In recent years, the trend of customer demand and personalization has become more and more obvious. The previous innovation model can no longer meet the diversified needs of consumers. Therefore, firms vigorously develop open innovation to promote internal and external innovation (von Hippel, 1988). With the rapid development of AI technology, open innovation communities have more interactions with the users. Organizations continue to rely on their open innovation community to collect innovative ideas from non-professional customers and then integrate them into their new product development process to produce innovative products that are more in line with customer preferences (Bayus, 2013). At present, the research on user design focuses on how to increase user design implementation and the idea popularity (Yang et al., 2022; Zhang et al., 2022). Few studies discussed how to motivate consumers to participate in innovative content output from the source. In addition, academic research on user design is mostly limited to management comments, lacking in-depth empirical research (Franke et al. 2008). Previous studies have proved that the number of leading users in the open innovation community is far less than that of non-leading users (Hofstetter et al., 2018), so it is very necessary to improve the willingness of users to participate in community creative activities. With the vigorous development of the new technology, it is an urgent problem to be solved to encourage users to participate in innovation activities and improve the innovation performance of firms (Chesbrough, 2012). Today, firms pay more and more attention on the implementation of AI technology. With AI and user design as the research background, “AI recommendation” and “willingness to design” as the key variables, and the “S-O-R model” and “Self-determination Theory” as the basis, this paper deeply explores whether AI recommendation can be used as a factor affecting user’s participation in design activities from the perspective of users, focusing on the intermediary role of user’s inspiration, competency and self-expression. It also puts forward that product involvement and aesthetic experience openness (Donghwy and Youn, 2018) are the boundary conditions that affect user’s willingness to participate in design. The results show that user’s willingness to participate in design is higher when providing AI recommedation, and the sense of inspiration, competence and self-expression play a mediating role in it. Furthermore, the results show that when product involvement is high, users are more willing to participate in design. Similarly, users with a high degree of aesthetic experience openness are more willing to participate in design activities. This study enriches the theory of enterprise community management, promote the internal information flow of the open innovation community, and provide theoretical guidance and reference for firms to optimize the new product design process.

• Ruping Liu(Northeastern University)
• Hao Zhang(Northeatern University)