Public and Private Partnerships in Disaster Management
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The objective of this dissertation is to provide insights to better understand how public and private partnerships (PPPs) play an important role in ensuring that private incentives are aligned with public policies. This dissertation applies game theory, and optimization models to study the best public and private resource allocation strategies in disaster preparedness with the considerations of the uncertain consequences of the disasters, investment costs, and the decision makers' risk preferences. It provides insights into understanding (a) how to construct optimal public and private partnerships when the qualitative human behaviors and quantitative risk factors are considered; and (b) under what conditions and to what extent the public and private investments in preparedness could form better PPPs. This dissertation includes four parts. The first part (Chapter 2) reviews the previous research on the topics of operations research, game theory, disaster management, decision making methods under uncertainty, and Monte Carlo analytic hierarchy process. In the second part (Chapter 3), three approaches are explored to model the private sector's risk behavior in studying the PPPs with single private sector and single public sector. Using an expected present value approach, efficient PPPs are studied in disaster preparedness using a decentralized model (sequential game where the public sector is the first mover) and a centralized model. This approach identifies the best public investment policies by evaluating the effectiveness of incentive provisions based on the various private strategic responses. We study the conditions of the private and public sectors' resource allocation strategies when they are strategic complements or substitutes. We find that the private sector who has a higher valued target or lives in more risky areas invests more, and has higher potential to partner with the public sector. We also compare the decentralized model results with the results of the centralized model to study the efficiency of the PPPs and find that the results are similar when the target valuation or the probability of disasters is small. In an expected utility theory approach, we obtain the analytical model results when the private sector's risk preference is risk neutral, and provide the numerical model solutions when the private sector's risk behaviors are risk averse and risk seeking. We compare the private sector's best response and the SPNE solutions when the private sector is risk averse, risk neutral or risk seeking. Our results show that the public sector provides the less amount of subsidy to the risk-averse private sector, and provides the highest amount of subsidy to the risk-seeking private sector. The amount of subsidy provided to the risk-neutral private sector is in between the previous two cases. We also find that the private investments of the risk-seeking private sector, the risk-neutral private sector, and the risk-averse private sector are in the reverse order of the public subsidy. We also study a psychologically more accurate description decision analysis approach that models the real-life decision making under risk: prospect theory approach. We obtain the private sector's best response and the SPNE solution numerically, and conduct the sensitivity analysis of the model results. From the analysis, we find that the public sector provides more subsidy to the private sector if the public sector's target valuation is high; and the private sector is more risk seeking. We also find that the private sector has higher potential to partner with the public sector if the private sector has a higher valued target; is more sensitive to loss; or locates in a higher risk area. The third part (Chapter 4) extends the PPPs with single private decision maker and single public decision maker to the PPPs with single public sector engaging with multiple private sectors. Both quantitative and qualitative optimization models are proposed in this part to study how the public sector distributes the public subsidy to multiple private sectors, and partners with them. In the quantitative optimization model, we study the PPPs under both risk neutral model and prospect theory model in a sequential game. The algorithms are provided to solve for the equilibrium solutions. In the qualitative optimization model, an extensive research is conducted to determine the criteria of evaluating the private sectors. A multiple criteria decision making method, Monte Carlo analytic hierarchy process approach (MCAHP) is introduced to rank the private partners based on the criteria. Algorithm is also provided to solve the numerical solutions for both public and private sectors. The fourth part (Chapter 5) conducts model validation through an experiment with two stages. A graphical user interface (GUI) software is developed to conduct experiments for testing the decision maker's risk behavior and validating the model results (the private sector's best response). There are Forty-one students from the State University of New York at Buffalo participated in the experiment. By analyzing the median data of the first part of the experiment, we find that the participants behave risk seeking in the negative prospect, risk averse in the positive prospect, are sensitive to loss (loss aversion), overestimate the low probability and underestimate the moderate and high probability as the descriptions of the prospect theory. We also compare the second part of the experiment results with the model results. We find that the experiment results are consistent with our model prediction results.