This article proposes a model for the design of a hybrid VET curriculum across the school-work boundary.
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Artificial Intelligence (AI) offers organizations unprecedented opportunities. However, one of the risks of using AI is that its outcomes and inner workings are not intelligible. In industries where trust is critical, such as healthcare and finance, explainable AI (XAI) is a necessity. However, the implementation of XAI is not straightforward, as it requires addressing both technical and social aspects. Previous studies on XAI primarily focused on either technical or social aspects and lacked a practical perspective. This study aims to empirically examine the XAI related aspects faced by developers, users, and managers of AI systems during the development process of the AI system. To this end, a multiple case study was conducted in two Dutch financial services companies using four use cases. Our findings reveal a wide range of aspects that must be considered during XAI implementation, which we grouped and integrated into a conceptual model. This model helps practitioners to make informed decisions when developing XAI. We argue that the diversity of aspects to consider necessitates an XAI “by design” approach, especially in high-risk use cases in industries where the stakes are high such as finance, public services, and healthcare. As such, the conceptual model offers a taxonomy for method engineering of XAI related methods, techniques, and tools.
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Across Dutch municipalities, unusual collaborative initiatives emerge that aim to stimulate the creation of value from municipal waste resources. Circular economy literature proposes that experimentation competences are important for developing initiatives towards circular business models and a wide range of innovation frameworks and business model toolkits have been developed to support the development of circular business models based on experimentation.However, more insight is needed to understand how experimentation contributes to the development of urban upcycling initiatives, in particular those where collaborative business models are created. Literature suggest that business model experimentation occurs differently in various collaborative contexts. For example, depending on the type of initiating focal actors involved, collaborative business models develop along different pathways Therefore, we aim to understand how experimentation occurs in various types of collaborative urban upcycling initiatives and we investigate the following research question: How do stakeholders in collaborative urban upcycling initiatives use experimentation to develop circular business models?
The maximum capacity of the road infrastructure is being reached due to the number of vehicles that are being introduced on Dutch roads each day. One of the plausible solutions to tackle congestion could be efficient and effective use of road infrastructure using modern technologies such as cooperative mobility. Cooperative mobility relies majorly on big data that is generated potentially by millions of vehicles that are travelling on the road. But how can this data be generated? Modern vehicles already contain a host of sensors that are required for its operation. This data is typically circulated within an automobile via the CAN bus and can in-principle be shared with the outside world considering the privacy aspects of data sharing. The main problem is, however, the difficulty in interpreting this data. This is mainly because the configuration of this data varies between manufacturers and vehicle models and have not been standardized by the manufacturers. Signals from the CAN bus could be manually reverse engineered, but this process is extremely labour-intensive and time-consuming. In this project we investigate if an intelligent tool or specific test procedures could be developed to extract CAN messages and their composition efficiently irrespective of vehicle brand and type. This would lay the foundations that are required to generate big data-sets from in-vehicle data efficiently.
In order to achieve much-needed transitions in energy and health, systemic changes are required that are firmly based on the principles of regard for others and community values, while at the same time operating in market conditions. Social entrepreneurship and community entrepreneurship (SCE) hold the promise to catalyze such transitions, as they combine bottom-up social initiatives with a focus on financially viable business models. SCE requires a facilitating ecosystem in order to be able to fully realize its potential. As yet it is unclear in which way the entrepreneurial ecosystem for social and community entrepreneurship facilitates or hinders the flourishing and scaling of such entrepreneurship. It is also unclear how exactly entrepreneurs and stakeholders influence their ecosystem to become more facilitative. This research programme addresses these questions. Conceptually it integrates entrepreneurial ecosystem frameworks with upcoming theories on civic wealth creation, collaborative governance, participative learning and collective action frameworks.This multidisciplinary research project capitalizes on a unique consortium: the Dutch City Deal ‘Impact Ondernemen’. In this collaborative research, we enhance and expand current data collection efforts and adopt a living-lab setting centered on nine local and regional cases for collaborative learning through experimenting with innovative financial and business models. We develop meaningful, participatory design and evaluation methods and state-of-the-art digital tools to increase the effectiveness of impact measurement and management. Educational modules for professionals are developed to boost the abovementioned transition. The project’s learnings on mechanisms and processes can easily be adapted and translated to a broad range of impact areas.
The valorization of biowaste, by exploiting side stream compounds as feedstock for the sustainable production of bio-based materials, is a key step towards a more circular economy. In this regard, chitin is as an abundant resource which is accessible as a waste compound of the seafood industry. From a commercial perspective, chitin is chemically converted into chitosan, which has multiple industrial applications. Although the potential of chitin has long been established, the majority of seafood waste containing chitin is still left unused. In addition, current processes which convert chitin into chitosan are sub-optimal and have a significant impact on the environment. As a result, there is a need for the development of innovative methods producing bio-based products from chitin. This project wants to contribute to these challenges by performing a feasibility study which demonstrates the microbial bioconversion of chitin to polyhydroxyalkanoates (PHAs). Specifically, the consortium will attempt to cultivate and engineer a recently discovered bacterium Chi5, so that it becomes able to directly produce PHAs from chitin present in solid shrimp shell waste. If successful, this project will provide a proof-of-concept for a versatile microbial production platform which can contribute to: i) the valorization of biowaste from the seafood industry, ii) the efficient utilization of chitin as feedstock, iii) the sustainable and (potentially low-cost) production of PHAs. The project consortium is composed of: i) Van Belzen B.V., a Dutch shrimp trading company which are highly interested in the valorization of their waste streams, hereby making their business model more profitable and sustainable. ii) AMIBM, which have recently isolated and characterized the Chi5 marine-based chitinolytic bacterium and iii) Zuyd, which will link aforementioned partners with students in creating a novel collaboration which will stimulate the development of students and the translation of academic knowledge to a feasible application technology for SME’s.
