Organisation profile

EMPOWERING MINDS. INSPIRING INNOVATIONS. SHAPING TRANSFORMATIONS.

As part of Leuphana University, the School of Management and Technology is a dynamic and innovative community of students and faculty with high-level expertise in the fields of organization studies, responsible management, entrepreneurship, product development process, digital transformation and data science, and psychology and societal transformation. Our core aspiration is driving innovation in management and technology to shape responsible and sustainable transformations. In our research, we pioneer understandings of and solutions to the core challenges of our time, such as digitalization and sustainable production. In our teaching, we challenge conventional wisdom and inspire entrepreneurial thinking and responsible action. In business and society, we team up with local and international partners to contribute to the regional development of northern Germany. We value the interrelationships between disciplines, which is reflected in our interdisciplinary degree programs and collaboration in research.

 

The School of Management and Technology is home to the disciplines of Accounting and Finance, Business Psychology, Business Information Systems, Engineering, Management and Marketing. We support the respective identities and profile development of the disciplines, while also promoting interdisciplinary research and teaching in the shape of programs of study and research centers. This interdisciplinary approach is characterized by a commitment to responsibility and helping meet societal challenges.

Main research areas

The School of Management and Technology is the academic and professional home to 1,500 bachelor’s, master’s and doctoral students, more than 50 professors, more than 70 research associates and research assistants, 36 professional staff members.

The main themes of the school are reflected in its study programs: The 3 major and 7 minor programs at the College, 5 master's programs and 4 doctoral programs at the Graduate School provide academic training. The doctoral programs focus on (1.) Entrepreneurship, Management and Innovation (EMI), (2.) Information Systems and Data Science, (3.) Engineering and (4.) Management, Finance and Accounting.

In total, we offer 16 programs of study in the disciplines of Business Administration (in particular Accounting and Finance), Business Information Systems, Business Psychology, Engineering and Management.  

  1. Published

    Precious property or magnificent money? How money salience but not temperature priming affects first-offer anchors in economic transactions

    Leusch, Y. M., Loschelder, D. D. & Basso, F., 04.07.2018, In: Frontiers in Psychology. 9, JUL, 9 p., 1099.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  2. Published

    Precipitation Kinetics of AA6082: An Experimental and Numerical Investigation

    Herrnring, J., Kashaev, N. & Klusemann, B., 12.2018, In: Materials Science Forum. 941, p. 1411-1417 7 p.

    Research output: Journal contributionsConference article in journalResearchpeer-review

  3. Published

    Precision Denoising in Medical Imaging via Generative Adversarial Network-Aided Low-Noise Discriminator Technique

    Alanazi, T. M. & Mercorelli, P., 12.2024, In: Mathematics. 12, 23, 21 p., 3705.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  4. Published

    Predicate‐based model of problem‐solving for robotic actions planning

    Tsymbal, O., Mercorelli, P. & Sergiyenko, O., 01.12.2021, In: Mathematics. 9, 23, 13 p., 3044.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  5. Published

    Predicting academic success with the big 5 rated from different points of view: Self-rated, other rated and faked

    Ziegler, M., Danay, E., Schölmerich, F. & Bühner, M., 06.2010, In: European Journal of Personality. 24, 4, p. 341-355 15 p.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  6. Published

    Predicting expatriate job performance: Using the normative NEO-PI-R or the ipsative OPQ32i?

    Kusch, R. I., Deller, J. & Albrecht, A.-G., 01.06.2008, In: International Journal of Psychology. 43, 3-4, p. 57-57 1 p.

    Research output: Journal contributionsConference abstract in journalResearchpeer-review

  7. Published

    Predicting online user behavior based on Real-Time Advertising Data

    Stange, M. & Funk, B., 06.2016, Proceedings of the Twenty-Fourth Conference on Information Systems (ECIS) 2016. AIS eLibrary, 14 p. (Research Papers; no. 152).

    Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

  8. Published

    Predicting recurrent chat contact in a psychological intervention for the youth using natural language processing

    Hornstein, S., Scharfenberger, J., Lueken, U., Wundrack, R. & Hilbert, K., 12.2024, In: npj Digital Medicine. 7, 1, 9 p., 132.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  9. Published

    Predicting the Difficulty of Exercise Items for Dynamic Difficulty Adaptation in Adaptive Language Tutoring

    Pandarova, I., Schmidt, T., Hartig, J., Boubekki, A., Jones, R. D. & Brefeld, U., 15.08.2019, In: International Journal of Artificial Intelligence in Education. 29, 3, p. 342-367 26 p.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  10. Published

    Predicting the future performance of soccer players

    Arndt, C. & Brefeld, U., 01.10.2016, In: Statistical Analysis and Data Mining. 9, 5, p. 373-382 10 p.

    Research output: Journal contributionsJournal articlesResearchpeer-review