Document Type

Dissertation

Date of Award

1977

Keywords

Public administration, Data processing, County government, Pennsylvania

Degree Name

Doctor of Philosophy (PhD)

Department

Political Science

First Advisor

Dennis Thompson

Second Advisor

Mary Hanna

Third Advisor

Bakhshish L. Jaggi

Abstract

This dissertation reports on the influence and impact that computers are having on county government in the state of Pennsylvania. It accesses the social and psychological implications of computer technology and to what extent this technology is affecting the functions and operations of county government.

The first part develops a brief history and formal orientation related to the development of the technology and its applications. The concepts of technology and computerization are merged with the application of computers into governmental operations.

Then the justification of an abuse of computers in county government is presented and a narrative is developed for the empirical evaluation and objective development of the survey. The propositions for the study’s foundation are established in the hypothesis, methodology and design to be followed in the research development.

Data from this research is evaluated along with observations and criteria from other similar studies. The factors affecting the historical development of computerization in county government, the impact on the organization, decision making, authority and control, and job content are analyzed to project what impacts the thrust of automation is having on the lower levels of governmental activities. The findings of this study were found to correlate closely to predictions made by Thomas L. Whisler on the impact of EDP on the Life Insurance Industry, except for some exceptions where the public sector differed from the private sector, namely relating to the changes in the various levels of the organization. In the private sector such changes could be identified by the large numbers of organizational levels, while in county government there are only a few distinct levels. Factors related to education, the work environment, management, new technology, and the acceptance of automation could explain the other divergencies encountered in this research.

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