Utilizing Data Science Techniques to Analyze the Demand vs. Supply of Workforce Skills and Competencies on the UAE and GCC Renewable Energy, Oil and Gas, and 4th Industrial Revolution Related Industries

  • Abdulla Mohammed Ali Al Shimmari

Student thesis: Doctoral Thesis

Abstract

Standardizing a classification of occupations tailored to represent each country or region occupational standards is essential. This is due to many reasons, including the importance of mapping jobs into clearly categorized groups according to the skills and competencies that are undertaken in the job, to help analyze the specific market in terms of its demand/supply set of skills that serves it. The Occupational Information Network (O*NET) sponsored by the US Department of Labor and the European Standardization Classification of Occupations (ESCO) which is a revolutionized extension to the International Standard Classification of Occupations (ISCO), have been analyzed in this research using data mining techniques to provide a base Standard Classification of Occupations for the UAE and hence GCC with the assistance of Mubadala® Investment Company 'TAKAFO' Program team. On the other hand, new emerging technologies to set new required skills for jobs, which in return, embeds stress over the educational system that supplies those needed skills. During the previous industrial revolutions, the factory system, for example, introduced the division of labor, which assigns different labors each with small tasks without the need to know how to make the entire process. This process revolutionized the old method of depending on highly skilled workers and empowered lower-skilled workers with the needed skills and knowledge focused on the assigned small tasks, which impacted the economic, social and political aspects of the society. Proper foresight of the dynamic change in the workplace can trigger the identification of needs for change in the academic field in order to bridge the gap between what is demanded by industries and what skills are supplied by academia. The Job Analysis Framework was developed through the utilization of Latent Semantic Indexing and Latent Dirichlet Allocation data science techniques to analyze the extensive margin change. Offering insights on the GCC specifically the UAE labor-market past and potential changes under different forcings; low-income labor (expat), sustainability and green economy (Masdar aspect), oil and gas (national interest); and penetration of the 4th industrial revolution technologies (Ex. AI, Blockchain, autonomous machines) for the future, then how these insights can reflect on the gap in the current academic offerings at the higher educational level.
Date of AwardMay 2020
Original languageAmerican English

Keywords

  • Data Analysis
  • NLP
  • 4th Industrial Revolution
  • Skills
  • Competencies
  • ESCO
  • O*NET
  • Mubadala®
  • FAHR
  • MOHRE.

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