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AuthorHwang, W. Y.
AuthorLee, J. S.
Available date2015-11-05T10:37:49Z
Publication Date2014
Publication NameInternational Transactions in Operational Research
ResourceWiley Online library
CitationHwang, W.-Y. and Lee, J.-S. (2014), A new forecasting scheme for evaluating long-term prediction performances in supply chain management. International Transactions in Operational Research, 21: 1045�1060.
AbstractSupply chain management (SCM) practitioners in inventory sites are often required to predict the future sales of products in order to meet customer demands and reduce inventory costs simultaneously. Although a variety of forecasting methods have been developed, many of them may not be used in practice for various reasons, such as insufficient viable information about sales and oversophisticated methods. In this paper, we provide a new forecasting scheme to evaluate long-term prediction performances in SCM. Three well-known forecasting methods for time series data�moving average (MA), autoregressive integrated MA, and smoothing spline�are considered. We also focus on two representative sales patterns, each of which is with and without a growth pattern, respectively. By applying the proposed scheme to various simulated and real datasets, this research aims to provide SCM practitioners with a general guideline for time series sales forecasting, so that they can easily understand what prediction performance measures and which forecasting method can be considered.
SponsorMinistry of Education, Science and Technology. Grant Number: 2012R1A1A1012153
PublisherJohn Wiley & Sons, Ltd.
Subjecttime series
sales forecasting
supply chain management
long-term prediction performances
TitleA new forecasting scheme for evaluating long-term prediction performances in supply chain management
Issue Number6
Volume Number21

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