Supply Chain Efficiency and Effectiveness Management Using Decision Support Systems

Abstract

In supply chain management, decision support systems and time series forecasting play an essential role. The accuracy of time-series predictions is critical for the performance optimization of every supply chain. This article suggests a method based on state-space modelling (SSM) for structured time series forecasting. Technology and advance implementations of decision support systems (DSS) have improved considerably. DSS has been used as a more restricted functionality of the database, modelling, and user interface, although technical advances made DSS even more effective. Web development has facilitated inter-organizational decision-making support systems and has resulted in many innovative implementations of current technology and many new decision-making technologies. The study of multiple configurations shows that the SSM and DSS are ideal for solving the problem being studied; in particular, the DSS guarantees appropriate prediction errors and a correct computational effort to provide adequate customer order plans.