Serial Mediation Model Linking Returnee Entrepreneurship Education and Green Returnee Entrepreneurial Behavior: An Analysis of Environmental Improvement

Abstract

With the increasingly negative impact of environmental pollution on human production and life caused by the non-green operation of enterprises, a new generation of returnee entrepreneurs is called upon to take on regional environmental protection and global ecological improvement. This study examined the impact of returnee entrepreneurship education (REE). A conceptual model is constructed based on REE as the core factor of environmental sustainability and uses the occurrence of green entrepreneurial behavior among new university graduates returning to their hometowns as an evaluation basis. Convenience sampling was applied, and the relevant data were collected from 358 new university graduates in Jiangsu Province, China who received REE during their university years. Empirical analysis based on partial least squares structural equation modeling shows that REE evokes a commitment to the environment (CE) and has an indirect significant impact on green returnee entrepreneurial behavior (GREB) through institutional support and intention. However, a CE did not have a significant direct effect. The findings of this study have significant reference value for decision-makers in government departments in developing countries, universities, and many social groups that are actively responding to the United Nations Sustainable Development Initiative.

The Role of AI in Improving Environmental Sustainability: A Focus on Energy Management

“…Once the methodological design of this research was defined, the unit of analysis and the selection of cases were defined. This was based on a theoretical and logical, rather than statistical and random, sampling, trying to choose those cases that could offer a greater opportunity for learning [45]. Accessibility to the information required (although in some cases it have been required to keep some of the data collected confidential), an adequate willingness on the part of the people most directly involved with the management of AI projects, and the implementation of AI-based solutions with at least 1 year of experience in full operation were required conditions.…”

“…Hassan and Trianni [13] argue that technologies such as AI and IoT positively influence the operational performance of energy efficiency measures, generating improvements in Overall Equipment Effectiveness (OEE), productivity, and reduced operating costs. The promotion of sustainable development (SD) globally involves adopting undertakings and production processes focused on environmental sustainability [45].…”