Luo, Ming (2018) Learning from actuarial science: approaches to collectively optimising warranty policies. Doctor of Philosophy (PhD) thesis, University of Kent,. (KAR id:67651)
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Abstract
This research starts from the comparison between warranty and insurance in their coverages, policies, data and, particularly, policy optimisation techniques. Based on abundant literature in related areas, the result of this comparison indicates that warranty policy optimisation can be improved by considering the application of the portfolio theory, dependence modelling and risk measures that are widely used in the actuarial science and the financial discipline. In the following chapters, Chapter 1 introduces the Importance of this research and lists its aim and objectives. Chapter 2 mainly conducts a critical and comprehensive literature review relating to warranty management and actuarial science and summarised the knowledge gaps identified. Chapter 3 establishes a collective warranty policy optimisation framework, with the benefits of the modern portfolio theory borrowed from the actuarial and financial disciplines and copulas from the probability and statistics. With progressing of this research, the disadvantage of the symmetric risk measure, variance, is uncovered in dealing with the extreme events. Chapter 4 proposes using two of the downside risk measures used in the financial discipline, Value-at-Risk and Conditional Value-at-Risk, into the optimisation of warranty policy and a new portfolio optimisation framework of warranty optimisation based on copulas. Chapter 5 investigates the interplay among the hardware, software and users of individual products under different scenarios relating to the warranty claims. Considering such an interplay, it then develops a more comprehensive framework for warranty policy optimisation. This fits the trend that that more and more products can be considered as a system composed of three subsystems: hardware, software and user subsystems and considers that the existing warranty policy optimisation methods in the literature merely focus on products composed of hardware systems. Even though the above chapters have developed warranty policy optimisation frameworks collectively and comprehensively, this research can also be improved in many aspects. As such, in Chapter 6, the sale volume modelling, renewing warranty policy optimisation and copula selection are discussed. Chapter 7 wraps up the research and discusses future research.
Item Type: | Thesis (Doctor of Philosophy (PhD)) |
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Thesis advisor: | Wu, Shaomin |
Thesis advisor: | Panopoulou, Ekaterini |
Uncontrolled keywords: | Warranty Portfolio Reliability Value-at-Risk Hardware Software Insurance |
Subjects: | H Social Sciences |
Divisions: | Divisions > Kent Business School - Division > Kent Business School (do not use) |
SWORD Depositor: | System Moodle |
Depositing User: | System Moodle |
Date Deposited: | 17 Jul 2018 09:10 UTC |
Last Modified: | 05 Nov 2024 11:08 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/67651 (The current URI for this page, for reference purposes) |
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