Yu Chen, Weizhong Wang, Guiqin Zhou, Muhammet Deveci, Seifedine Kadry, D’Maris Coffman
The circular economy, open innovation, and artificial intelligence (AI) have become prominent topics in academic, managerial, and policy discussions. Integrating the food supply chain has emerged as a crucial approach to attaining sustainable development within the food industry. Previous research has mainly concentrated on examining the relationships between any two of these three elements within supply chain management. In contrast to these studies, this research systematically analyzes the transformative power of AI-driven open innovation in advancing the circular supply chain in the food sector. To achieve this, we propose a novel interval-valued spherical fuzzy hierarchical structure model to identify the driving factors, construct the cause-and-effect relationships and driving paths, and ascertain the nature of each driving factor. First, an established Technology-Organization-Environment-Data (TOE-D) framework is introduced for the first time to identify the enablers from AI-driven open innovation. Within this framework, we propose the interval-valued spherical fuzzy the Decision-Making Trial and Evaluation Laboratory to express the cause-effect relationships. Then, the Interpretive Structural Modeling with Cross-Impact Matrix Multiplication Applied to Classification is utilized to construct the hierarchical structure with driving paths and classify the enablers. The findings indicate that the enablers can be divided into three layers and four types of influence effects. Our theoretical contribution consists of giving a quantitative framework for systematically understanding the driving force of AI-driven open innovation in adopting the practices of the circular supply chain in the food sector. The findings of this work are expected to be advantageous for relevant stakeholders in implementing effective AI-driven open innovation, thereby enhancing the promotion of the circular supply chain within the food sector.