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Optimal resource allocation estimation of agricultural sustainable systems based on inverse network DEA

Author

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  • Zhao, Jiqiang
  • Cheng, Lijun
  • Wu, Xianhua

Abstract

Sustainable agricultural systems are crucial for balancing food security and ecological protection. This study develops a two-stage inverse network data envelopment analysis (DEA) model that incorporates shared inputs and undesirable outputs to evaluate and optimize resource allocation in agricultural production and pollution control. Using data from 31 Chinese provinces (2010–2023), the model estimates optimal resource allocation strategies under constant-efficiency and efficiency-improvement scenarios. Results indicate that although system efficiency is generally improving, notable regional disparities remain. Under constant efficiency, achieving a 5 % output increase requires substantial input growth, particularly in pesticides, whereas efficiency improvement reduces overall inputs by an average of 5.84 %, indicating the role of technological progress in resource conservation. The proposed framework represents a dynamic and practical tool for policymakers to design targeted, forward-looking strategies for sustainable agriculture.

Suggested Citation

  • Zhao, Jiqiang & Cheng, Lijun & Wu, Xianhua, 2026. "Optimal resource allocation estimation of agricultural sustainable systems based on inverse network DEA," Socio-Economic Planning Sciences, Elsevier, vol. 104(C).
    • Handle: RePEc:eee:soceps:v:104:y:2026:i:c:s0038012125002599
    DOI: 10.1016/j.seps.2025.102410
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