The Auto-ID Trajectory - Contents Page
Table of Contents
Certification ii
Dedication iii
List of Tables, Diagrams and Exhibits xi
Acronyms and Abbreviations xiii
Abstract xxi
Acknowledgments xxii
List of Publications, Conferences and Seminars xxiii
1. Introduction 1
1.1. Automatic Identification 1
1.1.1. Auto-ID Technologies 1
1.1.2. Auto-ID Applications 2
1.1.3. The Significance of Auto-ID 2
1.1.4. Auto-ID Innovation 2
1.2. Previous Research 3
1.2.1. Current Knowledge 4
1.2.2. The Emergence of the Auto-ID Paradigm 5
1.2.3. The Gap in the Literature 6
1.2.4. The Auto-ID Trajectory 7
1.3. Purpose 7
1.3.1. Aims and Objectives 8
1.4. Conceptual Framework and Methodology 9
1.4.1. Systems of Innovation 9
1.4.2. Case Studies 10
1.4.3. Underlying Assumptions 10
1.4.4. Outline 11
2. Literature Review 13
2.1. Fundamental Definitions in the Innovation Process 15
2.1.1. Invention, Innovation and Diffusion 15
2.1.1.1. Invention: Mutation, Recombination, Hybrid 15
2.1.1.2. Innovation: Radical versus Incremental 16
2.1.2. The Innovation Process: Product versus Process 17
2.2. Setting the Stage- Karl Marx on Technology 18
2.3. Neoclassical Economic Theory (1870 - 1960) 19
2.3.1. Joseph Alois Schumpeter 19
2.4. Evolutionary Economic Theory (1980 - 1990) 20
2.4.1. Typical Research Style 22
2.4.2. Fundamental Concepts 23
2.4.2.1. Technological Trajectories 24
2.4.2.2. Selection Environment and Other Terms 25
2.5. The Emergence of the Systems of Innovation Approach (1990 - ) 26
2.5.1. The Value of the SI Approach 27
2.5.2. Typical Research Style 29
2.5.2.1. SI Empirical Studies at the SIS or TS Level 31
2.6. Auto-ID Technology Studies 32
2.6.1. Bar Code 33
2.6.2. Magnetic-stripe Card 33
2.6.3. Smart Card 34
2.6.4. Biometrics 37
2.6.5. RF/ID Tags and Transponders 38
2.6.6. Auto-ID and Other Technologies 39
2.6.7. Landmark Studies on Auto-ID and Innovation Studies 40
2.7. Forecasting 41
2.7.1. From “Electronic Banks” to “Digital Money” 44
2.8. Conclusion 47
3. Research Design 50
3.1 Research Paradigm 50
3.1.1. Qualitative Strategy 50
3.2 Research Design 50
3.2.1. The Architecture 50
3.2.2. The Narrative Approach 52
3.2.2.1. Audience 53
3.2.2.2. Encoding 53
3.2.2.3. Quoting 54
3.3 Methodology 54
3.3.1. Multiple Embedded Case Study 55
3.3.2. Literal Replication 58
3.3.3. Case Study Protocol 61
3.3.4. External Validity 62
3.4. Data Collection 63
3.4.1. Systems of Innovation Bounds 63
3.4.2. Construct Validity 66
3.4.3. Multiple Sources of Evidence 67
3.4.3.1. Documentation 67
3.4.3.2. Archival Records 69
3.4.3.3. e-Research 70
3.5. Data Analysis 71
3.5.1. The Data Management Process 71
3.5.2. Toward Naturalistic Generalisations 73
3.5.3. Content Analysis 73
3.5.3.1. Coding 74
3.5.3.2. Pictures as Content 75
3.5.4. Reliability 75
3.6. Conclusion 76
4. Historical Background: From Manual to Auto-ID 77
4.1. Manual Identification 77
4.1.1. Identification Techniques Throughout the Ages 77
4.1.2. The Misuse of Manual ID 78
4.2. Advances in Record Keeping 80
4.2.1. The Census- Registering the Population 80
4.2.2. The Notion of a Personal Document File 81
4.3. The Evolution of the Citizen ID Number 84
4.3.1. Case: The U.S. Social Security Administration (SSA) 84
4.3.1.1. The SSN Gathers Momentum 85
4.3.1.2. The Computerisation of Records 86
4.3.1.3. Problems with Government Citizen Identifiers 87
4.4. The Rise of Automatic Identification Techniques 88
4.4.1. The Commercialisation of Identification 88
4.4.2. Too Many IDs? 89
4.4.2.1. Numbers Everywhere 90
4.5. Conclusion 91
5. The Development of Auto-ID Technologies 92
5.1. Bar Codes 92
5.1.1. Revolution at the Check-out Counter 92
5.1.2. The Importance of Symbologies 94
5.1.3. Bar Code Limitations 97
5.2. Magnetic-Stripe Cards 97
5.2.1. The Virtual Banking Revolution (24x7) 98
5.2.2. Encoding the Magnetic-strip 100
5.2.3. Magnetic-stripe Drawbacks 102
5.3. Smart Cards 103
5.3.1. The Evolution of the Chip-in-a-Card 103
5.3.2. Memory and Microprocessor Cards 106
5.3.3. Standards and Security 108
5.4. Biometrics 110
5.4.1. Leaving Your Mark 110
5.4.2. Biometric Diversity 112
5.4.2.1. Fingerprint Recognition 114
5.4.2.2. Hand Recognition 115
5.4.2.3. Face Recognition 115
5.4.2.4. Iris Recognition 116
5.4.2.5. Voice Recognition 117
5.4.3. Is There Room for Error? 117
5.5. RF/ID Tags and Transponders 118
5.5.1. Non-contact ID 118
5.5.2. Active versus Passive Tags and Transponders 120
5.5.2.1. RF/ID Components Working Together 121
5.6. Evolution or Revolution? 122
5.6. Conclusion 125
6. The Dynamics of the Auto-ID Innovation System 127
6.1. Definition of Stakeholders 127
6.2. Bar Code: The Auto-ID Pioneer Technology 129
6.2.1. Committees, Subcommittees and Councils 129
6.2.2. Public Policy 132
6.2.3. Spreading the Word 133
6.2.4. Clusters of Knowledge and a Growing Infrastructure 134
6.2.5. Setting Standards 136
6.2.6. Legal Aspects 138
6.3. Magnetic-Stripe Card: the Consolidating Force 139
6.3.1. Retail and Banking Associations Join Forces 139
6.3.2. From Exclusivity to Interoperability 140
6.3.3. The ATM Economic Infrastructure 141
6.3.3.1. The Global Inter-bank Network 142
6.3.4. Calculated Social Change 143
6.3.5. A Patchwork of Statutes 146
6.3.6. Incremental Innovations 148
6.3.7. Collaborative Research 150
6.4. Smart Card: the Next Generation 151
6.4.1. Social Specialisation of Labour 151
6.4.2. Firm-to-Firm Collaboration 153
6.4.3. Geographic Clustering 154
6.4.3.1. Private Enterprise and University 155
6.4.3.2. Consortiums and Alliances 156
6.4.4. Communicating Information 157
6.4.5. The Importance of ISO 158
6.4.5.1. Specifications 159
6.4.6. Legal, Regulatory and Policy Issues 160
6.5. Biometrics: In Search of a Full-Proof Solution 163
6.5.1. An Emerging Technology 163
6.5.2. From Proprietary to Open Standards 165
6.5.2.1. BioAPI 166
6.5.3. Consortiums and Associations 167
6.5.4. Government and Industry Links with Academia 168
6.5.5. Legislation and New Technologies 169
6.5.6. Privacy: Friend or Foe? 172
6.5.7. End-User Resistance 174
6.6. RF/ID Tags and Transponders: The New Arrival 176
6.6.1. A Time to Grow, a Time to Nurture 176
6.6.2. Standardisation: Opposing Forces at Hand 178
6.6.2.1. From Industry-Specific to Global Standards 179
6.6.2.2. Organisations Supporting Change 180
6.6.3. Abiding to Regulations 181
6.6.3.1. Frequency Ranges and Radio Regulations 181
6.6.3.2. Application-specific Regulations 182
6.6.4. The Importance of Collaboration 183
6.6.4.1. Collaboration within the Firm 183
6.6.4.2. Private Enterprise and University Collaboration 184
6.6.5. Patent Explosion 186
6.6.6. Necessary Product Improvements 187
6.6.6.1. Consumer Fears 189
6.6.7. Once Labelled Conspiracy Theories 190
6.7. Conclusion 192
7. Ten Cases in the Selection and Application of Auto-ID 193
7.1. Bar code Product Innovation 194
7.1.1. Case 1: Retail 196
7.1.1.1. RF/ID Complementary or Replacement? 197
7.1.2. Case 2: Education 199
7.1.2.1. Smart Card or Hybrid Card 201
7.2. Magnetic-stripe Card Product Innovation 203
7.2.1. Case 3: Financial Services 205
7.2.1.1. Are Magnetic-stripe Cards Outdated? 206
7.2.1.1.1. Electronic Purse to Cashless Society 208
7.2.1.1.2. Biometrics and Beyond 210
7.2.2. Case 4: Transportation 211
7.2.2.1. The Smart Choice for Contactless Ticketing 213
7.3. Smart Cards Product Innovation 218
7.3.1. Case 5: Telecommunications 219
7.3.1.1. Smart versus “Dumb” Cards 222
7.3.2. Case 6: Health Care 224
7.3.2.1. Privacy Concerns over Smart Card 226
7.4. Biometric Product Innovations 227
7.4.1. Case 7: Government Services 231
7.4.1.1. Towards Integrated Auto-ID Systems 233
7.4.2. Case 8: Entertainment 237
7.4.2.1. Card Technologies Welcome 238
7.5. RF/ID Product Innovations 239
7.5.1. Case 9: Animal Tracking and Monitoring 240
7.5.1.1. Traditional Manual Identification for Animals 243
7.5.2. Case 10: Human Security and Monitoring 244
7.5.2.1. The Importance of the ID Number 250
7.6. Conclusion 252
8. The Auto-ID Trajectory: Converging Disciplines 254
8.1. The Rise of Wearable Computing 255
8.1.1. 1G Wearables: Mobile Phones, PDAs and Pagers 256
8.1.1.1. Industrial Application 258
8.1.2. 2G Wearables: E-Wallets and Wristwatches 260
8.1.2.1. Medical Application 262
8.1.3. 3G Wearables: Smart Clothes and Accessories 263
8.1.3.1. Military Application 265
8.2. The Paradigm Shift- From Wearable to Implantable Devices 266
8.2.1. The Role of Auto-ID 268
8.2.2. The Impact of Mobility 270
8.2.3. Global Positioning System (GPS) Tracking 272
8.2.4. Towards a Unique Identifier for UPT 275
8.3. Case Study: Auto-ID Adapted for Medical Implants 276
8.3.1. Biochips for Diagnosis and Smart Pills for Drug Delivery 277
8.3.2. Cochlear Implants- Helping the Deaf to Hear 279
8.3.3. Retina Implants- on a Mission to Help the Blind to See 280
8.3.4. Tapping into the Heart and Brain 282
8.3.4.1. Attempting to Overcome Paralysis 283
8.3.4.2. Granting a Voice to the Speech-impaired 284
8.4. Onward the Quest for Immortality 286
8.4.1. Towards Electrophoresis 288
8.4.1.1. The Soul Catcher Chip 289
8.5. The Evolutionary Paradigm 291
8.6 Conclusion 294
9. Evolving Trends and Patterns 295
9.1. Major Findings 295
9.1.1. The Auto-ID Industry as a Technology System (TS) 295
9.1.1.1. Auto-ID Technologies Share Same Trajectory 296
9.1.2. The Auto-ID Innovation Process 298
9.1.3. The Auto-ID Selection Environment 300
9.1.4. Auto-ID Device Migration, Integration and Convergence 302
9.1.4.1. Migration from Magnetic-stripe to Smart Cards 303
9.1.4.2. Migration from Bar Codes to RF/ID 305
9.1.4.3. Integration- the Rise of Multi-Technology Cards 306
9.1.4.4. Converging Auto-ID Technologies 306
9.1.5. Towards a Model of Coexistence 308
9.2. Minor Findings 310
9.2.1. The Suitability of SI in Studying Clusters of Technologies 310
9.2.2. The Requirement for Interaction Between Stakeholders 310
9.2.3. Increasing Level of Invasiveness in Auto-ID Techniques 312
9.2.4. The Wireless Communications Advantage 313
9.2.5. The Need to Forecast Auto-ID Innovation 314
9.2.6. Extensive Bibliography and Online Resources 315
9.3. Trends and Patterns Emerging from the Case Studies 315
9.3.1. Information Centralisation- Big Brother Plays “Eyes Spy” 316
9.3.1.1. Preserving Privacy in a Technological Society 317
9.3.2. Mandatory Proof of Identity 318
9.3.2.1. The Prospect of National ID Chip Implants 319
9.3.3. Regulating an Unexplored Technology 321
9.3.4. Social Consequences 323
9.3.5. The Potential for Health Risks 324
9.3.6. Religious Advocates Object to the “Mark” 325
9.3.7. From the ENIAC to High-Tech Gadgetry 328
9.3.7.1. Shifting Cultural Values 328
9.3.8. Ethics and a Growing Moral Dilemma 330
9.3.8.1. Beyond Chip Implants 331
9.4. The Evolution of the Electrophoresis Trajectory 332
9.4.1. Towards Ubiquitous Computing 332
9.4.1.1. The Human as an Electrophorus 334
9.4.2. Have We Really Thought About the Consequences? 335
10. Conclusion 338
10.1. Principal Conclusions 338
10.1.1. The Evolutionary Paradigm 338
10.1.2. Forecasting Technological Innovation 339
10.1.3. Technology is Autonomous 340
10.2. Major Implications 341
10.2.1. Reinterpreting the Meaning of Progress 341
10.2.2. Managing Technological Innovation 342
10.2.3. Who is in Control? 343
10.2.4. Back to the Future 344
10.3. Research Scope 345
10.3.1. Links to Earlier Findings 345
10.3.2. To Whom Do These Findings Apply? 345
10.3.3. Limitations 345
10.4. Recommendations 347
10.4.1. Further Research 347
10.4.2. Actions 348
10.5 Conclusion 349
Bibliography 352
Online Resources 428