Power, Performance, and Perception (P3): Integrating Usability Metrics and Technology Acceptance Determinants to Validate a New Model for Predicting System Usage

Abstract

Currently, there are two distinct approaches to assist information technology managers in the successful implementation of office automation software. The first approach resides within the field of usability engineering, while the second approach is derived from the discipline of management information systems (MIS). However, neither approach has successfully produced conclusive evidence that explains what characteristics facilitate system use as well as influence user acceptance of the system. This study reports on the validity of a new model, entitled the Power, Performance, Perception (P3) model, that links the constructs of usability engineering to user acceptance. Additionally, speech recognition software (SRS) was used in an experimental setting to validate the P3 model. This research also examined the viability of employing SRS in an Air Force office environment. The results of this study failed to validate the P3 model. However, an alternate model for predicting user acceptance, the Usability Acceptance Model, did emerge from the research which showed that the usability metric of user satisfaction can explain 53% of the variance of user intention to use a new technology. Additionally, the results of this study indicate that users in a typical Air Force office environment would utilize SRS for text processing.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1999
Accession Number
ADA374228

Entities

People

  • Alan P. Fiorello

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Energy and Power Technologies
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Application Software
  • Automated Speech Recognition
  • Cognitive Systems Engineering
  • Computer Programming
  • Computer Programs
  • Computers
  • Human Behavior
  • Human-Computer Interaction
  • Information Systems
  • Management Information Systems
  • Psychology
  • Regression Analysis
  • Software Development
  • User Interface
  • User Interface Engineering
  • Word Processors

Fields of Study

  • Computer science
  • Engineering

Readers

  • Computational Modeling and Simulation
  • Software Engineering.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - DoD AI Strategy