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Maël Schnegg
Title
Prof. PhD
Last Name
Schnegg
First name
Maël
Email
mael.schnegg@unisg.ch
Phone
+41 71 224 74 23
Now showing
1 - 10 of 30
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PublicationType: journal articleJournal: Journal of Management ControlVolume: 33Issue: 2
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PublicationType: journal articleJournal: Expert Focus
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PublicationImpact de la divulgation d’informations sur la responsabilité des entreprises – Des bénéfices extrinsèques et intrinsèques se font sentir( 2020)
;Derchi, Giovanni Battista ;Oyon, DanielType: journal articleJournal: Expert Focus -
PublicationDéploiement d’un système de suivi de l’environnement - Impacts sur la culture organisationnelle des entreprises( 2020)
;Oyon, Daniel ;Dubois, ThibaudDerchi, Giovanni BattistaType: journal articleJournal: Expert Focus -
PublicationFirms need new ways to monitor their environment( 2019)
;Markides, Costas ;Oyon, DanielType: journal articleJournal: London Business School Review -
PublicationLe système de suivi de l’environnement: Le Landscape Monitor pour percevoir les opportunités et les risques( 2017)
;Davila, Antonio ;Oyon, Daniel ;Parmigiani, PilarType: journal articleJournal: Expert Focus -
PublicationLook outside your firm: a tool to sense what’s coming: the landscape monitor( 2015)
;Davila, Antonio ;Oyon, Daniel ;Parmigiani, PilarType: journal articleJournal: IESE InsightVolume: 25Issue: 2 -
PublicationIdentifying and Overcoming Organization and Ethical Barriers to AI Adoption( 2023-05-26)
;Elita SabaniTechnology companies are leading the pack in the use of Artificial Intelligence (AI) and other industries are taking advantage of AI to streamline processes and increase competitive advantage. On the way to implementing AI, organizations face ethical and organizational obstacles, which this study identifies through a structured literature review. It identifies six general ethical barriers to AI adoption, i.e., human well-being, trust, fairness, transparency, oversight & regulation, and accountability and four organizational barriers, i.e., resources, governance, culture, and employee intention to use AI. The study then examines two AI organizational governance frameworks and discusses how they might be useful in overcoming the barriers.Type: conference paperJournal: 1ST INTERDISCIPLINARY CONFERENCE ON MANAGEMENT, INFORMATION TECHNOLOGY AND COMPUTER SCIENCES -
PublicationType: conference paperJournal: 20th EIASM WORKSHOP ON CORPORATE GOVERNANCE
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PublicationType: conference paper
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