Management Decision-Making, Artificial Intelligence and Analytics
Second Edition
Simone Gressel
- The Hague University of Applied Sciences, Netherlands.
David Pauleen
- Massey University, New Zealand
Nazim Taskin
- Massey University, New Zealand
If you’re in North America, please visit our Sage College Publishing website to purchase or sample this book:
Go to College Publishing WebsiteDescription
Both accessible and concise, this text examines data analytics, big data and AI from a managerial and organizational perspective and looks at how they can help managers become more effective decision-makers.
The second edition of this book has been fully revised and updated, including more content on AI throughout and more case studies from industry. Chapters look at emerging technologies and the ethical, security, privacy and legal aspects of data-driven decision-making.
Key updates include content on:
- How will AI impact management
- AI and automation
- Emerging technologies including GenAI
- How AI may augment, change and replace human decision-making.
- Ethical AI decision-making and responsible AI
Suitable for management students studying business analytics and decision-making or business and artificial intelligence at undergraduate, postgraduate and MBA levels.
The second edition of this book has been fully revised and updated, including more content on AI throughout and more case studies from industry. Chapters look at emerging technologies and the ethical, security, privacy and legal aspects of data-driven decision-making.
Key updates include content on:
- How will AI impact management
- AI and automation
- Emerging technologies including GenAI
- How AI may augment, change and replace human decision-making.
- Ethical AI decision-making and responsible AI
Suitable for management students studying business analytics and decision-making or business and artificial intelligence at undergraduate, postgraduate and MBA levels.
Contents
Chapter 1: Professional Mindsets
Chapter 1: Professional Mindsets
Chapter 2: Big Data, Analytics and AI
Chapter 2: Big Data, Analytics and AI
Chapter 3: Introduction to (Advanced) Analytics
Chapter 3: Introduction to (Advanced) Analytics
Chapter 4: Managing AI and Emerging Technologies
Chapter 4: Managing AI and Emerging Technologies
Chapter 5: Management Decision-Making
Chapter 5: Management Decision-Making
Chapter 6: Analytics in Management Decision-Making
Chapter 6: Analytics in Management Decision-Making
Chapter 7: Types of Managerial Decision-Makers
Chapter 7: Types of Managerial Decision-Makers
Chapter 8: Organizational Readiness for Data-Driven Decision-Making
Chapter 8: Organizational Readiness for Data-Driven Decision-Making
Chapter 9: Integrating Contextual Factors in Management Decision-Making
Chapter 9: Integrating Contextual Factors in Management Decision-Making
Chapter 10: Managing Technology’s Ethical, Security, Privacy and Legal Aspects
Chapter 10: Managing Technology’s Ethical, Security, Privacy and Legal Aspects
Description
Both accessible and concise, this text examines data analytics, big data and AI from a managerial and organizational perspective and looks at how they can help managers become more effective decision-makers.
The second edition of this book has been fully revised and updated, including more content on AI throughout and more case studies from industry. Chapters look at emerging technologies and the ethical, security, privacy and legal aspects of data-driven decision-making.
Key updates include content on:
- How will AI impact management
- AI and automation
- Emerging technologies including GenAI
- How AI may augment, change and replace human decision-making.
- Ethical AI decision-making and responsible AI
Suitable for management students studying business analytics and decision-making or business and artificial intelligence at undergraduate, postgraduate and MBA levels.
The second edition of this book has been fully revised and updated, including more content on AI throughout and more case studies from industry. Chapters look at emerging technologies and the ethical, security, privacy and legal aspects of data-driven decision-making.
Key updates include content on:
- How will AI impact management
- AI and automation
- Emerging technologies including GenAI
- How AI may augment, change and replace human decision-making.
- Ethical AI decision-making and responsible AI
Suitable for management students studying business analytics and decision-making or business and artificial intelligence at undergraduate, postgraduate and MBA levels.
Contents
Chapter 1: Professional Mindsets
Chapter 1: Professional Mindsets
Chapter 2: Big Data, Analytics and AI
Chapter 2: Big Data, Analytics and AI
Chapter 3: Introduction to (Advanced) Analytics
Chapter 3: Introduction to (Advanced) Analytics
Chapter 4: Managing AI and Emerging Technologies
Chapter 4: Managing AI and Emerging Technologies
Chapter 5: Management Decision-Making
Chapter 5: Management Decision-Making
Chapter 6: Analytics in Management Decision-Making
Chapter 6: Analytics in Management Decision-Making
Chapter 7: Types of Managerial Decision-Makers
Chapter 7: Types of Managerial Decision-Makers
Chapter 8: Organizational Readiness for Data-Driven Decision-Making
Chapter 8: Organizational Readiness for Data-Driven Decision-Making
Chapter 9: Integrating Contextual Factors in Management Decision-Making
Chapter 9: Integrating Contextual Factors in Management Decision-Making
Chapter 10: Managing Technology’s Ethical, Security, Privacy and Legal Aspects
Chapter 10: Managing Technology’s Ethical, Security, Privacy and Legal Aspects
Management Decision-Making, Artificial Intelligence and Analytics
October 2026 | 320 pages | Sage UK
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Both accessible and concise, this text examines data analytics, big data and AI from a managerial and organizational perspective and looks at how they can help managers become more effective decision-makers.
The second edition of this book has been fully revised and updated, including more content on AI throughout and more case studies from industry. Chapters look at emerging technologies and the ethical, security, privacy and legal aspects of data-driven decision-making.
Key updates include content on:
- How will AI impact management
- AI and automation
- Emerging technologies including GenAI
- How AI may augment, change and replace human decision-making.
- Ethical AI decision-making and responsible AI
Suitable for management students studying business analytics and decision-making or business and artificial intelligence at undergraduate, postgraduate and MBA levels.
The second edition of this book has been fully revised and updated, including more content on AI throughout and more case studies from industry. Chapters look at emerging technologies and the ethical, security, privacy and legal aspects of data-driven decision-making.
Key updates include content on:
- How will AI impact management
- AI and automation
- Emerging technologies including GenAI
- How AI may augment, change and replace human decision-making.
- Ethical AI decision-making and responsible AI
Suitable for management students studying business analytics and decision-making or business and artificial intelligence at undergraduate, postgraduate and MBA levels.
Table Of Contents:
- Chapter 1: Professional Mindsets
- Chapter 2: Big Data, Analytics and AI
- Chapter 3: Introduction to (Advanced) Analytics
- Chapter 4: Managing AI and Emerging Technologies
- Chapter 5: Management Decision-Making
- Chapter 6: Analytics in Management Decision-Making
- Chapter 7: Types of Managerial Decision-Makers
- Chapter 8: Organizational Readiness for Data-Driven Decision-Making
- Chapter 9: Integrating Contextual Factors in Management Decision-Making
- Chapter 10: Managing Technology’s Ethical, Security, Privacy and Legal Aspects