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After more fully de<br />

scribing <strong>the</strong>se attributes,<br />

Rogers goes on to observe<br />

how <strong>the</strong>y relate to <strong>the</strong> rate<br />

of adoption: In <strong>the</strong> left<br />

side of <strong>the</strong> chart we iden<br />

tify <strong>the</strong> five attributes<br />

perceived by potential a-<br />

dopters, on <strong>the</strong> right hand<br />

side we identify whe<strong>the</strong>r<br />

<strong>the</strong> attribute increases or<br />

slows down <strong>the</strong> rate of a-<br />

doption.<br />

>ERCEIVED<br />

RELATIVE ADVANTAGE<br />

COMPATIBILITY<br />

COMPLEXITY<br />

FRIALABILITY<br />

OBSERVABILITY<br />

Effects <strong>the</strong> rate of adoption<br />

Dy increasing it by slowing it<br />

I think that most of us would agree with <strong>the</strong> observations presented by Rogers.<br />

In fact, we might very well ask: Why was it necessary for him to state <strong>the</strong> obvious?<br />

But he goes a step fur<strong>the</strong>r<br />

by listing <strong>the</strong> number of<br />

empirical studies that sup<br />

port and do not support<br />

each of <strong>the</strong> five generali<br />

zations he makes regarding<br />

attributes of <strong>the</strong> innova<br />

tion and its rate of a-<br />

doption.<br />

Not all of Rogers'<br />

findings and particularly<br />

those related to complex<br />

ity have been fully sub<br />

stantiated by empirical<br />

evidence. That, of course<br />

does not mean <strong>the</strong>y are in<br />

correct. It simply means<br />

<strong>the</strong>y are hypo<strong>the</strong>ses not<br />

yet fully tested.<br />

PERCEIVED<br />

RELATIVE ADVANTAGE<br />

COMPATIBILITY<br />

COMPLEXITY<br />

FRIALABILITY<br />

OBSERVABILITY<br />

Effects<br />

Increases<br />

X<br />

X<br />

X<br />

X<br />

X<br />

X<br />

X<br />

X<br />

Slows<br />

X<br />

X<br />

Empirical<br />

Evidence<br />

Agree Disagree<br />

This review of Rogers' work brings two benefits. First, his findings provide<br />

us a sense of direction in finding <strong>the</strong> most effective ways of understanding <strong>the</strong><br />

diffusion process so that we can see that our ideas are not only developed but<br />

adopted as well. Secondly, we can see from reviewing his approach <strong>the</strong> need and <strong>the</strong><br />

importance of empirical evidence to demonstrate <strong>the</strong> utility of our ideas as we<br />

attempt to have <strong>the</strong>m adopted.<br />

Applying Rogers' work in a specific sense, I think one of <strong>the</strong> key obstacles to<br />

be overcome lies within <strong>the</strong> statistical graphics community itself. Professor Arthur<br />

Robinson referred to it in his Presidential Address to <strong>the</strong> International Cartographic<br />

Association in Ottawa in 1972. He said:<br />

When one looks at <strong>the</strong> history of cartography, one cannot but be<br />

impressed by <strong>the</strong> persistence of techniques, and <strong>the</strong> strength of<br />

<strong>the</strong> urge to maintain <strong>the</strong> status quo. This is true in many areas,<br />

perhaps most obviously in <strong>the</strong> graphic.<br />

29<br />

18<br />

9<br />

9<br />

7<br />

14<br />

9<br />

7<br />

4<br />

2<br />

Total<br />

43<br />

27<br />

16<br />

13<br />

9

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