This study explores the evaluation of research pathways of self-management health innovations from discovery to implementation in the context of practice-based research. The aim is to understand how a new process model for evaluating practice-based research provides insights into the implementation success of innovations. Data were collected from nine research projects in the Netherlands. Through document analysis and semi-structured interviews, we analysed how the projects start, evolve, and contribute to the healthcare practice. Building on previous research evaluation approaches to monitor knowledge utilization, we developed a Research Pathway Model. The model’s process character enables us to include and evaluate the incremental work required throughout the lifespan of an innovation project and it helps to foreground that innovation continues during implementation in real-life settings. We found that in each research project, pathways are followed that include activities to explore a new solution, deliver a prototype and contribute to theory. Only three projects explored the solution in real life and included activities to create the necessary changes for the solutions to be adopted. These three projects were associated with successful implementation. The exploration of the solution in a real-life environment in which users test a prototype in their own context seems to be a necessary research activity for the successful implementation of self-management health innovations.
MULTIFILE
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?
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.
MULTIFILE
Due to societal developments, like the introduction of the ‘civil society’, policy stimulating longer living at home and the separation of housing and care, the housing situation of older citizens is a relevant and pressing issue for housing-, governance- and care organizations. The current situation of living with care already benefits from technological advancement. The wide application of technology especially in care homes brings the emergence of a new source of information that becomes invaluable in order to understand how the smart urban environment affects the health of older people. The goal of this proposal is to develop an approach for designing smart neighborhoods, in order to assist and engage older adults living there. This approach will be applied to a neighborhood in Aalst-Waalre which will be developed into a living lab. The research will involve: (1) Insight into social-spatial factors underlying a smart neighborhood; (2) Identifying governance and organizational context; (3) Identifying needs and preferences of the (future) inhabitant; (4) Matching needs & preferences to potential socio-techno-spatial solutions. A mixed methods approach fusing quantitative and qualitative methods towards understanding the impacts of smart environment will be investigated. After 12 months, employing several concepts of urban computing, such as pattern recognition and predictive modelling , using the focus groups from the different organizations as well as primary end-users, and exploring how physiological data can be embedded in data-driven strategies for the enhancement of active ageing in this neighborhood will result in design solutions and strategies for a more care-friendly neighborhood.
Mode heeft een cruciale functie in de samenleving: zij maakt diversiteit en inclusiviteit mogelijk en is een middel voor individuen om zich uit te drukken. Desalniettemin is mode ook een raadsel op het gebied van duurzaamheid, zowel aan de sociale als aan de milieukant. Er bestaan echter alternatieven voor de huidige praktijken in de mode. Dit project heeft tot doel de ontwikkeling van een van die initiatieven te ondersteunen. In samenwerking met twee Nederlandse MKB bedrijven in de mode-industrie, willen we een of meer business modellen co-designen voor het vermarkten van circulair ontworpen laser geprinte T-shirts. Door lasertechnologie te introduceren in plaats van traditionele inktopties, kunnen de T- shirts hun CO2 voetafdruk verder verkleinen en een verstandig alternatief zijn voor individuen, die op zoek zijn naar duurzame modekeuzes. Maar hoewel de technologische haalbaarheid vaststaat, vereist het vermarkten sterke, schaalbare, bedrijfsmodellen. Via een haalbaarheidsstudie willen we dergelijke businessmodellen ontwikkelen en de commercialisering van deze producten ondersteunen. Wij zijn van plan de reacties van de consument op een dergelijke innovatie te bestuderen, evenals de belemmeringen en stimulansen vanuit het oogpunt van de consument, en de inkoop-, toeleveringsketen- en financiële kwesties die kunnen voortvloeien uit de schaalbaarheid van een potentieel bedrijfsmodel. Om praktische relevantie voor de bredere industrie te verzekeren, streven we ernaar om de resultaten te presenteren op evenementen georganiseerd door een van de consortiumpartners (in 2023), als ook om een teaching case en een wetenschappelijk artikel te ontwikkelen op basis van de resultaten van het project.
The Dutch main water systems face pressing environmental, economic and societal challenges due to climatic changes and increased human pressure. There is a growing awareness that nature-based solutions (NBS) provide cost-effective solutions that simultaneously provide environmental, social and economic benefits and help building resilience. In spite of being carefully designed and tested, many projects tend to fail along the way or never get implemented in the first place, wasting resources and undermining trust and confidence of practitioners in NBS. Why do so many projects lose momentum even after a proof of concept is delivered? Usually, failure can be attributed to a combination of eroding political will, societal opposition and economic uncertainties. While ecological and geological processes are often well understood, there is almost no understanding around societal and economic processes related to NBS. Therefore, there is an urgent need to carefully evaluate the societal, economic, and ecological impacts and to identify design principles fostering societal support and economic viability of NBS. We address these critical knowledge gaps in this research proposal, using the largest river restoration project of the Netherlands, the Border Meuse (Grensmaas), as a Living Lab. With a transdisciplinary consortium, stakeholders have a key role a recipient and provider of information, where the broader public is involved through citizen science. Our research is scientifically innovative by using mixed methods, combining novel qualitative methods (e.g. continuous participatory narrative inquiry) and quantitative methods (e.g. economic choice experiments to elicit tradeoffs and risk preferences, agent-based modeling). The ultimate aim is to create an integral learning environment (workbench) as a decision support tool for NBS. The workbench gathers data, prepares and verifies data sets, to help stakeholders (companies, government agencies, NGOs) to quantify impacts and visualize tradeoffs of decisions regarding NBS.
