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 |