Diffusion of Innovations

1. Diffusion of Innovations “Make a better mousetrap and the world will beat a path to your door.” –Ralph Waldo Emerson “Not necessarily.” Information Technology

2. Introduction • Diffusion – a process by which an innovation is communicated through certain channels over time among members of a social system • Innovation – an idea, practice, or object that is perceived as new by an individual or other unit of adoption • Hardware • Software • Example – QWERTY vs.. Dvorak • Home keys: 32% vs. 70% • Left hand (57%) vs.. Right hand (56%) Information Technology

3. Overview of Issues • Innovation • Social System • Time (Decision-making) • Communication Channels • Consequences Information Technology

4. 1. Innovation A. Origins • Needs/problems • Developers (skunkworks – Lockheed, 1943) • Poachers (Fax 1843, Alexander Bain, clockmaker, RCA, Xerox, Sharp) • Consumers • Serendipitously (Major Technologies for Heart Surgery/Treatment (41% no relation)) Information Technology

5. Innovation cont. B. Key Characteristics • Relative Advantage • Compatibility • Complexity • Trialability • Observability • Adaptability (Re-invention) Joseph Zimmerman 1948 Answering Machine Information Technology

6. Characteristics cont. • Relative Advantage • Economic • Status • Compatibility • Values, beliefs (hot water) • Previous ideas • Complexity • Software • Hardware 1st cell call, Oct.1983 Information Technology

7. Characteristics cont • Trialability • Experimenting without commitment • Observability • Immediate • Long-term (AIDS prevention) • Adaptability • Customize • Use for unintended purposes Information Technology

8. Example Information Technology

9. Information Technology

10. Innovation & Value Match the Examples • Toothbrush with angled brush • Detergents with improved cleaning power • QWERTY Key Board • Satellite Radio • Cell Phone • Linux operating System • Google Information Technology

11. Innovation cont. • So what? • Increase incentives • Increase visibility of results • Avoid the “empty vessel fallacy” • Be attentive to naming • Encourage “tinkering” • Decrease perceived complexity (use role-models) • Allow trial periods Information Technology

12. 2. Social System A. Definition – a set of interrelated units engaged in a joint problem-solving to accomplish a common goal. B. Key elements • Innovators • Early adopters • Early majority • Late majority • Laggards Information Technology

13. B. Key elements • Innovators • Cosmopolites • Venturesome • Early Adopters • Opinion-leaders http://video.google.com/videoplay?docid=-6994382959717863945&q=Walter+Mossberg&total=93&start=0&num=10&so=0&type=search&plindex=1 • Localites • Early Majority • Deliberate • Interact frequently with peers • Late majority (Skeptical) • Laggards (Traditional conventional) Information Technology

14. Comparison of Adopter Types Information Technology

15. C. Social System – The Big Picture Information Technology

16. Social System – The Big Picture Information Technology

17. Social System cont. D. So What? • Segment your audience • Stress different features of the innovation with different audiences • Recognize that the “change agent” may not be the best person to persuade certain groups. Information Technology

18. 3. Time (Decision-making process) A. Stages • Knowledge • Persuasion • Decision • Implementation • Confirmation Information Technology

19. Stages cont. • Knowledge stage • Recall of information • Comprehension of messages • Knowledge or skill to make adoption • Persuasion stage • Liking the innovation • Discussing new behavior with others • Accepting messages about innovation • Forming positive opinions • Supporting innovation Information Technology

20. Stages cont. • Decision stage • Form intention to seek more information • Form intention to try innovation • Implementation stage • Use the innovation on a regular basis • Acquire additional information • Confirmation stage • Recognizing the benefits • Integrating the innovation into routine • Promote to others Information Technology

21. Decision-making Process Information Technology

22. Stages cont. B. So what? • Recognize that adoption is not a one-shot decision • Active rejection • Passive rejection • Use mass media in the 1st phase • Use interpersonal networks in phases 2 –5 Information Technology

23. 4. Communication channels A. Important channels • Change agents • Mass media • Interpersonal networks Information Technology

24. Change agents • Examples – teachers, consultants, public health workers, agricultural extension agents, salespeople etc. (linkers) • Roles • Develop need • Establish information-sharing relationship • Diagnosis problems • Create intent to change • Translate intent into action • Stabilize adoption • Methods • Foster credibility • Emphasize homophily • Focus on clients Information Technology

25. Mass media • Hypodermic needle model • Two-step flow model • Multi-step flow Information Technology

26. Interpersonal Channel • Established through personal networks of like people • Achieving critical mass (80-20 rule) Information Technology

27. Channels cont. B. So What? • Recognize limits of mass media • Distinguish between “competence” and “interpersonal” credibility • Develop strategy linked to phases and timing Information Technology

28. 5. Consequences • Dimensions • Form • physical appearance • Function – • usage pattern • Meaning – • sense making, • categorizing Information Technology

29. Consequences cont. B. Types • Desirable versus undesirable (productivity, higher income, equity etc.) • Direct versus indirect • Anticipated versus unanticipated Information Technology

30. Example - Segway Information Technology

31. Consequences cont. • So what? • Anticipate both positive & negative consequences • Recognize that some important consequences will emerge over time • Discuss the implicit tradeoffs made by adoption • Realize that an innovations benefits and liabilities are not easily separated. • Monitor the meanings associated with the innovation. Information Technology

32. 6. The Gartner Hype Cycle(One more angle) Information Technology

33. 2006 Predictions Information Technology