Article: Neural-Net Based Business Forecasting Journal: Journal of Business and Management (JBM) 2000 Vol.7 No.1 pp.92 - 99 Abstract: One of the major problems facing the music industry today concerns returned product. Predicting product return rates and quantities has been a challenge. The total industry-wide estimate for product return exceeds $1 billion annually. A significant portion of this waste can be traced to relatively poor product forecasting. Recent developments in artificial intelligence (AI) techniques suggest that there is an opportunity to improve the predictive ability of business forecasts. The primary purposes of this study are twofold: 1) to introduce the use of neural nets as a simple and user-friendly forecasting system and 2) to develop a prototype model for estimating product return and sales. The preliminary results show that a neural network can accurately predict product return over a wide range of sales and initial return volumes. The reported R-squares exceed 95%. The new generation in AI technologies holds considerable promise for improving forecasting in this dynamic business. Inderscience Publishers - linking academia, business and industry through research

Title: Neural-Net Based Business Forecasting

Authors: Owen Hall

Addresses: Author address listing can be found in the "About the Authors" section at the end of the article.

Abstract: One of the major problems facing the music industry today concerns returned product. Predicting product return rates and quantities has been a challenge. The total industry-wide estimate for product return exceeds $1 billion annually. A significant portion of this waste can be traced to relatively poor product forecasting. Recent developments in artificial intelligence (AI) techniques suggest that there is an opportunity to improve the predictive ability of business forecasts. The primary purposes of this study are twofold: 1) to introduce the use of neural nets as a simple and user-friendly forecasting system and 2) to develop a prototype model for estimating product return and sales. The preliminary results show that a neural network can accurately predict product return over a wide range of sales and initial return volumes. The reported R-squares exceed 95%. The new generation in AI technologies holds considerable promise for improving forecasting in this dynamic business.

Keywords: Business forecasting; neural networks; artificial intelligence; music industry; product return; business forecasting; prototype model.

DOI: 10.1504/JBM.2000.141062

Journal of Business and Management, 2000 Vol.7 No.1, pp.92 - 99

Published online: 05 Sep 2024 *

Title: Neural-Net Based Business Forecasting

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