Supply chain learning and performance: a meta-analysis

Abstract

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.

Citation

Chen, L., Jiang, M., Li, T., Jia, F. and Lim, M.K. (2023), "Supply chain learning and performance: a meta-analysis", International Journal of Operations & Production Management, Vol. 43 No. 8, pp. 1195-1225. https://doi.org/10.1108/IJOPM-05-2022-0289