Review on fashion color forecasting researches

Authors

  • Li-xia Chang Henan Institute of Science and Technology, Garment Department, Xinxiang, China
  • Wei-dong Gao Jiangnan University, Ministry of Education, Key Laboratory Eco-textiles, Wuxi, China
  • Ru-ru Pan Jiangnan University, Ministry of Education, Key Laboratory Eco-textiles, Wuxi, China
  • Yu-zheng Lu Jiangnan University, Ministry of Education, Key Laboratory Eco-textiles, Wuxi, China

Keywords:

fashion color forecasting, color palette, methodology, model

Abstract

Color forecasting is one of the major driving forces of the fashion and textile industry. Though individuals or teams attempt to accurately forecast the colors that consumers will purchase in the near future, approximately two years ahead, how the fashion color forecast, remains a mystery for the public. This article made an overview on the important contributions, having been obtained on fashion color forecasting. The current research achievements were mainly classified into two groups in terms of analysis subjects and methodology, as we called systematic and historical data analysis. As a conclusion, it showed that fashion color preference and consumers‘ emotional response to current fashion trends are the crucial factors during the establishment of accurate forecasting system in systematic analysis method. While though there is little benefit for the analysis only focused on the historical fashion color data to discuss the future color trend, there must be some links between the emotion, color story and historical fashion color data. Therefore it is necessary to establish a useful information, that could clearly link past fashion color data and the events influencing those color choices and as the tool for understanding how to build color palettes based upon the moods as an inspiration resource for the future fashion color trend.

Published

2012-12-31

Issue

Section

Review article

How to Cite

[1]
2012. Review on fashion color forecasting researches. Tekstil. 61, 7-12 (Dec. 2012), 262–269.

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