Abstract:    Based on absorptive capability theory, by matching the activity process of enterprises′ exploratory innovation (knowledge acquisition, knowledge assimilation, knowledge transformation and knowledge creation) with knowledge relationship characteristics between enterprises and their collaboration partners, this paper investigates the impact of knowledge similarity between enterprises and their collaboration partners on enterprises′ exploratory innovation performance, and the moderating effect of tie strength between enterprises and their collaboration partners, intra-organizational collaboration network cohesion and network distance. And then, taking global enterprises in electric vehicle from 2005 to 2015 as research samples, the empirical test is conducted by Poisson Quasi Maximum Likelihood (PQML) regression model to test hypothesis.The results show that, knowledge similarity between enterprises and their partners has an inverted U-shaped relationship with exploratory innovation performance. As the level of knowledge similarity increases from slight to moderate, enterprises′ exploratory innovation performance increases; as the level of knowledge similarity increases from moderate to great, enterprises′ exploratory innovation performance declines. This indicates that increased knowledge similarity benefits for enterprises to get heterogeneous knowledge, which prevents enterprises′ exploratory innovation performance; when the knowledge similarity exceeds critical value, enterprises acquire few heterogeneous knowledge, and then prevent enterprises′ exploratory innovation performance. Thus, an appropriate level of knowledge similarity between enterprises and partners is most beneficial to exploratory innovation performance. Enterprises should choose enterprises that have certain similarities with their own knowledge structure but some differences as collaboration partners, so that they can acquire heterogeneous knowledge on the basis of effective communication. Furthermore, with tie strength between enterprises and their collaboration partners increasing, the inverted U-shape between knowledge similarity and exploratory innovation performance are steeper. This indicates that when knowledge similarity between enterprises and partners is at a low or moderate level, higher tie strength can ensure the effective identification of heterogeneous knowledge acquired from partners, thus promoting the positive influence between knowledge similarity and enterprises′ exploratory innovation performance. Therefore, enterprises should strengthen exchanges and trust with existing partners. Through close communication and the establishment of trusting relationship, enterprises can effectively absorb the external heterogeneity knowledge. On the other hand, when knowledge similarity is too high, high relationship strength will increase the cost of network maintenance and coordination, thus intensifying the negative impact between knowledge similarity and enterprises′ exploratory innovation performance.With network cohesion increasing, the inverted U-shape between knowledge similarity and exploratory innovation performance are flatter. This indicates that when enterprises have low network cohesion, the positive effect of knowledge similarity on enterprises′ exploratory innovation performance becomes stronger, which is more conducive for enterprises to transform heterogeneous knowledge to produce exploratory innovation performance. Therefore, when knowledge similarity between enterprises and partners is at a low or moderate level, the enterprises should reduce the close collaboration relationship among members within the organization. By building a loose intra-organizational collaboration network structure, the enterprise can promote the effective transformation of external heterogeneous knowledge. With network distance increasing, the inverted U-shaped relationship has no change. Based on the above findings, compared with intra-organizational collaboration network cohesion, intra-organizational collaboration network distance does not affect the transformation of collaboration partners′ heterogeneous knowledge.

Key words: dyadic collaboration relationship, knowledge similarity, tie strength, network cohesion, network distance, exploratory innovation