Diffusion (business)

MODELS OF DIFFUSION

There are several theories that proport to explain the mechanics of diffusion:

1) The Two-step Hypothesis - information and acceptance flows, via the media, first to Opinion Leaders , then to the general population

2) The trickle-down theory - products tend to be expensive at first, and therefore only accessible to the wealthy social strata - in time they become less expense and are diffussed to lower and lower strata

3) The Everett Rogers Diffusion Of Innovations theory - for any given product category, there are five categories of product adopters:

4) Crossing The Chasm model developed by G. Moore - This is basically a modification of Everett Rogers' theory applied to technology markets and with a chasm added. According to Moore, the marketer should focus on one group of customers at a time, using each group as a base for marketing to the next group. The most difficult step is making the transition between visionaries (early adopters) and pragmatists (early majority). This is the chasm that he refers to. If successful a firm can create a bandwagon effect in which the momentum builds and the product becomes a defacto standard.

5) Technology Driven Models - These are particularly relevant to software diffusion. The rate of acceptance of technology is determined by factors such as ease of use and usefulness.

THE RATE OF DIFFUSION

According to Everett M. Rogers, the rate of diffusion is influenced by:

DIFFUSION RATE MODELS

There are several types of diffusion rate models:

1) Penetration models - use test market data to develop acceptance equations of expected sales volume as a function of time - 3 examples of penetration models are:

2) Trial/Repeat models - number of repeat buyers is a function of the number of trial buyers

3) Deterministic models - assess number of buyers at various states of acceptance - later states are determined from calculations to previous states

4) Stochastic models - recognize that many elements of the diffusion process are unknown but explicitly incorporate probabilistic terms

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