Evolution Decision Drivers and Green Innovation Performance for Collaborative Innovation Center of Ecological Building Materials and Environmental Protection Equipment in Jiangsu Province of China

摘要

Faced with the bottlenecks and shortcomings brought about by the resource and environmental issues regarding the sustainable development of the economy and society, green innovation has become an important symbol to measure the sustainable competitive advantage of a country and a region. As an important carrier of green innovation, the evolution process of the collaborative innovation network and its green innovation performance are affected by many factors. Therefore, this paper refines the influencing factors of the formation and evolution of collaborative innovation networks and the evaluation indicators of the green innovation performance by literature analysis. According to the characteristics of each evolutionary influence factor, the relationship governance mechanism, relationship strength, and dominant role are defined as decision factors. The rest are defined as drivers. Then, the Analytic Network Process (ANP) is used to empirically analyze the interaction between network evolution decision, driving factors, and green innovation performance, and the interaction relationship model of decision factors, driving factors, and green innovation performance is obtained. The qualitative simulation algorithm based on qualitative simulation (QSIM) basic theory is used to simulate the evolution of a collaborative innovation network, and find the optimal decision to make the green innovation performance reach its relatively high point. Finally, this paper considers the Collaborative Innovation Center of Ecological Building Materials and Environmental Protection Equipment in Jiangsu Province of China as the research object, focusing on its initial stage of growth and maturity. Combining the theory of QSIM with the actual simulation, according to the different development stages of the Collaborative Innovation Center, this paper provides decisions that can promote the rapid improvement of green innovation performance in three aspects: relationship governance mechanism, relationship strength, and core leadership.