Supply chain learning and performance: a meta-analysis

Lujie Chen, Mengqi Jiang, Taiyu Li, Fu Jia*, Ming K. Lim

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

7 Citations (Scopus)


Purpose: This paper aims to provide a comprehensive understanding of the supply chain learning (SCL)–performance relationship based on the existing empirical evidence. Design/methodology/approach: We sampled 54 empirical studies on the SCL–performance relationship. We proposed a conceptual research framework and adopted a meta-analytical approach to analyse the SCL–performance relationship. Findings: The results of the meta-analysis confirm the positive effects of SCL on the performance of both firms and supply chains. In addition, building on the knowledge-based view, we found that learning from customers has a stronger positive effect on performance than does learning from suppliers, while joint learning has a stronger positive effect on performance than does absorptive learning. Business knowledge had a greater effect on performance than did general knowledge, process knowledge or technical knowledge, while explicit knowledge had a stronger effect than tacit knowledge. Moreover, the SCL–performance relationship is moderated by performance measure and industry type but not by regional economic development, highlighting the broad applicability of SCL. Originality/value: This study is the first meta-analysis on the SCL–performance relationship. It differentiates between learning from customers and learning from suppliers, examines a more comprehensive list of performance measures and tests five moderators to the main effect, significantly contributing to the SCL literature.

Original languageEnglish
Pages (from-to)1195-1225
Number of pages31
JournalInternational Journal of Operations and Production Management
Issue number8
Publication statusPublished - 8 Aug 2023


  • Firm performance
  • Meta-analysis
  • Supply chain learning
  • Supply chain performance


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