Developing Measures Of Effectiveness For Assessing And Predicting Technology Integration

Abstract

This thesis studies the development of measures of effectiveness (MOE) to determine the level of technology integration for Navy Environmental Sustainability Development to Integration (NESDI) projects, with a focus on identifying significant technology characteristics that can be used to predict the likelihood of integration for future projects. The definition of technology integration in this study comprises the three incremental phases of transition, adoption, and diffusion. Through case study analysis of completed NESDI projects, two approaches were employed to identify significant technology characteristics that seemed to impact the level of technology integration correlation approach and graphical approach. Multiple linear regression was used to demonstrate how predictive models could be generated for the correlation approach, whereas the graphical approach presented significant characteristics as a success profile in the form of a Venn diagram. The predictive models and success profile aim to assist decision-making on whether resources should be invested in a future project, by predicting the likelihood of technology integration for that project. While the results were limited by time constraints and the availability of suitable case studies for analysis, this study demonstrated the methodology on how technology integration could be measured and predicted using the developed MOEs and significant technology characteristics.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2018
Accession Number
AD1065428

Entities

People

  • Xinhong Lin

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Availability
  • California
  • Case Studies
  • Correlation Analysis
  • Data Science
  • Diffusion
  • Drinking Water
  • Engineering
  • Engineers
  • Environmental Protection
  • Fire Suppression
  • Information Science
  • Information Systems
  • Measures Of Effectiveness
  • Personnel Management
  • Predictive Modeling
  • Regression Analysis
  • Software Development
  • Spreadsheet Software
  • Standards
  • Statistical Analysis
  • Systems Engineering
  • Test And Evaluation
  • Water Quality

Readers

  • Computational Modeling and Simulation
  • Military Science and Technology Research and Modernization.
  • Organizational Process Management (OPM).