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Dissertation/Thesis Abstract

A Methodology for Analyzing and Managing Complex Stakeholder Networks
by Hill, Robert, Ph.D., The George Washington University, 2021, 211; 28412518
Abstract (Summary)

Systems engineers, strategists and technical leaders of all stripes are tasked with the challenge of managing stakeholders in a complex environment. In the complex domain, whether an engineered system or enterprise, the relations both with and between the persons and entities affecting the survival and growth of the organization can be modelled as a stakeholder network. In such networks, relationships are valuable but costly, consuming time, mental bandwidth, and resources. Interactions with and between stakeholders must be prioritized and made more efficient. In this research, a novel graph theoretic framework was developed, based on extensive review of the complex systems, stakeholder theory, strategy, and network science literatures. This methodology analyzes and even manages stakeholder relationships, improving the reliability and efficiency of communication within the network. Real-world, complex social networks were constructed using supply chain and financial data for one hundred of the largest public US firms and measured for robustness, global connectivity, and efficiency, connecting these qualities to statistics such as percolation threshold, assortativity and transitivity. A linear regression approach showed that these measures are associated with a wide range of financial and non-financial performance metrics. Practical examples of how enterprise managers could leverage these network characteristics are demonstrated. Future research directions are identified, and the research is applied to the problem of managing in a post-Covid world. The emphasis throughout is on gaining strategic advantage, by using resilient stakeholder networks to produce survivable stakeholder systems.

Indexing (document details)
Advisor: Mazzuchi, Thomas, Sarkani, Shahram
Commitee: Holzer, Thomas, Blackford, Joseph P., Etemadi, Amir
School: The George Washington University
Department: Systems Engineering
School Location: United States -- District of Columbia
Source: DAI-A 82/10(E), Dissertation Abstracts International
Subjects: Social research, Engineering
Keywords: Assortativity, Clustering, Network resilience, Percolation, Social networks, Stakeholders
Publication Number: 28412518
ISBN: 9798597097121
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