Simulation-based analytics: A systematic literature review

被引:16
作者
Ben Rabia, Mohamed Amine [1 ]
Bellabdaoui, Adil [1 ]
机构
[1] Mohammed V Univ Rabat, Informat Technol & Management ITM ENSIAS, Rabat, Morocco
关键词
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; SUPPLY CHAIN SIMULATION; BIG DATA ANALYTICS; BUSINESS INTELLIGENCE; DECISION-MAKING; DATA-DRIVEN; DATA WAREHOUSE; MANAGEMENT; FRAMEWORK; SUPPORT; OPPORTUNITIES;
D O I
10.1016/j.simpat.2022.102511
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页数:16
相关论文
共 93 条
[1]   Two decades of research on business intelligence system adoption, utilization and success - A systematic literature review [J].
Ain, NoorUl ;
Vaia, Giovanni ;
DeLone, William H. ;
Waheed, Mehwish .
DECISION SUPPORT SYSTEMS, 2019, 125
[2]   Application of predictive data mining to create mine plan flexibility in the face of geological uncertainty [J].
Ajak, Ajak Duany ;
Lilford, Eric ;
Topal, Erkan .
RESOURCES POLICY, 2018, 55 :62-79
[3]  
Ak R, 2015, PROCEEDINGS 2015 IEEE INTERNATIONAL CONFERENCE ON BIG DATA, P2782, DOI 10.1109/BigData.2015.7364081
[4]   Analytics-based decision-making for service systems: A qualitative study and agenda for future research [J].
Akter, Shahriar ;
Bandara, Ruwan ;
Hani, Umme ;
Wamba, Samuel Fosso ;
Foropon, Cyril ;
Papadopoulos, Thanos .
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2019, 48 :85-95
[5]  
Al-Taiban A., 2013, SPE SAUD AR SECT TEC, DOI [10.2118/168080-MS. SPE-168080-MS, DOI 10.2118/168080-MS.SPE-168080-MS]
[6]  
Alshaebi A., EVALUATION DIFFERENT, V7
[7]  
Amini S, 2017, 2017 5TH IEEE INTERNATIONAL CONFERENCE ON MODELS AND TECHNOLOGIES FOR INTELLIGENT TRANSPORTATION SYSTEMS (MT-ITS), P710, DOI 10.1109/MTITS.2017.8005605
[8]  
Aqlan F, 2017, WINT SIMUL C PROC, P3940, DOI 10.1109/WSC.2017.8248104
[9]   Advances in analytics: Integrating dynamic data mining with simulation optimization [J].
Better, M. ;
Glover, F. ;
Laguna, M. .
IBM JOURNAL OF RESEARCH AND DEVELOPMENT, 2007, 51 (3-4) :477-487
[10]   An Event-Based Data Warehouse to Support Decisions in Multi-Channel, Multi-Service Contact Centers [J].
Brunello, Andrea ;
Gallo, Paolo ;
Marzano, Enrico ;
Montanari, Angelo ;
Vitacolonna, Nicola .
JOURNAL OF CASES ON INFORMATION TECHNOLOGY, 2019, 21 (01) :33-51