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In the late 1960s, a number of multiple correlation analyses were made of organizational innovativeness, in which the dependent variable is the degree to which an organization (rather than an individual) is innovative; here the unit of analysis is an organization. An illustration is Mohr's (1969) study of the innovativeness of county health departments, in which each such organization is credited with a higher innovativeness score for adopting new public health ideas. About 63 percent of the variance in organizational innovativeness was explained by such independent variables as the resources available to the organization, the attitudes of the director of the health department, and various organizational characteristics (Chapter 10).Another recent trend in innovativeness-prediction research is to include independent variables that use (1) system-level variables, and (2) communication network variables, along with (3) individual-level variables, to predict individual innovativeness (Rogers and Kincaid, 1981, pp. 239-243). For example, system-level independent variables used by Lee (1977) included the average level of education in Korean villages and the average number of change agent contacts with the villagers. Network variables were also measured, such as the degree to which the individual is interconnected by network links with the rest of the village. Lee (1977) found that the individual-level and network variables were more important in explaining individual innovativeness in adopting family planning, than were the system-level variables. These results suggest that communication network variables should be considered for inclusion in future innovativeness-prediction studies (Rogers and Kincaid, 1981, p. 242). System-level variables (like a system's norms) may influence individual behavior (like innovativeness) through the individual's network links.
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