TY - JOUR
T1 - The resilience of on-time delivery to capacity and material shortages
T2 - An empirical investigation in the automotive supply chain
AU - Carvalho, Helena
AU - Naghshineh, Bardia
AU - Govindan, Kannan
AU - Cruz-Machado, Virgílio
N1 - info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00667%2F2020/PT#
info:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FEME-SIS%2F32232%2F2017/PT#
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/9
Y1 - 2022/9
N2 - Supply chains around the globe are susceptible to disturbances that negatively impact their performance. Generally, supply chain disturbances lead to failure modes that impact the ability of the supply chain to deliver the promised goods and services on time. Therefore, companies operating in different supply chains are willing to become resilient to disturbances and their ensuing failure modes to be able to deliver on time and remain competitive. In light of this willingness, this study aims to propose an index that enables companies to assess their resilience of on-time delivery to supply chain failure modes based on the resilience practices they deploy. To this end, drawing on the knowledge derived from case study data analysis and literature, eight propositions and an explanatory framework are put forward that theorize the identified relationships between supply chain disturbances, failure modes, resilience practices, and on-time delivery as the primary indicator for measuring supply chain performance. Next, considering the resilience practices companies tend to deploy, an index capable of assessing the companies’ resilience of on-time delivery to two prevalent supply chain failure modes, namely capacity shortage and material shortage is modelled and tested using a case study in an upstream automotive supply chain in Portugal. The results indicate high resilience levels of on-time delivery to the aforementioned failure modes, mainly due to the high cost of production halt in the automotive industry. Additionally, a set of supply chain capabilities and their related resilience practices and supply chain state variables are identified that can be deployed and controlled to improve supply chain resilience.
AB - Supply chains around the globe are susceptible to disturbances that negatively impact their performance. Generally, supply chain disturbances lead to failure modes that impact the ability of the supply chain to deliver the promised goods and services on time. Therefore, companies operating in different supply chains are willing to become resilient to disturbances and their ensuing failure modes to be able to deliver on time and remain competitive. In light of this willingness, this study aims to propose an index that enables companies to assess their resilience of on-time delivery to supply chain failure modes based on the resilience practices they deploy. To this end, drawing on the knowledge derived from case study data analysis and literature, eight propositions and an explanatory framework are put forward that theorize the identified relationships between supply chain disturbances, failure modes, resilience practices, and on-time delivery as the primary indicator for measuring supply chain performance. Next, considering the resilience practices companies tend to deploy, an index capable of assessing the companies’ resilience of on-time delivery to two prevalent supply chain failure modes, namely capacity shortage and material shortage is modelled and tested using a case study in an upstream automotive supply chain in Portugal. The results indicate high resilience levels of on-time delivery to the aforementioned failure modes, mainly due to the high cost of production halt in the automotive industry. Additionally, a set of supply chain capabilities and their related resilience practices and supply chain state variables are identified that can be deployed and controlled to improve supply chain resilience.
KW - Failure modes
KW - On-time delivery
KW - Resilience index
KW - Resilience practices
KW - Supply chain capabilities
KW - Supply chain disturbances
KW - Supply chain state variables
UR - http://www.scopus.com/inward/record.url?scp=85133898953&partnerID=8YFLogxK
U2 - 10.1016/j.cie.2022.108375
DO - 10.1016/j.cie.2022.108375
M3 - Article
AN - SCOPUS:85133898953
SN - 0360-8352
VL - 171
JO - Computers and Industrial Engineering
JF - Computers and Industrial Engineering
M1 - 108375
ER -