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To better understand factors that lead to business model innovation (BMI) in organizations, this study argues that inclusive leadership is the primary source that motivates employee engagement in boundary-spanning activities, which fosters BMI by generating and integrating employee knowledge through boundary-spanning exploration.

This paper analyzes the relationships between inclusive leadership, boundary-spanning exploration and BMI to discover how they influence each other. This is achieved by a survey of more than 30 enterprises in Zhejiang Province, China. The survey data are analyzed using SPSS.

Inclusive leaders who display characteristics of openness, accessibility and availability have a positive effect on BMI and boundary-spanning exploration; openness and accessibility have more significant positive effect on BMI and boundary-spanning exploration.

Because this study covers only in Zhejiang Province, in China, the findings may not be easily generalizable to other contexts. Other factors, such as organizational structure and contextual characteristics, could also be added as antecedents in a future investigation. Moreover, the scales could be revised more suitable for China in the future.

The empirical findings can be used as guidelines for firms seeking to take advantage of inclusive leadership and to help firms motivate their employees to engage in boundary-spanning exploration to acquire, generate and integrate knowledge from diverse sources to promote BMI.

This study provides insights that will be of value by adding to the theoretical foundation of our understanding of the antecedents to firms' BMI. This study argues that employees' boundary-spanning exploration is important to BMI as well. Inclusive leadership is crucial to stimulate boundary-spanning exploration by employees. Therefore, how to encourage inclusive leadership in firms is well worth examining.

In the context of open innovation, more and more enterprises are leveraging innovation networks to drive disruptive innovation performance, but there is no consensus on the relationship between network embeddedness and enterprise disruptive innovation performance. This paper aims to systematically explore the relationship between them.

This paper constructs a multi-level network embeddedness model and uses 58 independent studies as samples to explore the relationship between multi-level network embeddedness and enterprise disruptive innovation performance by meta-analysis.

First, network embeddedness at the enterprise and regional levels will promote the improvement of disruptive innovation performance. Although industrial relationship embeddedness will promote the improvement of disruptive innovation performance, its structural embeddedness will bring negative effects. Second, in terms of mediating effect, policy-oriented support will promote the relationship between network embeddedness and disruptive innovation performance at the enterprise and industry levels. Compared with large enterprises, small- and medium-sized enterprises will have more advantages in the performance of multi-level network embedding and disruptive innovation performance. Under the subjective performance measurement method, the promotion effect of multi-level network embedding is more prominent.

This study enriches the theoretical research of network embeddedness and disruptive innovation and provides management enlightenment for the network embeddedness strategy of enterprise disruptive innovation. Limited by data samples and article length, future research can further expand literature samples to test the stability of variable relationships and test the moderating effects of more internal and external factors.

First, it constructs a theoretical analysis model of “point-line-surface” multi-level network embedding and disruptive innovation performance of enterprises and expands the theoretical analysis framework of network embedding and disruptive innovation performance. The second is to explore the influence mechanism of multi-level network embeddedness and enterprise disruptive innovation performance. Third, it deepens the theoretical understanding of the moderating variables of the impact of network embeddedness and enterprise disruptive innovation performance.