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  • Search: subject:"robust regression models"
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Year of publication
Subject
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AI skills 2 Hofstede 2 OLS multiple regression 2 artificial intelligence (AI) 2 national culture 2 organisational competitiveness 2 robust regression models 2 Artificial intelligence 1 Künstliche Intelligenz 1 Multiple Regression 1 Multiple regression 1 National culture 1 Nationalkultur 1 Occupational qualification 1 Qualifikation 1 Regression analysis 1 Regressionsanalyse 1
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Online availability
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Free 2 CC license 1
Type of publication
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Article 2
Type of publication (narrower categories)
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Article 1 Article in journal 1 Aufsatz in Zeitschrift 1
Language
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English 2
Author
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Cernat-Gruici, Bogdan 2 Constantin, Laura-Gabriela 2 Iamandi, Irina-Eugenia 2 Munteanu, Sebastian Mădălin 2
Published in...
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Amfiteatru Economic 1 Amfiteatru economic : an economic and business research periodical 1
Source
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ECONIS (ZBW) 1 EconStor 1
Showing 1 - 2 of 2
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Insights on the relationship between artificial intelligence skills and national culture
Iamandi, Irina-Eugenia; Constantin, Laura-Gabriela; … - In: Amfiteatru Economic 26 (2024) 67, pp. 741-761
In order to fully benefit from the advantages induced by artificial intelligence (AI) at the corporate level, business organisations should be well aware of the factors contributing to the proper AI specialisation of their employees. In this context, the present paper aims to examine the role of...
Persistent link: https://www.econbiz.de/10015106478
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Cover Image
Insights on the relationship between artificial intelligence skills and national culture
Iamandi, Irina-Eugenia; Constantin, Laura-Gabriela; … - In: Amfiteatru economic : an economic and business research … 26 (2024) 67, pp. 741-761
In order to fully benefit from the advantages induced by artificial intelligence (AI) at the corporate level, business organisations should be well aware of the factors contributing to the proper AI specialisation of their employees. In this context, the present paper aims to examine the role of...
Persistent link: https://www.econbiz.de/10015077010
Saved in:
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