Digital-Intelligent Barriers to Resource Re-extraction in China’s Agrifood Manufacturing
DOI:
https://doi.org/10.71204/2bzhn793Keywords:
Resource Re-extraction Resistance, Circular Economy, Digital Barriers, Agrifood Manufacturing, Industry 4.0Abstract
China’s agrifood manufacturing sector produces millions of tons of organic and packaging waste annually, creating an urgent need for circular production models. Resource re-extraction (RE), the digital-enabled recovery of nutrients and materials from waste streams, offers a pathway toward sustainable value creation. However, its adoption remains limited despite strong policy incentives. Understanding why this resistance persists is critical for advancing the digital-intelligent circular economy agenda. This study addresses that gap by examining how cognitive barriers shape Resource Re-extraction Resistance (RRER), with a focus on identifying which obstacles carry the most weight in an emerging economy context. Drawing on Innovation Resistance Theory (IRT), we surveyed 256 agrifood manufacturers across multiple Chinese provinces and applied partial least squares structural equation modelling (PLS-SEM) to test the hypothesised barrier–resistance relationships. The model was evaluated using reliability, convergent and discriminant validity, and collinearity diagnostics, ensuring robust measurement quality. Structural analysis revealed that risk barriers exert the strongest influence on RRER, followed by image barriers and usage barriers, while tradition and value barriers had no significant effect. These results imply that resistance is driven more by concerns over operational failure, brand reputation, and process complexity than by cultural attachment or perceived return on investment. In response, we propose targeted digital-intelligent solutions such as AI-driven process simulation to mitigate perceived risks, blockchain-enabled traceability to safeguard brand image, and AR/VR-based training to lower complexity in implementation. By linking barrier diagnosis with technology-enabled management strategies, this research advances theoretical applications of IRT in industrial sustainability and provides actionable guidance for accelerating the circular transition in emerging markets.
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