Sales Forecasting for Fashion Retailing Service Industry: A Review
Open Access
- 21 November 2013
- journal article
- review article
- Published by Wiley in Mathematical Problems in Engineering
- Vol. 2013, 1-9
Abstract
Sales forecasting is crucial for many retail operations. It is especially critical for the fashion retailing service industry in which product demand is very volatile and product’s life cycle is short. This paper conducts a comprehensive literature review and selects a set of papers in the literature on fashion retail sales forecasting. The advantages and the drawbacks of different kinds of analytical methods for fashion retail sales forecasting are examined. The evolution of the respective forecasting methods over the past 15 years is revealed. Issues related to real-world applications of the fashion retail sales forecasting models and important future research directions are discussed.Keywords
This publication has 47 references indexed in Scilit:
- Demand Forecasting in the Fashion Industry: A ReviewInternational Journal of Engineering Business Management, 2013
- The hybrid forecasting model based on chaotic mapping, genetic algorithm and support vector machineExpert Systems with Applications, 2010
- Evolutionary extreme learning machinePattern Recognition, 2005
- Learning‐based fuzzy colour prediction system for more effective apparel designInternational Journal of Clothing Science and Technology, 2005
- Time Series Forecasting with a Hybrid Clustering Scheme and Pattern RecognitionIEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 2004
- Time series forecasting using a hybrid ARIMA and neural network modelNeurocomputing, 2003
- An exploratory investigation of new product forecasting practicesJournal of Product Innovation Management, 2002
- Fuzzy Adaptation of the Holt–Winter Model for Textile Sales-forecastingThe Journal of the Textile Institute, 1998
- An Application of the Bass Model in Long-Term New Product ForecastingJournal of Marketing Research, 1973
- Fashion Forecasting for a Mail Order Company Using a Bayesian ApproachJournal of the Operational Research Society, 1973