Countries, firms, and individual persons (units) are interconnected, such that the behaviour and the performance of an individual are often influenced by those of others. These connections also vary over time or regimes due to various shocks, e.g., Brexit, the Corona pandemic, policy implementations, and technology change. This research project will create innovative tools to model and uncover the varying connections of these units in a new but increasing popular type of data structure, namely multi-dimensional data.

This research will consider three phases of an individual’s life when future crime can be prevented. First, at birth through the effect of parental influence. Second, as a teenager because of psychological misconceptions. Third, by putting the right prisoner in the right prison. Main research question: which is most efficient?

This proposal is for an institutional pilot account of the Erasmus Research School of Management (ERIM). Many of the researchers in ERIM are tackling problems that are inherently computationally hard, either by definition (logistics), by the size of the analysed data (marketing, finance) or due to the computational complexity of realistic models (computational economics). Up until now the ERIM researchers have had to resort to analysing smaller problems, waiting longer times for computations to complete, or to outsource the computation to external, private cloud service providers. The current application of computational support from the Dutch national cluster, once granted, would provide us with an efficient solution for performing computations required for our basic research. The application is for a period of one year and 100.000 PNU (processor-node-uur).

Vehicle routing is the process of designing routes for vehicles, for example to deliver parcels, resupply stores and collect waste. Although software exists which finds usable but not optimal routes for real-world applications, software that creates optimal routes are too slow to be applied in practice. Using optimal routes in practice results in reducing for example costs, energy consumption, emission, congestion and noise. In this study, mathematical research is done with as goal to develop new procedures of creating optimal routes faster than before.

Bestaande duurzame energie indices tonen dat beleggen in aandelen van duurzame energiebedrijven te weinig rendement oplevert. Eigen onderzoek toont aan dat dit beeld onterecht is en het beleggers ervan weerhoudt te investeren in duurzame energie. Wij als EF-I hebben een nieuwe beleggingsindex voor duurzame energieaandelen ontwikkeld, de EF-I RE25 Index, en het toont dat beleggen in duurzame energieaandelen een goed rendement levert. Dit helpt de kapitaalstroom richting de duurzame energiebedrijven en komt ten goede aan de duurzame energie transitie. De technische haalbaarheid van de index is al bewezen. Met de STW take-off subsidie willen we de commerciële haalbaarheid van een start-up op basis van de index onderzoeken.