As society has to adapt to changing energy sources and consumption, it is driving away from fossil energy. One particular area of interest is electrical driving and the increasing demand for (public) charging facilities. For municipalities, it is essential to adapt to this changing demand and provide more public charging facilities.In order to accommodate on roll-out strategies in metropolitan areas a data driven simulation model, SEVA1, has been developed The SEVA base model used in this paper is an Agent-Based model that incorporate past sessions to predict future charging behaviour. Most EV users are habitual users and tend to use a small subset of the available charge facilities, by that obtaining a pattern is within the range possibilities. Yet, for non-habitual users, for example, car sharing users, obtaining a pattern is much harder as the cars use a significantly higher amount of charge points.The focus of this research is to explore different model implementations to assess the potential of predicting free-floating cars from the non-habitual user population. Most important result is that we now can simulate effects of deployement of car sharing users in the system, and with that the effect on convenience for habitual users. Results show that the interaction between habitual and non habitual EV users affect the unsuccessful connection attempts based increased based on the size of the car-sharing fleet up to approximately 10 percent. From these results implications for policy makers could be drawn.
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The research goal of this dissertation is to make configurational HRM usable for science and practice by developing a simulation model and serious game. These tools offer HRM professionals the opportunity to design a multiyear HRM configuration that shapes employee behaviour, while enabling HRM research to get access to a level of detail that was not achieved earlier, contributing to the current state of the art knowledge on strategic HRM. To shape employee behavior in such a way that it contributes to overarching organizational goals, organizations often deploy a set of human resource management (HRM) practices. If the set of individual HRM-practices is designed correctly, they amplify each other in shaping the desired behavior. However, while there is wide agreement on the importance of combining HRM-practices in a configuration that reflects the organizational strategy, we notice a lack of consensus on which HRM-practices need to be combined given a specific strategic goal and organizational starting point. Furthermore, we did not find an agreement on how to design HRM configurations that shape the desired employee behavior within organizations in multiple years. As a result, HRM professionals that design HRM configurations are left empty handed. While the configurational approach has the potential to provide new insight on how HRM shapes employees’ behavior, applying the configurational mode of theorizing to HRM remains challenging. We explain this challenge by the level of theoretical and practical detail that is needed, by the application of the holistic principle when studying HRM configurations, and due to methodological issues. Traditional methods do not align to the dynamic assumptions and the large number of variables included in configurational HRM. In this dissertation we pose that the time is ripe to unlock the deserved value of configurational HRM for theory and practice. We do so by specifying the underlying assumptions and dynamic implications of the configurational mode of theorizing in HRM, and by defining and adding the needed level of detail. In the current research, configurational HRM is made applicable with the use of a simulation model and serious game. -172- Five sequential steps are taken to make configurational HRM applicable. Firstly, key principles of configurational HRM are identified. Secondly, to ground the simulation we look at the manifestation of ideal type HRM configurations in theory and practice. Thirdly, we collect the solidified practical knowledge of HRM professionals on the alignment of HRM-practices. Fourthly, an initial simulation model is created and tested. And finally, we solidified the simulation model for practice and research by implementing it in a serious game for HRM professionals. Taking these five steps, we have specified configurational HRM to an unprecedented level of detail that allows us to address its complexity empirically and theoretically. We claim that with the results of this research we have opened the scientific and empirical “black box” of configurational HRM. Furthermore, the simulation model and serious game provides HRM professionals with a tool to design firm specific HRM configurations in an interactive and fun way. While prior studies did already acknowledge the importance of alignment when designing HRM, the simulation model and serious game specify the general concept of alignment to a level at which HRM professionals and researchers can start selecting, designing, implementing and researching HRM configurations. The tools provide HRM professionals with a method to grasp, maneuver through the complexity of, and explore the implementation of multi-year firm specific HRM.
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The viability of novel network-level circular business models (CBMs) is debated heavily. Many companies are hesitant to implement CBMs in their daily practice, because of the various roles, stakes and opinions and the resulting uncertainties. Testing novel CBMs prior to implementation is needed. Some scholars have used digital simulation models to test elements of business models, but this this has not yet been done systematically for CBMs. To address this knowledge gap, this paper presents a systematic iterative method to explore and improve CBMs prior to actual implementation by means of agent-based modelling and simulation. An agent-based model (ABM) was co-created with case study participants in three Industrial Symbiosis networks. The ABM was used to simulate and explore the viability effects of two CBMs in different scenarios. The simulation results show which CBM in combination with which scenario led to the highest network survival rate and highest value captured. In addition, we were able to explore the influence of design options and establish a design that is correlated to the highest CBM viability. Based on these findings, concrete proposals were made to further improve the CBM design, from company level to network level. This study thus contributes to the development of systematic CBM experimentation methods. The novel approach provided in this work shows that agent-based modelling and simulation is a powerful method to study and improve circular business models prior to implementation.
The drive to reduce the carbon intensity of the energy system has generated much interest in applying carbon-free fuels such as ammonia (NH3) in combustion systems. The high hydrogen density and well-established production processes make NH3 a valuable chemical energy carrier to address and sustain the energy shift toward renewable energy source integration. However, some difficulties can be highlighted in the NH3 practical application. The combustion of NH3 is prone to producing harmful nitric oxides. In addition, NH3 has lower reactivity than most hydrocarbon fuels, which makes ignition challenging. Also, admixing NH3 with highly reactive fuels such as DME will facilitate ignition. The partnerships of this proposal are very interested in applying renewable NH3 as fuel in combined heat and power engines, and this research proposal suggests simulating a dual-fuel engine with NH3 as its primary fuel. The results of this research will help determine the optimum operating conditions for performing an experimental study.
