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A mean-variance optimisation approach to collectively pricing warranty policies

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  • Luo, Ming
  • Wu, Shaomin

Abstract

Warranty policy can influence the profit and cost of a product. In practice, a manufacturer commonly produces more than one product, or a portfolio of products, and provides warranty servicing for them. Many authors have attempted to optimise warranty policy to maximise the profit or minimise the cost of each individual product. Warranty claims of the products produced by the same manufacturer, however, may be due to common causes, since the products may be designed by the same engineer team or using the same type of components. This implies that the numbers of warranty claims of different products may be related, and optimisation of warranty policies for each individual product may therefore cause biased decisions. To overcome this disadvantage, this paper aims to collectively optimise a manufacturer's total profit for a portfolio of different products by using a mean-variance optimisation approach. A tool from the probability theory, copulas, is used to depict the dependence among the warranty claims of different products. Numerical examples are provided to illustrate the application of the proposed methods.

Suggested Citation

  • Luo, Ming & Wu, Shaomin, 2018. "A mean-variance optimisation approach to collectively pricing warranty policies," International Journal of Production Economics, Elsevier, vol. 196(C), pages 101-112.
    • Handle: RePEc:eee:proeco:v:196:y:2018:i:c:p:101-112
    DOI: 10.1016/j.ijpe.2017.11.013
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Zhao, Xiujie & He, Shuguang & Xie, Min, 2018. "Utilizing experimental degradation data for warranty cost optimization under imperfect repair," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 108-119.
    2. Deprez, Laurens & Antonio, Katrien & Boute, Robert, 2021. "Pricing service maintenance contracts using predictive analytics," European Journal of Operational Research, Elsevier, vol. 290(2), pages 530-545.
    3. Liu, Bin & Shen, Lijuan & Xu, Jianyu & Zhao, Xiujie, 2020. "A complimentary extended warranty: Profit analysis and pricing strategy," International Journal of Production Economics, Elsevier, vol. 229(C).
    4. Luo, Ming & Wu, Shaomin, 2019. "A comprehensive analysis of warranty claims and optimal policies," European Journal of Operational Research, Elsevier, vol. 276(1), pages 144-159.
    5. Wang, Xiaolin & Liu, Bin & Zhao, Xiujie, 2021. "A performance-based warranty for products subject to competing hard and soft failures," International Journal of Production Economics, Elsevier, vol. 233(C).
    6. Yang, Li & Ye, Zhi-sheng & Lee, Chi-Guhn & Yang, Su-fen & Peng, Rui, 2019. "A two-phase preventive maintenance policy considering imperfect repair and postponed replacement," European Journal of Operational Research, Elsevier, vol. 274(3), pages 966-977.
    7. Dai, Anshu & Wang, Xin & Li, Yu & Li, Ting & He, Shuguang, 2023. "Design of a performance-based warranty policy with replacement–repair strategy and cumulative cost threshold," International Journal of Production Economics, Elsevier, vol. 255(C).
    8. Lamghari-Idrissi, Douniel & Basten, Rob & van Houtum, Geert-Jan, 2020. "Spare parts inventory control under a fixed-term contract with a long-down constraint," International Journal of Production Economics, Elsevier, vol. 219(C), pages 123-137.
    9. Deprez, Laurens & Antonio, Katrien & Boute, Robert, 2023. "Empirical risk assessment of maintenance costs under full-service contracts," European Journal of Operational Research, Elsevier, vol. 304(2), pages 476-493.
    10. Huang, Hongfu & Liu, Feng & Zhang, Peng, 2021. "To outsource or not to outsource? Warranty service provision strategies considering competition, costs and reliability," International Journal of Production Economics, Elsevier, vol. 242(C).
    11. Lu, Zhen & Shang, Jennifer, 2019. "Warranty mechanism for pre-owned tech products: Collaboration between E-tailers and online warranty provider," International Journal of Production Economics, Elsevier, vol. 211(C), pages 119-131.

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