Product Growth Models for Medium-Term Forecasting of Short Life Cycle Products

Kurawarwala, Abbas A.; Matsuo, Hirofumi

doi:10.1016/s0040-1625(97)00102-9

Cited by 52 publications

(43 citation statements)

References 15 publications

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“…To test the effect of forecasting, we select the data in Ref [17] to forecast, which are the sales data of five kinds computer products in a company. The products are sold in the same channel and have similar season features.…”

Section: Resultsmentioning

confidence: 99%

Forecasting demand of short life cycle products by SVM

Zhang

2008

2008 International Conference on Management Science and Engineering 15th Annual Conference Proceedings

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In this paper, the demand of short life cycle products is forecasted by the method of SVM in the conditions of data deficiency. The method considers products' demand, demand forecasted by Bass model and season factor as affecting factors of the demand of short life cycle product, the training sample and forecasting sample varies when the time changes. Then SVM forecasting model is set up and with it the demand is forecasted. The comparison with relative models indicates that the presented method is more valid in forecasting the demand of short life cycle products.

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Section: Resultsmentioning

confidence: 99%

Forecasting demand of short life cycle products by SVM

Zhang

2008

2008 International Conference on Management Science and Engineering 15th Annual Conference Proceedings

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“…Kurawarwala and Matsuo (1998) find the innovative and imitative parameters are easy to assess, but the magnitude of the total adopters has high uncertainty. Cases 7, 8, 9 and the base case show that the FP's optimal launch time is insensitive to various market sizes of the FP (Figure 3.3) when the cannibalization is strong.…”

Section: Expansionmentioning

confidence: 99%

Single firm product diffusion model for single-function and fusion products

Chen¹,

Carrillo²

2011

European Journal of Operational Research

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The prosperity of multifunction products (also referred to as fusion products) has changed the landscape of the marketplace for several electronics products. To illustrate, as fusion products gain popularity in cellular phones and office machines, we observe that single-function products (e.g., stand-alone PDAs and stand-alone scanners) gradually disappear from the market as they are supplanted by fusion products. This paper presents a product diffusion model that captures the diffusion transition from two distinct single-function products into one fusion product. We investigate the optimal launch time of the fusion product in various conditions and conduct a numerical analysis to demonstrate the dynamics among the three products. Similar to previous multi-generation single product diffusion models, we find that the planning horizon, the products' relative profit margin, and substitution effects are important to the launch time decision. However, there are several unique factors that warrant special consideration when a firm introduces a fusion product to the market: the firm's competitive role, buyer consolidation of purchases to a multifunction product, the fusion technology and the age of current single-function products.

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“…Customer requirements may also be inferred from the sales of products, by regarding the acts of purchase as customer needs and preferences expressions. In this study, an appropriately scaled and disguised proprietary dataset from a personal computer manufacturer is employed [57]. The data relates the purchases of five types of personal computer (P1-P5) over 38 months, in a particular market segment (see Table 2).…”

Section: A Case Studymentioning

confidence: 99%

“…The study has therefore demonstrated the function of the artificial neural network in approximating the variations of B-cells concentration levels over time domain. Table 2 Scaled personal computer sales data [57]. …”

Section: A Case Studymentioning

confidence: 99%