The Diffusion of Innovations II

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Lecture 14

• The Diffusion of Innovations 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

Not Adopt
Adopt
X
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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
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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.

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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
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Relational Networks
Relational How do the direct ties affect
adoption? In this case, ties could be
friendship
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Network relations and network density
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Network relations and network density
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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

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Structural Network Diffusion

• Weak Ties Revisited
• Centrality
• Structural Equivalence

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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

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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.

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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.

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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.

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Grade Distribution
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Assignment 1

• Overall Assessment
• Grading Decoded
• Thinking About Assignment 2
• Finally, no reading response due next week