The Relationship between Big Data Analytic-Artificial Intelligence and Environmental Performance: A Moderated Mediated Model of Green Supply Chain Collaboration (GSCC) and Top Management Commitment (TMC)

Table 1

Previous studies’ findings associated with the constructs of this study.

Authors	Constructs examined	Findings
Dubey et al. [7]	Big data analytics and artificial intelligence, operational performance, entrepreneurial orientation, and environmental dynamism	The study reported that manufacturing firms that are entrepreneurially oriented have the potential to use digital technologies such as BDA-AI to enhance their decision-making capabilities, which can further promote operational performance. It was also reported that the positive impact of entrepreneurial orientation on operational performance is less pronounced in more dynamic environments
Kitsis and Chen [25]	Stakeholder pressures, green supply chain practices, and top management commitment	The study reported significant empirical support for the relationship between stakeholder pressures and top management commitment. The study further suggested that stakeholder pressure can promote top management’s commitment and efforts to undertake green operations
Benzidia et. al. [6]	Big data analytics and artificial intelligence, green supply chain integration, and hospital environmental performance	The study reported that the use of BDA-AI has a significant positive effect on green supply chain collaboration in the hospital sector. It was suggested that the application of BDA-AI can promote better collaboration between supply chain stakeholders. It was also suggested that the use of BDA-AI systems enable managers to put in place new methods in real-time to enable them to visualize and comprehend knowledge on environmental initiatives
	Big data analytics-artificial intelligence, green supply chain collaboration, top management commitment, and environmental performance	The current study found a significant positive relationship between BDA-AI and EP. Green supply chain collaboration was found to play a mediating role between BDA-AI and EP. Our findings also revealed that the positive impact of BDA-AI on GSCC is further enhanced by the level of top management commitment and that the positive impact of BDA-AI on EP is dampened when the level of top management commitment is low. Our findings provide important practical implications for managers in the manufacturing industry seeking to explore and implement BDA-AI in their environmental efforts. They should intensify TMC to develop efficient green supply chain collaborative efforts that enhance environmental performance