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| The Population Symbiosis and Evolution Mechanism of Open Innovation Ecosystem of Firms |
| Xie Xuemei1,Han Yuhang 1,Dai Mengxin2 |
| (1.School of Economics and Management, Tongji University, Shanghai 200092, China;2. School of Management, Shanghai University, Shanghai 200444, China) |
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Abstract Research on the innovation ecosystem has become a hot topic in academia. Existing literature mainly focuses on innovation ecology or open innovation, but relatively few studies combine the two topics and explore their evolution mechanism. Furthermore, most of the literature conducts qualitative analysis on the evolution of innovation ecosystem from the theoretical perspective, while the evolution mechanism of open innovation ecosystem remain under researched. To take one step toward addressing this gap in prior research, this study brings a new perspective on the mechanism of the open innovation ecosystem by using the simulation approach.#br#Following the theory of population ecology and the prior research on open innovation at home and abroad, this study analyzes the evolution mechanism of firms' open innovation ecosystem by constructing an evolution model of the open innovation ecosystem. According to population ecology, this study uses four order parameters to measure the evolution mechanism of the open innovation ecosystem, including eco-network size, eco-network density, eco-network clustering coefficient, and ecological niche. By using MATLAB simulation, this study adopts the BA model with the scale-free network to construct the evolution mechanisms inter-period. Moreover, each period is required to go through 90 cycles of evolution. To reduce the fluctuation and random error, this study takes the average value of the same group of parameters repeated 10 times as the final simulation result. The results of visual simulation show the process that the four parameters evolve from generation to development.#br#The findings show that the evolution process of firms’ open innovation ecosystem includes three periods: viz., the start-up period, the growth period, and the mature period. First, there are genetic behaviors among innovation members and commensalism relationships between populations in the open innovation ecosystem. More specifically, great innovation genes (e.g., knowledge, resources, and technology) of the core members constantly spill out and are accepted by other members through imitation learning. Second, there are variation behaviors among the innovation members and symbiotic relationships between the populations in the open innovation ecosystem so as to acquire new resources, knowledge, and technologies by breaking old conventions. Third, according to genetic and variation behaviors, each innovation member will select innovative resources such as new ideas, new technologies, and new models generated in the process of variation. In other words, there are mutualistic symbiosis relationships between populations. Moreover, the findings reveal that the four order parameters of evolution show the following trends: the scale of the ecological network shows a gradual upward trend in three stages and reaches its maximum in the mature period; the density of the ecological network is in a slow-growing “S” trend in the three stages; the average clustering coefficient of the ecological network grows slowly during both the start-up and the mature period, and grow rapidly during the growth period; while core enterprises occupy the dominant ecological niche in all three stages, and reach the highest in the mature period.#br#In addition, this study examines the evolution mechanism of the open innovation ecosystem by establishing a simulation model to analyze the variation of parameters, thus contributing to the literature on the evolution of the open innovation ecosystem.It divides the development of the open innovation ecosystem into three different periods (the start-up period, the growth period, and the mature period), and analyze the evolution behaviors of ecosystem members, the relationships between members, as well as the characteristics of the innovation ecosystem. Hence, the simulation findings shed light on this complex issue about evolution mechanisms and expand the boundary of open innovation ecosystem research. The results also have significance for policymakers and enterprises to promote a more innovative environment in practice. On the one hand, the government should promote open innovation ecosystem by adjusting the industrial structure and distribution, and it should establish new institutions of cross-boundary innovative products and services, encourage new models of open innovation (including universities, research institutes, and enterprises), and improve the new business environment. On the other hand, enterprises need to actively integrate into the open innovation ecosystem by increasing their innovation investment and thus maintain exchanges of knowledge, resources, and technologies with the other members and explore diversified modes of cooperation in the ecosystem.#br#
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Received: 23 June 2021
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