Investigating information flow efficiency and employees’ centralization in a business organization: A network analysis approach

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dc.contributor.advisor Zollo, Fabiana it_IT
dc.contributor.author Giacomel, Greta <1998> it_IT
dc.date.accessioned 2022-10-03 it_IT
dc.date.accessioned 2023-02-22T10:57:35Z
dc.date.issued 2022-10-26 it_IT
dc.identifier.uri http://hdl.handle.net/10579/22459
dc.description.abstract Organizational Network Analysis (ONA) derives methods from network science for studying relationships within a business organization with the aim of helping companies make better strategic decisions. Companies adopting this system aim at analyzing relationships between employees that reveal information about relevant people, independent of their placement in the hierarchical structure, their experience in the organization, and their job level. Moreover, the objective could consist in investigating other types of connections, such as: relationships among resources, disclosing the ones that are often used together; relationships between people Knowledge, Skills and Abilities (KSAs) and resources, in order to measure if there is an excess or a lack of KSAs over the available resources; the relationships between people and KSAs, in order to facilitate the commission of projects and tasks, take hiring decisions or propose career development programs. Here, we will build the socio-technical network of a consulting firm in the Business Intelligence field to analyze an overview of the information flow among departments, identify relevant people and study their role in how efficiently information and knowledge flow in the network. it_IT
dc.language.iso en it_IT
dc.publisher Università Ca' Foscari Venezia it_IT
dc.rights © Greta Giacomel, 2022 it_IT
dc.title Investigating information flow efficiency and employees’ centralization in a business organization: A network analysis approach it_IT
dc.title.alternative Investigating information flow efficiency and employees’ centralization in a business organization: A network analysis approach it_IT
dc.type Master's Degree Thesis it_IT
dc.degree.name Data analytics for business and society it_IT
dc.degree.level Laurea magistrale it_IT
dc.degree.grantor Dipartimento di Economia it_IT
dc.description.academicyear 2021-2022_appello_171022 it_IT
dc.rights.accessrights closedAccess it_IT
dc.thesis.matricno 867057 it_IT
dc.subject.miur INF/01 INFORMATICA it_IT
dc.description.note it_IT
dc.degree.discipline it_IT
dc.contributor.co-advisor it_IT
dc.date.embargoend 10000-01-01
dc.provenance.upload Greta Giacomel (867057@stud.unive.it), 2022-10-03 it_IT
dc.provenance.plagiarycheck Fabiana Zollo (fabiana.zollo@unive.it), 2022-10-17 it_IT


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