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Research on decisions, models, and data

Models enable us to comprehend the world, infer beyond the data, and ultimately make better decisions.
Tech and human
men at the chackboard
Book on AI and Decision Making
The Financial Times' review of "Framers", co-authored by Prof. Francis de Véricourt

Why humanity is an asset in an age of tech

Financial Times
The United Nations report on research by professors Hüseyin Gürkan and Francis de Véricourt

Examining Dissemination of Information on COVID-19

United Nations - Academic Impact


Human Advantage in an Age of Technology and Turmoil

by Kenneth Cukier, Viktor Mayer-Schönberger, and Francis de Véricourt
The Economist reports on Prof. Martin Schweinsberg's research

Data don’t lie, but they can lead scientists to opposite conclusions

The Economist

The research on decisions, models, and data (DMD) is interdisciplinary research on models, be they mathematical representations, mental models, or other frameworks, to help leaders and their organizations better interpret data, uncover new possibilities, and improve their decision-making. Our approach draws from fields as diverse as data science, analytics, cognitive psychology, sociology, and economics.

The abundance of data and the increasing adoption of intelligent machines raise questions about the future role of human-based decisions in organizations. At the same time, the profound crises the world is experiencing today have highlighted the limits of data-driven predictions and the need to decide even when data are scarce.  

The DMD research is based on the fundamental premise that human decision-makers are most effective when they properly leverage their unique ability to model and represent the world. These models enable inferences beyond the data and reveal new courses of action in a way that machines cannot. The DMD research explores how individuals and organizations can create and apply better models, and how data-driven technologies complement – or hinder – humans’ ability to represent.

Core areas

Human decisions in the age of artificial intelligence

Deciding under data scarcity, leading into the unknown

Governance and responsible analytics

Disruptive models and open innovations


Feedback in the digital age: When do people trust machine-generated feedback more than feedback provided by humans? 

Gianluca Carnabuci

Linus Dahlander

Do machine-based prescriptions affect the mental mindset of decision makers? 

Francis  de Véricourt

Martin Schweinsberg

Human and machine: The impact of machine input on decision making under limited attention 

Caner Canyakmaz

Tamer Boyaci

Francis  de Véricourt


People analytics in the digital age: Modeling men’s and women’s career paths through machine learning

Jan Nimczik

Gianluca Carnabuci

Min Liu

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

July 19, 2021 | Journal Article
Martin Schweinsberg, Michael Feldman, Nicola Staub, Olmo R. van der Akker, Robbie C.M. van Aert, Marcel A.L.M. van Assen, Yang Liu et al. (2021)

Framers: Human advantage in an age of technology and turmoil

May 13, 2021 | Book
Kenneth Cukier, Viktor Mayer-Schönberger, Francis de Véricourt (2021)

Warning against recurring risks: An information design approach

October 15, 2020 | Journal Article
2018 Best Paper Award
Saed Alizamir, Francis de Véricourt, Shouqiang Wang (2020)


  • Steering committee

    • Francis de Véricourt. Professor of Management Science and President's Chair, ESMT Berlin
    • Gianluca Carnabuci, Professor of Organizational Behavior and Ingrid and Manfred Gentz Chair in Business and Society, ESMT Berlin
    • Henry Sauermann, Professor of Strategy, POK Pühringer PS Chair in Entrepreneurship


  • Faculty members

    • Tamer Boyaci, Professor and Michael Diekmann Chair in Management Science, ESMT Berlin
    • Gianluca Carnabuci, Professor of Organizational Behavior, Ingrid and Manfred Gentz Chair in Business and Society, and Director of Research, ESMT Berlin
    • Francis de Véricourt Professor, Joachim Faber Chair in Business and Technology, and Academic Director of the Institute for Deep Tech Innovation (DEEP), ESMT Berlin
    • Huseyin Gurkan, Assistant Professor of Management Science, ESMT Berlin
    • Henry Sauermann, Professor of Strategy and ESMT Chair in Entrepreneurship, ESMT Berlin
    • Martin Schweinsberg, Assistant Professor of Organizational Behavior, ESMT Berlin
  • Research associates

    • Ekaterina Gorbunova, ESMT PhD Fellow and Research and Teaching Assistant, ESMT Berlin
  • Executive Education

    • Nan Guo, Program Director, Executive Education, ESMT Berlin
Get in touch

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