Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/230808
Authors: 
Wu, Desheng Dang
Härdle, Wolfgang Karl
Year of Publication: 
2020
Series/Report no.: 
IRTG 1792 Discussion Paper No. 2020-002
Abstract: 
With growing economic globalization, the modern service sector is in great need of business intelligence for data analytics and computational statistics. The joint application of big data analytics, computational statistics and business intelligence has great potential to make the engineering of advanced service systems more efficient. The purpose of this COST issue is to publish high- quality research papers (including reviews) that address the challenges of service data analytics with business intelligence in the face of uncertainty and risk. High quality contributions that are not yet published or that are not under review by other journals or peer-reviewed conferences have been collected. The resulting topic oriented special issue includes research on business intelligence and computational statistics, data-driven financial engineering, service data analytics and algorithms for optimizing the business engineering. It also covers implementation issues of managing the service process, computational statistics for risk analysis and novel theoretical and computational models, data mining algorithms for risk management related business applications.
Subjects: 
Data Analytics
Business Intelligence Systems
JEL: 
C00
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.