The impact of culture on entrepreneurship: machine learning analysis
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Authors
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Publication date
2023
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01A - Journal article
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Parent work
Interdisciplinary Journal of Economics and Business Law
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Volume
12
Issue / Number
4
Pages / Duration
93-117
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CJEAS
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Abstract
Entrepreneurship is one of the main pillars of the economy and it has a substantial role to pay in economic development by creating new jobs and opportunities, driving innovation, and developing new markets, products, and services. This study aims to better understand the motivations of people who choose to undertake entrepreneurial activity and to try to pinpoint some of the key factors that move them to do so. Three independent data sets (the GEM, WVS and Hofstede) were computed and significant correlations with Total Early-Stage Entrepreneurial Activity (TEA) noted. Machine learning techniques were applied to the data sets in different regression models to show that the most important relationship between the different variables is the TEA with Perceived Capabilities (PC).
Keywords
Machine learning, Entrepreneurship, GEM, Cultural attributes
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ISSN
2047-8747
2047-8755
2047-8755
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
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Peer review of the complete publication
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Closed
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Citation
AL-KILANI, Mahmoud, Rolf MEYER, Dario MEYER, Daniel SCHNYDER und Vlad-Andrei SABO, 2023. The impact of culture on entrepreneurship: machine learning analysis. Interdisciplinary Journal of Economics and Business Law. 2023. Bd. 12, Nr. 4, S. 93–117. Verfügbar unter: https://irf.fhnw.ch/handle/11654/44629