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Decision Of Enterprise Product Recall Considering Consumer’s Losses

Posted on:2015-01-19Degree:MasterType:Thesis
Country:ChinaCandidate:J J YangFull Text:PDF
GTID:2269330428499805Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
In the process of production and sales, product defects are common. Enterprises are faced with challenges of how to conduct the recall of defective products, reducing the losses of enterprises and the losses of social welfare to the minimum. Based on the low rate of recall under the current circumstances, the article suggests enterprises give consumers reimburse of responding recall losses in order to enhance the recall rate, and at the same time establishes a model for determining the reimburse limits, and makes decisions on whether enterprises recall defective products to maximize enterprises their own profits. The paper also analyzes different compensation policies of the enterprise, and gives the best reimburse. The paper further analyzes the relations between enterprises’ best product recalls and social welfare losses, and acquires the relationship of optimal reimburse strategy for enterprises and optimal reimburse strategy for social welfare, plays a guiding significance to products recall of enterprises and government decision-making.For the; status quo that lacking of quantitative model research of the defective products’ recalls at home and abroad, we use mathematical modeling, decision theory and dynamic programming theory et al to study the enterprise’s optimal cost of the defective products’recall based on the second chapter of the dissertation literature review, and also study the best cost of the defective products recall which Government expects.The third chapter discusses the issue of compensation limits of the enterprises’ recall decision. Standing business perspective, by determining the optimal compensation limits of the enterprises’ recall decision in the recall event, enterprises gain the optimal expectations of total cost of the recall. Assuming enterprises can estimate the consumers’ losses which generated by the consumer response to the recall, the losses obey random distribution, the recalled products by maintenance-related that failures no longer occur, and assuming when there’s no recall, enterprises’ proportion of compensation is not lower than the enterprises’ proportion of compensation when there’s a recall. Selected the enterprises’ compensation limit as decision variables, and then establish a cost control model by using deterministic decision theory. Dynamic programming algorithm for solving the model to determine the optimal compensation limits, so that the expected minimum total cost.The fourth chapter discusses the government’s desired compensation limits decision-making problems. By introducing social welfare losses, considering the government should be in the role played by social welfare and how to play, using a dynamic programming algorithm for solving the optimal social welfare loss and the enterprises’ recall compensation limits. Through the government’s desired compensation limits compare with the enterprises’ best compensation limits, compensation limits obtained with the total cost of the recall enterprises and social welfare loss of relationships. And, in the case of the optimum loss of social welfare, the total cost of the recall is not necessarily the optimal for enterprises.Finally, we demonstrate that our study had improved the relevant theory’s research, and could help the decision-maker and managers formulate the best recalled strategy. In this paper, the conclusions and methods to give business executives some management enlightenment, while providing some supports for the theoretical basis and improve our recall system, help and guide managers to develop optimal recall strategies to reduce business costs and improve efficiency.
Keywords/Search Tags:products recall, consumer responding recall losses, rate of respondingrecall, corporate recall decisions, enterprises’ compensation limits, social welfarelosses
PDF Full Text Request
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