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Blockchain technology creates the possibility for developing knowledge-intensive goods. Only a few studies in Affordance theory deal with investigating blockchain. This paper aims to discover affordances in blockchain when designing an AI-based financial recommendation system as a decision support system. The design thinking methodology was extended with machine learning and business process modelling to discover financial offerings, digital objects to be tokenised, advantages gained from the tracing affordances and consensus mechanism, and the role of smart contracts for each persona. The implementation of discovered blockchain-based applications requires a multichain framework to meet the requirements of design affordances. [ABSTRACT FROM AUTHOR]

Industry 4.0 is seen as the beginning phase where computers and automation become connected and as an opportunity to increase the efficiency and effectiveness in the manufacturing industry. With the application of real-time data and information by integrating physical machinery and devices with networked sensors and software to predict, control and reduce costs in a long-term view. This study presents the basic fundamental concepts of Industry 4.0, where each technology of Industry 4.0 is described based on the current literature. Also, this study tries to understand the impact of Industry 4.0 to the ERP approach and how each technology of the Industry 4.0 can be related to ERP system and if current ERP systems are ready to support Industry 4.0. Based on the findings, there are many challenges related to the integration of Industry 4.0 and current ERP systems especially when it comes to the machine to machine, machine to ERP communication and the security of the data. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]