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dc.contributor.advisor | Krejci, Caroline | |
dc.creator | Farhan, Mohammed | |
dc.date.accessioned | 2023-06-27T17:15:44Z | |
dc.date.available | 2023-06-27T17:15:44Z | |
dc.date.created | 2021-05 | |
dc.date.issued | 2021-05-05 | |
dc.date.submitted | May 2021 | |
dc.identifier.uri | http://hdl.handle.net/10106/31317 | |
dc.description.abstract | The purpose of this research is to examine how a change in a team member's role, team dynamics, and organizational policies impact an individual's motivation to engage in helping behavior, as well as the impact of helping behavior on service system operational performance. To analyze these behavioral dynamics in a dynamic setting, this research integrates empirical human behavioral data into a hybrid discrete-event and agent-based simulation model of service operations in a restaurant. The model was then validated using Metamorphic Testing (MT), an approach that has previously been used for verification of software. Recent research shows that MT can be used to validate both agent-based models and discrete event simulation models. This research builds on that work by demonstrating that MT can also be used to validate hybrid simulation models. Metamorphic relations were systematically developed following the framework presented in this research to run different validation experiments. The experiments applied MT for validating both DES and ABM aspects of the hybrid model separately, as well as the combined overall model. Through the upholding of the predicted pseudo-oracle answers, the research shows increased confidence in the validity of the simulation model. | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en_US | |
dc.subject | Hybrid simulation | |
dc.subject | Agent-based modeling | |
dc.subject | Discrete-event modeling | |
dc.subject | Human Behavioral models | |
dc.subject | Model validation | |
dc.subject | Metamorphic testing validation | |
dc.title | USING EMPIRICAL DATA TO DESIGN AND VALIDATE HYBRID SIMULATION MODELS OF HUMAN BEHAVIOR IN SERVICE OPERATIONS | |
dc.type | Thesis | |
dc.date.updated | 2023-06-27T17:15:44Z | |
thesis.degree.department | Industrial and Manufacturing Systems Engineering | |
thesis.degree.grantor | The University of Texas at Arlington | |
thesis.degree.level | Doctoral | |
thesis.degree.name | Doctor of Philosophy in Industrial Engineering | |
dc.type.material | text | |
dc.creator.orcid | 0000-0002-7881-3875 | |
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