Covid 19 vaccine order allocation: an optimization model with substitution

PurposeThis paper focuses on multi-objective order allocation with product substitution for the vaccine supply chain under uncertainty.Design/methodology/approachThe weighted-sum minimization approach is used to find a compromised solution between three objectives of minimizing inefficiently vaccinated people, postponed vaccinations, and purchasing costs. A mixed-integer formulation with substitution quantities is proposed, subject to capacity and demand constraints. The substitution ratios between vaccines are assumed to be exogenous. Besides, uncertainty in supplier reliability is formulated using optimistic, most likely, and pessimistic scenarios in the proposed optimization model.FindingsCovid-19 vaccine supply chain process is studied for one government and three vaccine suppliers as an illustrative example. The results provide essential insights for the governments to have proper vaccine allocation and support governments to manage the Covid-19 pandemic.Originality/valueThis paper considers the minimization of postponement in vaccination plans and inefficient vaccination and purchasing costs for order allocation among different vaccine types. To the best of the authors' knowledge, there is no study in the literature on order allocation of vaccine types with substitution. The analytical hierarchy process structure of the Covid-19 pandemic also contributes to the literature.

Reimagining global value chains in the face of extreme events and contexts: Recent insights and future research opportunities

Over the last decades, businesses worldwide have witnessed the rise of global value chains (GVCs) as they and their competitors have been able to fine-slice their distinct value-creating activities. The emergence of GVCs has been accompanied by tremendous opportunities and challenges. In this vein, the COVID-19 pandemic exposed the significant vulnerabilities of interconnected and interdependent GVCs. Our special issue and this editorial seek to better understand how GVCs can be reimagined in the face of extreme events and contexts, drawing on insights provided by the COVID-19 pandemic. In so doing, this Special Issue advances knowledge of the dynamic nature of GVCs and changes embedded in the design, structure, and management of GVCs in response to extreme events and contexts. As an introductory background, in this editorial, we summarize GVCs, explain recent developments in GVCs in the aftermath of the COVID-19 pandemic, and highlight the relevance of data analytics GVCs in view of the need for reimagining GVCs amidst extreme events and contexts. Moreover, we distill and synthesize the research this Special Issue encompasses and conclude by proposing new research directions, especially within the three major areas of GVC design and structure, data analytics and GVCs, and environmental and social sustainability of GVCs.