Development of an Adaptive Forecasting System: A Case Study of a PC Manufacturer in South Korea
| Autor: | Chihyun Jung, Dae-Eun Lim |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Engineering
Process (engineering) 020209 energy Demand patterns Geography Planning and Development 0211 other engineering and technologies Bayesian updating TJ807-830 02 engineering and technology Management Monitoring Policy and Law TD194-195 Renewable energy sources demand forecasting product life cycle Bass diffusion model Product lifecycle 0202 electrical engineering electronic engineering information engineering Operations management GE1-350 021103 operations research Environmental effects of industries and plants Renewable Energy Sustainability and the Environment business.industry Demand forecasting Industrial engineering Product (business) Environmental sciences ComputingMilieux_GENERAL Personal computer business Technology forecasting |
| Zdroj: | Sustainability; Volume 8; Issue 3; Pages: 263 Sustainability, Vol 8, Iss 3, p 263 (2016) |
| ISSN: | 2071-1050 |
| DOI: | 10.3390/su8030263 |
| Popis: | We present a case study of the development of an adaptive forecasting system for a leading personal computer (PC) manufacturer in South Korea. It is widely accepted that demand forecasting for products with short product life cycles (PLCs) is difficult, and the PLC of a PC is generally very short. The firm has various types of products, and the volatile demand patterns differ by product. Moreover, we found that different departments have different requirements when it comes to the accuracy, point-of-time and range of the forecasts. We divide the demand forecasting process into three stages depending on the requirements and purposes. The systematic forecasting process is then introduced to improve the accuracy of demand forecasting and to meet the department-specific requirements. Moreover, a newly devised short-term forecasting method is presented, which utilizes the long-term forecasting results of the preceding stages. We evaluate our systematic forecasting methods based on actual sales data from the PC manufacturer, where our forecasting methods have been implemented. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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