CoChat
Sign Up
Cited by 218AI and HR TechnologiesImpact of AI and Big Data on Business and SocietyEmployer Branding and e-HRM

The DOI matches its Crossref record; 52 of the 54 references it cites were found in a registry or an index.

A study of Artificial Intelligence impacts on Human Resource Digitalization in Industry 4.0

Open access
Murugesan, Umasankar, Subramanian, Padmavathy, Srivastava, Shefali, Dwivedi, Ashish·2023·Decision Analytics Journal
DOI 10.1016/j.dajour.2023.100249
Open this paper in CoChat — free account

Abstract

Artificial Intelligence (AI) has opened up tremendous opportunities in the workplace through robotics innovation, which envelops both AI and the Internet of Things (IoT). Precision, Efficiency, and Flexibility are considered the potential benefits of Industry 4.0. The implementation of Industry 4.0 requires a lot of changes, including the Human Resource (HR) function. In Industry 4.0, the HR capability is more critical and gives an upper hand to the organization. The HR capability should be more cautious and adaptable to adjust to the difficulties and requirements. We study the contributions of AI in HR digitalization and practices in Industry 4.0. 271 HR experts working in Information Technology (IT), Manufacturing, and administration are selected to participate in this review focusing on five AI applications in HR capability and three elements of HR readiness. The information collected was examined utilizing the Statistical Package for Social Sciences (SPSS) tool and Analysis of Moment Structures (AMOS). The results uncovered that hierarchical organization examination is a fundamental part of acquiring sustainable development. Adaptability and human asset capability are upheld by each of the five components of AI application areas of HR. Well-being and Safety improvement were viewed as vital components under the AI application in HR.

Overview

Integrity signals

Registry

Crossref · 10.1016/j.dajour.2023.100249

Cites

52 of 52 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Research works printed but not linked: 23

  1. Bibi, 2016, Impact of human resource management practices on employee retention in telecom sector, J. Human. Soc. Sci., 21, 26
  2. Chui, 2010, McKinsey Quarterly, 2, 9
  3. Nazri, 2019, Predicting academician publication performance using decision tree, Int. J. Recent Technol. Eng., 8, 180
  4. Reddy, 2019, Artificial Intelligence (AI) in learning and development: A conceptual paper, J. Manag. Dev., 38, 34
  5. Bakeel, 2020, The impact of artificial intelligence on human resources management, J. Manag. Res., 12, 159
  6. Wang, 2020, An Artificial Intelligence-enabled health and safety management system for industry 4.0, Safety Sci., 124
  7. Ngai, 2020, Artificial intelligence applications in healthcare: A thematic analysis, J. Health Manag., 22, 220
  8. Arias, 2021, Chatbots: The future of HR and employee benefits communication, Benef. Quart., 37, 7
  9. Subramaniam, 2021, Artificial intelligence in workplace ergonomics: A review of current trends and future research directions, J. Occup. Health Psychol., 26, 135
  10. Zhang, 2021, Intelligent workplace comfort management based on Internet of Things and Artificial Intelligence, IEEE Access, 9, 143659
  11. Yu, 2020, An intelligent chair system for personalized sitting comfort management, Sensors, 20, 4478
  12. Ugwu, 2020, Stress detection in the workplace using artificial intelligence and Internet of Things technologies, J. Amb. Intell. Humanized Comput., 11, 89
  13. Sharma, 2022, Review on digitalisation and artificial intelligence in human resource function of energy sector, Water Energy Int., 65, 38
  14. Li, 2023, Real-time performance tracking and improvement for employee engagement using artificial intelligence, J. Bus. Res., 149, 675
  15. Dolan, 2022, Artificial intelligence and human resource management: Advancing theory and research, J. Manag., 48, 59
  16. Ye, 2021, Analyzing and visualizing organizational networks with deep learning and social network analysis, Inform. Manag., 58
  17. Lei, 2020, A social media-based approach for organizational network analysis, J. Bus. Res., 112, 1
  18. Vishwakarma, 2023, Employee engagement and collaboration: an empirical investigation of factors influencing in the age of AI, J. Bus. Res., 151, 666
  19. Yu, 2023, An intelligent network analysis for organizational collaboration improvement, IEEE Access, 11, 24609
  20. Naveen, 2020, Impact of wearables and IoT on employee health and wellness, Bus. Today
  21. A. Barman, K. Das, Internet of Things (IoT) as the Future Smart Solution to HRM-How would wearable IoT bring organisational efficiency, in: International Conference Dec, 2018.
  22. Yawson, 2019, Organisational agility: A review of the literature, J. Manag. Strat., 10, 33
  23. Gupta, 2020, Exploring relationship between employees well-being and green IOT using structural equation modeling, Innovation, 29, 2590

Cited by

Sorted by citations

See all 218

Related

See all

Metadata

Authors
Murugesan, U., Subramanian, P., Srivastava, S., & Dwivedi, A.
Affiliations
  • Christ University (IN)
  • O. P. Jindal Global University (IN)
Corresponding author
Dwivedi, Ashish
ORCID
Venue
Decision Analytics Journal
Publisher
Elsevier BV
Published
2023-06
Volume
7
Pages
100249
ISSN
2772-6622 (ISSN-L)
DOI
10.1016/j.dajour.2023.100249
OpenAlex
W4382173516
Cited by
217
References
54
Citations by year
2026: 57 · 2025: 79 · 2024: 50 · 2023: 31
FWCI
63.10
Type
journal article
Language
en
Open access
Licence
Locations
Decision Analytics Journal (publishedVersion, cc-by-nc-nd)
Topics
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Employer Branding and e-HRM
Keywords
artificial intelligence in human resource management, HR digitalization, Industry 4.0, organizational adaptability, human resource capabilities, employee well-being, occupational safety, Internet of Things

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review