| Author: | Pan, Yuqing |
| Title: | Selected topics in sustainability management : emergency relief allocation, vaccination, and blockchain technology |
| Advisors: | Ng, Chi To Daniel (LMS) Cheng, T. C. Edwin (LMS) Lee, K. C. Peter (LMS) |
| Degree: | Ph.D. |
| Year: | 2023 |
| Subject: | Sustainable development -- Management Resource allocation Epidemics Public health Industrial management -- Environmental aspects Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Logistics and Maritime Studies |
| Pages: | xv, 140 pages : color illustrations |
| Language: | English |
| Abstract: | Both healthcare management and environmental management are vital components of sustainability management, with the common goal of striking a balance between addressing present healthcare needs and safeguarding the environment for future generations. Sustainability management acknowledges the importance of healthcare and environmental factors, striving to find sustainable solutions that ensure longterm health and well-being. Today’s society places significant emphasis on addressing healthcare and environmental management issues. Despite researchers having focused on these matters for over a decade, numerous aspects remain unexplored due to the complexity of the social environment and technological advancements. In this thesis, we conduct three studies on healthcare and environmental management, considering different aspects in terms of emergency relief allocation, vaccination, and blockchain technology. In the first study, we study medical resources allocation during epidemic outbreaks. While some reports show that the existing real-life medical resources allocations during epidemic outbreaks are myopic, some experts claim that medical resources allocations based on foresighted future allocations might enable a better balance of supply and demand. To investigate this claim, we develop a foresighted medical resources allocation model to help governments manage large-scale epidemic outbreaks. We formulate a demand forecasting model with a general demand forecasting function based on the last-period demands, extra demand caused by the last-period unfulfilled demand, and uncertain demand. In the foresighted allocation model, the government decides the current-period allocation based on the foresighted demand, which considers the last-period area demand and uncertain demand from the current period to the end of a planning horizon, using a stochastic dynamic program. We find that the optimal allocation is a function of the allocation capacity in each period. The optimal foresighted allocation is always higher than the optimal static (one-period) allocation and decreases with allocation capacity. When the allocation capacity is sufficiently large, the foresighted demand is close to the static demand. Besides, if the cost of oversupply is close to zero, the optimal allocations for both the foresighted allocation and one-period models are the allocation capacity. Our results provide useful managerial implications for a government contemplating medical resources allocation in response to an epidemic outbreak. In the second study, we discuss the coordination between public and private resources for vaccination. Vaccination is a well-known method to protect the public against an epidemic outbreak, e.g., COVID-19. To this end, the government of a country or region would strive to achieve its target of vaccination coverage. Limited by the total vaccine capacity of public hospitals, the government may need to cooperate with private hospitals or clinics for more vaccination. Exploring in this study government coordination of public and private resources for vaccination, we model a vaccine system consisting of a public hospital, a profit-maximizing private clinic, and self-interested individuals, under three scenarios: (i) without information sharing (concerning vaccine inventory and vaccine price), (ii) with information sharing and subsidy, and (iii) with information sharing and allocation. We find that, under scenario (i), the vaccine demand is fully satisfied by the public hospital and the private clinic cannot make any profit. Under scenario (ii), the private clinic is willing to enter the vaccine market with a positive profit-maximizing vaccination coverage. Under scenario (iii), the socially optimal vaccination coverage may be lower than that under scenario (i). Moreover, we conduct a sensitivity analysis to generate practical implications of the research findings for vaccination policy-making. Our results provide both theoretical and managerial insights on vaccine supply decision, government intervention, and vaccination coverage. In the third study, we examine how a sustainable firm should communicate its environmental quality to consumers. Environmental labels are commonly used in practice, but their proliferation leads to label confusion among consumers. Blockchain-based transparency can solve the above dilemma. As such, whether and when to adopt environmental labels or blockchain technology to reveal its environmental efforts are critical questions faced by firms investing in environmental quality. To answer these questions, we develop a game-theoretic model with a sustainable firm and a non-sustainable firm. The sustainable firm needs to communicate its environmental quality to consumers via either environmental labels or blockchain-based transparency. In the case of environmental labels, a fraction of consumers are confused about the label standards and may underestimate or overestimate the sustainable firm’s environmental quality; in the case of blockchain-based transparency, all consumers have full information. We highlight several main findings. First, under environmental labels, as the fraction of confused consumers increases, the sustainable firm may either switch from a high-tier label to a low-tier one, or counterintuitively switch from a low-tier label to a high-tier one to differentiate itself from the competitor. Second, blockchain-based transparency is not always preferred by the sustainable firm. That is, full information is not necessarily better than partial information for the sustainable firm. Third, when the sustainable firm prefers blockchain-based transparency to environmental labels, the sustainable firm may improve or reduce its environmental quality and the non-sustainable firm may be better or worse off. |
| Rights: | All rights reserved |
| Access: | open access |
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