How does crowd interaction stimulate knowledge contribution behavior in crowdsourcing innovation communities? The serial mediating effect of absorptive capacity

Purpose Based on social network theory and knowledge management theories, the study aims to investigate the correlation between crowd interaction and knowledge contribution behavior, and how the serial moderating effects of absorptive capacity affect this relationship. Design/methodology/approach To test the research model, this study conducts empirical research on the crowd interaction network of the MIUI community. The negative binomial regression model, suitable for processing discrete data, serves to examine the main effects of crowd interaction, absorptive capacity and knowledge contribution behavior. Findings The findings reveal that, in a crowdsourcing innovation community, crowd interaction has an inverted U-shaped relationship with knowledge innovation behavior and knowledge sharing behavior. Both potential absorptive capacity and realized absorptive capacity play a significant positive role in the knowledge contribution behavior of crowds. Crowd interaction can enhance the absorptive capacity of crowds, which can convert crowd interaction strengths into knowledge contribution behavior in four ways. Research limitations/implications The research is based on the data from the MIUI community, and without the consideration of the quality of the interaction. Moreover, the study only examined the role of micro variables and failed to try to explore the macro variables’ effects. Practical implications The managers should guide the crowds to construct high-quality channels for knowledge acquisition, establish multiple feedback mechanisms and introduce gamification elements to stimulate crowds’ willingness to continue innovation. Social implications The study confirms the role of crowd interaction in stimulating knowledge contribution behavior and the serial mediating effect of absorptive capacity. In addition, the results indicate that the relationship between crowd interaction and knowledge contribution behavior is not always linear. Originality/value The study reveals the “black box” of relationships between crowd interaction and knowledge contribution behavior, enriching the theory of crowdsourcing innovation. It also provides practical guidance for how to better stimulate crowds’ knowledge contribution behavior in crowdsourcing innovation communities.