Alan L. Porter, Scott W. Cunningham, Jerry Banks, A. Thomas Roper, Thomas W. Mason, Frederick A. Rossini

Forecasting and Management of Technology (eBook, PDF)

• Format: PDF

Produktbeschreibung

Published in 1991, the first edition of Forecasting and Management of Technology was one of the leading handful of books to deal with the topic of forecasting of technology and technology management as this discipline was emerging. The new, revised edition of this book will build on this knowledge in the context of business organizations that now place a greater emphasis on technology to stay on the cutting edge of development. The scope of this edition has broadened to include management of technology content that is relevant to now to executives in organizations while updating and strengthening the technology forecasting and analysis content that the first edition is reputed for. Updated by the original author team, plus new author Scott Cunningham, the book takes into account what the authors see as the innovations to technology management in the last 17 years: the Internet; the greater focus on group decision-making including process management and mechanism design; and desktop software that has transformed the analytical capabilities of technology managers. Included in this book will be 5 case studies from various industries that show how technology management is applied in the real world.

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 352
• Erscheinungstermin: 25. Mai 2011
• Englisch
• ISBN-13: 9781118048214
• Artikelnr.: 37360192

Autorenporträt

ALAN THOMAS ROPER (retired) was a professor at Rose-Hulman Institute of Technology in Terre Haute, Indiana. He is the past editor of the journal Impact Assessment and Project Appraisal and the past director of the Center for Technology and Policy Studies at Rose-Hulman. SCOTT W. CUNNINGHAM obtained a MSc in public policy from the Georgia Institute of Technology and a DPhil in science, technology, and innovation policy from the University of Sussex. He is currently Assistant Professor of Policy Analysis in the Department of Technology, Policy, and Management at Delft University of Technology. ALAN L. PORTER has led development of "technology opportunity analysis" and mining electronic, bibliographic data sources to generate intelligence on emerging technologies. He holds an MA in psychology and a PhD in engineering psychology, both from UCLA. He is currently Director of Research and Development for Search Technology, Inc., in Norcross, Georgia. THOMAS W. MASON was the founding head of the Engineering Management Department (www.rose-hulman.edu/msem). While on a three-year leave from Rose-Hulman, he served as CFO and CEO of a 140-person network management systems business. FREDERICK A. ROSSINI (retired) is a former provost at George Mason University in Fairfax, Virginia. JERRY BANKS is Professor Emeritus, Department of Industrial and Systems Engineering, Georgia Institute of Technology in Atlanta, Georgia.

Inhaltsangabe

Acknowledgments xv 1 Introduction 1 1.1 About This Book
1 1.2 Technology and Society
2 1.2.1 Social Change
3 1.2.2 Technological Change
4 1.3 Management and the Future
6 1.3.1 Management and Innovation Processes
7 1.3.2 The Role of Technology Forecasting
9 1.3.3 The Importance of Technology Forecasting
10 1.3.4 The Role of Social Forecasting
12 1.4 Conclusions
13 References
13 2 Technology Forecasting 15 2.1 What Is Technology Forecasting?
15 2.1.1 Models of Technology Growth and Diffusion
17 2.1.2 Technology Forecasting in Context
18 2.1.3 What Makes a Forecast Good?
20 2.1.4 Common Errors in Forecasting Technology
21 2.2 Methodological Foundations
23 2.2.1 The Technology Delivery System
24 2.2.2 Inquiring Systems
28 2.3 Technology Forecasting Methods
31 2.3.1 Overview of the Most Frequently Used Forecasting Methods
33 2.3.2 Method Selection
37 2.4 Conclusion
37 References
38 3 Managing the Forecasting Project 40 3.1 Information Needs of the Forecasting Project
40 3.1.1 The Technology Manager's Needs
42 3.1.2 The Forecast Manager's Needs
43 3.1.3 Information about Team Members
44 3.2 Planning the Technology Forecast
46 3.3 Team Organization
Management
and Communications
47 3.3.1 Organizing and Managing the Technology Forecast
50 3.3.2 Communications
54 3.3.3 Summary Conclusions about Project Management and Organization
55 3.4 Success: The Right Information at the Right Time
56 3.5 Project Scheduling
57 3.5.1 Program Evaluation and Review Technique (PERT)
58 3.5.2 Gantt Chart
60 3.5.3 Project Accountability Chart (PAC)
60 3.5.4 Project Scheduling Software
61 3.6 Conclusions
62 References
62 4 Exploring 65 4.1 Establishing the Context--the TDS
65 4.1.1 Societal and Institutional Contexts
66 4.1.2 Technology Context
67 4.1.3 Stakeholders
68 4.1.4 Understanding the TDS
69 4.1.5 An Example TDS Model
70 4.2 Monitoring
72 4.2.1 Why Monitor?
74 4.2.2 Who Should Monitor?
75 4.2.3 Monitoring Strategy
76 4.2.4 Monitoring Focused on Management of Technology Issues
79 4.2.5 Monitoring Focused on the Stage of the Technology Development
81 4.3 The Stimulation of Creativity
81 4.3.1 Five Elements of Creativity
81 4.3.2 Group Creativity
92 4.4 Conclusion
95 References
95 5 Gathering and Using Information 98 5.1 Expert Opinion
99 5.1.1 Selecting Experts
99 5.1.2 Selecting Expert Opinion Techniques
100 5.2 Gathering Information on the Internet
105 5.2.1 Science and Technology on the Internet
106 5.2.2 Society and Culture on the Internet
109 5.3 Structuring the Search
113 5.4 Preparing Search Results
116 5.5 Using Search Results
117 5.6 Developing Science
Technology
and Social Indicators
119 5.6.1 Science and Technology Indicators
119 5.6.2 Social Indicators
122 5.7 Communicating Search Results
122 5.8 Conclusions
123 References
124 6 Analyzing Phase 129 6.1 Perspective on Data and Methods
129 6.1.1 Overview and Caveats
130 6.1.2 Internet Time Series Data and Trends
132 6.1.3 Analytical Modeling
133 6.2 Linear Regression and Extensions
134 6.3 Growth Models
138 6.3.1 The Models
138 6.3.2 Dealing with the Data
143 6.3.3 Regression and Growth Modeling: What Can Go Wrong?
144 6.4 Simulation
145 6.4.1 Quantitative Cross-Impact Analysis
146 6.4.2 Qualitative Cross-Impact Analysis
152 6.5 Monte Carlo Simulation
153 6.5.1 Generating and Displaying Random Values
153 6.5.2 Sampling Multiple Random Variables
154 6.5.3 RFID Application in a Hospital Decision
156 6.6 System Dynamics
158 6.6.1 The System Dynamics Modeling Cycle
159 6.6.2 A Technology Forecasting Example: The Cable-to-the-Curb Model
162 6.7 Gaming
164 6.7.1 Decision Trees
165 6.7.2 Bayesian Estimation
166 6.7.3 Value of Information
167 6.7.4 Real Options Analysis
169 6.8 Software Suggestions
170 6.8.1 Software for Regression
170 6.8.2 Simulation Analysis Software
170 6.8.3 Software for Analysis of Decisions
170 6.8.4 Real Options Super Lattice Software
170 6.8.5 Software Sites
171 References
171 7 Focusing Phase: Using Scenario Analysis 174 7.1 Uncertainty
175 7.1.1 Uncertainty Frameworks
175 7.1.2 Source and Nature of Uncertainty
176 7.1.3 Uncertainty and the Adaptive Paradigm
177 7.1.4 Techniques for Addressing Uncertainty
177 7.2 Scenarios
178 7.2.1 Steps in Creating Scenarios
178 7.2.2 Types of Scenarios
182 7.3 Examples and Applications
184 7.3.1 Scenarios for Renewable Energy Planning
184 7.3.2 Pervasive Computing Scenarios
185 7.3.3 Scenarios for Social Change
186 7.4 Scenarios: Extensions and Advanced Techniques
187 7.4.1 Scenarios in Multimethodology Forecasts
187 7.4.2 Extensions of Scenario Analysis
189 7.5 Conclusions
191 References
192 8 Economic and Market Analysis 194 8.1 The Context
194 8.1.1 Markets and Innovation
197 8.1.2 Technology and Institutions
199 8.2 Forecasting the Market
203 8.2.1 The Consumer/Customer Marketplace
204 8.2.2 Qualitative Techniques for Appraising Market Potential
206 8.2.3 A Quantitative Approach--Adoption and Substitution: S-Curve Models
207 8.3 Forecasting the Economic Context
208 8.3.1 Macroeconomic Forecasting
209 8.3.2 Input-Output Analysis
210 8.3.3 General Equilibrium Models
214 8.3.4 Hedonic Technometrics
215 8.4 Forecasting in an Institutional Context
216 8.4.1 Institutional Arrangements and the Market
216 8.4.2 Game Theory
218 8.4.3 Agent-Based Models
219 8.5 Conclusion
219 References
220 9 Impact Assessment 223 9.1 Impact Assessment in Technology Forecasting
223 9.2 Impacts on Technology and Impacts of Technology
224 9.3 A Comprehensive Approach to Impact Assessment
225 9.4 Impact Identification
226 9.4.1 Scanning Techniques
226 9.4.2 Tracing Techniques
227 9.4.3 Narrowing the Impact Set and Estimating Effects
229 9.4.4 A Final Word
229 9.5 Impact Analysis
230 9.5.1 Analyzing Impacts on and Impacts of the Technology
230 9.5.2 Analyzing Technological Impacts
232 9.5.3 Analyzing Economic Impacts
234 9.5.4 Analyzing Environmental Impacts
234 9.5.5 Analyzing Social Impacts
238 9.5.6 Analyzing Institutional Impacts
239 9.5.7 Analyzing Political Impacts
240 9.5.8 Analyzing Legal and Regulatory Impacts
241 9.5.9 Analyzing Behavioral
Cultural
and Values Impacts
242 9.5.10 Analyzing Health-Related Impacts
243 9.6 Impact Evaluation
244 9.7 Conclusion
245 References
245 10 Cost-Benefit and Risk Analysis 248 10.1 Opportunity Costs and Choices
248 10.2 Cost-Benefit Analysis
249 10.2.1 Cost-Benefit Analysis within the Organization
249 10.2.2 Societal Stake and the Organizational Response
253 10.2.3 Cost-Benefit Analysis Methods
260 10.2.4 Economic Value Added
263 10.2.5 Earned Value Management
264 10.2.6 The Balanced Scorecard
265 10.3 Accounting for Risk and Uncertainty
265 10.3.1 Accounting for Risk within Organizations
265 10.3.2 Accounting for Risk--the Social Dimension
269 10.4 Concluding the Focusing Phase
273 References
274 11 Implementing the Technology 277 11.1 Forecasting Continues
277 11.2 Implementation Issues
278 11.3 Strategic Planning for Technology Implementation
278 11.4 Selecting from among Alternative Implementations of the Technology
279 11.4.1 Measurement
282 11.4.2 Interpretive Structural Modeling
284 11.4.3 Analytic Hierarchy Process
285 11.4.4 Wrap-Up
286 11.5 Technology Roadmapping
286 11.6 Summary and Concluding Observations
287 References
287 12 Managing the Present from the Future 289 12.1 The Overall Approach
289 12.2 Selecting Methods and Techniques
290 12.2.1 Using the TDS and the Major Families of Techniques
290 12.2.2 The 80-20 Rule
291 12.3 Alternative Perspectives
291 12.4 Learning from Past Forecasts and Assessments
293 12.5 Visions
295 12.6 A Final Word
295 References
296 Appendix A Case Study on Forecasting Dye-Sensitized Solar Cells 297 A.1 Framing the Case Study
297 A.1.1 Characterizing the Technology
298 A.1.2 Dye-Sensitized Solar Cells
299 A.2 Methods
299 A.2.1 Engaging Experts and Multipath Mapping
299 A.2.2 Developing the TDS
300 A.2.3 Tech Mining (Chapter 5) and Science Overlay Mapping
304 A.2.4 Trend Analyses
310 A.2.5 Cross-charting and Social Network Analyses
311 A.3 The Rest of the Story
313 A.3.1 Market Forecasts
314 A.3.2 Scenarios
315 A.3.3 Technology Assessment
315 A.3.4 Further Analyses and Communicating Results
316 References
316 Index 319