Format:
1 Online-Ressource (236 Seiten)
ISBN:
9783030827632
Series Statement:
EAI/Springer Innovations in Communication and Computing Ser
Note:
Description based on publisher supplied metadata and other sources
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Intro -- Foreword -- Preface -- Acknowledgments -- Contents -- About the Editors -- 1 Analytics Techniques: Descriptive Analytics, Predictive Analytics, and Prescriptive Analytics -- 1.1 Introduction -- 1.2 Analytics -- 1.2.1 Role of Analytics in Business -- 1.2.2 Types of Analytics -- 1.3 Descriptive Analytics -- 1.3.1 Functions of Descriptive Analytics -- 1.3.2 Advantages of Descriptive Analytics -- 1.3.3 Descriptive Analytics and Its Uses -- 1.3.4 Need for Other Analytics -- 1.4 Predictive Analytics -- 1.4.1 Steps in Predictive Analytics -- 1.4.2 Predictive Analytics and Its Uses -- 1.4.3 Predictive Analytics Examples -- 1.5 Prescriptive Analytics -- 1.5.1 Advantages of Prescriptive Analytics -- 1.5.2 Prescriptive Analytics and Its Uses -- 1.5.3 Prescriptive Analytics Examples -- 1.6 Conclusion -- 1.7 Future Directions -- References -- 2 A Complete Overview of Analytics Techniques: Descriptive, Predictive, and Prescriptive -- 2.1 Introduction -- 2.2 Descriptive Analytics -- 2.2.1 The Ratio Analysis: An Elaborate Example of Descriptive Analytics in Business -- 2.2.2 The Gist of Descriptive Analytics -- 2.3 Predictive Analytics -- 2.4 Statistics -- 2.4.1 How Does It Work? -- 2.4.1.1 Classification Models -- 2.4.1.2 Regression Models -- 2.4.2 Predictive Analytics Process -- 2.4.3 Predictive Analytics Tools -- 2.4.4 Uses of Predictive Analytics in Different Industries -- 2.4.5 Why Now? -- 2.5 Prescriptive Analytics -- 2.5.1 Introduction -- 2.5.2 Background of Prescriptive Analytics -- 2.5.3 Methods for Prescriptive Analytics -- 2.5.3.1 Probabilistic Models -- 2.5.3.2 Machine Learning -- 2.5.3.3 Statistical Analysis -- 2.5.3.4 Mathematical Programming -- 2.5.3.5 Evolutionary Computation -- 2.5.3.6 Simulation -- 2.5.3.7 Logic-Based Models -- 2.6 Conclusion -- 2.7 Conclusion -- References
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3 Artificial Intelligence and Analytics for Better Decision-Making and Strategy Management -- 3.1 Introduction -- 3.2 India and AI -- 3.3 Potential of AI -- 3.3.1 Healthcare -- 3.3.2 Agriculture -- 3.3.3 Education -- 3.3.4 Smart Mobility in Transportation -- 3.4 Role of AI in Decision-Making -- 3.4.1 Strategic Management and AI -- 3.4.2 Key Challenges to Adopt AI in India -- 3.5 Conclusion -- References -- 4 Artificial Intelligence: Game Changer in Management Strategies -- 4.1 Introduction -- 4.2 Concept of Artificial Intelligence -- 4.3 Background of "AI" -- 4.4 The Digital Business Vagueness -- 4.5 Digital Transformation in Management -- 4.5.1 Ambition of the Organization -- 4.5.2 To Design a Product -- 4.5.3 Deliver Phase -- 4.5.4 Scaling -- 4.5.5 To Refine -- 4.6 Artificial Intelligence in Organization -- 4.7 Who Is Manager? -- 4.8 "Strategic Management" -- 4.8.1 Connection Between Strategic Management and Artificial Intelligence -- 4.8.2 Improvement and Redefining in the Organization Strategies Vis-a-Vis AI -- 4.8.3 Artificial Intelligence on Strength, Weakness, Opportunities, Threat (SWOT) -- 4.9 Conclusion -- References -- 5 Prospects and Future of Artificial Intelligence (AI) in Business Strategies -- 5.1 Introduction -- 5.2 Literature Review Including Research Gap -- 5.3 Materials and Methods -- 5.3.1 Worldwide Companies or Owners of Humanoid and Related to AI -- 5.3.2 Workforce Domain Contains Retention -- 5.4 Case Study and Application -- 5.4.1 Workforce Planning -- 5.4.1.1 Human Office and Oversight -- 5.4.1.2 Specialized Robustness and Well-being -- 5.4.1.3 Security and Data Organization -- 5.4.1.4 Straightforwardness -- 5.4.1.5 Assortment, Non-isolation, and Sensibility -- 5.4.1.6 Social and Common Success -- 5.4.1.7 Obligation -- 5.4.2 The Interest of Denmark, Finland, France, and Germany in AI is Likewise Significant
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5.4.2.1 Occupation Misfortunes AI in the Work Environment Have Meanings of Mass Occupation Misfortunes -- 5.4.2.2 Expenses -- 5.4.2.3 Absence of Mindfulness -- 5.5 Safety Measures -- 5.5.1 Diminishes Human Error -- 5.5.2 Attempts of Hazardous Undertakings -- 5.5.3 Track Worker Location and That is Only the Tip of the Iceberg -- 5.5.4 Screens Workplace Harassment -- 5.5.5 Work Environment Automation -- 5.6 Recruitment -- 5.7 Authors' Contribution -- 5.8 Result or Conclusion with Future Scope -- References -- 6 Artificial Intelligence: Technologies, Applications, and Policy Perspectives. Insights from Portugal -- 6.1 Introduction -- 6.2 Methodology -- 6.3 AI: Themes, Sectors, and Applications -- 6.4 Policy Reflections About Fostering Artificial Intelligence -- 6.5 EU Artificial Intelligence Strategy 2030 -- 6.6 Portugal Artificial Intelligence Overview -- 6.7 Portuguese AI Case Studies -- 6.8 Artificial Intelligence Policy Ramifications -- 6.9 Conclusion -- References -- 7 The Rise of Decision Intelligence: AI That Optimizes Decision-Making -- 7.1 The Rise of Decision Intelligence (DI) -- 7.2 The Rise of Decision Intelligence (DI) -- 7.3 An Opinion to Decision-Making -- 7.3.1 Decisions Are Judgements -- 7.3.2 Know the Criteria of Relevant Information/Data -- 7.3.3 Test your Opinions Against Reality/Actual Data -- 7.4 Decision Intelligence: The Pathway -- 7.5 A Framework of DI -- 7.6 The Emergence of Machines as Aids in Society -- 7.7 The Evolving Pervasiveness of AI and Capabilities in Human Life -- 7.8 AI, Decision Intelligence, and Business Organizations -- References -- 8 A Survey on Analytics Technique Used for Business Intelligence -- 8.1 Introduction -- 8.2 Literature Review -- 8.3 Models and Techniques: An Overview -- 8.4 Applications -- 8.5 Conclusion -- References
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9 Decision Intelligence Analytics: Making Decisions Through Data Pattern and Segmented Analytics -- 9.1 Introduction -- 9.2 Basic Terminologies -- 9.2.1 Panel Data Analysis -- 9.2.2 Formal Concept Analysis -- 9.3 Formal Panel Concept Analysis -- 9.4 Representation of Panel Data -- 9.5 Experimental Results -- 9.6 Conclusion -- References -- 10 Amalgamation of Business Intelligence with Corporate Strategic Management -- 10.1 Introduction -- 10.2 Strategic Management -- 10.3 The Role of Business Intelligence on Strategic Management Choices -- 10.4 The Role of Data Quality in Strategic Management -- 10.5 The Business Intelligence for Development of Data Integration -- 10.6 The Business Intelligence for the Development of a Reporting System -- 10.7 The Business Intelligence for Developing Future Scenarios -- 10.8 The Business Intelligence for Optimising Processes -- 10.9 The Role of Business Intelligence on Obtaining a Competitive Advantage -- 10.10 Case Study -- 10.11 Conclusion -- References -- 11 Role of Decision Intelligence in Strategic Business Planning -- 11.1 Introduction -- 11.2 Why Does Strategic Business Planning Need Decision Intelligence? And Decision Intelligence: How it Influences SBP? -- 11.2.1 Strategic Business Planning -- 11.2.2 Decision Intelligence -- 11.3 Decision Intelligence in Strategic Business Planning -- 11.4 Decision Intelligence and Strategic Business Planning Misconceptions -- 11.5 Conclusion/Recommendations -- References -- 12 Social and Web Analytics: An Analytical Case Study on Twitter Data -- 12.1 Introduction -- 12.2 Social Media Platforms and Analytics Tools -- 12.2.1 Social Media Platforms -- 12.2.2 Social Media Analytical Tools -- 12.3 Social Media Data Collection Using Twitter API -- 12.3.1 Data Collection from Twitter -- 12.3.2 Data Labeling -- 12.3.3 Data Pre-Processing and Cleaning -- 12.3.4 Data Analytics
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12.4 Conclusion -- References -- 13 People Analytics: Augmenting Horizon from Predictive Analytics to Prescriptive Analytics -- 13.1 Introduction -- 13.2 People Analytics Constituents -- 13.3 Descriptive People Analytics -- 13.4 Predictive People Analytics -- 13.5 Prescriptive People Analytics -- 13.6 Conclusion -- References -- 14 Machine Learning Based Predictive Analytics: A Use Case in Insurance Sector -- 14.1 Introduction -- 14.1.1 Descriptive Analytics -- 14.1.2 Diagnostic Analytics -- 14.1.3 Predictive Analytics -- 14.1.4 Prescriptive Analytics -- 14.2 Machine Learning Empowering Predictive Analytics -- 14.3 A Use Case of Machine Learning and Predictive Analytics: Prediction of Insurance Premium -- 14.3.1 Dataset Description -- 14.3.2 Exploratory Data Analysis -- 14.3.3 Implementation of Prediction Model and Results -- 14.4 Conclusion -- References -- 15 Machine Learning Applications in Decision Intelligence Analytics -- 15.1 Introduction -- 15.1.1 Application of Machine Learning -- 15.1.1.1 Virtual Personal Assistants (VPA's) -- 15.1.1.2 Traffic Predictions -- 15.1.1.3 Social Media Personalization -- 15.1.1.4 Email Spam Filtering -- 15.1.1.5 Online Fraud Detection -- 15.1.1.6 Assistive Medical Technology -- 15.1.1.7 Automatic Translation -- 15.1.1.8 Recommendation Engines -- 15.2 Summary and Conclusion -- References -- 16 Demystifying Behavioral Biases of Traders UsingMachine Learning -- 16.1 Introduction -- 16.1.1 Confirmation Bias -- 16.1.2 Illusion of Control Bias -- 16.1.3 Availability Bias -- 16.1.4 Representativeness Bias -- 16.1.5 Framing Bias -- 16.1.6 Self-Attribution Bias -- 16.1.7 Recency Bias -- 16.1.8 Outcome Bias -- 16.1.9 Cognitive Dissonance Bias -- 16.2 Concluding Remarks -- References
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17 Real-Time Data Visualization Using Business Intelligence Techniques in Small and Medium Enterprises for Making a Faster Decision on Sales Data
Additional Edition:
Erscheint auch als Druck-Ausgabe Jeyanthi, P. Mary Decision Intelligence Analytics and the Implementation of Strategic Business Management Cham : Springer International Publishing AG,c2021 ISBN 9783030827625
Language:
English
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