Firms' responses to the COVID-19 pandemic.

The COVID-19 pandemic requires firms to adequately respond. In this study, we first explore in our empirical data how firms responded to the COVID-19 crisis and identify five tactical response types, operational, digitalization, financial, supportive, and organizational responses. Furthermore, our findings indicate that responses vary in scope; Some firms act on their own, while others engage in collaborations. Finally, we find that the response angle is different across firms, as some firms leverage potential and others primarily mitigate risk. Second, we follow an event study design to measure the financial implications of these responses. We find that responses to the COVID-19 pandemic generally entail a positive stock market reaction. Financial and digitalization responses, as well as risk mitigation responses, are consistently evaluated positively. We discuss our findings in context of different theoretical lenses, substantiating the emerging literature on the COVID-19 crisis, and the established literature on crisis response management.

Mapping the Swiss Vaccine Supply Chain.

Objectives: The design of the supply chain determines how effectively any vaccination campaign can be operated. This case study of Switzerland's vaccine supply chain compares its design with public health objectives. It maps the vaccine supply chain in Switzerland as it was set up to handle the first shipments of Covid-19 vaccine in 2021 to enable a more holistic view of supply and demand flows. Recommendations are made to improve emergency logistics of vaccines in the future. Methods: Twenty-six semi-structured interviews with international and Swiss stake-holders were coded and analyzed to arrive at a description of planning and distribution processes. The vaccine supply chain network structure was mapped, linking upstream and downstream flows of material and information. The visualization of nodes and flows was combined with spatial information, including population data. The results are summarized in narrative form to support decision-makers across disciplines. Results: Despite adequate vaccine supply, abundant local endowments and high investment in infrastructure, the 2021 design of Switzerland's vaccine supply chain reduced the potential reach of target populations. The segmentation of catchment populations, collaboration between administrative units and better use of information on geolocation and material flows could have improved the speed and reach of vaccinations during the emergency response phase. Three recommendations are made for supply chain structures to support higher vaccination rates in the future. Conclusions: The visualization identifies design alternatives which could have improved vaccination rates under the prevailing conditions. A supply chain map provides public health officials with a shared view of the vaccine supply chain in order to better match supply with demand. The case study contributes to developed country studies. In order to improve public health outcomes in Switzerland, investments to secure supply, strong national endowments, and excellent infrastructure must be combined with optimized supply chain design.

Convalescent plasma bank facility location-allocation problem for COVID-19.

With convalescent plasma being recognized as an eminent treatment option for COVID-19, this paper addresses the location-allocation problem for convalescent plasma bank facilities. This is a critical topic, since limited supply and overtly increasing cases demand a well-established supply chain. We present a novel plasma supply chain model considering stochastic parameters affecting plasma demand and the unique features of the plasma supply chain. The primary objective is to first determine the optimal location of the plasma banks and to then allocate the plasma collection facilities so as to maintain proper plasma flow within the network. In addition, recognizing the perishable nature of plasma, we integrate a deteriorating rate with the objective that as little plasma as possible is lost. We formulate a robust mixed-integer linear programming (MILP) model by considering two conflicting objective functions, namely the minimization of overall plasma transportation time and total plasma supply chain network cost, with the latter also capturing inventory costs to reduce wastage. We then propose a CPLEX-based optimization approach for solving the MILP functions. The feasibility of our results is validated by a comparison study using the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) and a proposed modified NSGA-III. The application of the proposed model is evaluated by implementing it in a real-world case study within the context of India. The optimized numerical results, together with their sensitivity analysis, provide valuable decision support for policymakers.