In open innovation communities (OIC), people can propose ideas according to their own needs and interact with others. OIC have emerged as a vital resource for firms to obtain users’ wisdom, which in turn stimulates product innovation and enhances competitiveness. The interaction between users in OIC is an important idea generation process. On the basis of the transactive memory system and communication accommodation theory, we propose a research model to depict the influences of interaction characteristics (i.e., specialization, credibility, coordination) between users on the idea generation performance and explore the mediation effect of content diversity. We also investigate whether firm’s feedback strategies (convergence vs. maintenance) moderate the effects of interaction characteristics and idea generation performance. We validate our model with a dataset of 9,794 ideas with 20,482 comments and 10,044 firms’ feedback in the Joint Definition Community hosted by Huawei. Results show that an inverted U-shaped relationship exists between specialization and idea generation performance; credibility and coordination have a positive effect on the idea generation performance. Furthermore, content diversity has a partial mediation effect on the relationship between interaction characteristics and idea generation performance. Convergence feedback strengthen the inverted U-shaped relationship between specialization and idea generation performance and has a significantly positive moderation effect on the impact of credibility and coordination on idea generation performance. These findings provide theoretical support and practical guidance for firms to operate OIC.
Xin, Xiaping; Zhou, Xinxue; and Wang, Tianmei, "How Interaction Characteristics and Content Between Users Influence Idea Generation Performance in Open Innovation Communities" (2021). PACIS 2021 Proceedings. 155.
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