Journal of Decision Systems

Special Issue on Decision-Making Frameworks and Methods for Crisis Management

in a Global Pandemic

SUBMISSION DUE DATE: January 31, 2021



Global pandemics can be considered infrequent events (Lepan, 2020). In the 1900-2020 time period, there were nine pandemics including the Spanish Flu (1918-1919), HIV/AIDS (1981 - present), MERS (2015 - present) and now COVID-19 (2020). These pandemics have had significant impacts on global health, and some of them, including the current COVID-19 pandemic, have drastically modified all human dimensions - health, economic, educational, social, and recreational (Walker et al., 2020; IMF, 2020; Burgess & Sievertsen; Nicola et al., 2020; Liu et al., 2020; Gössling et al., 2020).


Thus, the pressing global COVID-19 pandemic calls for scientific efforts to cope with its consequential negative effects on human health and activities. One way to mitigate some of these impacts is to develop and employ decision systems and analytics to provide data and analysis to support decision making. Descriptive, predictive and prescriptive analytics (Delen & Ram, 2018) together with advanced decision-making processes can provide effective, efficient, and ethical decisional support to core stakeholders and decision makers (Araz, 2013; Mora et al., 2014; Moberg et al., 2018; Rehfuess et al., 2019; Currie et al., 2020; Shearer et al., 2020; Squazzoni et al., 2020).


Consequently, the COVID-19 crisis has revealed that new and updated decisional concepts, frameworks, methods and technologies (Hevner et al., 2004; Arnott & Pervan, 2014) are required to assist decision makers and policymakers in the context of a global pandemic crisis (Ionnadis, 2020; Currie et al., 2020).



The objective of this special issue is to advance decision support methods and decision-making processes to efficiently, effectively, and ethically manage critical decisions on core human dimensions (health, economic, educational, social, and recreational) impacted by global pandemics such as COVID-19. High-quality conceptual and empirical research papers are invited from the international interdisciplinary scientific community interested in helping to devise potential solutions from a decision-making perspective.



Consistently with the overall aim of the Journal of Decision Systems, the following topics are welcome in this special issue (but are not limited to):

  • Theoretical aspects of decision making in a crisis

  • Methods and applications of decision support in a crisis

  • Machine learning to support decision making in a crisis

  • Case studies of decision support in a crisis

  • Decision systems with descriptive analytics (visualization, dashboards, reporting, spatial systems)

  • Decision systems with predictive analytics (data mining, text/web mining, machine learning, soft systems)

  • Decision systems with prescriptive analytics (DSS, MADM, MCDM, KBS, KMS, networking science, optimization, simulation)

  • Collaborative decision-making frameworks, methods, and processes

  • Distributed decision-making frameworks, methods, and processes

  • Ethical decision-making frameworks, methods, and processes

  • Post-pandemic era implications for business decision makers

  • Post-pandemic era implications for policy makers



  • First submission deadline – January 31, 2021
    First editorial decision deadline – March 31, 2021
    Second version submission deadline (conditioned papers) – April 30, 2021
    Definitive editorial decision deadline – May 31, 2021
    Camera-ready paper submission deadline – June 15, 2021






Araz, O. (2013). Integrating complex system dynamics of pandemic influenza with a multi-criteria decision making model for evaluating public health strategies. Journal of Systems Science and Systems Engineering, 22(3), 319-339.


Arnott, D., & Pervan, G. (2014). A Critical Analysis of Decision Support Systems Research Revisited: The Rise of Design Science. Journal of Information Technology, 29(4), 269-293.


Burgess, S., & Sievertsen, H. H. (2020). Schools, skills, and learning: The impact of COVID-19 on education. VoxEu. org, 1. Online document at:


Currie, C. S., Fowler, J. W., Kotiadis, K., Monks, T., Onggo, B. S., Robertson, D. A., & Tako, A. A. (2020). How simulation modelling can help reduce the impact of COVID-19. Journal of Simulation, 1-15.


Delen, D., & Ram, S. (2018). Research challenges and opportunities in business analytics. Journal of Business Analytics, 1(1), 2-12.


Gössling, S., Scott, D., & Hall, C. M. (2020). Pandemics, tourism and global change: a rapid assessment of COVID-19. Journal of Sustainable Tourism, 1-20.


Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science in information systems research. MIS Quarterly, 75-105.

IMF (2020). World Economic Outlook, April 2020 - The Great Lockdown. International Monetary Fund, Washington, D.C.


Ioannidis, J.P. (2020).Coronavirus disease 2019 - the harms of exaggerated information and non-evidence-based measures. European Journal of Clinical Investigation, 50(4), e13222.


LePan, N. (2020). A visual history of pandemics. Document on line at


Liu, P., Zhong, X., & Yu, S. (2020). Striking a balance between science and politics: understanding the risk-based policy-making process during the outbreak of COVID-19 epidemic in China. Journal of Chinese Governance, 1-15.


Luke, D. A., & Stamatakis, K. A. (2012). Systems science methods in public health: dynamics, networks, and agents. Annual Review of Public Health, 33, 357-376.


Moberg, J., Oxman, A. D., Rosenbaum, S., Schünemann, H. J., Guyatt, G., Flottorp, S., ... & Alonso-Coello, P. (2018). The GRADE Evidence to Decision (EtD) framework for health system and public health decisions. Health research policy and systems, 16(1), 45.


Mora, M., Phillips-Wren, G., & Wang, F. (2014). An integrative evaluation framework for determining the value of group decision support systems. Engineering Management Journal, 26(2), 24-38.


Nicola, M., Alsafi, Z., Sohrabi, C., Kerwan, A., Al-Jabir, A., Iosifidis, C., ... & Agha, R. (2020). The socio-economic implications of the coronavirus and COVID-19 pandemic: a review. International Journal of Surgery. Online document at: mc/articles/PMC7162753/


Rehfuess, E. A., Stratil, J. M., Scheel, I. B., Portela, A., Norris, S. L., & Baltussen, R. (2019). The WHO-INTEGRATE evidence to decision framework version 1.0: integrating WHO norms and values and a complexity perspective. BMJ global health, 4(Suppl 1), e000844.


Shearer, F. M., Moss, R., McVernon, J., Ross, J. V., & McCaw, J. M. (2020). Infectious disease pandemic planning and response: Incorporating decision analysis. PLoS Medicine, 17(1).


Squazzoni, F., Polhill, J. G., Edmonds, B., Ahrweiler, P., Antosz, P., Scholz, G., ... & Gilbert, N. (2020). Computational models that matter during a global pandemic outbreak: A call to action. Journal of Artificial Societies and Social Simulation, 23(2).


Walker, P., Whittaker, C., Watson, O., Baguelin, M., Ainslie, K., Bhatia, S., ... & Cucunuba Perez, Z. (2020). Report 12: The global impact of COVID-19 and strategies for mitigation and suppression. Imperial College London. Online document at: