Crowdfunding success measure, crowdfunding model, platform popularity, and project location are important reasons for the inconsistencies in findings across individual studies. Our research offers valuable insights for stakeholders in the crowdfunding ecosystem. For backers, it empowers them to select projects with greater potential for success among the vast number of available options, ensuring more informed investment decisions. Fundraisers can leverage our findings to refine their fundraising strategies, thereby boosting their chances of securing funds effectively. Crowdfunding platforms can harness our findings to refine their system architecture, enrich service offerings, and improve user satisfaction. Furthermore, regulators and policymakers can draw from our study to devise regulations that nurture a robust and favorable crowdfunding environment.

Knowledge-sharing platforms such as Wikipedia are widely used by investors, yet much of the content they circulate is secondhand: factually accurate information that has already been disclosed and is later reshared without substantive updates. Under the efficient market hypothesis (EMH), such information should already be reflected in prices. However, qualitative evidence suggests that retail investors may react to it even when they recognize it as old, implying a behavioral mis-reaction. If systematic, such responses can amplify noise trading and misallocate capital. To provide causal evidence on whether recognized secondhand information influences investor behavior when reshared, we conducted a randomized field experiment on Wikipedia. We focused on salient negative secondhand information, operationalized as litigation news. Between June 15 and July 13, 2013, we introduced such content into the Wikipedia pages of selected public firms and compared their outcomes with those of matched control firms whose pages were left unedited. We also included a placebo group whose pages were edited with operations news. The results show that retail investors respond to recognized secondhand litigation news. Relative to controls, treated firms experienced significant increases in Wikipedia pageviews, a 15.7% rise in retail trading volume, and a 6.9 basis point reduction in bid–ask spreads. These effects were stronger when the litigation was more severe or recent, when firms operated in more visible and positive informational environments, and when the underlying litigation signaled governance weaknesses—a pattern consistent with representativeness-based judgment and therefore difficult to reconcile with the EMH. Mediation analysis further indicates that heightened attention is one channel through which secondhand information shapes trading behavior and market outcomes. We contribute to the information systems and behavioral finance literatures by identifying salient negative secondhand information as a distinct, behaviorally potent content category. Our findings carry implications for regulators, firms, and digital platforms, and point to mitigation strategies such as interface-level cues, investor education, and novelty-detection tools. Overall, we underscore the need to reconsider how platform-mediated salient negative secondhand information can shape market outcomes.