Identifying Future Demand in Fashion Goods: Towards Data Driven Trend Forecasting
Received Date: July 26, 2019; Published Date: August 02, 2019
Fashion is primarily based on adoption of trends by consumers in textiles, clothing, footwear, jewelry and art, inter alia. As fashion is based on human preferences, it is characterized by dynamic changes throughout seasons and years, short lifecycles, low predictability, high volatility of demand and impulse purchases. In the dynamic environment of apparel markets, fashion firms aim at successfully forecasting both the desirability of new collections and the volumes of each item produced and released to the market under terms of substantial levels of uncertainty. When demand for an item exceeds its supply, the firm is likely to lose additional profits that could have been collected had a sufficient volume of this item been present in the market. Alternatively, if the supply of an item surpassed its demand, it would remain unsold, thereby generating loss equal to its marginal production and distribution costs.
The paper suggests that accurate fashion trend forecasting in the context of multiple variants of color clothing can significantly enhance trend forecasting in textiles, consequently maximizing the profits of fashion companies while minimizing the forecasting error and reducing the costs that result from excess capacity of production or from loss of potential revenues due to low demand.
Keywords: Trend forecasting; Color variants; Excessive supply; Excessive demand