Abstract
Coronavirus (COVID-19) is a highly infectious respiratory disease which spread can be effectively curbed by wearing facial masks, especially N95 and surgical masks. In this paper, we develop a stylised game-theoretical model to evaluate the impacts of producing and selling masks on supply chain profits, safety index and consumer and social welfare. Firstly, we find that as the infection probability without protection (IPWP) increases, both the retail price and demand for these masks will increase. When the IPWP is sufficiently low, those consumers who want to purchase masks are more likely to purchase N95 masks, but when the IPWP increases, surgical masks are more popular amongst consumers. Secondly, we develop a safety index that indicates the effectiveness of using masks in preventing respiratory disease infection. This index is especially crucial in cases where the IPWP is moderate; in other words, recommending to wear masks is particularly important when the IPWP is moderate. We also examine the impacts of government involvement in handling the outbreak of respiratory diseases. Providing consumer subsidies and promoting the social mask enterprise can effectively combat respiratory diseases under different conditions. Our results can be used for combating COVID-19 and preparing for future health crisess.
Acknowlegement
We sincerely thank the editor and two reviewers for helpful and constructive comments.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 We focus on surgical and N95 masks and ignore cloth masks and elastomeric respirators because (1) surgical and N95 masks are recommended by WHO and can be easily found in the market (WHO Citation2020; Nierenberg Citation2020), (2) cloth masks cannot prevent wearers from transmitting COVID-19 to others (Grainger Citation2020) and (3) elastomeric respirators are not commonly used in public.
2 Data were collected from a pharmacy store in Munich, Germany in March 2020, during which Germany reached its first peak in COVID-19 cases.
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Notes on contributors
Bin Shen
Bin Shen is an Associate Professor in Glorious Sun School of Business and Management in Donghua University, Shanghai. He is Humboldt Fellow in Germany. His papers have appeared in leading journals, such as Annals of Operations Research, European Journal of Operational Research, IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE Transactions on Engineering Management, International Journal of Production Economics, International Journal of Production Research, Journal of Business Research, Journal of Cleaner Production, Journal of the Operational Research Society, Omega, Production and Operations Management, Supply Chain Management: An International Journal, Technological Forecasting and Social Change, and Transportation Research – Part E. His research interests focus on data-driven supply chain management, operations-marketing interface, and fashion industry.
Yang Liu
Yang Liu is a Doctoral student in Glorious Sun School of Business and Management in Donghua University, Shanghai. Her research interests focus on supply chain management.
Vincent Quan
Vincent Quan is a professor in the Business department at Fashion Institute of Technology, the State University of New York. His paper has appeared in Journal of the Operational Research Society. His research interests focus on fashion business.
Xin Wen
Xin Wen is currently a Research Assistant Professor in Department of Industrial and Systems Engineering at The Hong Kong Polytechnic University. She has published in journals such as IEEE Transactions on Systems, Man, and Cybernetics – Systems, International Journal of Production Research, International Journal of Production Economics, and Transportation Research – Part E. Her current research interest is on transportation and logistics engineering.