Hypothesis Testing of Edge Organizations: Empirically Calibrating an Organizational Model for Experimentation

Abstract

This paper presents our ongoing efforts to model, simulate, and eventually optimize work and knowledge flows in Edge organizations. We use the extended POW-ER 3.2 framework to model and compare two organizational forms (Edge vs. Hierarchy) to structure participants in a counter-intelligence student exercise, ELICIT - first without, and then with, learning micro-behaviors enabled in POW-ER 3.2. Empirical, experimental data on learning and forgetting from observations of student teams conducting repeated trials of the AROUSAL (Lansley, 1982) business simulation exercise at Stanford are used as the basis for calibrating agent learning and forgetting micro-behaviors derived from the cognitive psychology literature. We then compare empirical observations of student teams conducting the ELICIT exercise for both Edge and Hierarchy structural configurations with outputs from POW-ER 3.2 computational simulation models representing teams executing the ELICIT exercise in these two structural configurations. This initial comparison has the potential to further calibrate and validate POW-ER for potential use in analyzing and designing C2 organizations. Future output from ELICIT experiments and other empirical data on learning and forgetting will augment our initial comparison. Calibrated POW-ER 3.2 learning and forgetting micro-behaviors will improve the ability of POW-ER to model and simulate organization-level C2 knowledge flows in Edge vs. Hierarchical organizations.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2007
Accession Number
ADA481380

Entities

People

  • Douglas J. MacKinnon
  • Marc Ramsey
  • Mark E. Nissen
  • Raymond E. Levitt

Organizations

  • Stanford University

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acquisition
  • Cardiopulmonary Resuscitation
  • Classification
  • Cognitive Science
  • Command And Control
  • Commerce
  • Counterterrorism
  • Experimental Data
  • Hierarchies
  • Knowledge Management
  • Literature
  • Observation
  • Organizational Structure
  • Psychology
  • Simulations
  • Students
  • Websites

Readers

  • Computational Modeling and Simulation
  • Neural Network Machine Learning.
  • Organizational Process Management (OPM).