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Warranty policies for certain products, such as automobiles, often involve consideration of two attributes, for example, time and usage. Since consumers are not necessarily homogeneous in their use of the product, such policies provide protection to users of various categories. In this chapter, product usage at a certain time is linked to the product age through a variable defined as usage rate. This variable, usage rate, is assumed to be a random variable with a specified probability distribution, which permits modeling of a variety of customer categories. Another feature of the chapter is to model the propensity to execute the warranty, in the event of a failure within specified parameter values (say time or usage). In a competitive market, alternative product/warranty offerings may reduce the chances of exercising the warranty. This chapter investigates the impact of warranty policy parameters with the goal of maximizing market share, subject to certain constraints associated with expected warranty costs per unit not exceeding a desirable level.

For certain consumer durables, such as automobiles, warranty policies involve two attributes. These could be the time elapsed since sale of the product and usage of the product at a given point in time. Warranty may be invoked by the consumer if both time and usage are within specified warranty parameters when a product failure occurs. In this chapter, we assume that usage and product age are related through a random variable, the usage rate, which may have a certain probabilistic distribution as influenced by consumer behavior patterns. Additionally, product failure rate is influenced by the usage rate and product age. The integrated model includes expected unit warranty costs, expected unit research and development costs, and expected unit production costs. It is assumed that in production, there is a learning effect with time. A multiobjective model is incorporated with the objectives being market share and proportion of expected warranty costs relative to total manufacturing expenditures per unit. The goals could be conflicting in nature. The problem then is to determine the warranty policy parameters while attaining certain desirable values of the two objectives.

Various types of warranty programs are offered for consumer products. The two most common are a linear pro-rata warranty or a lump-sum warranty, if product failure occurs prior to the specified warranty time. In this chapter we consider additional types of warranty programs that allow the consumer to purchase a one-time extended warranty in the event of no failure within the initial warranty period. For the extended period, warranty may be linearly pro-rated, starting at an amount that is lower than the initial purchase price. Alternatively, for the extended period, warranty may be a lump-sum amount, that is less than the initial warranty amount. Expressions for the expected costs under each of the programs are derived. Guidelines are provided for determining the parameters of each warranty program under relevant constraints. Sensitivity analysis is also conducted to determine the effect of the problem parameters on the expected warranty costs.

Manufacturers and remanufacturers strive to maximize supply chain effectiveness by eliminating wastes in all their forms. This line of research extends the effectiveness during the products' working lives. Fraud in the warranty service chain (WSC) is one such source of waste that leads to revenue losses in the short term but when left unchecked leads to far worse results in the long term. Warranty frauds in the new product industry have received significant attention in recent literature. Addressing fraud issues in the remanufacturing industry have not been a high priority. Previous studies considered the primary parties in the WSC as possible sources of fraud. However, several unique opportunities exist for the secondary parties when it comes to fraud. This chapter considers fraud originating from one of the secondary parties of the WSC, namely the warranty administrator. The chapter models this fraud scenario using discrete event simulation and explores a possible fraud mitigation scenario.

Monetary conditions necessary for equilibrium:[Keynes] “A Treatise on Money,” Vol. I, Books 3 and 4Robertson's “Banking Policy and the Price Level”Hayek's “Prices and Production”Marshall (short period of equilibrium: quasi-rent – supplementary cost, Book V, Chapters 4, 5, 9)Harrod, The Economic Journal, June 1930, “Notes on Supply”Kahn, The Economic Journal, June 1931, “Relation of Home Investment to Unemployment”

The measurement of non-financial assets that are held for their service potential rather than for a financial return can be challenging in the public sector. In some cases, the information is not available about the historical cost for the initial measurement and there is not an active market neither that could allow inferring a value for those non-financial assets. In response to this problem, this chapter analyses the newly developed measurement base current operational value (COV) to measure assets in the public sector. This measurement base is part of the proposals in Exposure Draft (ED) 76 – Conceptual Framework Update: Chapter 7, Measurement of Assets and Liabilities in Financial Statements, and ED 77 – Measurement. This chapter was developed using evidence obtained through participant observation to the IPSASB meetings from the authors and the desk analysis of the comment letters (CLs) to the ED 76 and ED 77. The findings from this study reveal that comparability is a major concern of the stakeholders. The CLs also highlighted the need for further guidance on a number of issues and suggested the way forward for the future standard-setting process that address the concerns identified in the proposed COV.