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\begin{document}

\title{Role of Collaborative Resource Sharing in Supply Chain Recovery During
Disruptions: A Systematic Literature Review}



\author[1]{Saidi Mustapha }%
\author[2]{Mouhamad Shaker Ali Agha }%
\author[2]{Tariq Masood }%
\affil[1]{University of Strathclyde}%
\affil[2]{Affiliation not available}%


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  \date{May 27, 2024}


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\begin{abstract}
The COVID-19 crisis has attracted attention worldwide to the supply
chain disruptions and resilience. Several supply chain risk management
approaches have been revisited or reapplied such as collaborative
resource sharing. This study aimed to investigate the current academic
state of art and advances in using collaborative resources sharing as a
reactive method to facilitate supply chain recovery in the presence of
disruptive events. More specifically we considered the role of different
collaborative resource sharing strategies that organizations can adopt
to support supply chain functionalities during times of disruption. We
conducted a systematic literature review (SLR) to analyze academic
articles that were published online from 2000 to 2022. In order to
analyze the literature, we adopted a combination of text-mining,
automatic and manual categorization of selected articles, and
exploratory analyses such as cluster analysis and relational indicators.
We also consider the machine learning classification algorithm i.e.
agglomerative hierarchical clustering for the categorization of
clusters. The findings show that, for disruptive risks, collaborative
sharing of labour and material resources are effective for the recovery
of supply chains. More so, labour resources tend to contribute more to
the recovery of supply chains. Whilst information resources and a mix of
information and material resources are highly important in reducing the
impact of COVID-19 disruptive supply chain risk. In conclusion,
collaborating on the three resources, namely labour, material, and
information resources can be an effective post-disruption recovery
strategy for supply chains.%
\end{abstract}%



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