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논문 기본 정보

자료유형
학술저널
저자정보
이강우 (부산수산대학교 경영학과)
저널정보
한국수산경영학회 수산경영론집 수산경영론집 제21권 제2호
발행연도
1990.1
수록면
55 - 84 (30page)

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The objective of this study is to develop an inventory model for the inventory management of a stocking point which sells processed fisheries products. The study, first of all, sets up fisheries processing companies, food companies, apparel companies, pharmaceutical companies and electronic and electrical companies as a population. Then, a comparative study is empirically applied to obtain the inventory characteristics of final products by industry through a survey of a sample selected by a random sampling procedure. The major inventory characteristics of processed fisheries products obtained from the above analysis can be summarized as follows : 1) The major demand characteristics of processed fisheries products is to have wide seasonal fluctuations because the supply of raw materials (i.e., fisheries products) heavily depends on the productive capacity of nature. 2) It has found that fisheries processing companies are the worst in inventory management among the various industries selected in the sample. However, the self-rating of inventory management system by inventory managers of companies shows that the fisheries processing companies are relatively higher than the other companies. 3) The portion of inventory holding cost out of inventory relevant cost is very high for processed fisheries products compared with final products of the other industries. 4) Processed fisheries products are distributed to final consumers through roughly two distribution echelons and take a parallel type inventory system for their distribution structure. In order to develop an inventory model which reflects the inventory characteristics of processed fisheries products mentioned in the above, an inventory model with partial backorders is developed under the situation of stochastic lead time under the consideration of the inventory characteristics of processed fisheries products and then an iterative solution method is provided for the model. Then this study analyzes sensitivity for the standard deviation of lead time in the model by numerical examples.

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