Disruptive Technologies for Labor Market Information System Implementation Enhancement in the UAE: A Conceptual Perspective

In December 2019, the world learned about the first outbreak of the novel coronavirus (COVID-19) that first broke out in Wuhan, China. This limited outbreak in a small province of China has rapidly evolved into a global pandemic that has led to a health and economic crisis. As millions of individuals have lost their lives, others have lost their jobs due to the recession of 2020. While the skills and educational mismatch have been a prevalent problem in the UAE labor market, it is logical to assume that the global pandemic has likely increased this problem's extent. Therefore, there is an urgent need to adopt an agile, innovative solution to address the upcoming challenges in the labor markets due to the lack of skilled resources and the fear of future work amid the COVID-19 pandemic. Since industry and academia have identified skills and educational mismatch as a complex and multivariate problem, the paper builds a conceptual case from a system engineering perspective to solve this problem efficiently. Based on the literature reviewed related to disruptive technologies and labor market management systems, the paper proposes a new implementation approach for an integrated labor market information system enabled by the most widely used disruptive technologies components in the UAE (Machine Learning, AI, Blockchain, Internet of Things, Big Data Analytics, and Cloud Computing). The proposed approach is considered one of the immediate course of actions required to minimize the UAE economy’s negative impact due to the presence of the skills and educational mismatch phenomena.

@article{Goher2021,
  title     = {Disruptive Technologies for Labor Market Information System Implementation Enhancement in the UAE: A Conceptual Perspective},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {2},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Ghada Goher and Maslin Masrom and Astuty Amrin and Noorlizawati Abd Rahim},
  doi       = {10.14569/IJACSA.2021.0120247},
  url       = {https://doi.org/10.14569/IJACSA.2021.0120247}
}