Identifying green skills gaps through labor market intelligence

• Published in: Journal of Infrastructure, Policy and Development Vol. 8; no. 6; p. 4868
• Main Authors: Nikoloski, Dimitar, Sulich, Adam, Sołoducho-Pelc, Letycja, Mancheski, Gjorgi, Angelski, Marjan, Petkoska, Marija Midovska
• Format: Journal Article
• Language: English
• Published: 12.07.2024
• ISSN: 2572-7923; 2572-7931
• DOI: 10.24294/jipd.v8i6.4868

The aim of this paper is to introduce a research project dedicated to identifying gaps in green skills by using the labor market intelligence. Labor Market Intelligence (LMI). The method is primarily descriptive and conceptual, as the authors of this paper intend to develop a theoretical background and justify the planned research using Natural Language Processing (NLP) techniques. This research highlights the role of LMI as a tool for analysis of the green skills gaps and related imbalances. Due to the growing demand for eco-friendly solutions, there arises a need for the identification of green skills. As societies shift towards eco-friendly economic models, changes lead to emerging skill gaps. This study provides an alternative approach for identification of these gaps based on analysis of online job vacancies and online profiles of job seekers. These gaps are contextualized within roles that businesses find difficult to fill due to a lack of requisite green skills. The idea of skill intelligence is to blend various sources of information in order to overcome the information gap related to the identification of supply side factors, demand side factors and their interactions. The outcomes emphasize the urgency of policy interventions, especially in anticipating roles emerging from the green transition, necessitating educational reforms. As the green movement redefines the economy, proactive strategies to bridge green skill gaps are essential. This research offers a blueprint for policymakers and educators to bolster the workforce in readiness for a sustainable future. This article proposes a solution to the quantitative and qualitative mismatches in the green labor market.