Optimal degree of openness in open innovation: A perspective from knowledge acquisition & knowledge leakage

Abstract Open innovation has become an important mode for firms to improve innovation performance. If the openness is too low, it will reduce the opportunity to acquire external knowledge, while too open will increase the risk of internal knowledge leakage. Therefore, the degree of openness plays a key role in the use of open innovation to improve innovation performance. We use the openness breadth and openness depth to describe the openness of innovation. We conduct an agent-based simulation methodology to study the optimal degree of openness. Our findings show that there are great differences in the optimal degree of openness under different situations. Moreover, as the situation changes, the optimal degree of openness changes regularly. More specifically, the more a firm's knowledge network structure holes, the smaller the optimal openness breadth and the greater the optimal openness depth. The higher a firm's knowledge network centrality, the greater the optimal openness breadth and the smaller the optimal openness depth. The worse the institutional environment, the smaller the optimal openness breadth and openness depth. The fiercer the market competition, the greater the optimal openness breadth and the smaller the optimal openness depth.