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The aim of the ANIMATE project (Applications of artificial intelligence in medium-sized companies: data analytics – technology, competence and success factors in operational use) is the application of technologies from the area of artificial intelligence (AI) in medium-sized companies. Not only the potentials and technical feasibility will be tested on real-world applications but there will also be an assessment of how this disruptive key technology can be integrated in corporate structures.   


Corporate decisions stimulate disruptive innovations. Digital innovations and the application of up-to-date technologies will be essential in future for the competitiveness of companies. Digitisation plays an increasingly central role in all economic and societal areas and requires understanding on the part of management for technology and information-economic interrelationships. It changes corporate organisations and jobs and particularly influences and automates the business model. Especially companies which are not focused on software development find it difficult to use digital technologies for their own business models.   

Although many methods of artificial intelligence (AI) display a degree of development that is ready for application, they are not applied very often by companies, possibly due to a lack of skills and because the technologies can rarely be used out of the box. At the same time companies have a large volume and diversity of data that become available from the business processes without making sufficient use of this wealth of data. It is frequently not clear what additional information can be obtained from the data or for what purpose/gain information can be used, or there is a lack of know-how regarding data analysis with the help of modern methods. 

What is artificial intelligence?

Artificial intelligence is understood to mean a subfield of information technology which is concerned with the automation of intelligent behaviour and machine learning. Machine learning deals with learning algorithms. These can be used among other things to gain knowledge from existing data with whose help forecasts about future events can be made. The key feature of machine learning is the autonomous self-adaptation of the algorithms to the respective application environment.  


Project Goals and Development

The objective of the ANIMATE project is to gain a more precise understanding of the technical prerequisites and to find ways to implement methods of artificial intelligence in medium-sized companies. This is implemented in cooperation with medium-sized companies in three successive project steps.

1. Working with firms, AI-based data analysis and forecast models are developed and trained

Research on artificial intelligence has created a large number of learning algorithms for various applications, e.g. Bayesian belief networks, multilayer neural networks, genetic networks for various complex problems are applied, i.e. to very large multidimensional datasets. The recent growth in computer power allows work to be carried out successfully particularly with multilayer neuronal networks with many neurons (nodes), so called deep learning. Artificial neuronal networks are used successfully for forecasts and are particularly good for use with large data volumes.


2. Applications for these forecast models are being developed and tested under real conditions

In the companies, specific prerequisites for the successful use of artificial neuronal networks are identified and created as well as skills in this area developed. The use of this key technology especially in SMEs provides a big added value, shows companies the specific benefits of digitisation and at the same time raises awareness for further projects within the framework of the digital transformation.

3. Problem patterns are built from different applications in order to derive generalised models from them

The aim is rather to make a contribution to application in business practice. For this, different problem classes and application scenarios of artificial neuronal networks are identified and structured. On this basis, appropriate solutions for the individual problem classes are derived and specific algorithms implemented, adapted and trained so that companies are enabled to use artificial neuronal networks with little effort.


Project structure and partners

The project is a cooperative venture between Reutlingen University, the B2B trader REIFF and the consulting company 4flow. This collaboration allows the use and the evaluation of the key technology artificial intelligence on the basis of real scenarios from business life. REIFF, a trader in more than 140,000 different products, offers a variety of different applications, which will be investigated within the scope of the project. The practical results will subsequently be placed in a theoretical context and published.


  • Dinther, C. van & Mauch, S. (2019). Chancen der künstlichen Intelligenz zur Prognose im Mittelstand. Growth Magazine, 2.
  • Kiefer, D., Ulmer, A. & Dinther, C. van. (2019). Application of Artificial Intelligence to optimize forecasting capability in procurement. In U. Kloos, N. Martinez, & G. Tullius (Hrsg.), Wissenschaftliche Vertiefungskonferenz. Tagungsband 2019 (1. Aufl., S. 69–80). Reutlingen: Reutlingen University. doi: https://doi.org/10.5281/zenodo.3539397


Clemens van Dinther

Prof. Dr. Clemens van DintherEconomic Informatics, Business Analytics

Office Hours: by appointment

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Building 5
Room 210
Phone +49 7121 271 3118
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Role and Responsibilities
  • Programme Director of BSc International Management Double Degree (IMX)
  • Programme Leader of BSc International Management Double Degree German-Chinese
  • IMX Ressort: student affairs
  • Building and Maintenance Officer, building 5
Focus of Lectures
  • Management Information Systems
  • Computational Economics
  • Smart Grid Economics
  • Foundation of Internet-Startups
  • IT-Management
  • Knowledge Management
Research Topics

Fields of Interest:

  • Business Analytics, Big Data
  • Electronic Markets
  • Mechanism Design
  • Electronic Services
  • Value Networks
  • Artificial Intelligence

Research projects:

  • Since October 2014 Professor of Economic Informatics/Business Analytics at ESB
  • Managing Director of Genek GmbH und Co. KG
  • Lectureships at RWTH Aachen
  • Director Energy Management/Business Process Outsourcing, Manager Business Development at ista Deutschland GmbH
  • Assistant professor at Karlsruher Institut für Technologie (Venia Legendi for Business Administration - BWL)
  • Visiting professor for Information Management and Systems at Karlsruher Institut für Technologie
  • Head of Department for Information Management and Systems, Forschungszentrum Informatik (Research Center Informatics) Karlsruhe, Project manager of an EU project
  • Project manager of a BMBF research project doctoral candidate, Karlsruhe University (TH)
  • Studies at Stuttgart, Karlsruhe and Galway (Ireland) Universities; Degree in Industrial Engineering

Articles in reviewed specialist journals:

Salah, J. Ilg, C. Flath, H. Basse, C. van Dinther: Impact of Electric Vehicles on High-Voltage Grids – A Swiss Case Study, Journal of Applied Energy, 2015, vol. 137, pp. 88-96

Provider Learning in Service Value Networks (zusammen mit C. Haas, S. Kimbrough), Journal of Service Research (JSR), 16(3), 2013, pp. 259–276.

Stochastic simulation of the economic impact of load forecast errors on electricity storage systems (zusammen mit K.-H. Ahlert), Electric Power Systems Research, forthcoming

Clusteranalyse von Smart Meter Daten – Eine praxisorientierte Umsetzung (zusammen mit C. Flath, T. Conte, L. Filipova-Neumann, D. Nicolay), Zeitschrift Wirtschaftsinformatik, Vol. 54, No. 1, February 2012, pp. 33-42

Rewarding Participation in Service Value Networks, e-Service Journal, Vol. 7, No. 2, Indiana University Press, 2010 (zusammen mit: T. Conte, B. Blau, G. Satzger, C. Weinhardt ; Vorversion erschienen auf der AMCIS 2009)

A Multidimensional Procurement Auction for Trading Composite Services, Issue in the Electronic Commerce Research and Applications Journal (ECRA) on Emerging Economic, Strategic and Technical Issues in Online Auction and Electronic Markets, Elsevier, Vol. 9, No. 5, September 2010, pp. 460-472 (zusammen mit B. Blau, T. Conte)

How to Coordinate Value Generation in Service Networks? -- A Semantic Mechanism Design Approach. Journal of Business and Information Systems Engineering (Wirtschaftsinformatik), Vol. 1, No. 5., October 2009, pp. 343-356 (zusammen mit B. Blau, T. Conte, Y. Xu, C. Weinhardt)

Negotiation for Cooperation in Logistic Networks - An Experimental Study, Group Decision and Negotiation, Springer, Netherlands, Vol. 19, No. 3, May 2010, pp. 211-226 (zusammen mit D. Rief; Vorversion erschienen auf der GDN-Konferenz)

Agent-based Simulation in Market Engineering - Bidding under Uncertainty, KI - Zeitschrift Künstliche Intelligenz, Rubrik “Zusammenfassung von KI-Dissertationen”, 2007, pp. 70-72 (unreferiert)

Management Decision Support using Long-Term Market Simulation, Journal of Information Systems and e-Business Management (ISeB), 1(4), 2003, pp. 405-423 (zusammen mit W. Fichtner, D. Veit und C. Weinhardt)


Energieinformatik 2011, Tagungsband. FZI Forschungszentrum Informatik, Karlsruhe. ISBN 978-3-00-036436-5 (gemeinsam mit Appelrath, H. J.; Weinhardt, C.; Dinther, C. v.; Filipova-Neumann, L.; Nieße, A.; Sonnenschein, M.)

Designing Service Value Networks – Coordination, Competition and Cooperation, Habilitationsschrift, Karlsruher Institut für Technologie, 2010

Adaptive Bidding in Single Sided Auctions under Uncertainty, Whitestein Series in Software Agent Technologies and Autonomic Computing, Birkhäuser, Basel, Boston, Berlin, 2007

CAME-Toolsuite meet2trade - auf dem Weg zum Computer Aided Market Engineering, Universitätsverlag Karlsruhe, Karlsruhe, Abschlussbericht des Projekts electronic Financial Trading, 2006 (zusammen mit C. Weinhardt, M. Grunenberg, K. Kolitz, M. Kunzelmann, J. Mäkiö, I. Weber, H. Weltzien)

Reviewed articles in books and conferences:

Kimbrough, S. O.; McElfresh, M.; van Dinther, Clemens (2018): On the Business Case of Merchant Solar. In: Proceedings of the 19th IEEE International Conference on Industrial Technology, Lyon, February 20-22, 2018, S. 1012–1018. Online verfügbar unter proceedings.ieee-ies.org/icit18/.

Bischoff, Bettina und Clemens van Dinther (2016): Workflow Management Systems – an analysis of current open source products, in Dieter Hertweck, Christian Decker (Hrsg.): Digital Enterprise Computing 2016, Lecture Notes in Informatics (LNI), Gesellschaft für Informatik, Bonn 2016

Renewable Energy for Electric Vehicles: Price Based Charging Coordination, 12th IAEE European Energy Conference, Venice, Italy (gemeinsam mit J. Richstein, A. Schuller, W. Ketter und C. Weinhardt)

Demand Response in Smart Grids: Opportunities for IS Research, eingereicht bei der AMCIS 2012, (gemeinsam mit Jens Strüker)

Benchmarking Electric Vehicle Charging Control Strategies. Proceedings of the 2012 Innovative Smart Grid Technologies, Washington, 2012 (gemeinsam mit A. Schuller, und J. Ilg)

Personality Traits, Feedback Mechanisms and their Impact on Motivation to Contribute to Wikis in Higher Education, als Poster angenommen bei The International Symposium on Wikis and Open Collaboration 2011 (WikiSym), Mountain View, October 2011 (gemeinsam mit A. Mazarakis)

Motivation durch Feedbackmechanismen in Vorlesungswikis – Welche versprechen mehr Wirkung? Angenommen bei der Konferenz DeLFI 2011, September, Dresden (zusammen mit A. Mazarakis)

Motivationssteigerung in Wikis durch systemneutrales Feedback. angenommen bei der Konferenz Mensch&Computer, Chemnitz, 2011 (zusammen mit A. Mazarakis)

Designing Auctions for Coordination in Service Networks. in: The Science of Service Systems (Demirkan, H.; Spohrer, J. C.; Krishna, V., eds.), Springer Series: Service Science: Research and Innovations in the Service Economy, March 2011, ISBN: 978-1-4419-8269-8 (zusammen mit B. Blau, T. Conte, C. Weinhardt,)

Managing the Quality of Modular Services – a Process-Oriented Aggregation of Expected Service Levels Based on Probability Distributions, Proceedings of the 12th IEEE Conference on Commerce and Enterprise Computing, Shanghai, 2010 (zusammen mit R. Knapper., B. Blau, C. Conte, A. Anandasivam)

Innovation Assessment via Enterprise Information Markets. Proceedings of the 1st International Conference on IT-enabled Innovation in Enterprise, Athen, 2010 (zusammen mit S. Stathel, F. Teschner, T. Kullnig, T. Kranz, C. Weinhardt)

Robustness of Scheduling Algorithms for Distributed Storage Systems. Proceedings of the Multikonferenz Wirtschaftsinformatik (MKWI), Göttingen, 2010 (zusammen mit K.-H. Ahlert)

Annotieren von Bildschirmfotos zur Steigerung der Anwenderbeteiligung, 9. Konferenz Mensch und Computer, Berlin, 2009, pp. 193-202 (zusammen mit A. Rashid)

Open, Clocked And Multimodal Transport Networks, Volatile and Fragile Supply Chains, Logistics Research Network Conference 2009 (LRN), Cardiff, pp. 840-848 (zusammen mit A. Oelbermann, H. Breier)

Enabling Service Networks Through Contribution-Based Value Distribution, 15th Americas Conference on Information Systems, San Francisco, 2009, Paper 764 (zusammen mit T. Conte, B. Blau, G. Satzger)

Service Value Networks. In Proceedings of the 11th IEEE Conference on Commerce and Enterprise Computing, Vienna, 2009, pp. 194-201 (zusammen mit B. Blau, J. Krämer, T. Conte)

Coordinating Value Generation in Service Networks, 17th European Conference on Information Systems, Verona, 2009 (zusammen mit B. Blau, T. Conte; als Vortrag angenommen)

Sensitivity Analysis of the Economic Benefits from Electricity Storage at the End Consumer Level, Proceedings of the IEEE conference PowerTech 2009, Bucharest, published on CD, Paper 687 (zusammen mit K.-H. Ahlert)
Basil Papadias Award (Best Student Paper Award für K.-H. Ahlert)

Strategic Behavior in Service Networks under Price and Service Level Competition, 9. Internationale Tagung Wirtschaftsinformatik 2009, Wien, Band 1, pp. 599-608 (zusammen mit B. Blau, T. Conte)

Estimating economic benefits of electricity storage at the end consumer level, 9. Internationale Tagung Wirtschaftsinformatik 2009, Wien, Band 2, pp. 665-674 (zusammen mit K.-H. Ahlert)

Service Innovation with Information Markets, 9. Internationale Tagung Wirtschaftsinformatik 2009, Wien, Band 1, pp. 825-834 (zusammen mit S. Stathel, A. Schönfeld)

Definition of an Optimization Model for Scheduling Electricity Storage Devices. In Web 2008 - 7th Workshop on e-Business, Paris (zusammen K.-H. Ahlert)

Auctions for Service Brokerage in Business Value Networks, Proceedings of the GDN 2008, Coimbra, pp. 43-44 (zusammen C. Holtmann, T. Setzer, A. Stage, S. Stathel)

Incentives and control for information revelation - an empirical study, Proceedings of the GDN 2008, Coimbra, pp. 41-42 (zusammen mit T. Conte, G. Baust)

Offene getaktete robuste multimodale Dienstleistungsnetze. 13. Magdeburger Logistiktagung, 2008, pp. 73-92 (zusammen mit C. Cardeneo, K. Furmans, C. Weinhardt)

Agent-based Simulation for Research in Economics, Handbook of Finance, 2007, pp. 421-442

Collaborative Smart Items, INFORMATIK 2007 – Informatik trifft Logistik, GI Proceedings 110, Band 2,Bremen, pp. 221-226 (zusammen mit C. Decker, J. Müller, M. Schleyer, E. Peev)

Negotiation for Cooperation in Logistic Networks - An Experimental Study, Proceedings of the GDN 2007, Volume II, Montreal, pp. 293-306 (zusammen mit D. Rief)
Best Student Paper Award

meet2trade: A generic electronic trading platform, Proceedings of the 4th Workshop on e-Business (WEB 2005), Las Vegas, USA (zusammen mit C. Weinhardt, K. Kolitz, J. Mäkiö, I. Weber)

Simulation for Evaluating Electronic Markets – An Agent-based Environment, IEEE Workshop Proceedings of the International Symposium on Applications and the Internet (SAINT 2005), pp. 392-395

Simulation of Ending Rules in Online Auctions, Proceedings of The Eleventh Research Symposium on Emerging Electronic Markets (RSEEM 2004), pp. 97-106 (zusammen mit I. Weber, C. Weinhardt)

Integrating Electronic Market Models – Problems and Solution of Parallel Markets, Proceedings of the 10th Research Symposium on Emerging Electronic Markets (RSEEM 2003), pp. 93-104 (zusammen mit K. Kolitz, J. Mäkiö, I. Weber, C. Weinhardt)

Automated Bidding Strategy Adaption using Learning Agents in Many-to-Many e-Markets, Poster Proceedings of the Workshop on Agent Mediated Electronic Commerce V (AMEC-V), held AAMAS), Melbourne, 2003 (zusammen mit D. Veit)

Other articles:

F. Bomarius; G. Brunekreeft; H. Frey; B. Heinlein; H. Hubschneider; B. Jahn; van Dinther, Clemens et al. (2018): Künstliche Intelligenz aus der Sicht von Energie und Klima. Hg. v. Bundesverband der Deutschen Industrie e.V. Berlin (Positionspapier BDI Internet der Energie). Online verfügbar unter bdi.eu/publikation/news/internet-der-energie-kuenstlicheintelligenz-aus-der-sicht-von-energie-und-klima/. Seiten: 15

van Dinther, B. Fey, S. Renelt, J. Strüker, C. Flath, O. Terzidis und P. Brettschneider: Die 10 Punkte Agenda der Bundesregierung zur Energiewende – eine Reflektion anhand von fünf Prinzipien, Energiewirtschaftliche Tagesfragen (et), 03/2017

Boes, C. van Dinther, T. Heim, T. Keller, J. Meßmer, G. da Silva, H. Stoll, A. Weidlich: Klimafreundliches Pendeln in der Grenzregion Hochrhein, horizonte Nr. 49, Koordinierungsstelle für Forschung und Entwicklung, Mannheim, 2017, S. 32

C. van Dinther, P. Kleine-Möllhoff, S. Löbbe, H. Nebeling, G. Schullerus, B. Thomas, F. Truckenmüller, T. Zenner: Das Reutlinger Energiezentrum (REZ) – für die Energiewende gewappnet, horizonte Nr. 47, Koordinierungsstelle für Forschung und Entwicklung, Mannheim, 2016

Auf dem Weg zum Internet der Energie - Der Wettbewerb allein wird es nicht richten. Smart Grid. Paradigmenwechsel in Deutschland, BDI-Drucksache Nr. 450 Bundesverband der Deutschen Industrie e.V. (BDI), 05, 2011 (zusammen mit Kollegen des BDI-Arbeitskreises)

Service Procurement Auctions under Service Level Uncertainty. Abstract at the 18th Annual Frontiers in Service Conference 2009, Honolulu, USA (zusammen mit S. Haak, T. Conte)

Value co-creation by customers – Challenges in Web 2.0-based Business. Proceedings of the QUIS 11 (Stauss, B.; Brown, S. W.; Edvardsson, B.; Johnston, R., eds.), 2009, p. 52 (zusammen mit T. Conte, C. Holtmann, M. Umfahrer)

Information Efficiency and Liquidity in Information Markets - A market maker based approach, Third Workshop on Prediction Markets, ACM Conference on Electronic Commerce 2008, Chicago, USA (zusammen mit S. Stathel, S. Luckner)

Internet der Energie - IKT für die Energiemärkte der Zukunft, BDI-Drucksache Nr. 418 Bundesverband der Deutschen Industrie e.V. (BDI), 12, 2008 (zusammen mit Kollegen des BDI-Arbeitskreises)

Some strategic considerations on open service/logistics networks, Accepted Abstract, INFORMS Annual Meeting 2008, Washington D.C. (zusammen mit M. Schleyer)

Design of Warehouses under the Constraint of On-Time Order Fulfillment, Accepted Abstract, INFORMS Annual Meeting 2008, Washington D.C. (zusammen mit M. Schleyer)

Value Webs Evaluation and Pricing in Service Networks, Accepted Abstract at the Frontiers in Service Conference, Washington DC, October 2-5, 2008 (zusammen mit T. Conte, B. Blau, C. Weinhardt, S. Lamparter, C. Holtmann)

State of the Art in Service Modeling Languages, Technical Report, Universität Karlsruhe (TH),2007, zusammen mit B. Blau, M. Behrendt

Adaptive Bidding in Auctions under Uncertainty – An Agent-based Approach in Market Engineering, accepted abstract, INFORMS Annual Meeting 2007, Seattle

Energiemärkte der Zukunft, White Paper, 2006 (zusammen mit A. Weidlich, C. Block)

Mobiles Diktieren im Krankenhaus – Neue Wege mit mobiler IT (Teil 1+2), Krankenhaus IT-Journal, Ausgabe 01 und 02/2006, Antares Computerverlag, Dietzenbach, 2006 (zusammen mit A. Rashid, C. Holtmann)

Towards integrated parallel Markets - A Solution Approach to the Order Allocation Problem, Discussion Paper, Universität Karlsruhe (TH), 2002, zusammen mit K. Kolitz, J. Mäkiö, I. Weber and C. Weinhardt

ExpSoft in Java – Ein Programmpaket für internetunterstützte experimentelle Spiele, Working Paper in: "Game Theory and Experimental Economics" (12), Institut für Statistik und Mathematische Wirtschaftstheorie, Universität Karlsruhe (TH), 2000, zusammen mit Holländer, Wünstel, Ostmann

APLIGAME - Ein Programmpaket für Experimentelle Spiele, Working Paper in: "Game Theory and Experimental Economics" (9), Institut für Statistik und Mathematische Wirtschaftsforschung. Universität Karlsruhe (TH), 1998, zusammen mit A. Ostmann, K. Planta


Gerald Blessing

Dr. Gerald BlessingResearch Team Digitisation and Management

ESB profile page

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Room 011
Phone +49 7121 271- 1432
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Research Topics
  • Digital Marketing  (Internet of Things, Social Selling)
  • Quantitative methods of marketing
  • Customer Experience
  • Sales Management
  • 2015-2018: Goethe Universität Frankfurt, wissenschaftlicher Mitarbeiter am Marketing-Department
  • 2017-2019: Frankfurt School of Finance, Lehrbeauftragter
  • 2018: Promotion dr.rer.pol. (summa cum laude)
  • 1999-2013: Deutsche Telekom AG, leitender Angestellter im Bereich Vertrieb und Marketing
  • 1997-1999: Motorola Inc.: Director of Distribution EMEA
  • 1987-1996: Robert Bosch GmbH, zuletzt Leiter Produktbereich Funktechnik

Blessing, G.; Kühnl, C. (2020): Customer Experience in the Internet of Things, Marketin Review St. Gallen, (1), 30-37.

Blessing, G.; Natter, M. (2019): Do Mystery Shoppers Really Predict Customer Satisfaction and Sales Performance?, Journal of Retailing, 3, 47-62..

Florian Grimm

Florian Grimm, M.Sc.Research team Digitization and Management

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Building 5
Room 011
Phone +49 7121 271 1498
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Areas of Responsibilty

Research assistant in the research team Digitization and Management

Current Research Projects


Daniel Kiefer

Daniel Kiefer, M.Sc.Research team Digitization and Management

Office Hours: By arrangement

ESB profile page
LinkedIn profile page
Xing profile page

Building 5
Room 011
Phone +49 7121 271 1466
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Areas of Responsibilty

Research assistant in the research team Digitization and Management

Research Topics
  • Artificial Intelligence
  • Machine learning
  • Deep Learning
  • Digitization & Management
  • Industry 4.0
Current Research Projects

Professional Experience

  • Science & Research, ESB Business School
  • Management Consulting, Barkawi Management Consultants
  • Management Consulting, goetzpartners
  • Private Equity, CAPCELLENCE
  • Lean Management Consulting, STAUFEN.SHANGHAI
  • Management Consulting, TARGUS Management Consulting
  • SYNCHRO Inhouse Consulting, TRUMPF North America
  • Inhouse Consulting, Carl Zeiss Vision

Academic Education

  • PhD Candidate, Artificial Intelligence, Karlsruhe Institute of Technology (KIT)
  • Operations Management (M. Sc.), ESB Business School
  • Business & Entrepreneurship, Cambridge Judge Business School
  • Computer Science & Business Administration ,University Bologna
  • Maschinenbau – Wirtschaft und Management (B. Eng.), Aalen University


  • Studienstiftung des deutschen Volkes
  • Elevate VDI – Verein Deutscher Ingenieure
  • DAAD - Deutscher Akademischer Austauschdienst
  • McKinsey Firsthand Program
  • BCG Emerald Talent Program
  • Kiefer, D., Ulmer, A. & Dinther, C. van. (2019). Application of Artificial Intelligence to optimize forecasting capability in procurement. In U. Kloos, N. Martinez, & G. Tullius (Hrsg.), Wissenschaftliche Vertiefungskonferenz. Tagungsband 2019 (1. Aufl., S. 69–80). Reutlingen: Reutlingen University. doi: https://doi.org/10.5281/zenodo.3539397
  • Eberl, A., Fallert, B., Kiefer, D., Leuschner, D., Mastroianni, L., Richter, P., . . . Palm, D. (2018). Methoden zur Sofortpreis-kalkulation von CNC-Drehteilen. ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb, 113(12), 835–839. doi.org/10.3139/104.112020


Management Consultant & PhD Candidate in Machine Learning

4flow AG, Berlin