Why to purchase health knowledge on online platforms? A two-phased SEM-ANN approach

ABSTRACT

Previous research on online health knowledge payment has mainly focused on the health consultation context and knowledge contributors-related characteristics. However, less attention has been given to the roles of health knowledge itself and the underlying platforms. Based on the perceived value theory and S-O-R framework, this study investigated how health knowledge and platform characteristics influence consumers’ purchase intention. Through a survey of 432 Chinese respondents, we employed a multi-analytical approach, combining structural equation modelling (SEM) with artificial neural network (ANN) techniques. SEM results indicate that knowledge personalisation, platform information quality, and platform service quality positively influence both utilitarian and hedonic values, subsequently affecting purchase intention. Furthermore, our findings support the partial mediation role of perceived value. ANN results highlight platform information quality as the most influential stimulus factor. Our study broadens the research scope of online health knowledge payment and offers theoretical and practical insights for its further advancement.

KEYWORDS:

• Perceived value theory
• S-O-R model
• health knowledge payment
• purchase intention
• artificial neural network

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Natural Science Foundation of China [grant numbers 71971092 and 72271102].