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<p>Benign coordinated interactions between agricultural industrialization (AI) and rural infrastructure (RI) help achieve sustainable development goals (SDG). However, current studies fail to explicitly explain their coordinated interactions, making SDG less efficient and effective. To fill the gaps and explore their coupling coordination interactions, we establish a coupling coordination mechanism and an evaluation system to depict their dynamics theoretically. Then, we analyze the development status (D) and coupling coordination status (CCS) temporally and spatially in the case of China with the analytic hierarchy process, information entropy method and the technique for order preference by similarity to an ideal solution (TOPSIS); thirdly, we explore the main influencing factors and propose specific countermeasures based on the factors. We find that (1) AI and RI may not develop concurrently, and 2018 was a watershed year for AI-D as it witnessed apparent fluctuations; (2) better regions in AI-D are dotted while better-performing regions in RI-D are connected; (3) CCS is spatially correlated, and CCS values in different regions vary because of various reasons; (4) “technologicalization” and “mechanization” are critical dimensions to affect RI, while RI is increasingly affecting AI comprehensively. This study contributes to coupling coordination theory in AI and RI, to the coupling coordination practice to achieve SDG, and to enhance sustainability by proposing differentiated countermeasures.</p>

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Achieving sustainable development goals: coupling coordination between agricultural industrialization and rural infrastructure with the case of China

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月25日

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  • Yuqing Geng,
  • Yan Yan,
  • Qinjun Xiang,
  • Naiguang Zhang,
  • Xinlei Yang,
  • Xinying Jiang

摘要

Benign coordinated interactions between agricultural industrialization (AI) and rural infrastructure (RI) help achieve sustainable development goals (SDG). However, current studies fail to explicitly explain their coordinated interactions, making SDG less efficient and effective. To fill the gaps and explore their coupling coordination interactions, we establish a coupling coordination mechanism and an evaluation system to depict their dynamics theoretically. Then, we analyze the development status (D) and coupling coordination status (CCS) temporally and spatially in the case of China with the analytic hierarchy process, information entropy method and the technique for order preference by similarity to an ideal solution (TOPSIS); thirdly, we explore the main influencing factors and propose specific countermeasures based on the factors. We find that (1) AI and RI may not develop concurrently, and 2018 was a watershed year for AI-D as it witnessed apparent fluctuations; (2) better regions in AI-D are dotted while better-performing regions in RI-D are connected; (3) CCS is spatially correlated, and CCS values in different regions vary because of various reasons; (4) “technologicalization” and “mechanization” are critical dimensions to affect RI, while RI is increasingly affecting AI comprehensively. This study contributes to coupling coordination theory in AI and RI, to the coupling coordination practice to achieve SDG, and to enhance sustainability by proposing differentiated countermeasures.