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Efficiency Measurement of Urban and Rural Logistics Supply Chain System Based on Fuzzy Algorithm.

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Summary
This summary is machine-generated.

China's rapidly growing logistics sector needs efficiency metrics. This study uses data envelopment analysis (DEA) to measure urban and rural supply chain efficiency, finding distribution workforce size is key. Results show average efficiencies of 0.932 (technical) and 0.910 (scale).

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Area of Science:

  • Logistics and Supply Chain Management
  • Operations Research
  • Econometrics

Background:

  • China's logistics industry is experiencing rapid growth, crucial for economic development.
  • Existing methods for measuring logistics supply chain efficiency are limited.
  • Accurate efficiency measurement is needed for urban and rural logistics systems.

Purpose of the Study:

  • To develop and apply a Data Envelopment Analysis (DEA) model for measuring logistics supply chain efficiency in urban and rural China.
  • To identify key factors impacting logistics efficiency.
  • To evaluate the efficiency levels and trends in China's logistics sector.

Main Methods:

  • Established a Data Envelopment Analysis (DEA) model to assess efficiency.
  • Employed composite DEA and linear regression analysis to examine impact factors.
  • Developed a fuzzy algorithm optimization model to address the Logistics Route Planning and Production Distribution (LRPPD) problem.

Main Results:

  • Composite DEA analysis revealed a positive correlation among all indicators, with distribution workforce size having the most significant impact on logistics efficiency.
  • Annual average pure technical efficiency was 0.932, and scale efficiency was 0.910.
  • Empirical results indicated a significant positive correlation in the efficiency changes of the urban and rural logistics industry, with the eastern region showing a lower-middle efficiency level.
  • The fuzzy algorithm demonstrated good optimization performance, high computational efficiency, and strong convergence speed for the LRPPD problem.

Conclusions:

  • The study provides a robust framework for measuring logistics supply chain efficiency using DEA.
  • Distribution workforce size is a critical determinant of logistics efficiency.
  • The developed fuzzy algorithm effectively solves the LRPPD problem, enhancing operational efficiency.