| Title | How to Improve Green Innovation Performance: A Conditional Process Analysis |
|---|---|
| ID_Doc | 34996 |
| Authors | Wang, N; Zhang, JS; Zhang, XE; Wang, W |
| Title | How to Improve Green Innovation Performance: A Conditional Process Analysis |
| Year | 2022 |
| Published | Sustainability, 14, 5 |
| Abstract | Green innovation strategy (GIS) is an appropriate choice for most enterprises to deal with environmental problems. Organizational green learning (OGL) enables enterprises to obtain more updated environmental knowledge and promote green innovation performance (GIP). It is unclear whether adopting green innovation strategy is inevitably beneficial to green product innovation and green process innovation, and the studies in this area are still incomplete. According to the Natural Resource-Based View and Knowledge-Based View, this study advances a conditional processmodel to understand how green innovation strategy impacts green innovation performance through organizational green learning in a context of green technological turbulence (GTT). We conducted an empirical study with a probabilistic sample of 316 innovative enterprises using the partial least squares and regression analysis in order to verify the research framework. The results show a positive relationship between green innovation strategy and green innovation performance, organizational green learning played a partial mediating effect, and green technology turbulence significantly moderated the relationship between organizational green learning and green innovation performance. The impact of organizational green learning on green innovation performance is greater when green technology turbulence is higher than when it is low. These findings extend the green innovation performance research and practice. |
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