LECTURE 14The Diffusion of The Diffusion of Innovations IIInnovations II
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Cumulative and Individual Adoption Patterns
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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
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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.
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Accounting for Adoption Decisions Probit models
Various characteristics (xi) affects the profitability of adoption a new technology
5X*X*
Not Adopt
Adopt
“Relevant Characteristics”
Probit models depend on specifying relevant characteristics which might influence potential adoption.
Potential Relevant Characteristics (Geroski 2000) Firm Size as one of the most common– why? Suppliers Technological Expectations Costs
Learning costs Search Costs Switching Costs Opportunity Costs
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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
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.
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
Relational Networks
Relational: How do the direct ties affect adoption? In this case, ties could be “friendship”
Network relations and network density
Network relations and network density
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
Structural Network Diffusion
Weak Ties Revisited
Centrality
Structural Equivalence
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”
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.
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.
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.
Grade Distribution
Assignment #1
Overall Assessment…
Grading Decoded…
Thinking About Assignment 2…
Finally, no reading response due next week
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