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Understanding Diffusion of Innovations: Models and Patterns

Explore cumulative and individual adoption patterns, assumptions, probit models of adoption, and information cascades. Learn about network approaches, social thresholds, and critique of diffusion research.

december
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Understanding Diffusion of Innovations: Models and Patterns

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Presentation Transcript

  1. Lecture 14 The Diffusion of Innovations II

  2. Cumulative and Individual Adoption Patterns

  3. Assumptions of Simple Epidemic Models • Homophily • Individuals or groups tend to hang out with others who are similar to them (demographics, attitudes, etc) • N is usually constant • Speed of Diffusion usually constant

  4. Transmission versus Persuasion • The epidemic analogy begins to break down when we do not equate transmission with persuasion. • Persuasion may be influenced by several factors– e.g., risk, ‘trustworthiness’ of persuader.

  5. Accounting for Adoption Decisions • Probit models • Various characteristics (xi) affects the profitability of adoption a new technology Not Adopt Adopt X*

  6. “Relevant Characteristics” • Probit models depend on specifying relevant characteristics which might influence potential adoption. • Potential Relevant Characteristics (Geroski 2000) • Firm Sizeas one of the most common– why? • Suppliers • Technological Expectations • Costs • Learning costs • Search Costs • Switching Costs • Opportunity Costs

  7. Another Possibility: Information Cascades (Geroski) • What about the innovations that do not successfully diffuse? • “Information Cascades” involve the process of early inertia, potential adopter investment, and the adoption ‘bandwagon’ • Three phases: • Initial choice • Lock-in • bandwagon Photo: engadget.com

  8. Rethinking ‘Classic’ Diffusion Models • Taking “the” new technology for granted • S-curves may not just be the starting point of an analysis of diffusion, but rather exist as one possible outcome.

  9. The Network Approach: Valente (1996) • Two Network Approaches: • Relational Network Diffusion • Direct ties among individuals • Opinion Leaders, personal and network density, in-ties versus out-ties • Structural Network Diffusion • Considers the overall pattern in the network • Centrality, Number of “weak” versus “strong” ties Individuals’ contacts adoption behavior Pattern of network individual positions and roles

  10. Relational Networks Relational: How do the direct ties affect adoption? In this case, ties could be “friendship”

  11. Network relations and network density

  12. Network relations and network density

  13. Social Network Thresholds • Personal network thresholds (Valente 1996) • The number of members within personal network that must have adopted a given innovation before one will adopt • Accounts for some variation in overall adoption time • Opinion leaders have lower thresholds • Opinion leaders influence individuals with higher thresholds

  14. Structural Network Diffusion • Weak Ties Revisited • Centrality • Structural Equivalence

  15. Critiques of the Network Approach • Other factors may be more important than just the network structure: • Example: Tetracycline diffusion (Coleman, Katz et al. 1966) • Marketing may have been most important factor for explaining adoption. • Rationality of actors is not necessarily expressed– treated as a sort of “black box”

  16. Overall, what does the diffusion of innovation research help us to understand? • Can be used at the micro-level to track individuals who are targeted members for an innovation • Can be used at the meso and macro-level to consider economic development, technological advances, or other processes.

  17. Common Mistakes in Applying Diffusion Research • Treating diffusion only as dissemination or marketing • Confusing influence with status • Inadequate evaluation of the issue in its own context, as well as the surrounding social structure and perceptions of the innovation.

  18. Current Research and Applications • Diffusion of Electronic Newspapers • Li, S. S. (2003). Electronic newspaper and its adopters: Examining the factors influencing the adoption of electronic newspapers in taiwan. Telematics and Informatics, 20(1), 35-49. • Diffusion of Internet Adoption • Forman, C. (2005). The corporate digital divide: Determinants of internet adoption. Management Science, 51(4), 641. • Diffusion of Wireless Applications • Grantham, A., & Tsekouras, G. (2005). Diffusing wireless applications in a mobile world. Technology in Society, 27(1), 85-104.

  19. Grade Distribution

  20. Assignment #1 • Overall Assessment… • Grading Decoded… • Thinking About Assignment 2… • Finally, no reading response due next week

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