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Sebastian Speer was awarded a doctorate with the distinction cum laude for his dissertation: The (Dis)Honest and (Un)Fair Brain: Investigating the Neural Underpinnings of Moral Decisions.
In his dissertation Sebastian provided three contributions to better understand the neurocognitive underpinnings of individual differences in moral decision-making. First, it provides reconciliation of a long-standing debate in the literature on the role of cognitive control in (dis)honesty. Second, he contributed by identifying stable neural markers that can be used to predict individual differences in (dis)honesty. Lastly, Sebastian provided a behavioral paradigm that can be used to inconspicuously measure voluntary, spontaneous and repeated cheating on a trial-by-trial basis in the MRI scanner or while recording EEG.

In his dissertation ‘Cost Allocation in Collaborative Transportation’ Mathijs van Zon considered a centralised horizontal collaboration between logistic service providers that is governed by a third party. He focused on how to determine a stable allocation of the overall cost or profit among the logistic service providers. Second, Mathijs focused on a centralised horizontal collaboration that is not governed by a third party. He studied this setting both analytically and numerically for collaborations in transportation, and provided insights into the value of the quality of an algorithm in collaborations.

In his dissertation Sebastian examined how changes to the information landscape affect the quality of information reported by companies, its dissemination in capital markets, and investors’ processing of the information. In particular, Sebastian investigated experimentally how public scrutiny of companies, changes to the structure of transaction fees, and the framing of company disclosure affect capital market communications.

In his dissertation Cristian Stet put forward a series of four studies which scrutinise the flexibility of power markets in relation to the growing supply from variable renewable sources. The dissertation teaches us that supply from variable renewable sources affects the flexibility needs of a power market by changing the probability distribution function of power prices and altering the relation between forward and spot power prices, reducing the power price forward premium.

In his dissertation Viktor Koritarov dealed with the integration of Regulatory Focus Theory and Framing Theory into the standard Situational Crisis Communication Theory model (SCCT). Three related papers, using experimental design, deconstruct the basic principles of the SCCT model and show that they can be rearranged into a more effective contingency model.

In his dissertation Mohammad Ansarin detailed the influence of growing D-RES on the equity and economic efficiency of electricity tariffs. Newer time-based pricing schemes are necessary to prevent high (and probably undesirable) inefficiency and inequity within and between household populations. Installing smart meters is a prerequisite for these tariffs. Using extra meters at the generation resource simplify paying for D-RES generation, but the improvements for inequity are comparatively small.

In his dissertation Rowan Hoogervorst focused on improving both the scheduling and rescheduling of rolling stock, where he is specifically interested in further integrating these problems into the operational process of a railway operator. Railway transportation plays an important role in the Dutch mobility system. To make train travel both comfortable and affordable, it is essential for operators to efficiently use their train units. This means that these train units have to be scheduled such that a good balance between passenger service and operational costs is found. Moreover, efficient rescheduling of these train units is necessary to maintain a good service in case a disruption occurs in the railway system.

At the beginning of the digital age 30 years ago, Peter Vervest, Professor of Information Management and Networks, joined Rotterdam School of Management, Erasmus University (RSM) as a faculty member. To celebrate the professor’s career milestone and his retirement, RSM hosted a valedictory event to take a deeper look at the roles that universities should play in being digital leaders and how students can be equipped to learn with new technologies. The event, on 24 September, began with a debate and the official opening of a new facility for the university: the new Erasmus Data Collaboratory, before Professor Vervest’s farewell lecture Fast-Forward Digital: A new kind of university.

In her dissertation Sha Zhu presented three contributions to the problem of obsolescence of large spare parts inventories for capital goods. First, a new method based on extreme-value theory was developed to aid companies in forecasting the spare parts demand distribution. Next, the inventory control problem for on-condition maintenance and shutdown maintenance were analyzed. Finally, a model is established to model the spare parts ordering problem against the background of shutdown maintenance project planning.

In his dissertation 'Public Transport and Passengers: Optimization Models that Consider Travel Demand' Johann Hartleb presented integrated models to optimize public transport services while estimating the corresponding passenger choices. The first study compares different timetable evaluation functions for consistency and gives further motivation for the integration of passenger choice models into optimization models. In the next two studies, he presented novel optimization models with integrated demand estimation for the steps of timetabling and line planning, respectively. The resulting public transport services are designed for the passenger demand they generate. The second part of this thesis deals with new and more flexible forms of public transport: mobility on demand. In order to assess the consequences of large-scale on-demand services on cities and regions, travel demand models need to be extended to determine the service level of on-demand services. Both studies in this part present solution algorithms for a vehicle scheduling problem of on-demand services to estimate the required vehicle fleet size and distance traveled