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Review
. 2021 Apr:26:373-410.
doi: 10.1016/j.spc.2020.09.017. Epub 2020 Sep 28.

Sustainable supply chain management towards disruption and organizational ambidexterity: A data driven analysis

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Free PMC article
Review

Sustainable supply chain management towards disruption and organizational ambidexterity: A data driven analysis

Tat-Dat Bui et al. Sustain Prod Consum. 2021 Apr.
Free PMC article

Abstract

Balancing sustainability and disruption of supply chains requires organizational ambidexterity. Sustainable supply chains prioritize efficiency and economies of scale and may not have sufficient redundancy to withstand disruptive events. There is a developing body of literature that attempts to reconcile these two aspects. This study gives a data-driven literature review of sustainable supply chain management trends toward ambidexterity and disruption. The critical review reveals temporal trends and geographic distribution of literature. A hybrid of data-driven analysis approach based on content and bibliometric analyses, fuzzy Delphi method, entropy weight method, and fuzzy decision-making trial and evaluation laboratory is used on 273 keywords and 22 indicators obtained based on the experts' evaluation. The most important indicators are identified as supply chain agility, supply chain coordination, supply chain finance, supply chain flexibility, supply chain resilience, and sustainability. The regions show different tendencies compared with others. Asia and Oceania, Latin America and the Caribbean, and Africa are the regions needs improvement, while Europe and North America show distinct apprehensions on supply chain network design. The main contribution of this review is the identification of the knowledge frontier, which then leads to a discussion of prospects for future studies and practical industry implementation.

Keywords: Ambidexterity; Content analysis; Data driven; Disruption; Entropy weight method; Fuzzy Delphi method; Fuzzy decision-making trial and Evaluation laboratory; Sustainable supply chain management.

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Conflict of interest statement

This study is free of Conflict of interests.

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Image, graphical abstract
Graphical abstract
Fig 1
Fig. 1
Analytical process.
Fig 2
Fig. 2
Causal inter-relationship of indicators among regions.

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