Product Life Cycle Strategic Forecasting System

• Main Authors: Ching Hsiang Chang, 張晴翔
• Other Authors: Ping Teng Chang
• Format: Others
• Language: zh-TW
• Published: 1999
• Online Access: http://ndltd.ncl.edu.tw/handle/93374011863505335296

碩士 === 東海大學 === 工業工程學系 === 87 === Traditional management prediction system is always only basic on past historical information. It is used to forecast possibilities and direction of future developing happenings. Once the uncertain change has come to dynamic environment such as Southeast Financial Storm, we can’t do effective quick response just in time and forecast the happenings. Therefore, enterprises have to take the extreme failure risks and pay much lost running cost. Therefore, this article will be basic on product life cycle (PLC) and lead into the supply chain and demand chain of PLC. At first, we visit expert to analyze the Module of Consumers’ behavior and lead the feature factors of products and markets into the forecasting module of PLC with variable form. Besides, use inverse computing to analyze the requirement factor coefficient of consumers and supply factor of producers, and use the turning point of internal factor and external factor to analyze product life area. Because PLC has different effect and change to consumers and producers, we use regression method to gain internal and external characteristic value that belong to every phase and to indicate the characteristic value of every phase in consumer demand chain and producer supply chain. Moreover, the growing process of product life cycle should be affected differently by every phase characteristic value, so utilizing weighting method to give different kinds of effect. It can indicate product sale growth process in the real world. At last, we can give different strategic multi-object in each PLC characteristic value, PLC innovation and imitation coefficient, and PLC stage weight. Therefore, the policy-maker will become strong and powerful decision support system in running and managing business and enacting and analyzing policy.