Please use this identifier to cite or link to this item: https://rfos.fon.bg.ac.rs/handle/123456789/2787
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dc.creatorIvančević, Sonja-
dc.creatorKićanović, Ana-
dc.creatorDrinjak, Nikola-
dc.date.accessioned2024-10-04T17:00:52Z-
dc.date.available2024-10-04T17:00:52Z-
dc.date.issued2024-09-
dc.identifier.issn1849-5141-
dc.identifier.urihttps://rfos.fon.bg.ac.rs/handle/123456789/2787-
dc.description.abstractThe fast development and integration of (AI) artificial intelligence within the workplace led to significant transformations and disruptions across industries. Alongside its promises of improved eficiency and innovation, AI adoption has raised concerns regarding potential job displacement and workforce anxiety. One of the industries which has especially been transformed by AI is the IT industry. This study has the goal of assessing the IT employee's layoff anxiety in the two-year and ten-year period, taking into account ther attitudes and perceptions of how AI changes and complements their skillS. An econometric approach will be employed to model how perceptions of the transformational power of AI impact workforce anxiety. The results indicate that workforce anxiety can be successfully modeled and that the perceptiou of one's skills being less valuable is a significant predictor. It is hoped tnat the research findings will shed light on the complex nature of layoff anxiey in the context of AI-driven skill transformations, providing valuable insiguts for IT employees, human resource managers, organisational leaders and stakeholders.sr
dc.language.isoensr
dc.rightsopenAccesssr
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceBook of abstracts 20th International Conference on Operational Research, Edited by: Šestanović, T. & Škrabić Perićsr
dc.subjectturnover intentionsr
dc.subjectartificial intelligencesr
dc.subjectworkplace transformationsr
dc.subjecteconometric modellingsr
dc.titleNavigating AI-induced workplace transformation: An econometric study of layoff anxietysr
dc.typeconferenceObjectsr
dc.rights.licenseBYsr
dc.citation.epage26-
dc.citation.spage26-
dc.identifier.fulltexthttp://prototype2.rcub.bg.ac.rs/bitstream/id/4044/KOI 2024 - Ivančević et al. (2024).pdf
dc.type.versionpublishedVersionsr
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.grantfulltextopen-
item.openairetypeconferenceObject-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
Appears in Collections:Radovi istraživača / Researchers’ publications
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