Diffusion Networks
Abstract
Here we explore what is known about diffusion networks and how they function to convey innovation-evaluation information to decrease uncertainty about a new idea. We begin with a discussion of opinion leadership, the degree to which an individual is able informally to influence other individuals’ attitudes or overt behavior in a desired way with relative frequency. Opinion leaders are individuals who lead in influencing others’ opinions about innovations. The behavior of opinion leaders is important in determining the rate of adoption of an innovation in a system. In fact, the S-shape of the diffusion curve occurs because once opinion leaders adopt and tell others about the innovation, the number of adopters per unit of time takes off. We explore in this chapter the role of social modeling in diffusion networks, and how interpersonal communication drives the diffusion process through creating a “critical mass” of adopters. In order to understand better the nature of opinion leadership and diffusion networks, we now examine several models of mass communication flows, roughly in the temporal sequence of their entrance on the stage of communication study. The hypodermic needle model postulated that the mass media had direct, immediate, and powerful effects on a mass audience. The mass media in the 1940s and 1950s were perceived as a powerful influence on behavior change. The omnipotent media were pictured as conveying messages to atomized masses of individuals (Katz and Lazarsfe…
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According to the innovation diffusion theory, users are more likely to adopt new technological products or services if they perceive them as offering relevant advantages over existing alternatives.
“According to the innovation diffusion theory, users are more likely to adopt new technological products or services if they perceive them as offering relevant advantages over existing alternatives [46].”
Users who are familiar with the platform economy are more likely to sustain their use.
“Habit formation is another determinant identified in the adoption process, suggesting that users who are familiar with the platform economy are more likely to sustain their use [24,46].”
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Cited by 42
- Authors
- Rogers, E.
- Corresponding author
- Rogers, Everett
- Venue
- Networks in the Knowledge Economy
- Publisher
- Oxford University Press
- Published
- 2003-08-14
- OpenAlex
- W4239631761
- Cited by
- 42
- References
- 0
- Citations by year
- 2026: 2 · 2025: 15 · 2024: 3 · 2023: 6 · 2022: 2 · 2021: 2 · 2020: 3 · 2018: 1 · 2016: 1 · 2013: 2
- FWCI
- 1.21
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Oxford University Press eBooks (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Innovation Diffusion and Forecasting
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Opinion Dynamics and Social Influence
- Keywords
- diffusion networks, opinion leadership, diffusion of innovations, innovation adoption, social modeling, interpersonal communication, critical mass, S-shaped diffusion curve, media influence on behavior
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