Exploring persuasion and participation in online knowledge payment – a dual-route perspective

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Publicado en:Humanities & Social Sciences Communications vol. 12, no. 1 (Dec 2025), p. 1170
Autor principal: GAO, JIE
Otros Autores: Hassan, Siti Hasnah
Publicado:
Springer Nature B.V.
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Acceso en línea:Citation/Abstract
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Resumen:The intersection of digital technology and the knowledge economy has led to the rapid development of the online knowledge payment (OKP) industry, which has attracted increasing attention from scholars across various disciplines. However, research in this field remains relatively fragmented and lacks a coherent framework for understanding the evolutionary trajectory and mechanisms of OKP platforms. This study addresses this gap by conducting a bibliometric review of 226 core papers retrieved from Scopus and Web of Science databases and applying the Elaboration Likelihood Model (ELM) to interpret the underlying business logic of OKP models. Through ELM-guided classification, this paper distinguishes between central route mechanisms (such as knowledge quality and credibility in paid Q&A) and peripheral route mechanisms (such as emotional appeal and interactivity in live broadcast formats). The bibliometric analysis reveals emerging research trends focused on hybrid platform strategies, artificial intelligence-driven personalization, and blockchain-enabled trust systems, indicating a shift from static content monetization to dynamic, user-centered knowledge experiences. By integrating the ELM with quantitative mapping of the OKP research landscape, this study constructs a dual-perspective framework that links user cognitive processing with evolving platform affordances. The findings theoretically illustrate how persuasion and participation coexist in knowledge-driven digital environments, offering practical guidance for platform designers, knowledge creators, and policymakers seeking to promote innovation and user engagement in the OKP field.
ISSN:2662-9992
2055-1045
DOI:10.1057/s41599-025-05431-5
Fuente:Social Science Database