Cost allocation with learning and forgetting considerations in a monopolistically competitive market.
ABSTRACT The objective of this study is to investigate the optimal cost-allocation rate for a new product in order to minimise the incumbent firm's cost under a monopolistically competitive market. From the incumbent's perspective, within a given length of the production run in the introduction or growth stage of the product life cycle, the impacts of the competitors’ entry and the learning and forgetting effects are taken into account in estimating the incumbent's costs. Furthermore, a Bayesian decision model is proposed to determine the optimal cost-allocation rate by considering both expert opinions and available information. Such a rate may assist the managers in evaluating a favourable percentage of the production cost borne by the incumbent firm. A case illustration demonstrates the application of the proposed model. The sensitivity analyses indicate that a higher increasing rate of competition, or a smaller degree of dispersion of the competitors’ entry scale in the introduction or growth stage would incur a higher optimal cost-allocation rate with a higher incumbent's expected total cost. In addition, the optimal cost-allocation rate and the incumbent's expected total cost would be positively correlated with the learning and forgetting rates, regardless of being under setup or production. Finally, it is suggested that managers should pay more attention to the learning and forgetting effects at the production stage than those at the setup stage.
- Production Planning and Control 01/1997; 8(5):484-493. · 0.60 Impact Factor
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ABSTRACT: The purpose of the article is to apply contingent claim theory to the valuation of the type of participating life insurance policies commonly sold in the UK. The article extends the techniques developed by Haberman, Ballotta, and Wang (2003) to allow for the default option. The default option is a feature of the design of these policies, which recognizes that the insurance company's liability is limited by the market value of the reference portfolio of assets underlying the policies that have been sold. The valuation approach is based on the classical contingent claim pricing "machinery," underpinned by Monte Carlo techniques for the computation of fair values. The article addresses in particular the issue of a fair contract design for a complex type of participating policy and analyzes in detail the feasible set of policy design parameters that would lead to a fair contract and the trade-offs between these parameters. Copyright The Journal of Risk and Insurance, 2006.Journal of Risk & Insurance 01/2006; 73(1):97-121. · 1.41 Impact Factor
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ABSTRACT: In this study, we introduce a time-dependent learning effect into a single-machine scheduling problem. The time-dependent learning effect of a job is assumed to be a function of total normal processing time of jobs scheduled in front of it. We introduce it into a single-machine scheduling problem and we show that it remains polynomially solvable for the objective, i.e., minimizing the total completion time on a single machine. Moreover, we show that the SPT-sequence is the optimal sequence in this problem.European Journal of Operational Research 02/2006; · 2.04 Impact Factor