Maël Schnegg
Last Name
Schnegg
First name
Maël
Email
mael.schnegg@unisg.ch
Phone
+41 71 224 74 23
33 results
Now showing 1 - 10 of 33
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Item type:Publication, Strategies for data analytics projects in business performance forecasting: a field studyType:journal articleJournal:Journal of Management ControlVolume:33Issue:2Scopus© Citations 16 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Identifier et Exploiter avant Tout le Monde de Nouvelles OpportunitésType:journal articleJournal:Expert Focus - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Impact de la divulgation d’informations sur la responsabilité des entreprises – Des bénéfices extrinsèques et intrinsèques se font sentir(2020) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Déploiement d’un système de suivi de l’environnement - Impacts sur la culture organisationnelle des entreprises(2020); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Firms need new ways to monitor their environment(2019) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Le système de suivi de l’environnement: Le Landscape Monitor pour percevoir les opportunités et les risques(2017) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Look outside your firm: a tool to sense what’s coming: the landscape monitor(2015) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Best Fit in Context: an Analysis of the Target-Specific Application of Agile Project Management Practices(2023-05-24); Type:conference paper - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Identifying and Overcoming Organization and Ethical Barriers to AI Adoption(2023-05-26); ; Technology 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