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Simulation-based analytics: A systematic literature review
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AI
DOI：10.1016/j.simpat.2022.102511.png)
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Abstract
En 中文
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 ana-lytics 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.
Keywords:
Business analytics
Business intelligence
Big data analytics
Artificial intelligence
Simulation & analytics ops
What-if analysis
Decision Support System
Data-driven decision making
Model-driven decision making
Journal
IF:
4.6
Papers:
2.6K
Citations:
4.8K