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

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