Boundary-Spanning and Perceived Political Environments in Technologically-Intensive Public Agencies.

Abstract

This study seeks to test a number of hypotheses pertaining to boundary spanning in public organizations. The focus is on boundary-spanning behavior within state government with data drawn from questionnaire responses of a sample of individuals employed in technologically-intensive programs of New York State government n-650. Hypothesized predictions of boundary spanning activity include: interorganizational conflict; perception of the importance of external political change; program stability; organizations structure; and job satisfaction. A factor analysis yielded clustering patterns closely conforming to the predictor variables and scores on a boundary-spanning scale were correlated with factor scores for one dimension. Four of the independent variables factors are significantly associated with boundary - spanning activity. Taken together, the findings provide a profile of public sector boundary - spanning. The boundary spanner's organization is enjoying growth but at the expense of some external conflict. In such circumstances it is especially important that political change be closely monitored since any future growth can be expected to be closely tied to developments in the external political environment.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1980
Accession Number
ADA093137

Entities

People

  • Barry Bozeman
  • Robert Mcgowan

Tags

Communities of Interest

  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Clustering
  • Compensation
  • Executives
  • Factor Analysis
  • Governments
  • Job Satisfaction
  • Management Personnel
  • National Politics
  • New York
  • Organization Theory
  • Organizational Structure
  • Personnel Management
  • Political Science
  • Public Administration
  • Public Policy
  • State Governments
  • United States

Readers

  • East Asian Political and Security Studies within the Soviet Union
  • Organizational Process Management (OPM).
  • Regression Analysis.