Demand forecasting model for short life cycle products based on improved BASS model

被引：0
|
作者：
Xie, Jian-Zhong [1 ,2 ]
Yang, Yu [1 ]
Chen, Qian [1 ]
Li, Fei [1 ]
机构：
[1] State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing
[2] Foxconn Technology Group, Shenzhen
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2015年 / 21卷 / 01期
基金：
中国国家自然科学基金;
关键词：
BASS model; Demand forecasting; Product similarity; Short life cycle products;
D O I：
10.13196/j.cims.2015.01.006
中图分类号：
学科分类号：
摘要：
Aiming at the problem that low forecasting accuracy leaded by historical data deficiency and demand factors consideration insufficiency in demand forecasting of short life cycle products, an improved BASS model for demand forecasting of short life cycle products was proposed. The product similarity measure method based on importance of features was put forward, and the weight distribution of products similar features was achieved through the application of fuzzy clustering-rough sets. The similarity of product was measured by the system similarity measure method, which provided evidences for the acquisition and consolidation of similar products' historical sales data and the determination of similar products weights. By considering the influence of consumer preferences and seasonal factors on demand forecasting, the BASS model was improved, and a demand forecasting model for short life cycle products based on improved BASS model was proposed. With an example of demand for a mobile phone forecasting, the scientificity and validity of proposed method was verified. ©, 2015, CIMS. All right reserved.
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页码：48 / 56
页数：8
相关论文
共 22 条
  • [1] Xu X., Cai C., Shen G., A deterministic inventory model for short-life cycle products with variable lead timeand backorder discount considerations, Chinese Journal of Management Science, 18, 2, pp. 42-47, (2010)
  • [2] Xu X., Chen W., Liao L., Et al., Ordering strategy of short life-cycle products based on the demand forecasting, Journal of Management Sciences in China, 16, 4, pp. 22-32, (2013)
  • [3] Dekluyver C.A., A comparative-analysis of the bass and weibull new product growth-models for consumer durables, New Zealand Operational Research, 10, 2, pp. 99-130, (1982)
  • [4] Schmittlein D.C., Mahajan V., Maximum likelihood estimation for an innovation diffusion model of new product acceptance, Marketing Science, 1, 1, pp. 57-78, (1982)
  • [5] Trappey C.V., Wu H.Y., An evaluation of the time-varying extended logistic, simple logistic, and Gompertz models for forecasting short product lifecycles, Advanced Engineering Informatics, 22, 4, pp. 421-430, (2008)
  • [6] Bass F.M., A new product growth model for consumer durables, Management Science, 15, 5, pp. 215-227, (1969)
  • [7] Norton J.A., Bass F.M., A diffusion-theory model of adoption and substitution for successive generations of high-technology products, Management Science, 33, 9, pp. 1069-1086, (1987)
  • [8] Mahajan V., Peterson R.A., Innovation diffusion in a dynamic potential adopter population, Management Science, 24, 15, pp. 1589-1597, (1978)
  • [9] Jain D., Mahajan V., Muller E., Innovation diffusion in the presence of supply restrictions, Marketing Science, 10, 1, pp. 83-90, (1991)
  • [10] Xu X., Song Q., Forecasting for products with short life cycle based on improved BASS model, Industrial Engineering and Management, 18, 5, pp. 27-31, (2007)
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