Abstract
Open innovation communities (OICs) can help enterprises make full use of external knowledge resources from users, but problems such as low user participation and low conversion rate of creative ideas impact the efficiency of OICs. Most studies on this topic employ qualitative or empirical methods from a static perspective, but ignore the effect of interaction between enterprises and users as well as the cumulative effect of time. A discussion on the dynamic evolution process of open innovation is lacking. Based on a review of the literature on OICs, innovation performance, and system dynamics, this study proposes a conceptual model of innovation performance impact, which comprises the knowledge management, governance mechanism, and user behavior subsystems. Xiaomi’s OIC in China was selected as the research object, and relevant data were collected through a web spider. According to the system dynamics modeling method, a causal relationship analysis was carried out on the three aforementioned interrelated subsystems. Then, a stock flow chart with 32 variables was constructed to determine the initial values and calculation equations for each variable. Finally, the model was constructed and verified using Vensim PLE software. The simulation results were as follows. (1) The number of product releases in the Xiaomi OIC was positively correlated with the number of posts, comments, and views. Compared with user interaction behavior (i.e., commenting and viewing), the impact of user innovation behavior (i.e., posting) on enterprise innovation performance (i.e., number of patents) is clearer. Specifically, regarding interaction behavior, the impact of the users’ commenting behavior on innovation performance (i.e., number of product releases) was relatively clearer than that of their viewing behavior. (2) Governance mechanism (i.e., R&D investment and management expense), which comprises technical and organizational mechanisms, positively affected the innovation performance of enterprises. Compared with the organizational mechanism (i.e., management expense), the impact of the technical mechanism (i.e., R&D investment) on the innovation performance was clearer. (3) Governance mechanism helped to increase the number of users in the OIC, and, in turn, affected the user innovation and interaction behavior. (4) The technical mechanism positively affected knowledge application capability, which, in turn, had a positive impact on the innovation performance of enterprises. Based on these findings, management strategies are proposed for the establishment and development of OICs.
Highlights
With the advent of the knowledge economy, enterprises have formed various types of open innovation communities (OICs) to swiftly acquire knowledge resources from external users
First, the number of product releases in the Xiaomi OIC is positively correlated with the number of posts, comments, and views
The number of product releases in the Xiaomi OIC is positively correlated with the number of posts, comments, and views
Summary
With the advent of the knowledge economy, enterprises have formed various types of open innovation communities (OICs) to swiftly acquire knowledge resources from external users. These OICs help companies understand the market requirements, access external market information, collect external knowledge resources, and obtain feedback from users. In OICs, users actively share knowledge resources and create value, which is crucial for improving the companies’ innovation performance. Some creative ideas by OIC users have high innovation value, matching the companies’ open innovation strategy. User innovation and interaction behavior in an OIC generates a wealth of knowledge resources [1,2,3]. A large number of users share creative ideas every day, there are very few ideas that can lead to the creation of innovative products or services
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