Green logistics management and performance: Some empirical evidence from Chinese manufacturing exporters

Research output: Journal article publicationJournal articleAcademic researchpeer-review

279 Citations (Scopus)


The value chain of many business enterprises is increasingly required to demonstrate the profitability of their primary activities, starting from inbound logistics to operations, outbound logistics, marketing sales, and finally to services. The adoption of green logistics management (GLM) presents an opportunity for Chinese manufacturing exporters to competently respond to the escalating expectation of the international community for resources conservation and to achieve environmental performance profitably. This study makes several important contributions to the literature on managing logistics with environmental considerations. First, the authors identify the components of GLM: (i) procedure-based practices, (ii) evaluation-based practices, (iii) partner-based practices, and (iv) general environmental management practices. Second, they relate GLM to environmental and operational performance in a developing country context. Third, they identify the institutional and operational antecedents that prompt the adoption of GLM by export-oriented manufacturing enterprises in China. Fourth, they examine the moderating effect of environmental regulatory pressure on the GLM-performance linkage. The results are based on a survey of manufacturing exporters in China. The commonly held view that economic motivation is related to the adoption of GLM is not supported. However, GLM positively affects both environmental and operational performance, and regulatory pressure enhances the GLM-performance relationship.
Original languageEnglish
Pages (from-to)267-282
Number of pages16
Issue number3
Publication statusPublished - 1 Jun 2012


  • China
  • Environmental protection
  • Firm performance
  • Logistics management
  • Regulatory pressure

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Information Systems and Management

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