Bio-innovation-based economic business model construction and innovation practice driven by green logistics

Abstract

Driven by the global carbon neutrality target, the synergistic development of bio-innovation technology and green logistics has become the core path to reconfigure the supply chain system. Aiming at the problems of inefficient technology transformation and system coupling barriers, the study establishes a cross-scale assessment model, integrates entropy weight-TOPSIS algorithm and spatial Durbin model, and systematically analyses the data of 12 core logistics hubs around the world from 2014 to 2024. The empirical evidence shows that: the technology golden triangle consisting of Rotterdam-Singapore-Shanghai has a radiation radius of 800km, which increases the regional smart warehousing coverage by 23%; the enzyme catalytic stability barrier is 3.4 times higher in the hot and humid region (Mumbai) compared to the temperate zone (Rotterdam), and each 10% increase in humidity leads to a 17% increase in the rate of enzyme activity decay; the heterogeneity of the smart device protocols leads to the delay in the Chicago Hub's AGV task assignment of up to 4.7 seconds/trip, with a 37% loss in warehouse efficiency. The research reveals 23 key technical bottlenecks such as biodiesel cold start power decay (-20℃ environment decreased by 41%), DNA tag recognition conflict (Sao Paulo missed reading rate of 19%), etc., and puts forward 6 types of optimisation paths, such as edge computing node deployment and conflict-resistant RFID tag customisation. The results provide engineering-level parameter benchmarks for the iteration of intelligent logistics systems, support the revision of ISO/TC297 bio-logistics standards, and guide the optimisation of enterprise technology portfolios, which are expected to reduce the operating costs of low-carbon supply chains by 18%-27%.