Seeing what's next : using the theories of innovation to predict industry change

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Seeing what's next : using the theories of innovation to predict industry change

Clayton M. Christensen, Scott D. Anthony, Erik A. Roth

Harvard Business School Press, c2004

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Includes bibliographical references and index

Includes glossary: p[291]-296

Size of ISBN:9781591391852: 25 cm

Description and Table of Contents

Description

Every day, individuals take action based on how they believe innovation will change industries. Yet these beliefs are largely based on guesswork and incomplete data and lead to costly errors in judgment. Now, internationally renowned innovation expert Clayton M. Christensen and his research partners Scott D. Anthony and Erik A. Roth present a groundbreaking framework for predicting outcomes in the evolution of any industry. Based on proven theories outlined in Christensen's landmark books The Innovator's Dilemma and The Innovator's Solution, Seeing What's Next offers a practical, three-part model that helps decision-makers spot the signals of industry change, determine the outcome of competitive battles, and assess whether a firm's actions will ensure or threaten future success. Through in-depth case studies of industries from aviation to health care, the authors illustrate the predictive power of innovation theory in action.

Table of Contents

  • Section I: How to Use Theory to Analyze 1) Signals of Change
  • Where are the Opportunities? 2) Competitive Battles: How to Size Up Competitors 3) Firm Choices: Identifying What Choices Matter 4) Non-Market Factors Influence Innovation Section II: Theory-Based Analysis 5) Disruptive Diplomas - The Future of Education 6) Disruption Spreads Its Wings - The Future of Aviation 7) Whither Moore's Law? - The Future of Semiconductors 8) Healing the 800-Pound Gorilla - The Future of Health Care 9) Innovation Overseas - Using Theory to Assess Corporate and Country Strategies 10) Breaking the Wire - The Future of Telecommunications Conclusion: What's Next Appendix Glossary Index About the Authors

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