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<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>Technological advancements and organizational discrimination</dc:title><dc:creator>Aydin,	Erhan	(Avtor)
	</dc:creator><dc:creator>Rahman,	Mushfiqur	(Avtor)
	</dc:creator><dc:creator>Bulut,	Çağri	(Avtor)
	</dc:creator><dc:creator>Biloslavo,	Roberto	(Avtor)
	</dc:creator><dc:subject>Industry 5.0</dc:subject><dc:subject>migrant workers</dc:subject><dc:subject>organizational discrimination</dc:subject><dc:subject>human resource management</dc:subject><dc:subject>technological advancements</dc:subject><dc:description>This study explores the impact of Industry 5.0 on discriminatory behaviors toward migrant
employees within organizations. Through semi-structured qualitative interviews with 15 migrant
workers in the UK, this research identifies key challenges faced by migrant employees amidst the
integration of advanced technologies like AI and robotics in HRM systems. Thematic analysis reveals
that while Industry 5.0 has the potential to mitigate human biases, it can also perpetuate existing
prejudices if not managed effectively. This study highlights two main themes: the experiences of
discrimination and challenges in the context of Industry 5.0, and the role of technology in HRM
systems. The findings indicate that automated HR systems can both reduce and increase biases,
highlighting the importance of inclusive practices and targeted support programs to help migrant
workers adapt to a technologically advanced labor market. This research contributes to the literature
by providing insights into the duality of technological advancements in reducing and reinforcing
workplace discrimination.</dc:description><dc:date>2024</dc:date><dc:date>2024-09-30 08:34:33</dc:date><dc:type>Neznano</dc:type><dc:identifier>20497</dc:identifier><dc:identifier>UDK: 331.522:004</dc:identifier><dc:identifier>ISSN pri članku: 2076-3387</dc:identifier><dc:identifier>DOI: 10.3390/admsci14100240 </dc:identifier><dc:identifier>COBISS_ID: 209394435</dc:identifier><dc:language>sl</dc:language><dc:rights>The authors</dc:rights></metadata>
