Mid-Term Diffusion Models Flashcards
different types of models (5)
- exponential model
- external influence model
- logistic model
- gompertz model
- bass model
critical mass
sufficient number of adopters of an innovation in a social system so that rate of adoption becomes self-sustaining
exponential growth model
assumptions:
- no seasonality, no age structure, unlimited resources
- main problem: no limit on growth
model use
to study the evolution of the number of adopters of a technology
external influence model
- number of resources is not unlimited, population can not grow forever
- number of new adopters in specific point in time is proportional to the number of potential adopters
logistic model
introduces an imitation effect, upper limit effect, relative growth rate diminishes when the population gets higher values
imitation effect
adoption and diffusion of technology is based on the imitation of the behaviour of previous adopters
r0
maximum possible growth rate of the population
- net effect of reproduction and mortality
K
saturation level; upper limit for the number of members of the population
- carrying capacity
growth time
the length of the interval during which growth progresses from 10% to 90% of the carrying capacity
midpoint
time where the members of the population are half the carrying capacity
gompertz model
- growth is slowest at the start and end of a time period
- based on the assumption that the adoption rate is proportional to the logarithm of the number of potential adopters
- maximum adoption rate occurs when the adopters population has reached 37% of carrying capacity
bass model
exponential growth, capacity limit, imitation effect, and innovation effect
research goals (3)
- to find a common representation of innovation diffusion patterns across a large variety of ICTs
- to identify different classes of ICT having similar diffusion patterns in terms of the parameters of their diffusion curves
- To explore the relationship between innovation characteristics of the ITs and their general diffusion patterns
model best fit
least squares method, minimizes the sum of squared residuals
- model that best fits to the series of data