The spreading of an idea or an innovation through a population.&nbsp; Typically, an innovation such as television is initially used by a small number of people.&nbsp; The number of new users per year increases rapidly, then, after stabilizing, decreases as unsatisfied demand for the innovation dies away. Meade and Islam (2001) examine the use of diffusion models for time-series extrapolation. Rogers (1995), based on an extensive review of the literature, updated his conclusions that the speed of diffusion depends on: (1) the relative advantage of the product over existing products, (2) compatibility with existing solutions, (3) divisibility (the user can try part of the idea), (4) communicability, (5) complexity, (6) product risks (will it actually provide the benefits?), and (7) psychological risks (e.g., will people laugh at me if I adopt this new product or idea?).<o:p></o:p></P>
<ul>
  <li>Meade, N. &amp; T. Islam (2001), “Forecasting the 
diffusion of innovations: Implications for time-series extrapolatioin,” in J. S. 
Armstrong (ed.), <I>Principles of Forecasting</I>. Norwell, MA: Kluwer Academic 
Press.</li>
  <li><SPAN Plous, 
S. (1993), <I>Rogers, E. M. (1995) , <I>Diffusion of Innovations.</I> New York: The Free Press. </SPAN>
  </li>
</ul>