Modelling optimal warranty price for lifetime policies taking into account the uncertainties in life measures
Embargoed until: 2018-05-01
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Owing to the assurance of longer reliable service life and greater customer peace of mind, products with a lifetime warranty are becoming more and more popular. Under such policies, both the manufacturer and the buyer are exposed to uncertainties and risks of warranty pricing and product performance since product lifetimes are uncertain and are not well defined in these policies. Considering the uncertainties in the measure of lifetime (useful life), this paper extends previous work of the authors [Rahman, A., & Chattopadhay, G. N. (2010). Modelling risks to manufacturer and buyer for lifetime warranty policies. International Journal of Management Science and Engineering Management, 5, 203–209] to determine the optimal warranty price. Risk preference models are developed to find the optimal warranty price through the use of the manufacturer’s utility function for profit and the buyer’s utility function for repair costs. The sensitivity of the risk preferences models are analysed using numerical examples with respect to factors such as the buyer’s and the manufacturer/dealer’s risk preferences, the buyer’s anticipated and the manufacturer’s estimated product failure intensity, the buyer’s loyalty to the original manufacturer/dealer in repairing failed products, and the buyer’s repair costs for non-warrantied products. Analysis of the developed models reveals that the manufacturer’s decisions on warranty price are strictly related to useful life, failure intensity of the product, and risk preferences. On the other hand, the buyer’s acceptance of a lifetime warranty depends on the expected lifetime of the product, the buyer’s anticipated product failure intensity, anticipated repair costs, and most importantly the buyer’s risk preference.
International Journal of Management Science and Engineering Management
Copyright 2017 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Management Science and Engineering Management on 17 May 2017, available online: http://www.tandfonline.com/10.1080/17509653.2017.1312582
This publication has been entered into Griffith Research Online as an Advanced Online Version.
Engineering not elsewhere classified