Call for Papers: Special Issue 2/2021 – Machine Learning – Die Unternehmung/Swiss Journal of Business Research and Practice
Machine Learning Methods as Components of Existing Business Models
Machine learning and artificial intelligence have lately been hotly debated topics. This is reflected in substantial public attention, increased consideration in both business and economics research, and also in the aspirations of career starters.
The underlying methods were often developed decades ago and further refined over time. However, the pace of innovation in this area has greatly increased in recent years as a result of significant resources being dedicated to the issue, within and beyond academia, vast data sources, and equally vast computing capacities. Spectacular successes have been presented to the general public, such as IBM's Watson, Google's AlphaGo, or self-driving cars. Strategic plans for artificial intelligence formulated by major governments and industry leaders further emphasize that this is a trend that is here to stay.
It is foreseeable that these new technologies will fundamentally change existing business models. This includes fully automated customer communication for tasks such as address changes, enquiries, and changes to contractual conditions. In the near future, insurance companies could settle claims automatically, based entirely on descriptions and images. Only a few years from now, audit firms could have a wide range of manually performed tasks carried out by computer programs. There are already many applications in production processes and supply chain management.
This development has the potential to fundamentally reorganize market competition and the position of stakeholders in companies. However, the full extent of this transition and the widespread dissemination of machine learning applications into business models are still developing. Digital business models are still being designed and many organizations are currently developing the necessary know-how. In some cases, however, regulatory hurdles stand in the way. The interpretability of machine learning methods continues to represent an obstacle to trust in automated decision-making processes.
This special issue is therefore dedicated to the question of which business applications of machine learning methods are already being implemented successfully, and which applications can be expected in the near future. The issue is thus aimed at researchers who wish to provide practical insights into their current work in this field. This includes both empirical and conceptual/theoretical contributions. Furthermore, the special issue welcomes contributions on the effects of machine learning technologies on organizations and their stakeholders.
Submission deadline: August 31, 2020
Manuscripts can be submitted either in English or German. Please submit your paper by email (doc or PDF-file) to the guest editors of the special issue. For further information and questions, please contact the guest editors.
Guest Editor Contacts:
Dr. Johannes Kriebel (University of Münster) - Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!
Prof. Dr. Andreas Pfingsten (University of Münster) - Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!

Call for Papers: BFGA 2020



October 22-23, 2020


Rauischholzhausen Castle, near Marburg, Germany


The Justus Liebig University Giessen in conjunction with the GGS invite academics and PhD students to submit papers for consideration of presentation at the 2nd Conference on Behavioral Research in Finance, Governance, and Accounting (BFGA 2020). The conference will be held at the Rauischholzhausen Castle near Marburg.

Accepted papers will be considered for two Best Paper Awards.

The keynote speech will be given by Prof Steffen Andersen (Professor of Finance at Copenhagen Business School).


For more information visit:


Call For Papers
5th SDU Finance Workshop

June 11th 2020, University of Southern Denmark, Odense, Denmark

The finance group at the Department of Business and Economics of the University of Southern Denmark is pleased to announce the 5th SDU finance workshop. We invite submission in all areas of finance. This will be a one-day workshop with a small number of papers on the program in order to allow for ample time for discussions and to create a stimulating environment. Each paper will be reviewed twice for conference admission and have a discussant.

CONFERENCE DATE: June 11, 2020


KEYNOTE SPEAKER: Sascha Steffen from Frankfurt School of Finance & Management.

PAPER SUBMISSION PROCEDURE: Please submit the full paper or an extended abstract by March 22, 2020. The submission fee is 250 DKK per author (approx. 34 EUR). There is no participation fee and the workshop concludes with a conference dinner for all conference contributors (presenters and discussants).

Author notification will be given in early April. Participants are expected to cover their own travel and accommodation expenses. For more information, please contact Christian Riis Flor by email Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!.

ORGANIZING COMMITTEE: Christian Riis Flor, Steffen Meyer, and Alexander Schandlbauer.

PAST PROGRAMS: Information about past programs is available at:



27th Annual Meeting of the German Finance Association (DGF)


We cordially invite you to participate in the 27th Annual Meeting of the German Finance Association (DGF) held at University of Innsbruck on October 02-03, 2020. A doctoral workshop will take place on October 01, 2020.

The conference aims to bring together researchers and practitioners in order to discuss the latest theoretical and empirical results from all areas of finance, banking and insurance. Campbell R. Harvey, Professor of Finance at the Fuqua School of Business, Duke University, will deliver the keynote speech of the conference.

Submissions of papers for the conference is possible until April 30, 2020 (midnight CET).

For more information (paper submission, doctoral seminar, conference registration, etc.) please visit

We look forward to meeting you for an exciting conference in the heart of the Alps, Innsbruck.


Market Microstructure Database Xetra

Der Lehrstuhl für Finanzierung der Universität Mannheim hat gemeinsam mit dem Center for Financial Studies in Kooperation mit der Deutschen Börse AG und gefördert durch die DFG eine Microstructure-Datenbank erstellt, die tägliche Daten aus Xetra für alle im CDAX enthaltenen Aktien und den Zeitraum 1999 bis 2013 enthält. Zu den enthaltenen Variablen gehören etwa quotierte und effektive Geld-Brief-Spannen und viele andere. Diese Datenbank ist für Forscher und ausschliesslich für Forschungszwecke kostenlos verfügbar, wobei aber ein formelles Prozedere einzuhalten ist. Das zum Download bereitgestellte pdf-Dokument enthält nähere Informationen.



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