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Dynamic Controlling,Optimization And Simulation Of Residual Value Risk For Infrastructure Public Private Partnership Projects

Posted on:2017-04-06Degree:DoctorType:Dissertation
Country:ChinaCandidate:T L TengFull Text:PDF
GTID:1108330491464071Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
With the increasing application of public private partnerships (PPP) in the development of infrastructure and public utilities, the problems of budget constraint of public sectors are resolved, the risk allocation mechanisms between the public and private sectors are enhanced, and the supplying efficiency of public goods and services are improved. However, the implementation of objectives and even the success or failure of PPP project are frequently affected by all kinds of risks during the long concession period. So the mitigation of risks in PPP projects have always been accorded great attention by researchers and practitioners, but few of them have found out the way to resolve the risk control problem radically. Therefore, residual value risk (RVR) is proposed in this paper as the critical control index to explore methods of controlling and optimizing risks in PPP projects from the perspective of systematic thought and process management. As a result, the dynamic feedback control system and the optimal control system are established to achieve the control and optimization of RVR in PPP projects.First, the extant literatures and recent directions in the field of PPP model, RVR, and risk management of PPP projects are analyzed based on detailed literature review. Moreover, by comparing with the risk control research of general engineering project, gaps of extent researches are pointed out. Then, the research objectives, contents, methods and structure of this paper are formed.Second, the concept and connotation of RVR are defined through the system analysis of PPP project, and the advantage and utility of risk management from the perspective of RVR are analyzed clearly. Then, all the potential precursory risks leading to RVR are identified based on literature review method, and a worldwide structured questionnaire survey about the RVR is conducted to verify the effectiveness and significance of precursory risks.Third, the risk conduction effects in PPP project are summarized based on theory of risk conduction. On this basis, the causality hypothesis of risk conduction network in PPP project is inferred through causality analysis method, and the structural equation model (SEM) is proposed to conduct the causality test for the purpose of forming the final risk conduction network in PPP project. Moreover, the path coefficient result from the parameter estimation of SEM are utilized to establish the risk flow estimation model (RFEM), and the influence coefficient are utilized to solve the transforming degree (y) between every couple risk flows in PPP project.Forth, the concept of vulnerability is applied to open up the link between risk event and risk consequence in PPP project, and the dynamic risk conduction mechanisim adjusted by vulnerability is defined through deductive method. Then, the vulnerability breakdown structure (VBM) is structured to identify the vulnerability in PPP project, and a structured interview survey is conducted to verify the effectiveness and significance of vulnerability indexes. Furthermore, the dynamic vulnerability evaluation model (DVEM) for PPP project is proposed on the basis of survey results, and it is also verified through the empirical analysis of PPP case which is the western harbour tunnel in Hongkong.Fifth, the dynamic RVR control model (DRCM) is proposed step by step through system modeling method. The linguistic model of DRCM is established based on theory of dynamic feedback control. The network model of DRCM is established based on causal loop diagram method. The quantitative model of DRCM is established based on the transfer function, the coupling function, the diffusion function, etc which are derived through deductive method. The dynamic model of DRCM is established based on system dynamic (SD) method. Moreover, a simulation experiment is conducted to verify the correctness and reasonableness of DRCM through the empirical analysis, and also to verify the advantages of dynamic feedback control through the comparative analysis.Sixth, the beforehand optimization method is proposed to control and optimize the RVR before risk occurs. The vulnerability is adopted to conduct the sensitivity analysis of DRCM to investigate the beforehand control effect of RVR. On this basis, the beforehand optimization procedure is designed through theory of optimal control, and a simulation experiment is conducted to verify its correctness and reasonableness.In the end, an optimal coordinator based on dynamic programming algorithm is designed according to the database of risk control measures. Then, the optimal coordinator is integrated into the dynamic feedback control system to establish the RVR hierarchical control system (RHCS), which include the executive level, the coordination level and the organization level. Finally, a simulation experiment is conducted to verify the reliability, effectiveness, generality, correctness and convergence of RHCS.The research findings of this paper would be of tremendous value in more supplement and better maintenance of the risk management for PPP projects. It would also provide the decision-making support for both the public and private sectors, and perform a positive function in promoting PPPs development in China.
Keywords/Search Tags:public private partnerships, risk identification, risk conduction, risk aussessment, risk control, vulnerability, optimal control
PDF Full Text Request
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