Supply chain resilience and critical dynamic capabilities: a balanced scorecard approach

Elvira Kaneberg et al.

Production & Manufacturing Research2025https://doi.org/10.1080/21693277.2025.2523957article
AJG 1
Weight
0.48

What the paper says

This study explores the critical dynamic capabilities (DC) needed to ensure supply chain resilience during large-scale disruptions, such as those experienced during the COVID-19 pandemic. By utilising the balanced scorecard (BSC) framework, the research connects dynamic capabilities to organisational strategy and key perspectives on financial performance, processes, growth, and learning. Additionally, it considers the customer perspective to meet changes in demand and internal processes, which reveals the importance of operational-level flexibility. Through 24 expert interviews conducted online and in person in Sweden and Finland, the study demonstrates how strategic resources can be transformed into complementary capabilities that enhance supply chain resilience. The findings indicate that developing dynamic capabilities at all levels of the supply chain is a strategic action for achieving supply chain resilience and crucial for managerial action for effectively responding to large-scale disruptions. The research presents a comprehensive approach to building critical dynamic capabilities organised through the BSC framework.

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https://doi.org/https://doi.org/10.1080/21693277.2025.2523957

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@article{elvira2025,
  title        = {{Supply chain resilience and critical dynamic capabilities: a balanced scorecard approach}},
  author       = {Elvira Kaneberg et al.},
  journal      = {Production & Manufacturing Research},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1080/21693277.2025.2523957},
}

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Supply chain resilience and critical dynamic capabilities: a balanced scorecard approach

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Evidence weight

0.48

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.41 × 0.4 = 0.16
M · momentum0.63 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.