Particular kind of Production Systems move to substitute always more quickly their offering, defining new products with new proprieties in order to be competitive and enlarge target market. This is the case of a lot of industries, and one of the most representative is Fashion Industries. With changes of patterns, season by season and year by year, is impossible to analyze historical data series and apply traditional forecast models to evaluate expected sales. Are presented models, processes and applications to perform forecast in non continuative offering, basing on dynamic defining of comparative data between opposite seasons, sales campaign periods alignment, forecast algorithms, splitting bills definition to grant industrial forecast related to every single pattern (model, color, size), forcing tools to complete mathematical proposing with market evolution and enterprise directives.

Forecasting Models for Non Continuative Production Systems Application in Fashion Industry

BRUZZONE, AGOSTINO;MASSEI, MARINA;
2010-01-01

Abstract

Particular kind of Production Systems move to substitute always more quickly their offering, defining new products with new proprieties in order to be competitive and enlarge target market. This is the case of a lot of industries, and one of the most representative is Fashion Industries. With changes of patterns, season by season and year by year, is impossible to analyze historical data series and apply traditional forecast models to evaluate expected sales. Are presented models, processes and applications to perform forecast in non continuative offering, basing on dynamic defining of comparative data between opposite seasons, sales campaign periods alignment, forecast algorithms, splitting bills definition to grant industrial forecast related to every single pattern (model, color, size), forcing tools to complete mathematical proposing with market evolution and enterprise directives.
2010
978-145030069-8
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/276441
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