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dc.contributor.advisorMoser, Bryan R.
dc.contributor.authorHernandez, Matthew John
dc.date.accessioned2022-02-07T15:19:47Z
dc.date.available2022-02-07T15:19:47Z
dc.date.issued2021-09
dc.date.submitted2021-10-21T19:54:49.834Z
dc.identifier.urihttps://hdl.handle.net/1721.1/140027
dc.description.abstractThis thesis investigates individual and organizational learning, focusing on the impacts of knowledge acquisition and transfer due to cognitive, social, and organizational proximity. A literature review on individual, team, and organizational learning identified how knowledge is acquired and transferred. Knowledge can be broken down into two main categories, explicit and tacit. Tacit knowledge is difficult to articulate and transmit but can frequently occur through collaboration. Simulation analyses using an agent-based model was utilized to explore collaboration as a mechanism for knowledge transfer. Large cognitive distances showed significant increases in collaboration times and a decrease in overall organizational performance. Agents with no prior experience will acquire more knowledge when placed on mixed skilled teams than similarly skilled teams but at the cost of more senior agents’ ability to complete their work demands. With more data readily available, organizations should be more intentional about talent management regarding the development of new skills to penetrate an organization.
dc.publisherMassachusetts Institute of Technology
dc.rightsIn Copyright - Educational Use Permitted
dc.rightsCopyright retained by author(s)
dc.rights.urihttps://rightsstatements.org/page/InC-EDU/1.0/
dc.titleInvestigation of Learning by Proximity Using An Agent-based Model and Simulation
dc.typeThesis
dc.description.degreeS.M.
dc.contributor.departmentSystem Design and Management Program.
mit.thesis.degreeMaster
thesis.degree.nameMaster of Science in Engineering and Management


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