Reis, CarolinaRuivo, PedroOliveira, TiagoFaroleiro, Paulo2022-12-092022-12-092019-10-01PURE: 18762943PURE UUID: 498d8002-dbfe-4ad2-8eca-fded87f03973Scopus: 85086627013ORCID: /0000-0001-6523-0809/work/76258580http://hdl.handle.net/10362/146111Reis, C., Ruivo, P., Oliveira, T., & Faroleiro, P. (2019). Unlocking machine learning business value. In Atas da Conferencia da Associacao Portuguesa de Sistemas de Informacao 2019: Capsi 2019 (Atas da Conferencia da Associacao Portuguesa de Sistemas de Informacao).Machine learning (ML) stands out as one of the most successful advanced analytics for dealing with big data. However, as a quite recent tool amongst organizations, there are some doubts hanging over this technology. Through an original lens, we expect to substantiate how organizations can sustained ML business value. We developed a conceptual model, grounded on the resource-based view, that aims to validate key antecedents of ML business value. Through a positivist approach, we imply ML use, big data analytics maturity, top management support and process complexity enhance ML business value, in terms of firm performance. Due to the pioneering nature of our research model, we expect to support our data analysis with the partial least squares. To the authors’ best knowledge, this represents the first study aiming such findings on the ML discipline.280582engBusiness valueMachine learningResource-based viewInformation Systems and ManagementManagement Information SystemsManagement of Technology and InnovationInformation SystemsComputer Science ApplicationsSDG 8 - Decent Work and Economic Growthconference objecthttps://www.scopus.com/pages/publications/85086627013https://www.novaims.unl.pt/uploads/imagens_ficheiros/CAPSI-ata-da-conferencia/ebook-capsi-2019.pdf