Identification of the degree of greenness of the proposed skills with the requirements of green jobs based on fuzzy logic

The deepening climate crisis development have prompted most countries to recognize the importance of transition to a green economy. This causes a rapid growth of “green” jobs in various spheres of human activity and, accordingly, the need for “green” skills necessary to use new technologies. New professions and specialties requiring the acquisition of green skills create a discrepancy between the demand for human resources of the required profile and their supply. In this context, it was clarified what the terms green jobs and green skills mean. Considering the content of these two concepts, studies dedicated to determining the relationship between the green transition and relevant skills were reviewed. In this regard, the selection of personnel with the necessary skills determines the relevance of developing methods for assessing the supply and demand for specialists, providing an opportunity to assess the compliance of the proposed skills with the requirements of green jobs. This article proposes a methodological approach to intelligent management of supply and demand in the green segment of the labor market. It also develops decision support methods to identify of compliance the greenness degree of the proposed skills with the level of the requirements of green jobs. Decision making methods were based on fuzzy situational analysis and pattern recognition: reference situations are determined (fuzzy reference pattern), real situations are determined (fuzzy real pattern); degree of green similarity of the reference situation to each real situation is calculated in accordance with the chosen measure of assessment of similarity between two fuzzy situations