With the approach of the zero emission zone implementation in 30-40 cities mandated by the Dutch Klimaatakkord, comes the need to determine whether the SMEs located within these zones are aware of the coming changes and if they are, how far they have come in their preparation. This paper delves into the development of the zero emission city logistics maturity model tool which is used to indicate the progress of these small to medium enterprises in light of reaching fully zero emission city logistics operations. The paper starts off with a review of existing maturity models which forms the baseline for the zero emission city logistics maturity model in rubric form. A QuickScan analysis is developed in order to facilitate data collection by students who then approach businesses and use the QuickScan results to benchmark the businesses progress against other businesses. This paper then concludes with the preliminary results from the initial QuickScans performed by HBO level students.
Municipalities play an important role in tackling city logistics related matters, having many instruments at hand. However, it is not self-evident that all municipalities use these instruments to their full potential. A method to measure city logistics performance of municipalities can help in creating awareness and guidance, to ultimately lead to a more sustainable environment for inhabitants and businesses. Subsequently, this research is focused on a maturity model as a tool to assess the maturity level of a municipality for its performance related city logistics process management. Various criteria for measuring city logistics performance are studied and based on that the model is populated through three focus fields (Technical, Social and Corporate, and Policy), branching out into six areas of development: Information and communication technology, urban logistics planning, Stakeholder communication, Public Private Partnerships, Subsidisation and incentivisation, and Regulations. The CL3M model was tested for three municipalities, namely, municipality of Utrecht, Den Bosch and Groningen. Through these maturity assessments it became evident the model required specificity complementary to the existing assessment interview, and thus a SWOT analysis should be added as a conclusion during the maturity assessment.
‘Efficiënter en groener’, dat vat samen wat moderne stadslogistiek kan brengen. De realisatie van deze voordelen is niet altijd eenvoudig gebleken. Stadslogistiek wordt een succes als verzenders, ontvangers, consultants en stadslogistieke dienstverleners elk vanuit hun eigen rol, stappen gaan zetten. Deze stappen moeten niet vrijblijvend zijn en bij voorkeur ook nog eens onomkeerbaar. In deze bluepaper presenteert de expertgroep Next-level City Logistics oplossingsrichtingen voor de belangrijkste showstoppers op het gebied van stadslogistiek. Geschreven door expertgroep Shopping Tomorrow (Walther Ploos van Amstel is lid)
Many lithographically created optical components, such as photonic crystals, require the creation of periodically repeated structures [1]. The optical properties depend critically on the consistency of the shape and periodicity of the repeated structure. At the same time, the structure and its period may be similar to, or substantially below that of the optical diffraction limit, making inspection with optical microscopy difficult. Inspection tools must be able to scan an entire wafer (300 mm diameter), and identify wafers that fail to meet specifications rapidly. However, high resolution, and high throughput are often difficult to achieve simultaneously, and a compromise must be made. TeraNova is developing an optical inspection tool that can rapidly image features on wafers. Their product relies on (a) knowledge of what the features should be, and (b) a detailed and accurate model of light diffraction from the wafer surface. This combination allows deviations from features to be identified by modifying the model of the surface features until the calculated diffraction pattern matches the observed pattern. This form of microscopy—known as Fourier microscopy—has the potential to be very rapid and highly accurate. However, the solver, which calculates the wafer features from the diffraction pattern, must be very rapid and precise. To achieve this, a hardware solver will be implemented. The hardware solver must be combined with mechatronic tracking of the absolute wafer position, requiring the automatic identification of fiduciary markers. Finally, the problem of computer obsolescence in instrumentation (resulting in security weaknesses) will also be addressed by combining the digital hardware and software into a system-on-a-chip (SoC) to provide a powerful, yet secure operating environment for the microscope software.
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.
