Shared Vision Planning (SVP) is a collaborative approach to water (resource) management that combines three practices: (1) traditional water resources planning; (2) structured participation of stakeholders; (3) (collaborative) computer modeling and simulation. The authors argue that there are ample opportunities for learning and innovation in SVP when we look at it as a form of Policy Analysis (PA) in a multi-actor context. SVP faces three classic PA dilemmas: (1) the role of experts and scientific knowledge in policymaking; (2) The design and management of participatory and interactive planning processes; and (3) the (ab)use of computer models and simulations in (multi actor) policymaking. In dealing with these dilemmas, SVP can benefit from looking at the richness of PA methodology, such as for stakeholder analysis and process management. And it can innovate by incorporating some of the rapid developments now taking place in the field of (serious) gaming and simulation (S&G) for policy analysis. In return, the principles, methods, and case studies of SVP can significantly enhance how we perform PA for multi-actor water (resource) management.
DOCUMENT
Social innovation and co-creation have been discussed in academic literature for the last twenty years. However, the interrelatedness and application of these concepts in European Union policy deserves more attention. In our study, we focus on this relationship and application, by analysing the value of co-creation for social innovation. By analysing a large EU dataset, we showed that social innovation and co-creation were used more and more widely and that their use took off after 2010 and 2015 respectively. By applying a contextual analysis, we also revealed that both concepts became connected in EU policy on research and innovation. Our analysis also shows that co-creation became an indicator for successful social innovation in the Horizon Europe Framework programme. These results show the importance of co-creation in policies, but because the concept has not been defined properly, this carries the risk of simplifying co-creation into a box-ticking exercise.
DOCUMENT
Between 2009 and 2013 a project has been executed in the Utrecht region to strengthen the workplace innovation capacity of SMEs (My Company 2.0). The participating companies were asked to fill in a questionnaire on the workplace innovation capacity of the company at two moments: at the beginning (T0) and at the end of the project (T1). The workplace innovation capacity was measured with questions about the organization (responds on changing demands in the environment), labor (employee flexibility), strategy (innovation with other companies) and market (improvement or renewal of products/services). We divided the companies (n=103) into two groups, namely companies that implemented an intervention an companies that did not. We found that the companies that received an intervention during the project had a significantly higher score with regard to the workplace innovation capacity at T1 compared to T0. The companies in which no intervention took place had a small (not significant) decrease in workplace innovation capacity between the baseline- (T0) and the post- test (T1). We also compared the data with data from a national reference population. It appeared that the companies in our study scored higher in workplace innovation capacity at both measurements (T0 and T1) than the reference population
DOCUMENT
Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.
Client: Foundation Innovation Alliance (SIA - Stichting Innovatie Alliantie) with funding from the ministry of Education, Culture and Science (OCW) Funder: RAAK (Regional Attention and Action for Knowledge circulation) The RAAK scheme is managed by the Foundation Innovation Alliance (SIA - Stichting Innovatie Alliantie) with funding from the ministry of Education, Culture and Science (OCW). Early 2013 the Centre for Sustainable Tourism and Transport started work on the RAAK-MKB project ‘Carbon management for tour operators’ (CARMATOP). Besides NHTV, eleven Dutch SME tour operators, ANVR, HZ University of Applied Sciences, Climate Neutral Group and ECEAT initially joined this 2-year project. The consortium was later extended with IT-partner iBuildings and five more tour operators. The project goal of CARMATOP was to develop and test new knowledge about the measurement of tour package carbon footprints and translate this into a simple application which allows tour operators to integrate carbon management into their daily operations. By doing this Dutch tour operators are international frontrunners.Why address the carbon footprint of tour packages?Global tourism contribution to man-made CO2 emissions is around 5%, and all scenarios point towards rapid growth of tourism emissions, whereas a reverse development is required in order to prevent climate change exceeding ‘acceptable’ boundaries. Tour packages have a high long-haul and aviation content, and the increase of this type of travel is a major factor in tourism emission growth. Dutch tour operators recognise their responsibility, and feel the need to engage in carbon management.What is Carbon management?Carbon management is the strategic management of emissions in one’s business. This is becoming more important for businesses, also in tourism, because of several economical, societal and political developments. For tour operators some of the most important factors asking for action are increasing energy costs, international aviation policy, pressure from society to become greener, increasing demand for green trips, and the wish to obtain a green image and become a frontrunner among consumers and colleagues in doing so.NetworkProject management was in the hands of the Centre for Sustainable Tourism and Transport (CSTT) of NHTV Breda University of Applied Sciences. CSTT has 10 years’ experience in measuring tourism emissions and developing strategies to mitigate emissions, and enjoys an international reputation in this field. The ICT Associate Professorship of HZ University of Applied Sciences has longstanding expertise in linking varying databases of different organisations. Its key role in CARMATOP was to create the semantic wiki for the carbon calculator, which links touroperator input with all necessary databases on carbon emissions. Web developer ibuildings created the Graphical User Interface; the front end of the semantic wiki. ANVR, the Dutch Association of Travel Agents and Tour operators, represents 180 tour operators and 1500 retail agencies in the Netherlands, and requires all its members to meet a minimum of sustainable practices through a number of criteria. ANVR’s role was in dissemination, networking and ensuring CARMATOP products will last. Climate Neutral Group’s experience with sustainable entrepreneurship and knowledge about carbon footprint (mitigation), and ECEAT’s broad sustainable tourism network, provided further essential inputs for CARMATOP. Finally, most of the eleven tour operators are sustainable tourism frontrunners in the Netherlands, and are the driving forces behind this project.
The developments of digitalization and automation in freight transport and logistics are expected to speed-up the realization of an adaptive, seamless, connected and sustainable logistics system. CATALYST determines the potential and impact of Connected Automated Transport (CAT) by testing and implementing solutions in a real-world environment. We experiment on smart yards and connected corridors, to answer research questions regarding supply chain integration, users, infrastructure, data and policy. Results are translated to overarching lessons on CAT implementations, and shared with potential users and related communities. This way, CATALYST helps logistic partners throughout the supply chain prepare for CAT and accelerates innovation.
