Essays on management of scarce resources

• Main Author: LUO, Qian
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Scarce Resources; Healthcare Resources Management; Health Transition Estimation; Urban Water Management; Wastewater Recycling Capacity; Business Administration, Management, and Operations; Operations and Supply Chain Management
• Online Access: https://ink.library.smu.edu.sg/etd_coll/333; https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1337&context=etd_coll
• Institution: Singapore Management University

Efficient management of scarce resources is critical to the improvement of economic, social and/or environmental performances. In this dissertation, I focus on the management of two scarce resources: i) healthcare resources and ii) water, and investigate two important problems: i) the estimation of patients’ health transition to support healthcare resources control under the context of sequential medical treatments, and ii) the urban water system control with a specific focus on the wastewater recycling capacity investment in the presence of climate change and urban water scarcity. The first chapter studies how to estimate patients’ health transition considering the effects of treatment-effect-based policies. Treatment-effect-based decision policies are increasingly used in healthcare problems, which leverage predictive information on patient health transitions and treatment outcomes for specific medical treatment decisions. However, treatment-effect-based policies will significantly censor patients’ observed health transitions and distort the estimation of transition probability matrices (TPMs). I propose a structural model to recover the underlying true TPMs from censored transition observations to address this issue. I show that the estimated TPMs from the structural model are consistent, asymptotically normally distributed and maximize the log-likelihood function on observed censored data. I compare the proposed model with other estimation methods through numerical experiments and demonstrate its advantages in various performance metrics, e.g., deviations from the ground truth TPMs. I also implement the proposed model to estimate patient health transitions using real censored data in ICUs extubation problems. Formulating the extubation problem as a classical optimal stopping Markov Decision Process model, I show that the proposed model, with more accurate estimated TPMs considering censored data, can reduce the length of stay of patients in ICU compared to other benchmark transition estimation methods. In the second chapter, considering multiple urban water resources (e.g., freshwater from reservoirs, recycled water, and desalinated water/imported freshwater) and multiple streams of urban water demand (e.g., household and non-household demands), I examine the economic and sustainable implications of wastewater recycling capacity investment under rainfall and recycling cost uncertainties. To this end, I formulate the problem as a two-stage stochastic minimization model and characterize the optimal wastewater recycling capacity. I find that the optimal recycling capacity first decreases and then increases in the freshwater capacity, suggesting that they are substitutes when the freshwater capacity is relatively small and complements otherwise. I also perform sensitivity analysis on how the uncertainties (rainfall and recycling cost variabilities and their correlation) affect the optimal recycling capacity and the optimal expected cost and find that the water utility always benefits from a higher correlation coefficient but a lower rainfall variability. In this chapter, I also discuss urban water sustainability using the measures such as urban water vulnerability and characterize the specific conditions under which urban water may become more vulnerable. The third chapter calibrates the economic model presented in the second chapter based on the publicly available data from the urban water supply practice in Adelaide, the capital city of South Australia. To complement the analytical results, I conduct comprehensive numerical analysis in this chapter to investigate the effects of uncertainties on the optimal expected cost and optimal recycling capacity. Moreover, I study the value of wastewater recycling and how rainfall and recycling cost variabilities, correlation and demand expansion affect it. For example, the results show that the value of wastewater recycling increases in the correlation coefficient and decreases in the rainfall variability. Based on the calibrated baseline scenario, I find that the expansion of both the household and non-household demands increase the value of recycling; moreover, the expansion of non-household demand tends to have a larger impact when the deviations from the baseline scenario become relatively large. I further study the leakage reduction, water vulnerability and overflow risk. The insights from the numerical analysis in this chapter complement the analytical results presented in Chapter 2. I put forward important practical implications relevant to both urban water utilities and water policymakers based on the findings.