Avermann, N., & Schlüter, J. C. (2019). Determinants of customer satisfaction with a true door-to-door DRT service in rural Germany. Research in Transportation Business & Management, 32: 100420. doi:10.1016/j.rtbm.2019.100420
Gebauer, A., Fingerhut, J., Lahner, J., & Schlüter, J. C. (2019). Verkehrsanbindung von Berufsschülern. Standort, 43(1), 9-19. doi:10.1007/s00548-019-00567-4
Grunicke, C., Schlüter, J. C., & Jokinen, J.-P. (2020). Evaluation methods and governance practices of new flexible passenger transport projects. Research in Transportation Business & Management, 100575. doi:10.1016/j.rtbm.2020.100575
Harbering, M., & Schlüter, J. C. (2020). Determinants of transport mode choice in metropolitan areas the case of the metropolitan area of the Valley of Mexico. Journal of Transport Geography, 87: 102766. doi:10.1016/j.jtrangeo.2020.102766
Kern, L., Seebaß, J. V., & Schlüter, J. C. (2019). Das Potenzial von vertikalen Windenergieanlagen im Kontext wachsender Flächennutzungskonflikte und Akzeptanzprobleme der Windenergie. Zeitschrift für Energiewirtschaft, 43, 289-302. doi:10.1007/s12398-019-00264-7
Kersting, M., Matthies, E., Lahner, J., & Schlüter, J. (2020). A socioeconomic analysis of commuting professionals. Transportation, 1-32. doi:10.1007/s11116-020-10124-w
Lahner, J., Schlüter, J. C., & Sörensen, L. (2019). Digitalisierung im ÖPNV: vom Rufbus zu einem intelligenten nachfrageorientierten System im ländlichen Raum. Neues Archiv für Niedersachsen, II/2019, 178-191. doi:10.5771/9783529096112-178
Lichter, J., Hosius, E., Wacker, B., & Schlüter, J. C. (2020). Der Einfluss von Offshore-Windenergie auf die EEX-Strompreise. Zeitschrift für Energiewirtschaft, 44, 85-99. doi:10.1007/s12398-020-00276-8
Matthies, E., Preuß, S., Lahner, J., & Schlüter, J. C. (2019). Alternative Bedienformen im ÖPNV. Implikationen für den Planungsprozess. Zeitschrift für Verkehrswissenschaft, 90, 21-47. www.z-f-v.de
Nyga, A., Minnich, A., & Schlüter, J. C. (2020). The effects of susceptibility, eco-friendliness and dependence on the Consumers’ Willingness to pay for a door-to-door DRT system. Transportation Research Part A, 132, 540-558. doi:10.1016/j.tra.2019.11.030
Schlüter, J. C., Frewer, M., Sörensen, L., & Coetzee, J. (2020). A stochastic prediction of minibus taxi driver behaviour in South Africa. Humanities and Social Sciences Communications, 7: 13. doi:10.1057/s41599-020-0508-2
Simons, J., Wacker, B., Bossert, A., & Schlüter, J. C., Verkehrsökonomische Analyse von Minibustaxiverkehren in der Metropolregion Kapstadt und der Minenstadt Rustenburg in Südafrika, Zeitschrift für Verkehrswissenschaft, 91, 1-27. www.z-f-v.de
Sörensen, L., Bossert, A., Jokinen, J. P., & Schlüter, J. (2020). How much flexibility does rural public transport need?–Implications from a fully flexible DRT system. Transport Policy, 100, 5-20. doi:10.1016/j.tranpol.2020.09.005
Wacker, B., & Schlüter, J. C. (2020). Time-continuous and time-discrete SIR models revisited: theory and applications. Advances in Difference Equations, 2020: 556. doi:10.1186/s13662-020-02995-1
Wacker, B., Seebaß, J. V., & Schlüter, J. C. (2020). A modular framework for estimating annual averaged power output generation of wind turbines. Energy Conversion and Management, 221: 113149. doi:10.1016/j.enconman.2020.113149
Wacker, B., & Schlüter, J. C. (2020). An age- and sex-structured SIR model: Theory and an explicit-implicit numerical solution algorithm. Mathematical Biosciences and Engineering, 17, 5752-5801. doi:10.3934/mbe.2020309
Schröder, M., Bossert, A., Kersting, M. et al. COVID-19 in South Africa: outbreak despite interventions. Sci Rep 11, 4956 (2021). doi:10.1038/s41598-021-84487-0
Schlüter, J., Sörensen, L., Bossert, A. et al. Anticipating the impact of COVID19 and comorbidities on the South African healthcare system by agent-based simulations. Sci Rep 11, 7901 (2021). doi.org/10.1038/s41598-021-86580-w
Wacker, B., Schlüter, J. C.(2021). A Cubic Non-Linear Population Growth Model for Single Species: Theory, An Explicit-Implicit Solution Algorithm and Applications. Advances in Difference Equations, 2021: 236. doi:10.1186/s13662-021-03399-5
Schlüter, J. C., Simons, J., Sörensen, L., & Coetzee, J. (2021).Optimierung von Minibustaxiverkehren in Südafrika unter Einbindung von Geoinformationssystemen, Standort 45, 96–101.
Schlüter, J., Bossert, A., Rössy, P., & Kersting, M. (2021). Impact assessment of autonomous demand responsive transport as a link between urban and rural areas. Research in Transportation Business & Management, 39, 100613. doi:10.1016/j.rtbm.2020.100613
Kersting, M., Sörensen, L., Bossert, A., Wacker, B., & Schlüter, J. C. (2021), Predicting Effectiveness of Countermeasures during the COVID-19 Outbreak in South Africa using Agent-Based Simulation, Humanit Soc Sci Commun 8, 174
Bossert, A., Kersting, M., Timme, M., Schröder, M., Feki, A., Coetzee, J., & Schlüter, J. (2020). Limited containment options of COVID-19 outbreak revealed by regional agent-based simulations for South Africa. Open Peer Review@F1000
Bossert, A., von Hausegger, K., Schlüter, J. C. (06/2020), Behavioural analytics for smart cities: The influence of weather on cycle superhighway utilisation in cities with seasonal inhabitant effects. submitted@Cities
Hahn, A., Fruehling, W., Schlüter, J. C. (2021), Determination of optimized pick-up and drop-off locations in transport routing - A Cost-Distance approach. submitted@Transportation Science
Herbst, H., Minnich, A., Herminghaus, S., Kneib, T., Wacker, B., & Schlüter, J. C. (03/2020), A Behavioral Economic Perspective on Demand Responsive Transportation, Transportation Research Interdisciplinary Perspectives. submitted@Transportation Research Interdisciplinary Perspectives
Kersting, M., Kallbach, F., & Schlüter, J. C. (12/2020). For the young and old alike - A comparison of senior citizens’ satisfaction with the true DRT system EcoBus in rural Germany.
submitted@Journal of Transport Geography
Knierim, L. & Schlüter, J. C. (12/2020). The attitude of potentially mobility-impaired people towards demand responsive transport in a rural area in central Germany.
submitted@Journal of Transport Geography
Schöller, G., Sörensen, L. & Schlüter, J. C. (06/2020). Socially-optimal public transport operations in a developing country.
Veshapidze, L., Sörensen, L. & Schlüter, J. C. (06/2020). How do contract types and incentives influence driver behavior? An analysis of the Kigali bus network.
submitted@Humanities & Social Sciences Communications
Wacker, B., Kneib, T., & Schlüter, J. C. (02/2020), Revisiting Maximum Log-Likelihood Parameter Estimation for Two-Parameter Weibull Distributions: Theory and Applications. doi:10.13140/RG.2.2.15909.73444/2
Wacker, B., Schlüter, J. C.. Pipeline for Annual Averaged Wind Power Output Generation Prediction of Wind Turbines Based on Large Wind Speed Data Sets and Power Curve Data submitted@MethodsX
Wacker, B., Schlüter, J. C.. Qualitative Analysis of Two Systems of Non-Linear First-Order Ordinary Differential Equations for Biological Systems submitted@Mathematical Methods in the Applied Sciences
Grunicke, C., Schlüter, J. C., & Jokinen, J.-P. (12/2020), Implementation of a cost-benefit analysis of Demand-Responsive Transport with a Multi-Agent Transport Simulation. arXiv preprint arXiv:2011.12869
Books & Technical Reports
Technical Report 1: Transportanalyse zur Implementierung eines intelligenten Demand Responsive Transport Systems im ländlichen Raum
Technical Report 2: Transportanalyse zur Implementierung eines intelligenten Demand Responsive Transport Systems im ländlichen Raum
Technical Report: Machbarkeitstudie zur Ansiedlung von Hochtechnologien in Schleswig-Holstein.
Jokinen, J.-P., Sörensen, L., Schlüter, J. C. (2021), Public transport in low density areas. In: Vickerman, Roger (eds.) International Encyclopedia of Transportation. vol. 1, pp. 589-595. UK: Elsevier Ltd. doi:10.1016/B978-0-08-102671-7.10628-1
by Jan Schlüter
@ Uni Göttingen
by Jan Schlüter
@ Uni Göttingen
by Jan Schlüter
@ Uni Göttingen
Topics in Descriptive Statistics
by Jan Schlüter
@ Uni Göttingen
Statistics and Operations Research
by Jan Schlüter
@ Uni Göttingen
Seminar in Operations Research
by Jan Schlüter
@ Uni Göttingen
2016 to 2020 Next Generation Mobility Groupleader, Department of Dynamics of Complex Fluids, Max Planck Institute for Dynamics und Self-Organization, Göttingen
2020 Fellowship at the NATO Energy Security Center of Excellence
2014 to 2015 Group Nonlinear Dynamics and Turbulence, Institute of Science and Technology Austria, Klosterneuburg, Österreich
2011 to 2020 Institute for the Dynamics of Complex Systems, Faculty of Physics, Georg August University of Göttingen
2011 to 2014 MPRG Turbulence und Complex Dynamics, Max Planck Institute for Dynamics und Self-Organization, Göttingen
2009 to 2011 Department of Materials Physics, ELTE University Budapest, Hungary
Award for innovation of the district of Göttingen, environmental category
Diploma Georg-August-University of Göttingen
PhD Georg-August-University of Göttingen
32x Supervised and completed Master theses since 2016
23x Supervised and completed Bachelor theses since 2016
Supervised award-winning theses
Transport Hubs in
In times of passenger transport transformation, nodes that enable inter- and multimodality in the transport sector are becoming particularly important. New forms of mobility in the context of public transport are thus strongly emphasized on these starting and transfer points. Hence, these nodes need to be considered separately but at the same time in the overall spatial context of the region.
Transport Systems in
Innovation processes in mobility are spreading rapidly in urban areas. On the contrary, rural areas lag behind due to low demand and cumbersome revenue generation. Innovative solutions offer a chance to bring benefits of modern mobility into low density areas and altering current business models.
Public Transport in
The proportion of the population aged 60 and older in western countries is growing steadily. The mobility of older people is therefore of increasing importance, as this rapid growth can lead to serious traffic problems if, with increasing age, the deficites in driving skills become more pronounced. Up to now, public transport availability in rural regions is often centered around school hours and offers only reduced services throughout the rest of the day. Hence, these regions are facing new challenges and must adapt their structures accordingly.
The most important energy source from the field of renewable energies in Europe is wind. Currently, wind can still be interpreted as a stochastic variable. Accordingly, we improve our understanding of wind structures with mathematical and statistical tools.
Wind energy represents an important future economic sector due to the increasing interest in renewable energy worldwide. For this reason, wind turbine performance prediction is an important task for economists. Therefore, the field of energy economics is in a state of flux and offers a variety of new research questions.
Wind energy is gaining an ever-increasing share in the electricity mix of many countries. Our goal is to estimate the wholesale price and thus provide planning certainty in the markets and reduce the impact of wind energy fluctuation. For these analyses, we treat offshore and onshore wind energy as variables to be considered and their impact on the European Energy Exchange. Using these models, we can identify various parameters and how they affect wholesale electricity prices.
Currently, a gradual change in the perspective of cities can be observed worldwide due to global warming and the shortage of raw materials. With the signing of the Kyoto Protocol and the associated goal of the international community to slow global warming to a maximum of 2 degrees Celsius compared to pre-industrial levels, the world has committed itself to taking effective steps to reduce greenhouse gas emissions. Consequently, the bicycle is gaining ground as a sustainable, CO2-neutral means of transport. because of its potential to replace motorized transport and contribute to climate protection and quality of life.
Cost Benefit in Transportation
Interdisciplinarity is an essential key to the effectiveness of innovations and technologies. Accordingly, the aim of this work is to evaluate the potential of transport systems from an economic point of view and thereby generate recommendations. Digital approaches enable new options for an optimal interaction of these disciplines.
Transport in Metropolitan Areas
Transportation in the megacities has a multitude of problems. One of the core problems is the inadequate public transportation system which leads to a multitude of other problems such as extreme traffic congestion, long commute times, air pollution or even fatal traffic accidents. The external cost of these consequences is a high damage to the economic development of these cities. With the continuous growth of these cities, this research area is continuously gaining importance to provide for a more sustainable world.
Transport Behaviour, Gamification and Nudging
One of the biggest challenges in the mobility transition is human behavior. This is influenced by many different factors and must be considered accordingly for special requirements. This makes it easier to derive more efficient and better economic models and policy implications for these requirements. Our goal here is to enable more sustainable transport behavior. Extrinsic incentives and monetary incentives could be a solution for this. Therefore, such concepts have to be identified and tested in experiments.
Agent Based Simulations and Policy Recommendations for Epidemics in the Global South
The People´s Republic of China was the first region to be affected by a global pandemic outbreak in January 2020. COVID-19 spread quickly around the globe, presenting the international community with new dimensions of economic, social and moral problems. Countries responded by making macroscopic decisions for their nations. The individual regions were not equipped with the appropriate applications to be able to act regionally. Accordingly, micro-management decision support tools could be developed by us to advise the regional decision makers.
New Business Concepts for Public Transport
On-going digitization has already produced numerous disruptive innovations, with many more to follow. The transportation sector is particularly affected by these innovations, whether through drones, autonomous vehicles or the digitization of public transport. New business models must be developed and adapted accordingly.
Demand Responsive Transport Systems in rural Areas
Demographic change is prevalent in rural regions against the backdrop of an aging society as well as out-migration due to a lack of employment opportunities and poor infrastructure. Given a fixed budget for transport operators, declining demand leads to high operating costs per transported customer. This makes the provision of public transport economically inefficient and people in rural areas become highly dependent on private motorized transport. Therefore, public transport needs to be transformed through digitization measures. For this purpose, the DRT system EcoBus was developed for rural areas as a door-to-door system.
Socio-Economic Optimisation of Public Transport Systems in Africa
While urbanization and population growth are expanding city boundaries, public transportation systems are required to accompany this process in order to provide accessible public transport. The results of this study provide a basis for further analyses of public transport systems around the world to determine deficiencies in parameters and service design. It also contributes to the toolkits for the assessment of public transport services within a city and provides guidelines for political processes.
Corporate Mobility Management
The scope and tools of modern corporate mobility management concepts go far beyond pure business travel. Changing mobility needs and digital solutions enable intelligent networking and efficient coordination of different mobility needs and affect other business areas such as corporate social responsibility. Smart and tailored mobility management can create cost-efficient, sustainable and attractive offers for employees and the region.
Simulations for future Transport Systems
Disruptive developments in automated driving systems, new drive concepts and digital mobility are shaping the way people in rural and urban areas. In combination with these technical potentials, novel mobility concepts can improve people`s everyday mobility of people in terms of both cost efficiency and sustainability. In addition, the challenges of demographic change and urbanization can be and negative developments can be mitigated.
AI for Aerospace Technology
A major driver of climate change is flying, so we are striving to make this more sustainable. in doing so, we are focusing on researching the effects of operating conditions on aircraft engines to improve the timely planning of maintenance events and optimize them. To do this, we use machine learning mainly with time series of aircraft engines and numerical weather prediction models. The research aims to improve fuel efficiency and increase component longevity. This should enable plant operators and service providers to reduce costs and environmental footprint.
In a comparison of the German states, Schleswig-Holstein scores below average on indicators such as gross domestic product per employee and research and development spending. One possible remedy against such scenarios is to provide impetus for technological innovations that have an impact on both economic growth and industrial development.
Door to Door DRT System (Ecobus)
The most flexible DRT system is a door-to-door service. This offers a high degree of flexibility and thus ensures a comprehensive understanding of the user`s routes. Accordingly, such a system can also achieve a high degree of customer satisfaction, as there is no need to change. Depending on the system, the pooling rate and the resulting detours can be problematic.
Demand Responsive Transport Systems in Urban Areas
The most flexible DRT system is a door-to-door service. This offers a high degree of flexibility and thus ensures a comprehensive understanding of the users routes. Accordingly, such a system can also achieve a high degree of customer satisfaction, as there is no need to change. Depending on the system the pooling rate and the resulting detours can be problematic.
Research fields involved
Strengthening public transport is an essential contribution to the mobility turnaround. Digitalization enables a better understanding between supply and demand.
Economic development also depends heavily on the regions` capacity for innovation. Individual technologies or the interaction of various technology players creates an environment in which disruptive technologies trigger structural disruptions.
Applied Artificial Intelligence
Due to the large amount of data from the areas of transportation and energy, we use artificial intelligence to analyze it. New use cases for artificial intelligence are emerging in the process.
Wind energy is the backbone of renewable energies in Europe. The high fluctuation of this energy source is one of the main problems to be solved. Accordingly, complementary technologies and smart power grids are promising approaches.
The combination of methods from the transport sector and the inclusion of digital technologies enable new applications in the field of public health. In this context, it is possible to take a look at the micro level and to model regions in a targeted manner.
Renewable energies lead to strong fluctuations on the markets. accordingly, these have to be analyzed and understood more precisely in order to supply the economy with energy and to maintain its functionality.
The behavior of individuals and firms in decisions about the allocation of scarce resources is studied in economic models. Thus, microeconomics forms the theoretical basis of the other research fields.
Economic Policy and Management
Transport, energy and public health are among the biggest infrastructure issues for a state. Accordingly, our research is closely related to the economic policy of a state or the management of a company. Therefore, we develop recommendations for these actors according to our models and data.