从规避风险的维修供应商的角度看航空业的绩效合同

IF 1.7 4区 工程技术 Q3 ENGINEERING, INDUSTRIAL
Canek Jackson, Rodrigo Pascual, F. Kristjanpoller
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引用次数: 0

摘要

航空业是一个低利润、高经营风险的行业。有时,由于缺乏劳动力或缺乏具有专业能力的人员,将飞机维修外包是强制性的。它提出了通过绩效合同(PBC)来谈判协议的挑战,作为传统随叫随到的维护服务或时间和材料合同(t&mc)的替代方案,这些合同不会将风险转移给服务提供商。鉴于PBC下风险转移对承包商的重要性,作者提出了一个模型来确定当飞机维修外包给提供两种PBC选项的风险规避服务提供商时,最优合同价格和服务客户数量。据笔者所知,在现有文献中,没有考虑到维护提供商风险规避的最优化定价合同的定量研究。为此,作者将排队、博弈和现代投资组合理论结合在拟议的公式中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance-based contracting in the airline industry from the standpoint of risk-averse maintenance providers
Airline industry is a business characterized by its low profit and high operational risk. Sometimes contracting out aircraft maintenance is mandatory due to the lack of labor capacity or shortage of staff with specialized capabilities. It raises the challenge of negotiating an agreement through performance-based contracting (PBC) as an alternative to traditional on-call maintenance services, or time and material contracts (T &MC), where no risk is transferred to the service provider. Due to the importance of risk transfer to contractors under PBC, the authors propose a model to determine the optimal contract price and the number of customers to serve when aircraft maintenance is outsourced to a risk-averse service provider offering two PBC options. To the best of the author’s knowledge, no quantitative studies for pricing contracts optimally when taking into account maintenance provider’s risk-aversion have been presented in the existing literature. For that purpose, the authors combine queuing, game, and modern portfolio theories in the proposed formulation.
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来源期刊
CiteScore
4.50
自引率
19.00%
发文量
81
审稿时长
6-12 weeks
期刊介绍: The Journal of Risk and Reliability is for researchers and practitioners who are involved in the field of risk analysis and reliability engineering. The remit of the Journal covers concepts, theories, principles, approaches, methods and models for the proper understanding, assessment, characterisation and management of the risk and reliability of engineering systems. The journal welcomes papers which are based on mathematical and probabilistic analysis, simulation and/or optimisation, as well as works highlighting conceptual and managerial issues. Papers that provide perspectives on current practices and methods, and how to improve these, are also welcome
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