Higher education has a number of key roles to play in accelerating progress toward sustainability goals. It has a responsibility to provide and teach curricula that are tailored to labor market needs, to help change people’s attitudes and motivation toward sustainability, and to reduce inequalities between different students. Course leaders and developers of curricula should monitor and assess these needs in order to improve their curricula from time to time. In the present work, we describe a data-driven approach based on text-mining techniques to identify the competences required for a given position based on job advertisements. To demonstrate the usefulness of our suggested method, the supply chain management occupation was selected as the supply chain is a constantly changing domain that is highly affected by green activities and initiatives, and the COVID-19 pandemic strongly influenced this sector, as well. This data-driven process allowed the identification of required soft and hard skills contained in job descriptions. However, it was found that some important concepts of green supply chain management, such as repair and refurbishment, were only marginally mentioned in the job advertisements. Therefore, in addition to labor market expectations, a business process model from relevant green supply chain management literature was developed to complement the required competences. The given new techniques can support the paradigm shift toward sustainable development and help curriculum developers and decision makers assess labor market needs in the area of sustainability skills and competences. The given result can serve as an input of outcome-based training development to design learning objective-based teaching materials.
Optimizing electric taxi charging system: A data-driven approach from transport energy supply chain perspective