Abstract
ABSTRACT Firms increasingly use ideas from online innovation communities to solve problems or to better address customer needs. However, in many cases the number of submitted ideas has exploded, it leads to an information overload that firms hardly can handle considering 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 and the subsequent idea review process as a central route of information processing. In our empirical study with a sample of more than 163,000 ideas collected from the Xiaomi MIUI community, we analyse 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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.