EconPapers    
Economics at your fingertips  
 

Identification and Characterization of Supply Chain Operational Risk Profiles in Manufacturing Companies

Hai Thanh Pham and Chiara Verbano
Additional contact information
Hai Thanh Pham: Department of Management and Engineering, University of Padova, Stradella San Nicola 3, 36100 Vicenza, Italy
Chiara Verbano: Department of Management and Engineering, University of Padova, Stradella San Nicola 3, 36100 Vicenza, Italy

Sustainability, 2022, vol. 14, issue 4, 1-17

Abstract: Research on the interactions between risk, integration, and performance in supply chains (SCs) is increasingly attracting attention of researchers in recent years. Although risk usually has negative effects on performance, limited evidence has been provided to show whether companies differently exposed to operational risk (i.e., high, moderate, or low exposure) also have different levels of integration and operational performance. Therefore, this study aims to identify and characterize different profiles of operational risk (i.e., supply, manufacturing, and demand risks) between manufacturing companies along with considering contextual factors such as company size and industry type. Data are collected from the fourth round of the High Performance Manufacturing Project and subsequently analyzed by cluster analysis and analysis of variance (ANOVA). Three different clusters have been identified: Two clusters are moderately and highly impacted by operational risk, respectively, while the other cluster is almost not impacted by manufacturing risk but highly impacted by supply risk and demand risk. The results also indicate that companies with different profiles of operational risk have different levels of integration and operational performance. An important contribution of the current study is the development of a hypothesized framework of interactions between operational risk, integration, and operational performance to provide opportunities for further research.

Keywords: operational risk; performance; supply chains; integration; cluster analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/4/1996/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/4/1996/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:4:p:1996-:d:746124

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jsusta:v:14:y:2022:i:4:p:1996-:d:746124