Driving policy support for open eco-innovation enterprises in Thailand: A probit regression model

Abstract

Open eco-innovation, which involves collaborative processes to develop environmentally sustainable solutions with diverse stakeholders, heavily relies on collaboration. This study aims to address this research gap in open eco-innovation by (1) examining perceived support and participation in an open innovation program for SMEs, predicting the outcomes of open eco-innovation, and (2) providing a foundation for a targeted public policy program. A sample of 495 SMEs in Thailand was analyzed using multiple probit regressions to understand how different forms of support and participation in open innovation programs affect the probability of open eco-innovation. Findings indicate that SMEs with uncertain internal open innovation programs are more likely to decrease the predicted probability of open eco-innovation. For instance, Thai SMEs investing in R&D and network activities may lack a clear pathway to enhance their eco-innovation capabilities, resulting in reduced R&D alliances and joint ventures. Practically, it is advised that SMEs carefully consider the advantages and disadvantages of open innovation before developing eco-innovation capabilities. Moreover, the study offers empirical evidence on the open innovation activities that influence SMEs' engagement in open eco-innovation. From a policy perspective, policymakers should prioritize creating a supportive environment, such as enhancing green cooperation. The originality of this paper lies in the use of a probit regression model to analyze factors influencing open eco-innovation and a logic model to provide actionable steps for promoting it.