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.
"A number of scholars, such as Kim and Arnond , attested that, in addition to the four dimensions of cost, quality, delivery, and flexibility, the service factor is essential. They therefore divided the competitiveness of manufacturing corporations into five dimensions and 15 competitive attributes for measurement         . "
[Show abstract][Hide abstract] ABSTRACT: This study adopted 14 criteria for order-winners and qualifiers as the attributes for evaluation. The first stage used a simultaneous importance-performance analysis to analyse the competitive market situations of a corporation and its competitors. The second stage used the decision-making trial and evaluation laboratory method to analyse the attributes' causal relationships and levels of influence; then two methods of analysis were integrated to analyse and re-formulate the competitive strategies for the winning orders. As well as serving as a novel theory-based method to examine how manufacturers win orders, the proposals in this study can be applied to practical industry experiences.
South African Journal of Industrial Engineering 11/2013; 24(3):112-124. DOI:10.7166/24-3-657 · 0.06 Impact Factor
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