From November 2013 till January 2014 a minor ‘Smart Life Rhythms’ was taught at The Hague University of Applied Sciences. In the minor students used service design methods to develop solutions for improving life rhythms. Reflection on the minor produced the insight that building physical prototypes early on in the design process was key to success. Further discussions with colleagues and a literature review gave more arguments for the motto ‘Just build it’ – an encouragement to build simple physical models in the early stages of the service design process. Building these simple physical models is not just advocated by educators and in line with service design principles such as being iterative and user-centered. In his book ‘the Craftsman’ (Sennett, 2009) Richard Sennett provides us with more fundamental arguments regarding the value of ‘making things’. On top of the added value to the design process in itself, simple physical models are a tool for engaging both clients, users and students in the design process. So get out your glue gun and start building!
Abstract Business Process Management (BPM) is an important discipline for organizations to manage their business processes. Research shows that higher BPM-maturity leads to better process performance. However, contextual factors such as culture seem to influence this relationship. The purpose of this paper is to investigate the role of national culture on the relationship between BPM-maturity and process performance. A multiple linear regression analysis is performed based on data from six different countries within Europe. Although the results show a significant relationship between BPM-maturity and process performance, no significant moderation effect of national culture has been found. The cultural dimension long term orientation shows a weak negative correlation with both BPM-maturity and process performance. Through a post-hoc moderation analysis on each dimension of BPM-maturity, we further find that long term orientation negatively moderates the relationship between process improvement and process performance. Three other moderation effects are also discovered. The results of this study contribute to insights into the role of culture in the field of BPM.
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De markt voor Business Process Management (BPM) software groeit razend snel. Voor 2010 wordt er een marktomvang voorspeld van tussen de 1 tot 6 miljard dollar, dit betekend dat deze markt sinds 2005 meer dan verdubbeld is. BPM krijgt ook in toenemende mate publiciteit in de markt echter dan gaat het veelal om wat BPM nu precies wel en niet is en niet over hoe het toegepast kan worden. Hetzelfde geldt voor BPM software, beter bekend als Business Process Management Systemen (BPMS). Het onderzoek beschreven in dit proefschrift focust op BPMS, het ontstaan, waar het naartoe gaat en wat er allemaal komt kijken bij de invoering en het gebruik ervan. De hoofdonderzoeksvraag in dit proefschrift is: Welke factoren en competenties bepalen het succes van de implementatie van Business Process Management Systemen in een specifieke situatie? Centraal in dit proefschrift staan de volgende onderzoeksvragen: 1. Wat zijn de succes factoren bij de implementatie van Business Process Management Systemen? 2. Welke competenties hebben stakeholders in een Business Process Management Systeem implementatie project nodig? 3. Hoe ziet een Business Process Management Systeem implementatie methodiek eruit welke rekening houdt met de omgevingsfactoren van een organisatie?
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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.
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.
