Contagion, trajectory, and turnover : exploring network factors influencing turnover over time.

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dc.contributor.advisorTripp, John F.
dc.creatorVillafranca, Eric S., 1984-
dc.creator.orcid0000-0003-4613-7224
dc.date.accessioned2016-09-01T14:25:29Z
dc.date.available2016-09-01T14:25:29Z
dc.date.created2016-08
dc.date.issued2016-07-13
dc.date.submittedAugust 2016
dc.date.updated2016-09-01T14:25:29Z
dc.description.abstractOrganizations use a large portion of their budget on building and maintaining human resources. Losing an employee, especially a good one, can be expensive. While turnover has been studied using a network lens, it has traditionally viewed network characteristics as a property of the particular individual, and the majority of research that has examined social network position and its outcomes has focused on a cross-sectional view of an individuals’ position. We consider that an individual’s network position changes over time: moving toward the center of the network becoming more embedded, away from the center becoming less embedded, or staying relatively static. We call this an individual’s Structural Trajectory. We build a research model using Structural Trajectory, and social contagion, to explore the drivers of turnover in a dataset containing employee email metadata. The results show a strong contagion effect, and a relationship between large network movements (Structural Trajectory) and turnover.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/2104/9837
dc.language.isoen
dc.rights.accessrightsWorldwide access.
dc.subjectTurnover. Social contagion. Social network analysis.
dc.titleContagion, trajectory, and turnover : exploring network factors influencing turnover over time.
dc.typeThesis
dc.type.materialtext
thesis.degree.departmentBaylor University. Dept. of Information Systems.
thesis.degree.grantorBaylor University
thesis.degree.levelMasters
thesis.degree.nameM.S.I.S.

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