Diffusion of Innovations by Everett M. Rogers

Author:Everett M. Rogers
Language: eng
Format: epub, pdf
Publisher: THE FREE PRESS
Published: 1995-07-15T00:00:00+00:00

The Method of Adopter Categorization

Anyone seeking to standardize adopter categories must decide: (1) on the number of adopter categories, (2) on the portion of the members of a system to include in each category, and (3) on the method, statistical or otherwise, of defining the adopter categories.

The criterion for adopter categorization is innovativeness, the degree to which an individual or other unit of adoption is relatively earlier in adopting new ideas than other members of a social system. Innovativeness is a relative dimension, in that an individual has more or less of it than others in a system. Innovativeness is a continuous variable, and partitioning it into discrete categories is a conceptual device, much like dividing the continuum of social status into upper, middle, and lower classes. Such classification is a simplification that aids the understanding of human behavior, although it loses some information as a result of grouping individuals.

Ideally, a set of categories should be (1) exhaustive, or include all the units of study, (2) mutually exclusive, or exclude a unit of study that appears in one category from also appearing in any other category, and (3) derived from a single classificatory principle.

We have previously demonstrated that S-shaped adopter distributions closely approach normality. This is important because the normal frequency distribution has several characteristics that are useful in classifying adopters. One characteristic or parameter is the mean (x), or average, of the individuals in the system. Another parameter of a distribution is its standard deviation (sd), a measure of dispersion or variation about the mean. The standard deviation indicates the average amount of variance from the mean for a sample of individuals.

These two statistics, the mean (x) and the standard deviation (sd), are used to divide a normal adopter distribution into categories. Vertical lines are drawn to mark off the standard deviations on either side of the mean so that the normal curve is divided into categories with a standardized percentage of respondents in each category. Figure 7-2 shows the normal frequency distribution divided into the five adopter categories. These five adopter categories and the approximate percentage of individuals included in each are located on the normal adopter distribution in Figure 7-2.

The area lying to the left of the mean time of adoption (of innovation) minus two standard deviations includes the first 2.5 percent of the individuals in a system to adopt an innovation—the innovators. The next 13.5 percent to adopt the new idea are included in the area between the mean minus one standard deviation and the mean minus two standard deviations; they are labeled early adopters. The next 34 percent of the adopters, called early majority, are included in the area between the mean date of adoption and the mean minus one standard deviation. Between the mean and one standard deviation to the right of the mean are the next 34 percent to adopt the new idea, the late majority. The last 16 percent to adopt are called laggards.

Figure 7-2. Adopter Categorization on the Basis of Innovativeness

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