基于复杂系统的云南咖啡产业链脆弱性测度与影响因素分析

Measurement of Vulnerability and Analysis of Influencing Factors in the Coffee Industry Chain in Yunnan Based on Complex Systems

  • 摘要:
    目的/意义 全球多重压力加剧致使咖啡产业链脆弱性问题凸显,开展云南省咖啡产业脆弱性水平评估及成因分析,能够为强化产业韧性、保障区域经济安全提供科学依据。
    方法/过程 基于复杂系统理论构建“暴露度—敏感性—适应能力”三维框架,采用2019—2024年云南省7个主产州市面板数据,综合运用熵权法、综合指数法、因子分析与逐步回归进行测度与归因。
    结果/结论 结果显示,云南省咖啡产业链整体脆弱性较高,空间上呈“西高东低、边强中弱”格局;因子分析提取出产业规模与效益、成本市场敏感性、组织化与抗风险能力、灾害暴露度4个主因子;回归分析识别出单位生产成本、国际市场依存度和接待培训与研学情况为核心影响因素。据此,从韧性治理、空间优化、组织化提升与产业转型等方面提出系统性对策建议。

     

    Abstract:
    Objective/Meaning  The intensification of global multiple pressures has led to the vulnerability of the coffee industry chain. The assessment and cause analysis of the vulnerability level of the coffee industry in Yunnan Province can provide a scientific basis for strengthening the industrial resilience and ensuring the regional economic security.
    Methods/Procedures  Based on the complex system theory, a three-dimensional framework of “exposure-sensitivity-adaptability” was constructed. By using the panel data of 7 major coffee-producing prefectures and cities in Yunnan Province from 2019 to 2024, the entropy weight method, comprehensive index method, factor analysis and stepwise regression were adopted for the measurement and attribution analysis.
    Results/Conclusions  The results showed that the overall vulnerability of the coffee industry chain in Yunnan Province was relatively high, and the spatial pattern was “higher in the west and lower in the east, stronger in border areas and weaker in central regions”. Four principal factors of industrial scale and benefit, cost market sensitivity, organizational and risk resilience capacity, and disaster exposure were extracted by factor analysis. The regression analysis identified the unit production costs, dependence on the international market, and the status of training reception and research leaning as the core influencing factors. Accordingly, the systematic countermeasures were put forward from the aspects of resilience governance, spatial optimization, organizational improvement, and industrial transformation.

     

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