Author
Listed:
- Dilshad Sarwar
(Faculty of Computing, Mathematics, Engineering and Natural Sciences (CoMENS), Northeastern University, London E1W 1LP, UK)
Abstract
Global supply chain disruptions, most acutely demonstrated during the COVID-19 pandemic, have exposed fundamental tensions between efficiency-oriented design and the adaptive capacity required for resilience. This paper addresses a critical gap in the existing literature: the absence of an integrative, operationalisable framework that treats sustainability and resilience as mutually reinforcing strategic objectives rather than competing trade-offs. Employing a systematic literature review guided by PRISMA protocols, complemented by comparative analysis of documented organisational responses across multiple sectors and commodity markets, the study identifies four primary pathways through which sustainability investments generate resilience: structural diversification, information and visibility, social capital and trust, and adaptive capabilities. The principal finding is that sustainability practices, particularly those enhancing supply network visibility, structural diversification, and workforce stability, create option value that becomes strategically decisive during periods of disruption. A decision intelligence framework is proposed that translates these insights into three managerial tools: a sustainability–resilience assessment matrix, a disruption scenario analysis tool, and a capability development roadmap. The framework challenges the prevailing trade-off assumption by demonstrating that efficiency, sustainability, and resilience can function as complementary dimensions of supply chain performance. Findings carry particular relevance for commodity-dependent supply chains, where price volatility, trade structure rigidity, and resource concentration constitute persistent sources of systemic disruption. Theoretical contributions include the integration of supply chain resilience theory, sustainable operations management, and decision science under deep uncertainty.
Suggested Citation
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jcommo:v:5:y:2026:i:2:p:10-:d:1936469. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.