WHU

Assistant Professor Dr. Martin Prause

Institute for Industrial Organization

Assistant Professor of Computational Economics and Business Analytics

Contact:

+49 (0)261 6509 273

 +49 (0)261 6509 279
martin.prause[at]whu.edu

Research Focus

Traditionally, business strategy dictates IT strategy. Nowadays, this top-down approach has been disrupted by data-driven methods such as descriptive, predictive and prescriptive analytics. These data-driven approaches summarized as Business Analytics, shape business models, and organizations from the bottom. 

Big Data in conjunction with Machine Learning Algorithms are revamping entire industries. In particularly automated self-learning and economic reasoning advances the decision-making processes in business management. It provides a toolbox to test innovative ideas and strategic market interaction within the scope of predictive and prescriptive analytics. 

Martin’s research focus combines two fields: (1) Computer Science (Computational Intelligence) and (2) Economics (Industrial Organization), and he is approaching the topic of Machine Learning in Business Management from three angles:

  1. Modelling imperfect markets using either Discrete Event Simulation, System Dynamics or Agent-based models for business simulations and business war games. 
  2. Developing computational intelligence-based agents pursuing supervised, unsupervised and reinforcement learning for decision-making in business management.
  3. Studying the organizational determinants for creating business value from Machine Learning and analyzing its implications.

     

Short Biography

Martin received his Ph.D. in Economics from WHU – Otto Beisheim School of Management in December 2014. He has been involved in numerous lecturer and teaching assistant positions during his Ph.D. and as a post-doctoral researcher in 2015. Martin received two visiting research scholarships (India 2013, Japan 2015), the best Ph.D. award from Infosys/India in 2013 and the best student paper award from the Association for Business Simulation and Experimental Learning in 2014. From 2012 to 2014 he has been involved in joint research projects with the London School of Economics and Google Inc. in the Google Summer of Code Program. Before he started his doctoral studies, he received his MBA from WHU, was the CIO of a fashion wholesaler for three years and graduated from the TU Dortmund with a Diploma in Computer Science.

Selected publications

From Industrial Organization to Entrepreneurship. Springer, Cham.

The Shape of Things to Come. In: Lehmann & Keilbach (eds)

Prause & Weigand (2019)
International Journal of Computational Economics and Econometrics 9 (1-2), 29-48.

Technology Diffusion of Industry 4.0: An Agent-Based Approach

Prause & Günther (2019)

An Economist’s View of the Digital World, Infosys Insights – Disruption

Prause (2018).
IEEE Computational Intelligence Magazine, 13(4), 14-24.

Market Model Benchmark Suite for Machine Learning Techniques

Prause & Weigand (2018)
Proceedings of the 2017 Winter Simulation Conference, 4312 - 4323

The Rig: A leadership practice game to train on debiasing techniques

Prause & Weigand (2017)
Game-On - 18th International Conference on Intelligent Games and Simulation, 101 -105.

Global Strategy Game: A Serious Game for Teaching International Business

Prause & Weigand (2017)
Infosys Insights – Purposeful AI, 68-75.

On the Trail of Machina Economicus.

Prause (2017)
Journal of Technology, Management and Innovation, 11(2), 104-110.

Industry 4.0 and Object-Oriented Development: Incremental and Architectural Change.

Prause and Weigand (2016).
Proceeding of the Computing in Economics and Finance Conference (May 2014, Oslo).

Simplified Cuckoo Search: A robust metaheuristic for agent-based artificial markets.

Prause & Weigand (2014)
Developments in Business Simulation and Experiential Learning, 41, 96-106.

A business simulation game for location-based strategies.

Prause, Guenther & Weigand (2014)
From Industrial Organization to Entrepreneurship. Springer, Cham.

The Shape of Things to Come. In: Lehmann & Keilbach (eds)

Prause & Weigand (2019)
International Journal of Computational Economics and Econometrics 9 (1-2), 29-48.

Technology Diffusion of Industry 4.0: An Agent-Based Approach

Prause & Günther (2019)

An Economist’s View of the Digital World, Infosys Insights – Disruption

Prause (2018).
IEEE Computational Intelligence Magazine, 13(4), 14-24.

Market Model Benchmark Suite for Machine Learning Techniques

Prause & Weigand (2018)
Proceedings of the 2017 Winter Simulation Conference, 4312 - 4323

The Rig: A leadership practice game to train on debiasing techniques

Prause & Weigand (2017)
Game-On - 18th International Conference on Intelligent Games and Simulation, 101 -105.

Global Strategy Game: A Serious Game for Teaching International Business

Prause & Weigand (2017)
Infosys Insights – Purposeful AI, 68-75.

On the Trail of Machina Economicus.

Prause (2017)
Journal of Technology, Management and Innovation, 11(2), 104-110.

Industry 4.0 and Object-Oriented Development: Incremental and Architectural Change.

Prause and Weigand (2016).
Proceeding of the Computing in Economics and Finance Conference (May 2014, Oslo).

Simplified Cuckoo Search: A robust metaheuristic for agent-based artificial markets.

Prause & Weigand (2014)
Developments in Business Simulation and Experiential Learning, 41, 96-106.

A business simulation game for location-based strategies.

Prause, Guenther & Weigand (2014)
WHU