Year: 2020
Type: dissertation
Abstract: Machine learning (ML) has become one of the hottest trends in the IT field. Knowing that ML can positively impact an organization’s performance, it is, therefore, crucial that the drivers upon its adoption are studied. Using the technology-organization-environment (TOE) framework and the institutional (INT) theory, an empirical measurement of the key determinants of ML adoption was made in a single framework. A structural equation modeling (SEM) technique was used in a dataset of 319 firms to test the suggested hypotheses. The research empirically sustains the impact of the environment on ML adoption, not only as a predictor but also as a moderator of the technological context.
Author: Pedro Miguel Teixeira Filipe
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W3084062860