03934nam 22004333 450 991084759590332120240508080251.03-658-44453-3(CKB)5860000000528023(MiAaPQ)EBC31319773(Au-PeEL)EBL31319773(Exl-AI)31319773(EXLCZ)99586000000052802320240508d2024 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierImplementation and Benefits of Digital Twin on Decision Making and Data Quality Management1st ed.Wiesbaden :Springer Vieweg. in Springer Fachmedien Wiesbaden GmbH,2024.©2024.1 online resource (188 pages)3-658-44452-5 Intro -- Foreword by Atilla Wohllebe -- Foreword by Stefan Waitzinger -- Acknowledgment -- Contents -- Abbreviations -- List of Figures -- List of Tables -- 1 Introduction -- 2 Literature Review -- 2.1 Basic Definitions -- 2.1.1 Data and Big Data -- 2.1.2 Analytics -- 2.1.3 Digital Twin -- 2.1.4 Decision Making -- 2.2 Data Quality Management -- 2.2.1 Data Quality -- 2.2.2 Data Quality Management -- 2.2.3 Corporate Data Quality Management -- 2.2.4 Data Quality Dimensions -- 2.3 Digital Twin -- 2.3.1 Digital Twin for Decision Making -- 2.3.2 Process Digital Twin -- 2.3.3 Five-Dimensional Digital Twin -- 2.3.4 Requirements -- 2.3.5 Industry Dissemination -- 2.3.6 Benefits -- 2.4 Decision Support System -- 2.4.1 Decision Support System -- 2.4.2 Model-Driven Decision Support System -- 2.4.3 Characteristics -- 2.5 Summary-Digital Twin-Driven Decision-Making Model -- 3 Objectives -- 3.1 Strategic Positioning -- 3.2 Digital Twin-Driven Decision-Making Model -- 3.3 Operational Effectiveness -- 4 Materials and Methods of Dissertation -- 4.1 Research Design -- 4.2 Data Collection and Sample Description -- 4.2.1 Data Collection Procedure -- 4.2.2 Sample Description -- 4.3 Methods for Data Analysis -- 5 Results and Evaluation -- 5.1 Data Analysis-Preliminary Study -- 5.1.1 Strategic Positioning -- 5.1.2 The Digital Twin-Driven Decision-Making Model -- 5.2 Data Analysis-Main Study -- 5.2.1 Strategic Positioning -- 5.2.2 The Digital Twin-Driven Decision-Making Model -- 5.2.3 Operational Effectiveness -- 6 Conclusions and Recommendations -- 6.1 Conclusion of Hypotheses -- 6.2 Recommendations -- 6.3 Practical Implications -- 6.4 Limitations -- 7 New Scientific Results -- 8 Summary -- References.This dissertation by Florian Blaschke explores the implementation and benefits of digital twin technology in decision-making and data quality management. With a focus on applications within manufacturing and e-commerce, the work highlights how digital twins, as virtual representations of physical systems, can optimize operations, enhance data accuracy, and support informed decision-making processes. The study delves into the potential of digital twins to improve productivity, reduce costs, and personalize consumer experiences. It emphasizes the importance of data quality management and suggests that digital twins will become increasingly vital in research and practice, particularly in the context of Industry 4.0. The book targets professionals and academics interested in the intersection of management, IT, and emerging technologies.Generated by AI.Digital twins (Computer simulation)Generated by AIData integrityGenerated by AIDigital twins (Computer simulation)Data integrity.Blaschke Florian1777111MiAaPQMiAaPQMiAaPQBOOK9910847595903321Implementation and Benefits of Digital Twin on Decision Making and Data Quality Management4296569UNINA