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The changing digital dynamics of multichannel marketing The feasibility of the weblog: text mining approach for fast fashion trending

The changing digital dynamics of multichannel marketing The feasibility of the weblog: text... Purpose – The purpose of this paper is to examine the theoretical/conceptual development and application of weblog‐textmining to fashion forecasting in general and street fashion trending in particular. Design/methodology/approach – The current methods of forecasting cannot keep pace with the changing dynamics of the marketplace – mostly due to the rampant diffusion of data/information. The company that can tap the continual flow of data/information in the present, contrast it with a stored set of information from the past, and adjust based on repeated cycles, will have the best insight into the lingering trend, changing trend, or dynamic trend. The paper uses a simple example to explain blog trend analysis using Nielsen BuzzMetrics' BlogPulse. Findings – The study finds that to make fashion weblog forecasting a reality, there needs to be a rich accumulation of fashion communication in structured blogs. In addition, there needs to be a classification of the various forms of industry web text, web venue. Furthermore, rich research traditions must be in place to chronicle the cultural, behavioral, linguistic, socioeconomic, and communication behaviors over time for the weblog and the fashion weblogger in particular. Practical implications – The changing dynamics of the fashion business makes it a good example for understanding the weblog‐text mining approach developed in this paper. Originality/value – The understanding and implementation of trend forecasting using blogs as data mining sources will add another dimension of forecasting techniques to survive the multi‐channel revolution in fashion marketing. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Fashion Marketing and Management Emerald Publishing

The changing digital dynamics of multichannel marketing The feasibility of the weblog: text mining approach for fast fashion trending

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References (26)

Publisher
Emerald Publishing
Copyright
Copyright © 2007 Emerald Group Publishing Limited. All rights reserved.
ISSN
1361-2026
DOI
10.1108/13612020710824634
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to examine the theoretical/conceptual development and application of weblog‐textmining to fashion forecasting in general and street fashion trending in particular. Design/methodology/approach – The current methods of forecasting cannot keep pace with the changing dynamics of the marketplace – mostly due to the rampant diffusion of data/information. The company that can tap the continual flow of data/information in the present, contrast it with a stored set of information from the past, and adjust based on repeated cycles, will have the best insight into the lingering trend, changing trend, or dynamic trend. The paper uses a simple example to explain blog trend analysis using Nielsen BuzzMetrics' BlogPulse. Findings – The study finds that to make fashion weblog forecasting a reality, there needs to be a rich accumulation of fashion communication in structured blogs. In addition, there needs to be a classification of the various forms of industry web text, web venue. Furthermore, rich research traditions must be in place to chronicle the cultural, behavioral, linguistic, socioeconomic, and communication behaviors over time for the weblog and the fashion weblogger in particular. Practical implications – The changing dynamics of the fashion business makes it a good example for understanding the weblog‐text mining approach developed in this paper. Originality/value – The understanding and implementation of trend forecasting using blogs as data mining sources will add another dimension of forecasting techniques to survive the multi‐channel revolution in fashion marketing.

Journal

Journal of Fashion Marketing and ManagementEmerald Publishing

Published: Sep 25, 2007

Keywords: Distribution channels and marketing; Worldwide web; Fashion; Forecasting; Text retrieval

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