Unlocking the power of supply chain innovativeness: a meta-analysis of performance drivers across national, industry and firm contexts

Purpose Despite a prevailing yet fragmented consensus on the importance of supply chain innovativeness (SCI), the SCI-performance correlation and causation remain unclear. Our research resolves these contradictions by investigating the multi-dimensional SCI-performance link, incorporating multi-level moderators and the mediating role of non-financial performance in the SCI-financial performance relationship. Design/methodology/approach Drawing on dynamic capabilities theory, resource-based view and contingency theory, this meta-analysis of 45 articles (2009–2025) examines how SCI (overall, marketing-oriented, logistics-oriented and technology-development-oriented) impacts overall and specific performance (financial, operational and innovation). The mediating role of non-financial performance is examined through meta-analytic structural equation modeling (MASEM). We also consider contingent factors at the national (economic development level and innovative capacity), industry (diversity and type) and firm (size) levels. Findings The findings reveal that SCI exerts a positive effect on firm performance. Specifically, all dimensions of SCI are positively correlated, with the strongest association of overall innovativeness. Furthermore, SCI is positively related to all performance dimensions, and non-financial performance positively mediates the link between SCI and financial performance. Multi-level moderators are observed. The SCI-performance relationship is stronger in developing and regions with low innovative capacity. It is also more pronounced in single-industry settings and among small- and medium-sized enterprises. Although the relationship appears slightly stronger in manufacturing than in services, the sector difference is not statistically significant. Originality/value The multi-dimensional, multi-level framework proposed in this study offers a novel perspective for resolving existing theoretical conflicts and provides deeper insights into the performance influence mechanisms of SCI.