Impact of the resource cost factor <i>ν</i> and the environmental construction cost factor <i>μ</i>.

Impact of the resource cost factor ν and the environmental construction cost factor μ.</p

Optimal return of the support layer.

Exploratory innovation is a pivotal way to seize future opportunities in green manufacturing innovation ecosystems, and exploitative innovation is conducive to expanding existing markets and resources, so it is essential to discuss the balanced incentive strategy of dual innovation for the sustainable development of ecosystems. Based on the hierarchical structure, this paper divides the core subjects in the green manufacturing innovation ecosystem into the application layer, the support layer, and the scientific research layer, constructs the differential game model of the no-incentive scenario, the cost-sharing scenario, and the collaborative scenario, and discusses the incentive strategies of the three types of subjects and the ecosystem in the evolution process of the dual innovation balance. The conclusions are as follows: (1) The level of dual innovation balance effort of the three types of subjects decreases with the increase of resource costs and environmental construction costs and increases with the increase of innovation balance capacity; (2) Cost sharing from the application layer to the support layer and the scientific research layer can enhance the effort level of both, which in turn enhances the optimal benefits for the three types of subjects and the ecosystem as a whole; (3) In the collaborative scenario, the level of effort and total ecosystem benefits of the innovation balance of the three types of subjects are strictly better than in the no incentive scenario, and the Pareto-optimality of the three subjects and the ecosystem will be realized after the coefficients of the distribution of benefits among the three types of subjects are determined. Based on this, this paper puts forward specific suggestions for the optimization of the structural relationship of the innovation body hierarchy, the exploitation of green manufacturing resources, and the macro-planning of the management department.</div

Parameters and values.

Exploratory innovation is a pivotal way to seize future opportunities in green manufacturing innovation ecosystems, and exploitative innovation is conducive to expanding existing markets and resources, so it is essential to discuss the balanced incentive strategy of dual innovation for the sustainable development of ecosystems. Based on the hierarchical structure, this paper divides the core subjects in the green manufacturing innovation ecosystem into the application layer, the support layer, and the scientific research layer, constructs the differential game model of the no-incentive scenario, the cost-sharing scenario, and the collaborative scenario, and discusses the incentive strategies of the three types of subjects and the ecosystem in the evolution process of the dual innovation balance. The conclusions are as follows: (1) The level of dual innovation balance effort of the three types of subjects decreases with the increase of resource costs and environmental construction costs and increases with the increase of innovation balance capacity; (2) Cost sharing from the application layer to the support layer and the scientific research layer can enhance the effort level of both, which in turn enhances the optimal benefits for the three types of subjects and the ecosystem as a whole; (3) In the collaborative scenario, the level of effort and total ecosystem benefits of the innovation balance of the three types of subjects are strictly better than in the no incentive scenario, and the Pareto-optimality of the three subjects and the ecosystem will be realized after the coefficients of the distribution of benefits among the three types of subjects are determined. Based on this, this paper puts forward specific suggestions for the optimization of the structural relationship of the innovation body hierarchy, the exploitation of green manufacturing resources, and the macro-planning of the management department.</div

Logic of dual innovation balance in the green manufacturing innovation ecosystem.

Logic of dual innovation balance in the green manufacturing innovation ecosystem.</p

Optimal returns of the green manufacturing innovation ecosystem.

Optimal returns of the green manufacturing innovation ecosystem.</p

Impact of the innovation balance capacity factor on the support and scientific research layers.

Impact of the innovation balance capacity factor on the support and scientific research layers.</p

Impact of innovation balancing capacity factor on application layer.

Impact of innovation balancing capacity factor on application layer.</p

Model symbols and meanings.

Exploratory innovation is a pivotal way to seize future opportunities in green manufacturing innovation ecosystems, and exploitative innovation is conducive to expanding existing markets and resources, so it is essential to discuss the balanced incentive strategy of dual innovation for the sustainable development of ecosystems. Based on the hierarchical structure, this paper divides the core subjects in the green manufacturing innovation ecosystem into the application layer, the support layer, and the scientific research layer, constructs the differential game model of the no-incentive scenario, the cost-sharing scenario, and the collaborative scenario, and discusses the incentive strategies of the three types of subjects and the ecosystem in the evolution process of the dual innovation balance. The conclusions are as follows: (1) The level of dual innovation balance effort of the three types of subjects decreases with the increase of resource costs and environmental construction costs and increases with the increase of innovation balance capacity; (2) Cost sharing from the application layer to the support layer and the scientific research layer can enhance the effort level of both, which in turn enhances the optimal benefits for the three types of subjects and the ecosystem as a whole; (3) In the collaborative scenario, the level of effort and total ecosystem benefits of the innovation balance of the three types of subjects are strictly better than in the no incentive scenario, and the Pareto-optimality of the three subjects and the ecosystem will be realized after the coefficients of the distribution of benefits among the three types of subjects are determined. Based on this, this paper puts forward specific suggestions for the optimization of the structural relationship of the innovation body hierarchy, the exploitation of green manufacturing resources, and the macro-planning of the management department.</div

Optimal returns of the application layer.

Exploratory innovation is a pivotal way to seize future opportunities in green manufacturing innovation ecosystems, and exploitative innovation is conducive to expanding existing markets and resources, so it is essential to discuss the balanced incentive strategy of dual innovation for the sustainable development of ecosystems. Based on the hierarchical structure, this paper divides the core subjects in the green manufacturing innovation ecosystem into the application layer, the support layer, and the scientific research layer, constructs the differential game model of the no-incentive scenario, the cost-sharing scenario, and the collaborative scenario, and discusses the incentive strategies of the three types of subjects and the ecosystem in the evolution process of the dual innovation balance. The conclusions are as follows: (1) The level of dual innovation balance effort of the three types of subjects decreases with the increase of resource costs and environmental construction costs and increases with the increase of innovation balance capacity; (2) Cost sharing from the application layer to the support layer and the scientific research layer can enhance the effort level of both, which in turn enhances the optimal benefits for the three types of subjects and the ecosystem as a whole; (3) In the collaborative scenario, the level of effort and total ecosystem benefits of the innovation balance of the three types of subjects are strictly better than in the no incentive scenario, and the Pareto-optimality of the three subjects and the ecosystem will be realized after the coefficients of the distribution of benefits among the three types of subjects are determined. Based on this, this paper puts forward specific suggestions for the optimization of the structural relationship of the innovation body hierarchy, the exploitation of green manufacturing resources, and the macro-planning of the management department.</div

Dual innovation balance scenario with three types of subjects.

Dual innovation balance scenario with three types of subjects.</p