Date of Award

12-22-2016

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Department of Systems Engineering and Management

First Advisor

John M. Colombi, PhD.

Abstract

Supply networks exist throughout society in manufacturing and knowledge-intensive industries as well as many service industries. Organizations have been noted to behave as complex adaptive systems or information supply networks with both formal and informal structures. Thoroughly understanding supply network structure and behavior are critical to managing such organizations effectively, but their properties of complex adaptive systems make them more difficult to analyze and assess, forcing researchers to rely on unrealistic data or assumptions of behavior. This research proposes an information theoretic methodology to discover such complex network structures and dynamics while overcoming the difficulties historically associated with their study. Indeed, this was the first application of an information theoretic methodology as a tool to study complex adaptive supply networks. Moreover, managing these complex networks with formal and informal structures poses additional challenges because the effects of intervention can result in even more unpredictable effects. Noting that two primary functions of organizational networks are to transfer information between nodes and store information in the network, this research quantifies the effects of increased and decreased node performance on the ability of multiple organizational network topologies to accomplish these tasks. Multiple qualitative observations from previous researchers are quantitatively analyzed using information theoretic modeling and simulation. Results show an increased ability in local teams to store information within the network as well as a decreased ability by core-periphery networks to respond to increased information rates.

AFIT Designator

AFIT-ENV-DS-16-D-029

DTIC Accession Number

AD1032039

Download

Share

COinS