TOWARD A MULTI-STAGE INFORMATION CONVERSION MODEL OF THE RESEARCH AND DEVELOPMENT PROCESS.

Abstract

Research and development activities in a business firm or government laboratory are portrayed as a multi-stage information generation and conversion process. A 'basic research' phase generates opportunities, in the form of findings in a set of scientific disciplines, which are available for subsequent exploitation. It is assumed that increments to information in a subject area are stochastic, proportional to the amount of knowledge which already exists in the area, and have values which are randomly distributed. An 'exploratory development' phase is viewed as a process of selecting a subset of alternative research opportunities, improving each opportunity in the direction of its applications, estimating the value of the improved opportunity and using these estimates to choose the exploratory development results to be implemented in engineering development. The 'engineering development' phase makes the value of exploratory results realizable without changing value or risk. Engineering development costs are assumed to increase as value increases. If exploratory development is not successful, additional costs in engineering development must be incurred to bring the design up to a minimum desirable level. The model is intended as a step toward formulating and analyzing problems in management planning and control of the several interrelated stages of the research and development process. (Author)

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1965
Accession Number
AD0621847

Entities

People

  • Andrew C. Stedry
  • Richard G. Brandenburg

Organizations

  • Carnegie Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Commerce
  • Conversion
  • Demographic Cohorts
  • Engineering
  • Governments
  • Industrial Engineering
  • Management Engineering
  • Management Planning And Control
  • Political Science
  • Social Sciences

Readers

  • Statistical inference.
  • Systems Analysis and Design