Performance Measurement in Supply Chains During Disruptions: Lessons from COVID-19 Pandemic


Submission Portal Opens : 1st December 2021

Author Deadline : 23rd March 2022



The COVID-19 outbreak has threatened and caused unprecedented disruptions to supply chains showing the supply chain management inability to deal with Black Swan events. The unexpected event like COVID-19 has deeply impacted the world in terms of health systems as well as the business environment. Supply chains have been challenged to avoid imminent disruptions on their upstream and downstream flows. Both practitioners and researchers have engaged in discussions to exchange knowledge and explore strategies to enhance the robustness and resilience of supply chains to minimise disruptions when subjected to events like that. According to Kumar, Basu and Avittathur (2017), unprecedented supply chain disruptions are low frequency-high impact events that result in the severance of one or more nodes of the supply chain leading to the unavailability of services or goods. Supply chain disruptions represent an opportunity to learn from its effects (Bode et al., 2011) and learning from the COVID-19 event can improve future decision-making in disruption situations (Van Hoek, 2020). That is relevant because the disruption events cause a significant impact in both financial and operational performance (Macdonald and Corsi, 2013). The challenge is to improve or design new Performance Measurement Systems (PMS) to provide warnings regarding the risks of disruptions for better support the decision-making process during situations such as COVID-19 pandemic. Furthermore, the PMS should also provide the impacts of decision-making to managers during the unpredictable events. 

Performance measurement systems provide meaningful information about past actions to decision makers to help them to take informed decisions regarding the future performance (Neely, Gregory and Plats, 1995; Lebas and Euske, 2002; Rouse and Putterill, 2003). Furthermore, a supply chain PMS is “a set of metrics used to quantify the efficiency and effectiveness of supply chain processes and relationships, spanning multiple organizational functions and multiple firms and enabling SC orchestration” (Maestrini et al., 2017). Besides, the supply chain PMS encompasses both the internal and the external supply chain that includes the immediate supply chain (customers and first-tier suppliers) and other supply chain tiers (the entire supply chain) (Maestrini et al., 2017). Considering the environmental transformation due to the pandemic occurrence, some authors argue the importance of adapting PMS according to the environmental dynamics and changes of the business environment (Bititci Turner and Begemann, 2000, Kennerley and Neely, 2003). Yet, in the supply chain context, some authors also point out that Performance Measurement - PM must be adapted according to the organizational context and stakeholders’ requirements as well as to the dynamic of the environment where the supply chain is inserted (Cuthbertson and Piotrowicz, 2011, Mishra et al., 2018). Hence, it becomes essential to understand the Performance Measurement aspects in the face of emergency situations such as the COVID-19. 

Since the seminal article by Benita Beamon proposing new performance measures for evaluating supply chain performance, the literature has evolved. Many authors proposed many frameworks changing the focus from performance measures to PMS (e.g. Van Hoek, 1998, Beamon, 1999, Holmberg, 2000, Brewer and Speh, 2000, Gunasekaran, Patel and Tirtiroglu, 2001, Chan and Qi, 2003, Park, Lee and Yoo, 2005, Bhagwat and Sharma, 2007, Reefke and Trocchi, 2013, Beske-Janssen, Johnson and Schaltegger, 2015, Liang, 2015, Laihonen and Pekkola, 2016, Dweekat, Hwang and Park, 2017, Nouri, Nikabadi and Olfat, 2019). More recently, following the context of the Fourth Industrial Revolution, Frederico et al. (2020) proposed a performance measurement framework for Supply Chain 4.0.  

Although some proposals in the literature focus on risk dimensions and disruption management on supply chains (e.g., Kleindorfer and Saad, 2005, Macdonald and Corsi, 2013, Durach, Glasen and Straube, 2017), a relevant gap for a predictive PMS remains in the face of the COVID-19 occurrence when supply chains have been challenged to keep the continuity of their upstream and downstream flows. 

Expected Contributions 

Considering the huge impact of the COVID-19 outbreak on supply chains, significant lesson learned and the opportunity to better prepare organisations for the post-pandemic period, this SI aims to identify papers that bring relevant theoretical and practical contributions in terms of deeply exploring how to effectively measure the supply chains performance in disruption situations. Some suggestions of research themes that may be considered by the authors, but are not limited to, include: 


  • What Performance Measurement Systems (PMSs) can be used to evaluate the supply chain performance during unexpected events 

  • What performance measures should be considered to measure supply chains during emergency situations 

  • How to effectively use the supply chain performance measurement during emergency situations 

  • How to effectively measure the contingency strategies in supply chains amid the occurrence of emergency risks 

  • How performance measurement contributes to the success of supply chain responses and relief amid pandemic situations 

  • What is the contribution of Industry 4.0 disruptive technologies (e.g., Big Data Analytics, Cloud Computing, etc.) to the performance measurement of supply chains during Black Swan events 

  • How to measure resilience to better prepare supply chains before unexpected situations occur and to recovery immediately 

  • How to measure the maturity of supply chain’s risk management on emergency events 

  • How PMSs can be effectively and rapidly deployed as an initial strategy to counter significant disruption in supply chains due to emergency events  


For this SI, both empirical (e.g., surveys, case studies) and theoretical (e.g., conceptual developments, literature reviews) contributions are most welcome. Papers must clearly show the link of the proposal with disruption/emergency situations such as COVID-19 pandemic.  Should you have any query regarding this special issue please do not hesitate to contact one of the guest editors. 


Submissions must be done considering the deadline aforementioned through ScholarOne System. Authors must follow the guidelines of the International Journal of Quality & Reliability Management. 


Guest Editors 


Prof. Guilherme F. Frederico 

Professor of Operations and Supply Chain Management 

School of Management 

Federal University of Paraná – UFPR 

Curitiba - Brazil 

[email protected] 


Prof. Vikas Kumar 

Professor of Operations and Supply Chain Management 

Bristol Business School 

University of the West of England  

Bristol – UK 

[email protected] 




Prof. Jose Arturo Garza-Reyes 

Professor of Operations and Supply Chain Management 

Centre for Supply Chain Improvement 

University of Derby 

Derby – UK 

[email protected] 


Prof. Roberto A. Martins 

Professor of Operations Management 

Industrial Engineering Department 

Federal University of São Carlos – UFSCar 

São Carlos – Brazil 

[email protected] 


Dr. Anil Kumar 

Senior Lecturer of Operations and Supply Chain Management 

Guildhall School of Business and Law 

London Metropolitan University 

London – UK 

[email protected] 



Beamon, B. (1999) “Measuring Supply Chain Performance”, International Journal of Operations & Production Management, Vol.19 No.3, pp.275-292 

Beske-Janssen, P., Johnson, M.P. and Schaltegger, S. (2015), "20 years of performance measurement in sustainable supply chain management – what has been achieved?", Supply Chain Management: An International Journal, Vol. 20 No. 6, pp. 664-680. 

Bititci, U. S., Turner, T. and Begemann, C. (2000). Dynamics of performance measurement systems. International Journal of Operations & Productions Management, Vol.20 No.6, pp.692-704. 

Bhagwat, R. and Sharma, M. (2007). “Performance measurement of supply chain management: A balanced scorecard approach”, Computers & Industrial Engineering, Vol.53, pp.43-62. 

Brewer, P. and Speh, T. (2000) “Using the Balanced Scorecard to measure supply chain performance”, Journal of Business Logistics, Vol.21 No.1, pp.75-93.  

Bode, C., Wagner, S.M., Petersen, K.J. and Ellram, L.M. (2011). “Understanding responses to supply chain disruptions: insights from information processing and resource dependence perspectives”, Academy of Management Journal, Vol. 54 No.4, pp. 833–856. 

Chan, F.T. and Qi, H.J. (2003) “An innovative performance measurement method for supply chain management”, Supply Chain Management: An International Journal, Vol.8 No.3, pp.209-223. 62"662.;6073.7820628.896  

Cuthbertson, R. and Piotrowicz, W. (2011) “Performance measurement systems in supply chains”, International Journal of Productivity and Performance Management, Vol.60 No.6, pp.583-602. 

Durach, C.F., Glasen, P.C. and Straube, F. (2017), "Disruption causes and disruption management in supply chains with Chinese suppliers: Managing cultural differences", International Journal of Physical Distribution & Logistics Management, Vol. 47 No. 9, pp. 843-863. 

Dweekat, A.J., Hwang, G. and Park, J. (2017), "A supply chain performance measurement approach using the internet of things: Toward more practical SCPMS", Industrial Management & Data Systems, Vol. 117 No. 2, pp. 267-286. 

Frederico, G., Garza-Reyes, J. A., Kumar, A. and Kumar, V. (2020). “Performance Measurement for Supply Chains in the Industry 4.0 Era: A Balanced Scorecard Approach”, International Journal of Productivity and Performance Management, ahead to print, 

Gunasekaran, A.,   Patel, C. and Tirtiroglu, E. (2001). “Performance measures and metrics in a supply chain environment”, International Journal of Operations & Production Management. Vol.21 No.1/2, pp.71-87. 

Holmberg, S. (2000). “A systems perspective on supply chain measurements,” International Journal of Physical Distribution & Logistics Management. Vol.30 No.10, pp.847-868. 

Kennerley, M. and Neely, A. (2003). “Measuring performance in a changing business environment”, International Journal of Operations & Productions Management, Vol.23 No.2, pp.213-229. 

Kleindorfer, P. R and Saad, G.H. (2005) “Managing Disruption Risks in Supply Chains”, Production and Operations Management, Vol.14 No.1, pp.53-68.  

Kumar, M., Basu, P. and Avittathur, B. (2018) “Pricing and sourcing strategies for competing retailers in supply chains under disruption risk”, European Journal of Operational Research, Vol.265 No.2, pp.533-543.  

Laihonen, H. and Pekkola, S. (2016). “Impacts of using a performance measurement system in supply chain management: a case study, International Journal of Production Research, Vol.54 No.18, pp. 5607-5617, 

Lebas, M., and Euske, K. (2002). A conceptual and operational delineation of performance. In Neely, A. (Ed.), Business performance measurement: Theory and practice, pp. 65–79. Cambridge: Cambridge University Press. 

Liang, Y. (2015) Performance measurement of interorganizational information systems in the supply chain, International Journal of Production Research, Vol.53 No.18, pp. 5484-5499, 

Macdonald, J. R. and Corsi, T. M. (2013). “Supply Chain Disruption Management: Severe Events, Recovery, and Performance”, Journal of Business Logistics, Vol.34 No.4, pp. 270-288. 

Maestrini, V., Luzzini, D., Maccarrone, P., Caniato, F. (2017) “Supply chain performance measurement systems: A systematic review and research agenda”, International Journal of Production Economics, Vol.183, p.299-315 

Mishra, D., Gunasekaran, A., Papadopoulos, T. and Dubey, R. (2018). “Supply chain performance”, Benchmarking: An International Journal, Vol.25 No.3, pp. 932-967. 

Neely, A., Gregory, M., and Platts, K. (1995). “Performance measurement system design: a literature review and research agenda”, International Journal of Operations & Production Management, Vol.15 No.4, pp. 80-117 

Nouri, F.A., Nikabadi, M.S. and Olfat, L. (2019). “Developing the framework of sustainable service supply chain balanced scorecard (SSSC BSC)”, International Journal of Productivity and Performance Management, Vol.68 No.1, pp. 148-170. 

Park, J.H., Lee, J.K. and Yoo. J.S. (2005) “A framework for designing the balanced supply chain scorecard”, European Journal of Information Systems, Vol.14 No.4, pp.335-346. 

Reefke, H. and Trocchi, M. (2013) “Balanced scorecard for sustainable supply chains: design and development guidelines”, International Journal of Productivity and Performance Management, Vol.62 No.8, pp.805-826. 

Rouse, P. and Putterill, M. (2003), "An integral framework for performance measurement", Management Decision, Vol. 41 No. 8, pp. 791-805. 

Van Hoek, R.  (1998). “Measuring    the unmeasurable - measuring and improving performance in   the supply   chain”, Supply Chain Management: An International Journal.  Vol.3 No.4, pp.187-192. 

Van Hoek, R.  (2020) “Research opportunities for a more resilient post-COVID-19 supply chain – closing the gap between research findings and industry practice”, International Journal of Operations & Production Management. Vol.40 No.4, pp. 341-355.