How user personality and information characteristics influence the creative information quality on open innovation platforms: an elaboration likelihood model

Large volumes of users' creative information have rapidly become vital resources in the open innovation platforms, so it is crucial to identify high-quality information from massive creative information. However, the existing literature on the quality of creative information only focuses on the information characteristics or publishers' features.

In this paper, the authors used the elaboration likelihood model to examine the joint effect of central route factors (information characteristics: timeliness, readability and sentiment) and peripheral route factors (source characteristics: personality traits, past successful experiences and social network location) on the quality of creative information. Furthermore, the author explored the moderating roles of companies' support between central and peripheral route factors on the quality of creative information. Finally, binary logistic regression was adopted to test the research hypotheses on the empirical data from Salesforce.

The results indicated that users with high extroversion, conscientiousness, social centrality and prior success rate tended to propose high-quality information. Meanwhile, information timeliness, readability and sentiment also negatively influence the quality of creative information.

Different from previous studies, the study findings not only provide insights on identifying the quality of creative information from an information perspective, but also promotes the awareness of the intrinsic personality traits of information users and innovative support efforts by platforms and their managers.