Kooperativer Bibliotheksverbund

UID:

Format: 1 Online-Ressource (X, 238 p. 35 illus., 30 illus. in color)

Edition: 1st ed. 2024

ISBN: 9783031635731

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-63572-4

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-63574-8

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-63575-5

Language: English

DOI: 10.1007/978-3-031-63573-1

URL: Volltext  (URL des Erstveröffentlichers)

UID:

Format: 1 Online-Ressource (XIX, 226 p. 66 illus., 56 illus. in color)

Edition: 1st ed. 2022

ISBN: 9783030827632

Series Statement: EAI/Springer Innovations in Communication and Computing

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-82762-5

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-82764-9

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-82765-6

Language: English

DOI: 10.1007/978-3-030-82763-2

URL: Volltext  (URL des Erstveröffentlichers)

UID:

Format: VIII, 206 Seiten , Illustrationen, Diagramme

ISBN: 9783110722642 , 311072264X

Series Statement: Smart computing applications volume 2

Additional Edition: Erscheint auch als Online-Ausgabe, PDF ISBN 978-3-11-072278-9

Additional Edition: Erscheint auch als Online-Ausgabe, EPUB ISBN 978-3-11-072293-2

Language: English

Subjects: Computer Science , Economics

Keywords: Wissensmanagement ; Geschäftsmodell ; Blockchain ; Semantic Web ; Aufsatzsammlung

URL: https://www.degruyter.com/isbn/9783110722642

URL: Inhaltsverzeichnis

URL: https://www.degruyter.com/isbn/9783110722642

UID:

Format: 1 Online-Ressource (VIII, 206 Seiten) : , Illustrationen, Diagramme.

ISBN: 978-3-11-072278-9

Series Statement: De Gruyter series on smart computing applications volume 2

Content: Knowledge Management makes the management of information and resources within a commercial organization more effective. The contributions of this book investigate the applications of Knowledge Management in the upcoming era of Semantic Web, or Web 3.0, and the opportunities for reshaping and redesigning business strategies for more effective outcomes

Additional Edition: Erscheint auch als Online-Ausgabe, EPUB ISBN 978-3-11-072293-2

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-11-072264-2

Language: English

Subjects: Computer Science , Economics

Keywords: Wissensmanagement ; Geschäftsmodell ; Blockchain ; Semantic Web ; Aufsatzsammlung ; Aufsatzsammlung

DOI: 10.1515/9783110722789

URL: Volltext  (URL des Erstveröffentlichers)

URL: Volltext  (URL des Erstveröffentlichers)

UID:

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 , 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 , 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 , 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 , 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 , 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 , 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

UID:

Format: 1 online resource (xvi, 350 pages) : , illustrations (some color).

Edition: First edition.

ISBN: 9781003300632 , 1003300634 , 9781000608892 , 1000608891 , 9781000608908 , 1000608905

Content: " With businesses becoming ever more competitive, marketing strategies need to be more precise and performance oriented. Companies are investing considerably in analytical infrastructure for marketing. This new volume, Marketing Analytics: A Machine Learning Approach, enlightens readers on the application of analytics in marketing and the process of analytics, providing a foundation on the concepts and algorithms of machine learning and statistics. The book simplifies analytics for businesses and explains its uses in different aspects of marketing in a way that even marketers with no prior analytics experience will find it easy to follow, giving them to tools to make better business decisions. This volume gives a comprehensive overview of marketing analytics, incorporating machine learning methods of data analysis that automates analytical model building. The volume covers the important aspects of marketing analytics, including segmentation and targeting analysis, statistics for marketing, marketing metrics, consumer buying behavior, neuromarketing techniques for consumer analytics, new product development, forecasting sales and price, web and social media analytics, and much more. This well-organized and straight-forward volume will be valuable for marketers, managers, decision makers, and research scholars, and faculty in business marketing and information technology and would also be suitable for classroom use."--

Additional Edition: Print version: Marketing analytics. Palm Bay, FL, USA ; Burlington, ON, Canada : Apple Academic Press ; Boca Raton, FL, USA ; Abingdon, Oxon, UK : CRC Press, 2023 ISBN 1774910888

Additional Edition: ISBN 9781774910887

Language: English

Keywords: Electronic books.

DOI: 10.1201/9781003300632

URL: https://www.taylorfrancis.com/books/9781003300632