Smart Hrm 4.0: The Digital Transformation of Human Resource Management in Tourism

Marijana Seočanac

The European Journal of Applied Economics, 2025, vol. 22, issue 1, 19-31

Abstract: Industry 4.0 technologies, including artificial intelligence, robots, and the Internet of Things (IoT), have fundamentally reshaped human resource management (HRM). The adoption of these technologies has led to the emergence of smart HRM practices that have the potential to increase employee engagement and operational efficiency. This paper aims to investigate how HRM practices in tourism have changed as a result of new technologies and whether this has led to improvements in operational efficiency, employee engagement, and/or satisfaction. For this purpose, a bibliometric and content analysis was conducted on a sample of 18 papers identified in the Web of Science scientific database. The bibliometric analysis provided a general overview of scientific research, i.e., the dominant journals, authors, and countries in the field, as well as the main research topics. Content analysis was used to summarize the findings of previous research on technology implementation in the following HRM processes: 1) recruitment and selection and employee training and development, and 2) performance management and employee engagement. The findings of this study provide researchers and managers with an overview of the existing research and, by summarizing the main conclusions, provide guidelines for future research and the application of Industry 4.0 technologies in HRM processes in tourism.

Keywords: fourth industrial revolution; industry 4.0; artificial intelligence (AI); HR; tourism and hospitality industry (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journal.singidunum.ac.rs/paper/smart-hrm-4 ... anagement-in-tourism (text/html)

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:sng:ejae01:220

DOI: 10.5937/EJAE22-56542

Access Statistics for this article

More articles in The European Journal of Applied Economics from Singidunum University, Belgrade
Bibliographic data for series maintained by EJAE Editorial Office ().