| Title | Green innovation ecosystem evolution: Diffusion of positive green innovation game strategies on complex networks |
|---|---|
| ID_Doc | 35382 |
| Authors | Zhang, RJ; Tai, HW; Cao, ZX; Wei, CC; Cheng, KT |
| Title | Green innovation ecosystem evolution: Diffusion of positive green innovation game strategies on complex networks |
| Year | 2024 |
| Published | Journal Of Innovation & Knowledge, 9, 3 |
| Abstract | The essence of the evolution of the green innovation ecosystem is the process by which the positive strategy of green innovation spreads in a complex network. In this study, the "Object-Technology-Environment-Management-Culture (OETMC)" structure paradigm of innovation ecosystems is presented, and a causal analysis framework of green innovation ecosystem evolution based on green innovation behavior strategy, supported by green innovation efficiency and focused on green innovation ecosystems is developed. Based on this framework, the structure of the green innovation ecosystem and the diffusion process of positive green innovation in the network are discussed. The results reveal the following. (1) The complexity of the green innovation ecological network has visibly improved, but numerous blank connections remain. These are the key constraints that hinder structural evolution. (2) The appearance of a large number of long-range connections weakens the constraint of geographical distance but also hinders edge nodes from joining the network. (3) The existence of preference attachment and power law distribution of the green innovation ecological network leads to the incomplete convergence of positive green innovation strategy at any initial strategy ratio. (4) Default cost and pollution tax rate ensure the enthusiasm of green innovation actors to seek innovation cooperation by increasing opportunity costs, thus accelerating the formation and reconstruction of the green innovation ecological network. These conclusions provide a decision-making reference for governments to encourage green innovation subjects to formulate targeted policies. (c) 2024 The Author(s). Published by Elsevier Espa & ntilde;a, S.L.U. on behalf of Journal of Innovation & Knowledge. (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
| https://doi.org/10.1016/j.jik.2024.100500 |
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