Achieving supply chain resilience: market orientation vs technological orientation
Purpose Disruptive events underscore the importance of building supply chain resilience (SCR). While existing studies have explored the impact of various strategic orientations, particularly market orientation (MO) and technological orientation (TO), their interaction remains underexplored. This study, grounded in matching theory and dynamic capabilities theory, examines how different configurations of MO and TO (alignment and misalignment) influence SCR, with artificial intelligence (AI) acting as a moderating factor. Design/methodology/approach This study uses a quantitative approach based on data from 250 Chinese firms. Polynomial regression and response surface analysis are employed to examine the relationships between MO, TO, their alignment and SCR. AI’s moderating role is also assessed in the context of SCR. Findings This study finds that MO–TO alignment significantly enhances SCR, with a “high MO–high TO” configuration yielding the strongest resilience. Misaligned configurations, especially those favoring MO over TO, negatively impact SCR, although to a lesser degree. Furthermore, AI amplifies the positive effect of MO-TO alignment on SCR by enhancing data integration and real-time decision-making capabilities. Originality/value While existing research has focused on the independent effects of MO and TO, this study adopts a matching perspective to explore how different MO-TO configurations influence SCR. This research not only enriches the understanding of SCR antecedents but also provides new strategic insights for firms to adapt to disruptive events. Additionally, it highlights AI’s moderating role in enhancing SCR through MO-TO alignment, underscoring the importance of AI adoption in today’s dynamic environment.
Authors
- Fanchen Kong (ORCID: https://orcid.org/0009-0003-1022-4390)
- Liubao Du
Institutions
- Beijing Technology and Business University (CN)
- China Agricultural University (CN)
Publication Details
- Journal
- Industrial Management & Data Systems
- Published
- 2025-05-20
- DOI
- https://doi.org/10.1108/imds-01-2025-0017
- Citations
- 1
- Primary Topic
- Supply Chain Resilience and Risk Management
- Type
- article
- Field-Weighted Citation Impact
- 2.23