Research of The Decision to Set up A New Manufacturing Site in The Global Logistics

• Main Authors: Pei-chieh Hsieh, 謝佩潔
• Other Authors: Chun-Chen Lee
• Format: Others
• Language: zh-TW
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/45967988361600807243

碩士 === 東吳大學 === 會計學系 === 93 === A multinational corporation which has carried global logistics out for a period of time may face the decision-making problem of increasing capacity because the volume of the market demands will increase over a long period of time when the market recovers or the sales condition of product is good. Thus, this study applies the net present value method to set up three decision models, increasing（1）maintaining the existing production scale;（2）expanding the production scale of existing manufacturing site;（3）establishing a new manufacturing site to cope with the exceeding demand problem, and then using the line programming method to solve the model. The plan which has the biggest net present value is the finally suggestive decision. Besides, according to the results of examples and the sensitivity analysis, this study can get some conclusions: 1. When expecting the global market demands will increase totally, the plan to expand the production scale of existing manufacturing site is the optimal decision, and the plan to establish a new manufacturing site is the second optimal decision. 2. The market price and the exchange rate of market location are positively associated with the optimal net present value. The variable production cost, transportation cost and the exchange rate of manufacturing site are negative associated with the optimal net present value. 3. When expecting one of the conditions will happen, including that the market price will decrease much, the cost will increase much or the exchange rate of manufacturing site will revalue much, the plan to maintain the existing production scale may be the optimal decision. 4. When the market price changes, the changing extent of the optimal net present value is the biggest.