Background: Advanced statistical modeling techniques may help predict health outcomes. However, it is not the case that these modeling techniques always outperform traditional techniques such as regression techniques. In this study, external validation was carried out for five modeling strategies for the prediction of the disability of community-dwelling older people in the Netherlands. Methods: We analyzed data from five studies consisting of community-dwelling older people in the Netherlands. For the prediction of the total disability score as measured with the Groningen Activity Restriction Scale (GARS), we used fourteen predictors as measured with the Tilburg Frailty Indicator (TFI). Both the TFI and the GARS are self-report questionnaires. For the modeling, five statistical modeling techniques were evaluated: general linear model (GLM), support vector machine (SVM), neural net (NN), recursive partitioning (RP), and random forest (RF). Each model was developed on one of the five data sets and then applied to each of the four remaining data sets. We assessed the performance of the models with calibration characteristics, the correlation coefficient, and the root of the mean squared error. Results: The models GLM, SVM, RP, and RF showed satisfactory performance characteristics when validated on the validation data sets. All models showed poor performance characteristics for the deviating data set both for development and validation due to the deviating baseline characteristics compared to those of the other data sets. Conclusion: The performance of four models (GLM, SVM, RP, RF) on the development data sets was satisfactory. This was also the case for the validation data sets, except when these models were developed on the deviating data set. The NN models showed a much worse performance on the validation data sets than on the development data sets.
The need to better understand how to manage the real logistics operations in Schiphol Airport, a strategic hub for the economic development of the Netherlands, created the conditions to develop a project where academia and industry partnered to build a simulation model of the Schiphol Airport Landside operations. This paper presents such a model using discrete-event simulation. Arealistic representation of the open road network of the airport as well as the (un)loading dock capacities and locations of the five ground handlers of Schiphol Airport was developed. Furthermore, to provide practitioners with applicable consolidation and truck-dispatching policies, some easy-to-implement rules are proposed and implemented in the model. Preliminary results from this model show that truck-dispatching policies have a higher impact than consolidation policies in terms of both distances travelled by cooperative logistic operators working within the airport and shipments’ average flow time. Furthermore, the approach presented in this study can be used for studying similar mega-hubs
PBL is the initiator of the Work Programme Monitoring and Management Circular Economy 2019-2023, a collaboration between CBS, CML, CPB, RIVM, TNO, UU. Holidays and mobility are part of the consumption domains that PBL researches, and this project aims to calculate the environmental gains per person per year of the various circular behavioural options for both holiday behaviour and daily mobility. For both behaviours, a range of typical (default) trips are defined and for each several circular option explored for CO2 emissions, Global warming potential and land use. The holiday part is supplied by the Centre for Sustainability, Tourism and Transport (CSTT) of the BUas Academy of Tourism (AfT). The mobility part is carried out by the Urban Intelligence professorship of the Academy for Built Environment and Logistics (ABEL).The research question is “what is the environmental impact of various circular (behavioural) options around 1) holidays and 2) passenger mobility?” The consumer perspective is demarcated as follows:For holidays, transportation and accommodation are included, but not food, attractions visited and holiday activitiesFor mobility, it concerns only the circular options of passenger transport and private means of transport (i.e. freight transport, business travel and commuting are excluded). Not only some typical trips will be evaluated, but also the possession of a car and its alternatives.For the calculations, we make use of public databases, our own models and the EAP (Environmental Analysis Program) model developed by the University of Groningen. BUAs projectmembers: Centre for Sustainability, Tourism and Transport (AT), Urban Intelligence (ABEL).
DISCO aims at fast-tracking upscaling to new generation of urban logistics and smart planning unblocking the transition to decarbonised and digital cities, delivering innovative frameworks and tools, Physical Internet (PI) inspired. To this scope, DISCO will deploy and demonstrate innovative and inclusive urban logistics and planning solutions for dynamic space re-allocation integrating urban freight at local level, within efficiently operated network-of-networks (PI) where the nodes and infrastructure are fixed and mobile based on throughput demands. Solutions are co-designed with the urban logistics community – e.g., cities, logistics service providers, retailers, real estate/public and private infrastructure owners, fleet owners, transport operators, research community, civil society - all together moving a paradigm change from sprawl to data driven, zero-emission and nearby-delivery-based models.
In line with European sustainability goals, small and medium sized enterprises (SMEs) in the Dutch automotive aftermarket face the challenge of maintaining competitiveness while transitioning to circular business models. These models, supported by EU policies such as the Circular Economy Action Plan and the European Green Deal, drive innovation in product lifecycle management, recycling, and sustainability. However, as SMEs adapt to these changes, they must also navigate the growing competition from imported Chinese electric vehicles (EVs), which bring both opportunities and risks. Logistics plays a critical role in this transition, as optimizing supply chains, enhancing resource efficiency, and minimizing waste are essential for achieving circularity. Will the Chinese car manufacturers move their value chain to Europe? Or will they further localize in aftersales businesses? Either scenario would affect a chain of SMEs in automotive aftermarket. Focusing on the auto parts SMEs in the Brainport region, this research examines how SMEs can stay competitive by leveraging logistics strategies to support circular practices, and navigate the challenges posed by the influx of Chinese EVs while remaining resilient and adaptable in the automotive aftermarket value chain. Together with our consortium partners, we help the regional SMEs in the automotive aftermarket with: 1. Mapping out logistical challenges and objectives, 2. Risk mitigation and demand planning, 3. Strategic supply chain development. Involving Fontys International Business graduation projects on data analysis, this project combines quantitative and qualitative insights to examine the transition of automotive aftermarket to an EV-dominated future. The SMEs in our consortium network are drive to adapt to the evolving landscape by investing in new measures. Through scenario assessment, we help them with scenario strategies in circular transition. For a broader impact, this project brings SMEs, branch and public organizations together and presents shared responsibilities in creating a resilient supply chain.
