Knowledge interaction is vital in order that interdisciplinary innovation teams (IITs) develop sustainably. This paper aims to reveal the laws of knowledge interaction in IITs from a perspective of knowledge fission and fusion. Herein, the conceptions of knowledge fission to depict the team member’s divergent thinking and knowledge fusion to depict the team member’s convergent thinking based on the concept of social physics are proposed. Furthermore, the Markov process describing knowledge interaction is built. The paper uses a case study and a simulation analysis to explain the process of knowledge interaction. The results show that knowledge fission and knowledge fusion have different influences on the various stages of knowledge interaction. To conclude, the model built describes the complex phenomenon of the knowledge interaction process. It reveals the transformation rules from knowledge fission to knowledge fusion in the process of knowledge interaction in IITs. This study also provides new insight for IITs to maintain team sustainability.

This paper mainly focuses on two questions: (1) Which factors mainly influence knowledge interaction in a sustainable interdisciplinary research team (SIDRT)? and (2) How are knowledge interaction processes structured in a SIDRT? This paper first defines the conception of knowledge interaction in a SIDRT from the complex system perspective. Then the model of key influencing factors in a SIDRT is constructed through grounded theory, including subjects’ attributes, objects’ characteristics, environment, and resources of knowledge interaction. Furthermore, we propose hypotheses and empirically validate our conceptual model. The combination of the two methods can strengthen the research conclusions from different angles. Finally, based on our qualitative and quantitative results, the theoretical and practical implications are discussed.

Based on the analysis of influencing factors of knowledge interaction, a system dynamics model of knowledge interaction in the interdisciplinary team is constructed. And Vensim PLE is used to simulate and test the sensitivity of the model. The results show that as the depth of knowledge interaction increases, the team innovation ability gradually increases. With the interaction frequency increasing, the team's knowledge accumulation and innovation ability will gradually increase. However, when the interaction frequency reaches a certain level, the knowledge accumulation of the team will not increase and the team's innovation ability will decline. This model could validly reflect the process of knowledge interaction in the interdisciplinary team, and provide effective decision support for similar knowledge interaction process. Analysis of the Influencing Factors of Knowledge InteractionKnowledge interaction in the interdisciplinary team is a complex process, which is influenced by such factors as the depth of knowledge interaction, knowledge absorptive capacity, the degree of 988