Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/26201
Title: What do Owners of SMEs Think about Big Data Analytics and Artificial Intelligence Technologies in Their Operations? Evidence from North Macedonia
Authors: Arifi, Mimoza
Cvetkoska, Violeta 
Jovevski, Dimitar 
Keywords: big data analytics, artificial intelligence, financial performance, small and medium-sized enterprises
Issue Date: Mar-2023
Publisher: University of Maribor, University Press
Source: Arifi, M., Cvetkoska, V., & Jovevski, D. (2023). “What do Owners of SMEs Think about Big Data Analytics and Artificial Intelligence Technologies in Their Operations? Evidence from North Macedonia”, in the Conference Proceedings (e-book) of the 42nd International Conference on Organizational Science Development, titled "Interdisciplinarity counts”, held from 22nd to 24th March 2023, Portoroz, Slovenia, pp. 51-64. DOI: https://doi.org/10.18690/um.fov.3.2023. Available at: https://press.um.si/index.php/ump/catalog/book/768
Conference: 42nd International Conference on Organizational Science Development, titled "Interdisciplinarity counts”, held from 22nd to 24th March 2023, Portoroz, Slovenia
Abstract: Small and medium-sized businesses can use big data analytics and artificial intelligence algorithms to fully realize the potential of big data, giving them a competitive edge. The discovered information from big data can serve as a recommendation for making better and faster decisions and creating values for those enterprises, such as higher profit, efficiency, productivity, customer, and employee satisfaction, etc. The aim of this paper is to investigate what owners of SMEs in a developing country consider about big data analytics and artificial intelligence (AI) in their operations. The data is collected for the first time by using a semi-structured questionnaire distributed by email. For descriptive analytics, we use Power BI software, and we develop a logistic regression model to find the key influencers of AI and big data automated features that completely affect staffing levels. The obtained results are visualized and analyzed. The findings are beneficial for SMEs to invest in those technologies and in the staff's skills in these areas, as well as for the nation's economic policymakers to support and boost the use of those technologies by small and medium-sized businesses.
URI: http://hdl.handle.net/20.500.12188/26201
DOI: https://doi.org/10.18690/um.fov.3.2023
Appears in Collections:Faculty of Economics 02: Conference papers / Трудови од научни конференции

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