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Research focus

Shaping digital transformation

Based on our research, we are following a concept for shaping the digital transformation that links the perspectives of regional actors and uses them beneficially.

The potential for innovation and digitalization can be utilized by linking the perspectives of the actors:

  • Policy makers promote the transfer of knowledge and regional innovative and corporate cultures.
  • Purpose-driven human-machine interaction is crucial for successful innovation within  companies.
  • The involvement of employees and the wider public boosts acceptance of digitalization and underpins its success.

 

Abbildung der Forschungsschwerpunkte an den Ecken eines Dreieicks © M. Hellmann, J. Schlüter​/​TU Dortmund

Research focus

The dilemma

What are the consequences of digitalisation? How does this affect people, technology and organisations, and what is required of them?

Effects of digitalisation

  • Increased complexity of work tasks
  • Increased monitoring through technology
  • Increased need for communication and interaction
  • More flexible working hours

New challenges for people, technology and organisations

  • Changing skills and qualification requirements
  • Stimulated creativity and a culture of innovation
  • Participative change management
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Publications

The dilemma

The electrical grid is currently undergoing a paradigm shift. We are progressively moving from a centralised system, characterised by a few large centralised power plants and the large-scale distribution of electricity to end customers, to a decentralised system with an increasing prevalence of inconsistent, renewable energy sources. While the move towards new sources of energy supply and production is accompanied by new uncertainties and challenges, it also presents opportunities for shaping such a complex, socio-technological system.

How is the energy system changing? What might the design of a future energy system look like?

  • Future scenarios taking into account the ongoing digitalisation of the grid (smart grid) and  rising power generation from renewable energy sources.
  • Information and risk management as measures to stabilise the system (demand response, energy efficiency)

To what extent will roles change in a future energy system?

  • End users (e.g., households, industry and commerce) as cooperation partners in maintaining system stability
  • Passive consumers and active prosumers as heterogeneous system participants
  • Changes in energy-related practices, values and perceptions
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The dilemma

Agent-based modelling and simulation (ABMS) offers an experimental, computer-based approach to investigating  questions about the future. What makes it special is the bottom-up conception of a socio-technological system: Accordingly, the behaviour and interactions of a multitude of heterogenous, adaptive and rule-based agents (e.g. organisations or individuals are reflected in the complexity and dynamics of the system .


How can experiments help us to understand the evolution of a changing complex socio-technological system?

  • Analysis of alternative developments and pathways (what-if scenarios), e.g., in the area of mobility and energy
  • Effects of (political) interventions in a socio-technological system, e.g., incentives or constraints
  • Design and testing of an artificial system and its social mechanisms

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The issue

Research on future mobility tends to focus primarily on the interaction between people and technology and the requirements of technology design

  • Human-machine interaction
  • User-friendly design
  • Competence development and qualification

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Publications

Question

The emergence of big data in recent years has not only been a hot topic in the media but has also attracted a great deal of attention from the scientific community: on the one hand, new ways of generating and evaluating data have provided the impetus for a number of new research topics. For example, growing amounts of data can be generated and automatically analysed, which offers considerable potential for the governance of complex socio-technological systems, such as transport or energy supply, in real time and thus optimising their efficiency.

           
At the same time, there is also a focus on the societal changes triggered by big data: The aforementioned collection of data not only facilitates the emergence of new social practices, but also depends on the trust of users, for example in the organisations processing and using their data (i.e. for intended purposes) or in data-security regulations.         
Data is also playing an increasingly important role in the economy relative to conventional goods, described as "de-materialisation" (it-daily) or even “data society”, as Houben and Prietl term it.

These developments  raise numerous socio-technological questions

  • What are the opportunities and risks for society?
  • How can the new methods of data generation and evaluation be used for data-based governance of complex systems?
  • What role does trust play in the acceptance of these systems?
  • Analysis of user trust in technology and app-based recommendations for action
  • Governance and transformation of transport and energy systems

Projects

Publications
  • Weyer, Johannes, 2019: Die Echtzeitgesellschaft. Wie smarte Technik unser Leben steuert. Frankfurt/M.: Campus.
  • Kappler, Karolin;Jan-Felix Schrape;Lena Ulbricht;Johannes Weyer, 2018: Societal implications of Big Data. In: Künstliche Intelligenz. Special Issue „Big data“ 32 (1): 55-60.
  • Weyer, Johannes;Delisle, Marc;Kappler, Karolin;Kiehl, Marcel;Merz, Christina;Schrape, Jan-Felix, 2018: Big Data in soziologischer Perspektive. In: Thomas Hoeren/Barbara Kolanyi-Raiser (Hg.), Big Data und Gesellschaft. Eine multidisziplinäre Annäherung. Berlin: Springer, 69-149.
  • Cepera, Kay;Julius Konrad;Johannes Weyer, 2018: Trust in algorithms. An empirical study of users’ willingness to change behaviour. In: Günter Getzinger/Stefanie Egger (Hg.), Critical Issues in Science, Technology and Society Studies. Conference Proceedings of the 17th STS Conference Graz 2018. Graz: Verlag der Technischen Universität, 38-47.

Location & approach

The  Technical University of Dortmund campus is located near the Dortmund West autobahn junction, where the A45  (Frankfurt-Dortmund) crosses the A40 (Ruhrschnellweg B1). The most convenient autobahn exits are found on the A45 in Dortmund-Eichlinghofen (closer to the south campus) and on the B1 / A40 in Dortmund-Dorstfeld (closer to the north campus). The university is signposted at both exits.

The TU Dortmund has its own S-Bahn station ("Dortmund Universität") on the North Campus. From there, the S-Bahn line S1 runs every 20 or 30 minutes to Dortmund’s central station and in the opposite direction to Düsseldorf’s central station via "Bahnhof Düsseldorf Flughafen". This makes the university directly accessible from the cities of Bochum, Essen, Mülheim an der Ruhr and Duisburg. Furthermore, the TU Dortmund may be reached via buslines 445, 447 and 462.
Individual timetable information for public transport is also available on the website of the Rhine-Ruhr Transport Association, and the Dortmund Transport Authority also offers an interactive route network map.

One of the landmarks of the TU is the H-Bahn overhead monorail which connects the two campuses. Line 1 runs every 10 minutes between the stops Dortmund Eichlinghofen and the Technology Center via Campus South and Dortmund Universität S. Line 2 shuttles every 5 minutes between the stops Campus North and Campus South. It covers this distance in two minutes.

To get from the Dortmund airport to the campus, we recommend taking the "Airport Express" to Dortmund's central train station (20 minutes), and then boarding the S-Bahn there.  A wider range of international flight connections is offered by Düsseldorf Airport, about 60 kilometres away, which can be reached directly by S-Bahn from the university station.