Forecasting analysis for global copper clad laminate market

Yu Yao Hsiao*, Fu Kwun Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Demand forecasting is one of critical reference by top managers to make the strategy decision for future investment. The copper clad laminate(CCL) is the key material for print circuit board(PCB) and it can apply for consumer, computer, LCD, communication, automotive, aero space, medicine and defense application. The total global sale for PCB in 2008 is US$ 48.2 billion. In this research, we use grey model GM(1,1), rolling grey model(RGM) and Bass diffusion model to analysis global CCL market by six market segments - paper, composite, FR-4, FR-4 High Tg, FR-4 halogen free, Specialty between 2001-2008. The forecasting accuracy of global CCL market by six market segment was evaluated along with mean absolute percentage error(MAPE). In this study, Bass diffusion model MAPE outperforms the others two models GM(1,1) and RGM for this global CCL market forecasting analysis and is recommend for global CCL market forecasting analysis.

Original languageEnglish
Title of host publicationProceedings - 3rd International Conference on Data Mining and Intelligent Information Technology Applications, ICMIA 2011
Pages217-221
Number of pages5
StatePublished - 2011
Externally publishedYes
Event3rd International Conference on Data Mining and Intelligent Information Technology Applications, ICMIA 2011 - Macau, Macao
Duration: 24 10 201126 10 2011

Publication series

NameProceedings - 3rd International Conference on Data Mining and Intelligent Information Technology Applications, ICMIA 2011

Conference

Conference3rd International Conference on Data Mining and Intelligent Information Technology Applications, ICMIA 2011
Country/TerritoryMacao
CityMacau
Period24/10/1126/10/11

Keywords

  • Bass diffusion model
  • Copper clad laminate
  • GM(1,1)
  • Print circuit board
  • Rolling GM

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