Publicação
The Impact of ChatGPT on Workers Performance using the Task-Technology Fit Theory
| datacite.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | pt_PT |
| dc.contributor.advisor | Rodrigues, Teresa Maria Ferreira | |
| dc.contributor.advisor | Costa, Maria Manuela Simões Aparício da | |
| dc.contributor.author | Monteiro, Ana Luísa Luz do Val Correia | |
| dc.date.accessioned | 2024-11-11T12:21:01Z | |
| dc.date.embargo | 2027-10-30 | |
| dc.date.issued | 2024-10-30 | |
| dc.description | Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence | pt_PT |
| dc.description.abstract | The integration of generative AI technologies like ChatGPT in professional settings is transforming how workers interact with information systems and perform their tasks. This study examines the factors influencing the use of ChatGPT in the workplace, and how these factors affect individual performance. We developed a conceptual model grounded in the Task-Technology Fit (TTF) theory, the Technology Acceptance Model (TAM), and perceived risk frameworks. To evaluate this model, we conducted a survey in Portugal, among 229 ChatGPT users in the workplace and analyzed the data using partial least squares structured equation modeling. Our findings indicate that the model explains 65% of the variance in individual performance, through TTF, use and perceived usefulness. Additionally, use is explained by our model in 50.1%, through TTF, perceived usefulness and perceived ease of use. Perceived risk was found to moderate the relationship between perceived usefulness and use of ChatGPT. | pt_PT |
| dc.identifier.tid | 203777913 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/174964 | |
| dc.language.iso | eng | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | ChatGPT | pt_PT |
| dc.subject | Individual performance | pt_PT |
| dc.subject | Task-Technology Fit | pt_PT |
| dc.subject | Technology Acceptance Model | pt_PT |
| dc.subject | Perceived Risk | pt_PT |
| dc.subject | SDG 8 - Decent work and economic growth | pt_PT |
| dc.subject | SDG 9 - Industry, innovation and infrastructure | pt_PT |
| dc.title | The Impact of ChatGPT on Workers Performance using the Task-Technology Fit Theory | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | embargoedAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | Mestrado em Gestão de Informação, especialização em Gestão do Conhecimento e Inteligência de Negócio | pt_PT |