The data industry: the business and economics of information and big data
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Hoboken, NJ
Wiley
[2016]
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xx, 195 Seiten Illustrationen |
| ISBN: | 9781119138402 |
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Datensatz im Suchindex
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|---|---|
| adam_text | CONTENTS
Preface
1 What is Data Industry?
1.1 Data, 2
1.1.1 Data Resources, 3
1.1.2 The Data Asset, 4
1.2 Industry, 6
1.2.1 Industry Classification, 7
1.2.2 The Modern Industrial System, 7
1.3 Data Industry, 10
1.3.1 Definitions, 10
1.3.2 An Industry Structure Study, 10
1.3.3 Industrial Behavior, 13
1.3.4 Market Performance, 16
2 Data Resources
2.1 Scientific Data, 19
2.1.1 Data-Intensive Discovery in the Natural Sciences, 20
2.1.2 The Social Sciences Revolution, 21
2.1.3 The Underused Scientific Record, 22
2.2 Administrative Data, 22
2.2.1 Open Governmental Affairs Data, 24
2.2.2 Public Release of Administrative Data, 25
2.2.3 A “Numerical” Misunderstanding in Governmental
Affairs, 26
xii
CONTENTS
2.3 Internet Data, 26
2.3.1 Cyberspace: Data of the Sole Existence, 27
2.3.2 Crawled Fortune, 28
2.3.3 Forum Opinion Mining, 28
2.3.4 Chat with Hidden Identities, 29
2.3.5 Email: The First Type of Electronic Evidence, 30
2.3.6 Evolution of the Blog, 31
2.3.7 Six Degrees Social Network, 32
2.4 Financial Data, 33
2.4.1 Twins on News and Financial Data, 33
2.4.2 The Annoyed Data Center, 33
2.5 Health Data, 34
2.5.1 Clinical Data: EMRs, EHRs, and PHRs, 34
2.5.2 Medicare Claims Data Fraud and Abuse Detection, 35
2.6 Transportation Data, 36
2.6.1 Trajectory Data, 37
2.6.2 Fixed-Position Data, 37
2.6.3 Location-Based Data, 38
2.7 Transaction Data, 38
2.7.1 Receipts Data, 39
2.7.2 e-Commerce Data, 39
3 Data Industry Chain 41
3.1 Industrial Chain Definition, 41
3.1.1 The Meaning and Characteristics, 41
3.1.2 Attribute-Based Categories, 43
3.2 Industrial Chain Structure, 43
3.2.1 Economic Entities, 44
3.2.2 Environmental Elements, 44
3.3 Industrial Chain Formation, 46
3.3.1 Value Analysis, 46
3.3.2 Dimensional Matching, 50
3.4 Evolution of Industrial Chain, 51
3.5 Industrial Chain Governance, 53
3.5.1 Governance Patterns, 53
3.5.2 Instruments of Governance, 54
3.6 The Data Industry Chain and its Innovation Network, 56
3.6.1 Innovation Layers, 56
3.6.2 A Support System, 57
4 Existing Data Innovations 59
4.1 Web Creations, 59
4.J..1 Network Writing, 60
4.1.2 Creative Designs, 61
CONTENTS
xiii
4.1.3 Bespoke Style, 62
4.1.4 Crowdsourcing, 63
4.2 Data Marketing, 63
4.2.1 Market Positioning, 64
4.2.2 Business Insights, 64
4.2.3 Customer Evaluation, 66
4.3 Push Services, 67
4.3.1 Targeted Advertising, 67
4.3.2 Instant Broadcasting, 68
4.4 Price Comparison, 69
4.5 Disease Prevention, 70
4.5.1 Tracking Epidemics, 71
4.5.2 Whole-Genome Sequencing, 72
5 Data Services in Multiple Domains 73
5.1 Scientific Data Services, 73
5.1.1 Literature Retrieval Reform, 74
5.1.2 An Alternative Scholarly Communication Initiative, 74
5.1.3 Scientific Research Project Services, 75
5.2 Administrative Data Services, 76
5.2.1 Police Department, 77
5.2.2 Statistical Office, 78
5.2.3 Environmental Protection Agency, 78
5.3 Internet Data Services, 79
5.3.1 Open Source, 79
5.3.2 Privacy Services, 80
5.3.3 People Search, 82
5.4 Financial Data Services, 82
5.4.1 Describing Correlations, 83
5.4.2 Simulating Market-Makers’ Behaviors, 84
5.4.3 Forecasting Security Prices, 85
5.5 Health Data Services, 86
5.5.1 Approaching the Healthcare Singularity, 87
5.5.2 New Drug of Launching Shortcuts, 87
5.5.3 Monitoring in Chronic Disease, 88
5.5.4 Data Supporting Data: Brain Sciences and Traditional Chinese
Medicine, 90
5.6 Transportation Data Services, 91
5.6.1 Household Travel Characteristics, 91
5.6.2 Multivariate Analysis of Traffic Congestion, 92
5.6.3 Short-Term Travel Time Estimation, 93
5.7 Transaction Data Services, 94
5.7.1 Pricing Reform, 94
5.7.2 Sales Transformation, 95
5.7.3 Payment Upgrading, 96
xiv
CONTENTS
6 Data Services in Distinct Sectors 99
6.1 Natural Resource Sectors, 99
6.1.1 Agriculture: Rely on What?, 100
6.1.2 Forestry Sector: Grain for Green at All Costs?, 101
6.1.3 Livestock and Poultry Sector: Making Early Warning to Be More
Effective, 101
6.1.4 Marine Sector: How to Support the Ocean
Economy?, 102
6.1.5 Extraction Sector: A New Exploration Strategy, 103
6.2 Manufacturing Sector, 104
6.2.1 Production Capacity Optimization, 104
6.2.2 Transforming the Production Process, 105
6.3 Logistics and Warehousing Sector, 106
6.3.1 Optimizing Order Picking, 106
6.3.2 Dynamic Equilibrium Logistic Channels, 107
6.4 Shipping Sector, 107
6.4.1 Extracting More Transportation Capacity, 108
6.4.2 Determining the Optimal Transfer in Road, Rail, Air, and Water
Transport, 108
6.5 Real Estate Sector, 109
6.5.1 Urban Planning: Along the Timeline, 109
6.5.2 Commercial Layout: To Be Unique, 110
6.5.3 Property Management: Become Intelligent, 110
6.6 Tourism Sector, 111
6.6.1 Travel Arrangements, 111
6.6.2 Pushing Attractions, 112
6.6.3 Gourmet Food Recommendations, 112
6.6.4 Accommodation Bidding, 113
6.7 Education and Training Sector, 113
6.7.1 New Knowledge Appraisal Mechanism, 114
6.7.2 Innovative Continuing Education, 114
6.8 Service Sector, 115
6.8.1 Prolong Life: More Scientific, 115
6.8.2 Elderly Care: Technology-Enhanced, Enough?, 116
6.8.3 Legal Services: Occupational Changes, 117
6.8.4 Patents: The Maximum Open Data Resource, 117
6.8.5 Meteorological Data Services: How to
Commercialize?, 118
6.9 Media, Sports, and the Entertainment Sector, 119
6.9.1 Data Talent Scout, 119
6.9.2 Interactive Script, 120
6.10 Public Sector, 121
6.10.1 Wargaming, 121
6.10.2 Public Opinion Analysis, 122
CONTENTS
xv
7 Business Models in the Data Industry 123
7.1 General Analysis of the Business Model, 123
7.1.1 A Set of Elements and Their Relationships, 124
7.1.2 Forming a Specific Business Logic, 125
7.1.3 Creating and Commercializing Value, 125
7.2 Data Industry Business Models, 126
7.2.1 A Resource-Based View: Resource Possession, 126
7.2.2 A Dynamic-Capability View: Endogenous
Capacity, 127
7.2.3 A Capital-Based View: Venture-Capital Operation, 128
7.3 Innovation of Data Industry Business Models, 129
7.3.1 Sources, 129
7.3.2 Methods, 131
7.3.3 A Paradox, 132
8 Operating Models in the Data Industry 135
8.1 General Analysis of the Operating Model, 136
8.1.1 Strategic Management, 136
8.1.2 Competitiveness, 137
8.1.3 Convergence, 137
8.2 Data Industry Operating Models, 138
8.2.1 Gradual Development: Google, 138
8.2.2 Micro-Innovation: Baidu, 139
8.2.3 Outsourcing: EMC, 140
8.2.4 Data-Driven Restructuring: IBM, 140
8.2.5 Mergers and Acquisitions: Yahoo!, 141
8.2.6 Reengineering: Facebook, 142
8.2.7 The Second Venture: Alibaba, 143
8.3 Innovation of Data Industry Operating Models, 144
8.3.1 Philosophy of Business, 144
8.3.2 Management Styles, 145
8.3.3 Force Field Analysis, 145
9 Enterprise Agglomeration of the Data Industry 147
9.1 Directive Agglomeration, 148
9.1.1 Data Resource Endowment, 148
9.1.2 Multiple Target Sites, 149
9.2 Driven Agglomeration, 149
9.2.1 Labor Force, 150
9.2.2 Capital, 150
9.2.3 Technology, 151
9.3 Industrial Symbiosis, 152
9.3.1 Entity Symbiosis, 152
9.3.2 Virtual Derivative, 153
xvi
CONTENTS
9.4 Wheel-Axle Type Agglomeration, 154
9.4.1 Vertical Leadership Development, 154
9.4.2 The Radiation Effect of Growth Poles, 154
9.5 Refocusing Agglomeration, 155
9.5.1 “Smart Heart” of the Central Business District, 155
9.5.2 The Core Objective “Besiege”, 156
10 Cluster Effects of the Data Industry 159
10.1 External Economies, 159
10.1.1 External Economies of Scale, 160
10.1.2 External Economies of Scope, 160
10.2 Internal Economies, 161
10.2.1 Coopetition, 161
10.2.2 Synergy, 163
10.3 Transaction Cost, 164
10.3.1 The Division of Cost, 164
10.3.2 Opportunity Cost, 165
10.3.3 Monitoring Cost, 166
10.4 Competitive Advantages, 167
10.4.1 Innovation Performance, 167
10.4.2 The Impact of Expansion, 168
10.5 Negative Effects, 169
10.5.1 Innovation Risk, 169
10.5.2 Data Asset Specificity, 169
10.5.3 Crowding Effect, 170
11 A Mode of Industrial Development for the Data Industry 171
11.1 General Analysis of the Development Mode, 171
11.1.1 Influence Factors, 172
11.1.2 Dominant Styles, 172
11.2 A Basic Development Mode for the Data Industry, 173
11.2.1 Industrial Structure: A Comprehensive Advancement Plan, 173
11.2.2 Industrial Organization: Dominated by the SMEs, 174
11.2.3 Industrial Distribution: Endogenous Growth, 174
11.2.4 Industrial Strategy: Self-Dependent Innovation, 175
11.2.5 Industrial Policy: Market Driven, 176
11.3 An Optimized Development Mode for the Data Industry, 176
11.3.1 New Industrial Structure: Built on Upgrading of Traditional
Industries, 176
11.3.2 New Industrial Organization: Small Is Beautiful, 178
11.3.3 New Industrial Distribution: Constructing a Novel Type of
Industrial Bases, 178
11.3.4 New Industrial Strategy: Industry/University Cooperation, 179
11.3.5 New Industrial Policy: Civil-Military Coordination, 180
CONTENTS
xvii
12 A Guide to the Emerging Data Law
12.1 Data Resource Law, 183
12.2 Data Antitrust Law, 185
12.3 Data Fraud Prevention Law, 186
12.4 Data Privacy Law, 187
12.5 Data Asset Law, 188
References
Index
183
189
193
|
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| spelling | Tang, Chunlei Verfasser (DE-588)1108589065 aut The data industry the business and economics of information and big data Chunlei Tang Hoboken, NJ Wiley [2016] © 2016 xx, 195 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier Information technology Economic aspects Big data Economic aspects Big Data (DE-588)4802620-7 gnd rswk-swf Data Mining (DE-588)4428654-5 gnd rswk-swf Informationswirtschaft (DE-588)4412411-9 gnd rswk-swf Informationswirtschaft (DE-588)4412411-9 s Data Mining (DE-588)4428654-5 s Big Data (DE-588)4802620-7 s DE-604 Erscheint auch als Online-Ausgabe, PDF 978-1-119-13841-9 Erscheint auch als Online-Ausgabe, EPUB 978-1-119-13842-6 Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029177821&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Tang, Chunlei The data industry the business and economics of information and big data Information technology Economic aspects Big data Economic aspects Big Data (DE-588)4802620-7 gnd Data Mining (DE-588)4428654-5 gnd Informationswirtschaft (DE-588)4412411-9 gnd |
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| title | The data industry the business and economics of information and big data |
| title_auth | The data industry the business and economics of information and big data |
| title_exact_search | The data industry the business and economics of information and big data |
| title_full | The data industry the business and economics of information and big data Chunlei Tang |
| title_fullStr | The data industry the business and economics of information and big data Chunlei Tang |
| title_full_unstemmed | The data industry the business and economics of information and big data Chunlei Tang |
| title_short | The data industry |
| title_sort | the data industry the business and economics of information and big data |
| title_sub | the business and economics of information and big data |
| topic | Information technology Economic aspects Big data Economic aspects Big Data (DE-588)4802620-7 gnd Data Mining (DE-588)4428654-5 gnd Informationswirtschaft (DE-588)4412411-9 gnd |
| topic_facet | Information technology Economic aspects Big data Economic aspects Big Data Data Mining Informationswirtschaft |
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