Introduction The development of new quality productivity in agricultural enterprises is of great significance for unleashing the potential of agricultural productivity and achieving the sustainability of the food system. Methods This study takes 286 agricultural listed companies on China’s A-share market from 2013 to 2023 as samples. Based on the quasi-natural experiment of the pilot policy for supply chain innovation and application in cities, it uses A dual machine learning model to investigate the impact of supply chain innovation (SCI) on the new quality productivity (NPRO) of agricultural enterprises and its mechanism of action. Results The research findings are as follows: Firstly, SCI significantly improves the NPRO of agricultural enterprises, and the research conclusion remains unchanged after robustness tests such as resetting the machine learning model and the instrumental variable method. Second, SCI mainly promotes the NPRO of agricultural enterprises through two paths: alleviating financing constraints and enhancing the efficiency of resource allocation. Thirdly, the promoting effect of SCI on the NPRO of agricultural enterprises is more obvious in non-state-owned enterprises, small and medium-sized enterprises, low-marketization regions and highly digitalized enterprises. Fourth, from the perspective of economic consequences, SCI can enhance the value of agricultural enterprises by improving their NPRO. Discussion This study suggests that efforts should be made to strengthen the construction of agricultural supply chain collaboration platforms, establish a long-term mechanism that links green orientation with financing, and unleash the potential of factor allocation brought about by supply chain innovation. The research conclusion provides a new perspective for the development of agricultural enterprises NPRO and also offers ideas for solving the problem of food security.
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Fanhao Wu
Xiang Li
Hailong Yan
SHILAP Revista de lepidopterología
Frontiers in Sustainable Food Systems
Guizhou University of Finance and Economics
IFMR Graduate School of Business
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Wu et al. (Fri,) studied this question.
www.synapsesocial.com/papers/69e7132bcb99343efc98cedd — DOI: https://doi.org/10.3389/fsufs.2026.1802974