Impact of platform differences in online word-of-mouth on consumer purchase intention

Ke Gao (), Nusanee Meekaewkunchorn (), Chaiyawit Muangmee () and Tatchapong Sattabut ()

Edelweiss Applied Science and Technology, 2025, vol. 9, issue 5, 3032-3045

Abstract: This study investigates how relationship strength and self-disclosure enhance electronic word-of-mouth (eWOM) credibility on social media and e-commerce platforms, thereby reducing decision uncertainty and strengthening purchase intentions. Additionally, it explores the moderating role of platform type. Grounded in the Information Adoption Model and trust transfer theory, the study employs computational intelligence methods, including structural equation modeling (SEM) and multi-group analysis. Data were collected through 400 valid questionnaires from four major Chinese cities. The analysis reveals that strong interpersonal relationships and high self-disclosure significantly improve eWOM credibility. eWOM credibility partially mediates the enhancement of purchase intentions. Platform type moderates these effects differently: relationship strength is more influential on social media platforms, while self-disclosure has a greater impact on e-commerce platforms. The study advances the Information Adoption Model by uncovering the interaction between relational and informational mechanisms in eWOM dissemination through computational intelligence. Businesses can optimize user interactions and content authenticity using intelligent algorithms, tailoring strategies to platform-specific dynamics to effectively influence consumer behavior.

Keywords: Computational intelligence; Electronic word-of-mouth; Intelligent algorithms; Platform type. (search for similar items in EconPapers)
Date: 2025
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