3 Intelligent Decision-support Systems in Supply Chains: Requirements Identification
The research area on artificial intelligence and machine learning is pushing a trigger effect for the appearance of a new generation of intelligent decision-support systems (iDSS), which aim at achieving more efficient, agile and sustainable industrial systems. The implementation of intelligent DSS is conceived as a challenging issue for managing sustainable operations among the enterprises taking part in supply chains (SC), in an environment characterized by rapid changes and uncertainty. This paper establishes the state of the art and identifies new research challenges and trends for designing intelligent DSS, within the SC context (iDSS-SC).
Current markets, globally operating, must work in an environment that demands agility and resilience of the enterprises; in which the decision-making process has to be as quick as possible, by considering all the information available that may affect the decision. The consideration of DSS has been widely addressed in the context of individual enterprises [GOU 17]. Nevertheless, enterprises are more and more aware about the establishment of collaborative relationships, and business, among its downstream and upstream partners [AND 16]. It is because of this that the DSS research area needs to extend individual DSS towards an extended DSS that covers the decision-making process performed within the supply chain (SC) [BOZ 09]. Moreover, ...
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