Dissertation Abstract




B. S., Syracuse University, 1962
M. A., Syracuse University, 1971


Submitted in partial fulfillment of the requirements for
the degree of Doctor of Philosophy in Sociology in
the Graduate School of Syracuse University
January, 1972

Approved, Thesis Advisor:
Dr. Gerald J. Karaska
Department of Geography
Clark University
Worcester, MA

Date: November 16, 1971

This thesis has three objectives. The first goal is to clearly identify the major processes operating in the technology innovation diffusion phenomenon. The second goal is to construct, based on the wealth of empirical research in Sociology and Geography, a comprehensive micro-level model of one of these processes. And, the third goal is to provide an indication of the applicability of simulation technology to the study of a complex social process.

To fulfill the first goal, a general model of technology innovation diffusion is constructed in which a minimum number of important processes are identified. These processes are the awareness process, the adoption process, the discontinuation process, and the readoption process. Between each of these processes, several states are identified that contain individuals of the community once they pass through a process. These states are the initial state of non-aware individuals, the state of aware individuals, the state of adopters, the state of discontinuers, and the state of readopters.

To fulfill the second goal, the awareness process, the first process identified, is modeled. To the awareness process, the state of non-aware individuals prior to this process and the state of aware individuals following this process are included.

The awareness process, a micro-level process, is found to operate on every individual in a community. It involves first identifying whether the individual in question is an opinion leader or not. On that basis, one of two empirical information utilization schedules is selected to determine which of three information sources, proximity sources, social network sources, or impersonal sources, will be utilized by this individual. Once this determination is made and if either proximity sources or social network sources are chosen, then another identification has to be made. This is to identify whether the individual is a cosmopolitan influential or not. On the basis of this determination, either a mean information probability field for non-opinion leaders and local influentials or a mean information probability field for cosmopolitan influentials is used to compute either the probability of becoming aware of an innovation given proximity sources of information or the probability of becoming aware of an innovation given social network source of information. If social network sources of information are selected and there are aware opinion leaders in the individual's mean information probability field, then an enhanced probability of becoming aware of an innovation given social network sources of information is computed. If impersonal sources are chosen, then the probability of becoming aware of an innovation given impersonal sources of information is computed using a modified De Fleur and Larsen community response function. There is also the probability that an individual does not come into contact with any source of information regarding the innovation. In that case this individual remains non-aware of the innovation. After one of the above probabilities is computed, a decision based on that probability is made as to whether the individual becomes aware of the innovation. If he does not become aware, then he remains in the non-aware state. If he does become aware of the innovation, he enters the state of aware individuals.

To fulfill the third goal, a simulation of the awareness process model is written using the GASP II simulation language. A preliminary description of an early simulation run shows that complex social relationships begin to appear in this information process only after some initial saturation of the community with aware individuals. The early tail of the cumulative awareness curve also seems to indicate a rising trend.

This construction of a model of the awareness process within technology innovation diffusion stands as an initial attempt to construct a theory of innovation diffusion.

Social Systems Simulation Group
P.O. Box 6904
San Diego, CA  92166-0904
Roland Werner, Principal
Phone/FAX  (619) 660-1603

Copyright © 1996-2004 Social Systems Simulation Group.
All rights reserved.