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Simulation-based analytics: A systematic literature review

TitreSimulation-based analytics: A systematic literature review
Publication TypeJournal Article
Year of Publication2022
AuthorsBen Rabia, MA, Bellabdaoui, A
JournalSimulation Modelling Practice and Theory
Volume117
Mots-clésArtificial intelligence, Big data, Business analytics, Competitive intelligence, Data Analytics, Data driven decision, Data-driven decision making, Decision making, Decision support systems, Decisions makings, Model-driven, Model-driven decision making, Predictive analytics, Simulation & analytic ops, Systematic literature review, What-if Analysis
Abstract

Over time, Decision Support Systems have helped decision makers solve complex problems through Operational Research and Simulation. Nowadays, data explosion is having a profound effect on the ways in which many sectors operate. This advent of massive data gives rise to new concepts and requires new methods and analysis tools. In this paper, we highlight the role of simulation in Business Analytics. In a framework-based analytics, simulation is a technique that can be incorporated into predictive or prescriptive stage. For that, we have posed research questions to limit results to what give a comprehensive description of models, techniques and architectures used in the hybridization between simulation and business analytics. The presented analyses confirm that simulation remains an indispensable mechanism for adding value to analytics project and the coupling between the two techniques is in its embryonic phase. A conclusion presented prospects and future improvements found during the writing of the research. © 2022 Elsevier B.V.

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85125647406&doi=10.1016%2fj.simpat.2022.102511&partnerID=40&md5=b8a2d6f53d7e2a53c6c1e7675770c74b
DOI10.1016/j.simpat.2022.102511
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