EXPLORING GENERATIONAL DIFFERENCES IN ATTITUDES TOWARD HUMAN-LIKE ROBOTS
Maria Barbul (),
Irina Bojescu () and
Miruna Niculescu ()
Additional contact information
Maria Barbul: The Bucharest University of Economic Studies, Bucharest, Romania
Irina Bojescu: : The Bucharest University of Economic Studies, Bucharest, Romania
Miruna Niculescu: The Bucharest University of Economic Studies, Bucharest, Romania
Annals of Faculty of Economics, 2024, vol. 33, issue 2, 295-306
Abstract:
The rapid advancement of robotic technologies and artificial intelligence (AI) has sparked widespread interest and debate regarding their integration into various aspects of daily life. As robots become increasingly capable of performing tasks traditionally carried out by humans, understanding public perception of these technologies becomes crucial. The objective of this paper is to explore the generational differences in attitudes toward robots. While younger generations may be more open to the integration of robots into daily life, addressing the concerns of older generations will be crucial for widespread acceptance. This analysis highlights the importance of considering generational perspectives when developing and implementing robotic technologies in various sectors.
Keywords: artificial intelligence; robots; consumers; anthropomorphic; acceptance; generations. (search for similar items in EconPapers)
JEL-codes: M31 (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:
Downloads: (external link)
https://anale.steconomiceuoradea.ro/en/wp-content/ ... December.2024.25.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ora:journl:v:2:y:2024:i:2:p:295-306
Access Statistics for this article
More articles in Annals of Faculty of Economics from University of Oradea, Faculty of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Catalin ZMOLE ( this e-mail address is bad, please contact ).