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Fashion Trends

Analysis and Forecasting
Authors: Eundeok Kim; Ann Marie Fiore; Alice Payne; Hyejeong Kim;

Fashion Trends

Abstract

In a fast-moving global industry how does anyone know what the next trend will be? To answer this question, fashion professionals engage in a systematic, analytical process to predict and understand changes in society and consumer behavior. Forecasting companies and developers collect information related to culture, the economy, politics, and technology that may influence future trends. Gleaning information wherever they can, online or from books, arts, music, movies, fashion, and architecture, fashion forecasters research cultural indicators that signpost new ways of living, shopping, and designing. Fashion Trends offers a clear pathway into the theory and practice of forecasting fashion, using professional case studies to demonstrate each technique and concept. This revised edition includes expanded coverage of social media, crowd sourcing, digital influencers, and the use of technology such as augmented reality, radio-frequency identification (RFID), and big data. With the rise of individualism, the authors also walk you through the “end of fashion” and what comes next, including clothing subscription and rental services, the circular economy, transparency and traceability, and the role of forecasting in provoking the desire for a sustainable lifestyle.

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    17
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Top 10%
Top 10%
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