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A multi-attribute supply chain network resilience assessment framework based on SNA-inspired indicators

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A Correction to this article was published on 22 July 2021

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Abstract

This study proposes a supply chain resilience assessment framework at the network (i.e. structural) level based on quantifying supply chain networks’ structural factors and their relationships to different resilience strategies, by using a hybrid DEMATEL–ANP approach. DEMATEL is used to quantify interdependencies between the structural resilience factors, and between the resilience strategies. ANP is then used to quantify the outer-dependencies among these elements and to construct the limit super-matrix from which the global weights of all the decision network’s elements are estimated. To create the structural resilience factors, different network factors are selected and adopted from the social network analysis and supply chain resilience literatures. A case study is then performed to assess the performance of the proposed approach and to derive important observations to support future decision making. According to the results, the proposed approach can suitably measure the resilience performance of a supply chain network and help decision makers plan for more effective resilience improvement actions.

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Fig. 1
Fig. 2

(adopted from Kim et al. 2011)

Fig. 3

(adopted from Kim et al. 2011)

Fig. 4

(adopted from Kim et al. 2011)

Fig. 5

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Notes

  1. Number of fundamental circuits in the network \((\mu = e - \nu + G)\), where e = number of links in the graph, v = number of nodes in the graph, and G = number of sub-graphs in the network).

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Authors and Affiliations

  1. School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

    Iman Kazemian & S. Ali Torabi

  2. Department of Business Information Technology, Virginia Tech, Blacksburg, VA, USA

    Christopher W. Zobel

  3. Department of Information Technology and Decision Sciences, Old Dominion University, Norfolk, VA, USA

    Yuhong Li

  4. Information Technology and Operations Management, Florida Atlantic University, Boca Raton, FL, USA

    Milad Baghersad

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  1. Iman Kazemian
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  2. S. Ali Torabi
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Correspondence to Christopher W. Zobel.

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The article was revised as the Figure 1 was erroneously published in the original publication. This has now been corrected.

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Kazemian, I., Torabi, S.A., Zobel, C.W. et al. A multi-attribute supply chain network resilience assessment framework based on SNA-inspired indicators. Oper Res Int J 22, 1853–1883 (2022). https://doi.org/10.1007/s12351-021-00644-3

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