Firms increasingly use ideas from online innovation communities to solve problems or to better address customer needs. Before adopting external ideas, firms have to evaluate their suitability and value. However, the number of submitted ideas has exploded, it leads to the information overload that firms hardly can handle based their limited cognitive resources. Therefore, we use the elaboration likelihood model to distinguish between the quick and lean idea preselection process as a peripheral route of information processing, based on characteristics of the idea provider, and the subsequent idea review process as a central route of information processing, based on an in-depth elaboration of the idea itself. In our empirical study with a sample of more than 163,000 ideas collected from the Xiaomi MIUI community, we analyze influencing factors that increase the likelihood of ideas being preselected or reviewed. Results show that user status, user initiative contribution, and community recognition have a significantly positive influence on idea preselction, whereas user response contribution has no influence. Idea presentation characteristics have an inverted U-curve relationship with idea adoption. Community absorptive capacity has a moderate effect on the curvilinear relationship between idea description length and idea adoption.


Wang, N., Tiberius, V., Chen, X., Brem, A., & Yu, F. (2020). Idea selection and adoption by users – a process model in an online innovation community, Technology Analysis & Strategic Management, doi:10.1080/09537325.2020.1863055.