Measuring Performance in Complex Adaptive Systems:  An Agent-Based Approach to Managerial and Technological Change

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dc.contributor.authorLyddane, Glen Edwarden
dc.contributor.committeechairTriantis, Konstantinos P.en
dc.contributor.committeechairVan Aken, Eileen Mortonen
dc.contributor.committeememberGhaffarzadegan, Naviden
dc.contributor.committeememberHerrera-Restrepo, Oscar A.en
dc.contributor.departmentIndustrial and Systems Engineeringen
dc.date.accessioned2026-01-23T09:00:30Zen
dc.date.available2026-01-23T09:00:30Zen
dc.date.issued2026-01-22en
dc.description.abstractgeneralIn today's fast-paced and unpredictable world, organizations must constantly adapt to stay efficient, innovative, and competitive. This dissertation explores how organizational performance can be better understood and measured by viewing the organization as a Complex Adaptive System (CAS), a dynamic network of socio-technical systems including people, teams, and technologies that continuously evolve and respond to change. To measure how well these systems perform over time, this research uses advanced models from the efficiency measurement paradigm, such as the Malmquist Index (MI) and Hicks-Moorsteen Index (HMI). These models can track improvements in how resources are used (efficiency) and progress in innovation or technology (productivity shifts), considering both managerial and technological perspectives. This dissertation separates managerial and technological change efficiency analysis over multiple time periods for CASs, constituting a major contribution of this dissertation. Furthermore, the study creates a flexible and powerful system by linking a simulation platform with data analysis tools in testing ideas, performing sensitivity analyses, and validating results using real-world data. At the heart of this study is a computer simulation model called Complex Adaptive Productive Efficiency Model (CAPEM). This dissertation dives into model version 2.0 (CAPEM 2.0), which builds on previous versions of CAPEM. CAPEM 2.0 integrates new insights from complexity science and behavioral theory in simulating how diverse parts of an organization interact, learn, and make decisions, especially in decentralized environments. A guiding metaphor in this research is "flocking," which has inspired me through the way birds move as a group. Just as birds adjust their paths based on the movements of leaders and nearest neighbors, like peers around them, people and teams in organizations often appear to adapt their actions based on local information, collaboration, and feedback. A case study involving deregulated power plants (DPPs) demonstrates how CAPEM 2.0 can assist in uncovering which factors have the optimal impact on system-wide outcomes. For example, it reveals how certain roles, behaviors, or conditions can excessively affect an organization's success by providing crucial guidance for decision-makers who operate in dynamic environments. Overall, this research offers a new way to think about performance in complex systems. It emphasizes the importance of adaptive strategies, decentralized decision-making, and innovation-driven efficiency. CAPEM 2.0 gives analysts and policymakers an approach for designing systems that advance and innovate as they continue to evolve and improve over time.en
dc.description.degreeDoctor of Philosophyen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:45630en
dc.identifier.urihttps://hdl.handle.net/10919/140948en
dc.language.isoenen
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectsocio-technical systemsen
dc.subjectinfrastructure systems engineeringen
dc.subjectefficiency performance measurementen
dc.subjectData Envelopment Analysis (DEA)en
dc.subjectMalmquist Index (MI)en
dc.subjectMalmquist Production Index (MPI)en
dc.subjectHicks-Moorsteen Index (HMI)en
dc.subjectmultivariate statisticsen
dc.subjectrobust prien
dc.titleMeasuring Performance in Complex Adaptive Systems:  An Agent-Based Approach to Managerial and Technological Changeen
dc.typeDissertationen
thesis.degree.disciplineIndustrial and Systems Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.nameDoctor of Philosophyen

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