Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10362/146111| Título: | Unlocking machine learning business value |
| Autor: | Reis, Carolina Ruivo, Pedro Oliveira, Tiago Faroleiro, Paulo |
| Palavras-chave: | Business value Machine learning Resource-based view Information Systems and Management Management Information Systems Management of Technology and Innovation Information Systems Computer Science Applications SDG 8 - Decent Work and Economic Growth |
| Data: | 1-Out-2019 |
| Resumo: | 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. |
| Descrição: | Reis, 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). |
| Peer review: | yes |
| URI: | http://hdl.handle.net/10362/146111 |
| Aparece nas colecções: | NIMS: MagIC - Documentos de conferências internacionais |
Ficheiros deste registo:
| Ficheiro | Descrição | Tamanho | Formato | |
|---|---|---|---|---|
| Unlocking_Machine_Learning_Business_Value.pdf | 274,01 kB | Adobe PDF | Ver/Abrir |
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