Nicht aus der Schweiz? Besuchen Sie lehmanns.de

The Future of Digital Business Innovation (eBook)

Trends and Practices
eBook Download: PDF
2016 | 1st ed. 2016
XXI, 185 Seiten
Springer International Publishing (Verlag)
978-3-319-26874-3 (ISBN)

Lese- und Medienproben

The Future of Digital Business Innovation - Vincenzo Morabito
Systemvoraussetzungen
53,49 inkl. MwSt
(CHF 52,25)
Der eBook-Verkauf erfolgt durch die Lehmanns Media GmbH (Berlin) zum Preis in Euro inkl. MwSt.
  • Download sofort lieferbar
  • Zahlungsarten anzeigen
This book identifies and discusses the main challenges facing digital business innovation and the emerging trends and practices that will define its future. The book is divided into three sections covering trends in digital systems, digital management, and digital innovation. The opening chapters consider the issues associated with machine intelligence, wearable technology, digital currencies, and distributed ledgers as their relevance for business grows. Furthermore, the strategic role of data visualization and trends in digital security are extensively discussed. The subsequent section on digital management focuses on the impact of neuroscience on the management of information systems, the role of IT ambidexterity in managing digital transformation, and the way in which IT alignment is being reconfigured by digital business. Finally, examples of digital innovation in practice at the global level are presented and reviewed. 
The book will appeal to both practitioners and academics. The text is supported by informative illustrations and case studies, so that practitioners can use the book as a toolbox that enables easy understanding and assists in exploiting business opportunities involving digital business innovation.


Vincenzo Morabito, PhD, is Associate Professor at the Management & Technology Department, Università Commerciale Luigi Bocconi (Bocconi University), Milan, Italy. He gained his doctorate from the Università Commerciale Luigi Bocconi and was a Research Scholar at both the Center for Information System Research, MIT Sloan School of Management (2006) and the Decision and Information Science Department, University of Florida (2005/2006). Vincenzo Morabito is in charge of the course on Business Organization, Management of Information Systems, and Information Management for the various degree programs of Bocconi University. He has participated in a variety of research projects, many financed by the Italian Ministry of University and Scientific Research (Ministero dell'Università e della Ricerca Scientifica e Tecnologica).

Vincenzo Morabito, PhD, is Associate Professor at the Management & Technology Department, Università Commerciale Luigi Bocconi (Bocconi University), Milan, Italy. He gained his doctorate from the Università Commerciale Luigi Bocconi and was a Research Scholar at both the Center for Information System Research, MIT Sloan School of Management (2006) and the Decision and Information Science Department, University of Florida (2005/2006). Vincenzo Morabito is in charge of the course on Business Organization, Management of Information Systems, and Information Management for the various degree programs of Bocconi University. He has participated in a variety of research projects, many financed by the Italian Ministry of University and Scientific Research (Ministero dell'Università e della Ricerca Scientifica e Tecnologica).

Foreword 6
Preface 8
Outline of the Book 9
References 9
Acknowledgments 10
Contents 16
Acronyms 22
Part I: Digital Systems Trends 23
1: Machine Intelligence 24
1.1 Introduction 24
1.2 Intelligent and Expert Systems 25
1.3 Machine Learning and Deep Learning 26
1.4 Data Mining and Pattern Recognition 27
1.4.1 Knowledge Discovery in Database (KDD) 28
1.4.2 Sample, Explore, Modify, Model and Assess (SEMMA) 30
1.4.3 Cross-Industry Standard Process for Data Mining (CRISP-DM) 30
1.5 Applications of Machine Intelligence in Industry 32
1.5.1 Artificial Intelligence (AI) in Healthcare 32
1.5.1.1 Smart Wearables and Healthcare 33
1.5.1.2 Intelligent Robotics in Healthcare 33
1.5.1.3 Data Mining in Healthcare 34
1.5.2 Artificial Intelligence (AI) in Manufacturing 34
1.5.2.1 AI in Oil Production Management 34
1.5.2.2 AI for the Reconfigurable Manufacturing Systems (RMS) 35
1.5.2.3 Hybrid AI System to Control Temperature in Steel Industry 35
1.5.2.4 Machine Intelligence Enhanced Robots in Manufacturing 36
1.6 Machine Intelligence for Smarter Industries 36
1.7 Challenges for Machine Intelligence 37
1.8 Case Studies 37
Point of Attention 38
Point of Attention 39
1.9 Summary 39
References 40
2: Wearable Technologies 43
2.1 Introduction 43
2.2 Market Size and Outlook 44
2.3 Trends for Wearable Adoption 47
2.4 Applications 49
2.4.1 Entertainment 49
2.4.1.1 Wearable Headsets 49
2.4.1.2 Smartwatches 49
2.4.1.3 Fitness Devices 49
2.4.2 Healthcare 50
2.5 Wearable Technology and Big Data 51
2.6 Challenges of Wearable Technology 52
2.6.1 Design Constraints 54
2.6.2 High Power Consumption 55
2.6.3 High Initial Cost and Usage Restrictions 55
2.6.4 Lack of Data Privacy and Security 55
2.6.4.1 Vulnerability of Google Glass on Public Wi-Fi 56
2.6.4.2 Denial-of-Service Attacks May Affect Doctors´ Tools 57
2.6.4.3 Privacy Is at Risk as Wearables Collect Data 57
2.6.4.4 Digital Pickpocketing Is Likely to Rise 57
2.6.4.5 Smartphone Connections Could Be Exploited 57
2.7 Case Studies 58
Point of Attention 58
Point of Attention 59
2.8 Summary 59
References 60
3: Digital Currencies and Distributed Ledgers 63
3.1 Introduction 63
3.2 Understanding Digital Currencies 64
3.2.1 Litecoin 68
3.2.2 BBQCoin 68
3.2.3 Chinacoin 68
3.2.4 Devcoin 68
3.2.5 Feathercoin 69
3.2.6 PPCoin 69
3.2.7 Novacoin 70
3.2.8 Groupcoin 70
3.2.9 Ixcoin 70
3.2.10 Namecoin 70
3.2.11 Terracoin 71
3.2.12 Ven 71
3.2.13 Zen 72
3.3 Digital Currencies Versus Distributed Ledger 72
3.4 Digital Currencies Advantages, Limitations, and Risks 73
3.5 Case Studies 75
Point of Attention 76
Point of Attention 77
3.6 Summary 78
References 78
4: Data Visualization 81
4.1 Introduction 81
4.2 The Power of Data Visualization 82
4.2.1 Interactive Data Visualization 83
4.3 Data Visualization: The State of the Art 84
4.4 Visualization Techniques 85
4.4.1 Radial and Hyperbolic Tree 86
4.4.2 Treemaps 86
4.4.3 Geo-spatial Visualization 87
4.4.4 Animated Data Visualization 88
4.4.5 Networks Visualization 88
4.5 Applications of Data Visualization in Industry 89
4.5.1 Data Visualization in Bioinformatics 91
4.5.2 Data Visualization in Social Sciences 94
4.5.2.1 Social Node-Link Visualization 94
4.5.2.2 Geographic Based Social Networks Visualization 95
4.5.2.3 Geo-temporal Based Social Networks Visualization 96
4.6 Key Factors for Good Visualization 96
4.7 Challenges Facing Data Visualization Software Development 97
4.8 Review of Data Visualization Tools 98
4.8.1 Tableau 98
4.8.2 JMP (SAS) 99
4.8.3 Qlik 99
4.8.4 IBM Cognos 99
4.8.5 Tibco Spotfire 100
4.9 Case Studies 100
Point of Attention 101
Point of Attention 101
4.10 Summary 101
References 102
5: Digital Security 104
5.1 Introduction 104
5.2 Digital Security Challenges Facing Business Organizations 105
5.3 The Rise of Malware Attacks 106
5.4 Digital Security Challenges Facing Business Organizations 107
5.5 Threat Implications on Business Organizations 108
5.5.1 Revenue Loss 108
5.5.2 Brand Damage 111
5.5.3 Data Loss 111
5.5.4 Recovery Costs 112
5.6 Existing Techniques for Disaster Recovery 113
5.6.1 Configuration Management 114
5.7 Case Studies 115
Point of Attention 117
Point of Attention 117
5.8 Summary 118
References 119
Part II: Digital Management Trends 122
6: NeuroIS 123
6.1 Introduction 123
6.2 Neurophysiological Tools: An Overview 124
6.2.1 Electroencephalogram Tools (Brain Imaging Tools) 124
6.2.2 Functional Magnetic Resonance Imaging (Brain Imaging Tools) 125
6.2.3 Electro Dermal Activity (Psychophysiological Tools) 126
6.3 Challenges of Neurophysiological Tools 126
6.3.1 Slow Information Transfer Rate 126
6.3.2 High Fault Rate 127
6.3.3 Autonomy 128
6.3.4 Varied Cognitive Load 128
6.4 Business Application of NeuroIS: Neuromarketing 128
6.4.1 The Barriers of Neuromarketing 130
6.4.2 Benefits of Neuromarketing 131
6.5 Challenges of Adopting Neuromarketing 132
6.6 Case Studies 132
Point of Attention 133
Point of Attention 134
Point of Attention 135
Point of Attention 135
6.7 Summary 136
References 137
7: Digital Transformation and IT Ambidexterity 139
7.1 Introduction 139
7.2 Organizational Transformation as Loss and Gain 142
7.2.1 IT Innovations as Disruptive IT Events 144
7.2.2 Types of IT Events 145
7.3 The Challenges of IT-Induced Changes for System Users 146
7.3.1 Employees´ Emotions 146
7.3.2 Users´ Psychological Stress 147
7.4 User Adaptation to Disruptive IT Events 148
7.4.1 Coping to IT-Related Organizational Changes 148
7.5 IT Ambidexterity and Organizational Agility 149
7.6 Case Studies 153
Point of Attention 153
Point of Attention 154
7.7 Summary 154
References 154
8: Digital Business Strategy and IT Alignment 159
8.1 Introduction 159
8.2 IT and Business Strategy 160
8.3 Digital Business Strategy 162
8.3.1 Scope of Digital Business Strategy 162
8.3.2 Scale of Digital Business Strategy 164
8.3.3 Speed of Digital Business Strategy 164
8.3.4 Value Creation and Capture 165
8.4 Getting Digitally Engaged 166
8.5 Think Data Think Bigger 168
8.5.1 Volume 170
8.5.2 Velocity 170
8.5.3 Variety 171
8.6 Case Studies 172
Point of Attention 173
Point of Attention 174
8.7 Summary 175
References 176
Part III: Digital Innovation Practices 178
9: Innovation Practices 179
9.1 Introduction 179
9.2 Skytree 180
9.2.1 Developer 180
9.2.2 Applications 181
9.3 DataHero 182
9.3.1 Developer 182
9.3.2 Applications 183
9.4 Ripjar 184
9.4.1 Developer 184
9.4.2 Applications 184
9.5 Oculus 185
9.5.1 Developers 185
9.5.2 Applications 186
9.6 Ginger.io 187
9.6.1 Developer 187
9.6.2 Applications 188
9.7 iMotions 188
9.7.1 Developer 189
9.7.2 Applications 190
9.8 Abatis 191
9.8.1 Developer 191
9.8.2 Applications 192
9.9 Dataloop 193
9.9.1 Developers 193
9.9.2 Applications 194
9.10 Summary 195
References 195
10: Conclusion 197
10.1 Digital Business Innovation: A Toolbox for a Future Agenda 197
References 198
Index 199

Erscheint lt. Verlag 5.3.2016
Zusatzinfo XXI, 185 p. 40 illus. in color.
Verlagsort Cham
Sprache englisch
Themenwelt Mathematik / Informatik Informatik
Wirtschaft Betriebswirtschaft / Management Wirtschaftsinformatik
Schlagworte Business technology organization • Data Visualization • digital business innovation • digital currencies • digital governance • Digital strategy and transformation • Innovation practices • machine intelligence • Management of Information Systems • wearable technology
ISBN-10 3-319-26874-0 / 3319268740
ISBN-13 978-3-319-26874-3 / 9783319268743
Haben Sie eine Frage zum Produkt?
PDFPDF (Wasserzeichen)
Größe: 3,0 MB

DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasser­zeichen und ist damit für Sie persona­lisiert. Bei einer missbräuch­lichen Weiter­gabe des eBooks an Dritte ist eine Rück­ver­folgung an die Quelle möglich.

Dateiformat: PDF (Portable Document Format)
Mit einem festen Seiten­layout eignet sich die PDF besonders für Fach­bücher mit Spalten, Tabellen und Abbild­ungen. Eine PDF kann auf fast allen Geräten ange­zeigt werden, ist aber für kleine Displays (Smart­phone, eReader) nur einge­schränkt geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.

Zusätzliches Feature: Online Lesen
Dieses eBook können Sie zusätzlich zum Download auch online im Webbrowser lesen.

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

Mehr entdecken
aus dem Bereich
Datenanalyse für Künstliche Intelligenz

von Jürgen Cleve; Uwe Lämmel

eBook Download (2024)
De Gruyter (Verlag)
CHF 73,20
Digitale Geschäftsmodelle auf Basis Künstlicher Intelligenz

von Christian Aichele; Jörg Herrmann

eBook Download (2023)
Springer Fachmedien Wiesbaden (Verlag)
CHF 53,70
Wie Sie Daten für die Steuerung von Unternehmen nutzen

von Mischa Seiter

eBook Download (2023)
Vahlen (Verlag)
CHF 38,95