Demand Management

Research output: Chapter in Book/Published conference outputChapter


In this chapter, we explore demand management for effective supply chain management. First, we introduce the concept and the SPSS (sense, predict, seize, and stabilize) model of demand management. Second, demand forecasting is discussed including both qualitative and quantitative methods. Third, we specifically look at time series forecasting using both the traditional methods such as Weight Moving Average, Exponential Smoothing, ARIMA and SARIMA, and the machine learning methods such as Random Forest Regression and Extreme Gradient Boosting (XGBoost).
Original languageEnglish
Title of host publicationSupply Chain Analytics Concepts, Techniques and Applications
PublisherPalgrave Macmillan
ISBN (Electronic)9783030922245
ISBN (Print)9783030922238
Publication statusPublished - 8 Apr 2022


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