Implikationen einer wertorientierten Unternehmensführung für Standortplanungsentscheidungen - Fiedler, Moritz (Aktuelle Fragestellungen zu Produktion, Logistik und Controlling)

Betriebliche Standortplanung international agierender Unternehmen - Osthoff, Lennart (Aktuelle Fragestellungen zu Produktion, Logistik und Controlling)

Kategorisierungsmöglichkeiten für die Erzeugung von Dienstleistungen - Opitz, Oliver (Aktuelle Fragestellungen zu Produktion, Logistik und Controlling)

Entscheidungsunterstützung durch das Controlling mittels Reporting Design - Faupel, Christian (Aktuelle Fragestellungen zu Produktion, Logistik und Controlling)

Aktuelle Fragestellungen zu Produktion, Controlling und Logistik

Strom statt Gas: Nachhaltige Herstellung von Karosseriebauteilen - Pfeifer, Florian; Jungeilges, André; Behm, Jonathan (Transforming Economies)

Process Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing - Löhr, Bernd; Brennig, Katharina; Bartelheimer, Christian; Beverungen, Daniel; Müller, Oliver (International Conference on Business Process Management)
Existing process mining methods are primarily designed for processes that have reached a high degree of digitalization and standardization. In contrast, the literature has only begun to discuss how process mining can be applied to knowledge-intensive processes—such as product innovation processes—that involve creative activities, require organizational flexibility, depend on single actors’ decision autonomy, and target process-external goals such as customer satisfaction. Due to these differences, existing Process Mining methods cannot be applied out-of-the-box to analyze knowledge-intensive processes. In this paper, we employ Action Design Research (ADR) to design and evaluate a process mining approach for knowledge-intensive processes. More specifically, we draw on the two processes of product innovation and engineer-to-order in manufacturing contexts. We collected data from 27 interviews and conducted 49 workshops to evaluate our IT artifact at different stages in the ADR process. From a theoretical perspective, we contribute five design principles and a conceptual artifact that prescribe how process mining ought to be designed for knowledge-intensive processes in manufacturing. From a managerial perspective, we demonstrate how enacting these principles enables their application in practice.

(How) do advanced data and analyses enable HR analytics success? A neo-configurational analysis - Strohmeier, Stefan; Collet, Julian; Kabst, Rüdiger (Baltic Journal of Management)
Purpose Enabled by increased (“big”) data stocks and advanced (“machine learning”) analyses, the concept of human resource analytics (HRA) is expected to systematically improve decisions in human resource management (HRM). Since so far empirical evidence on this is, however, lacking, the authors' study examines which combinations of data and analyses are employed and which combinations deliver on the promise of improved decision quality. Design/methodology/approach Theoretically, the paper employs a neo-configurational approach for founding and conceptualizing HRA. Methodically, based on a sample of German organizations, two varieties (crisp set and multi-value) of qualitative comparative analysis (QCA) are employed to identify combinations of data and analyses sufficient and necessary for HRA success. Findings The authors' study identifies existing configurations of data and analyses in HRM and uncovers which of these configurations cause improved decision quality. By evidencing that and which combinations of data and analyses conjuncturally cause decision quality, the authors' study provides a first confirmation of HRA success. Research limitations/implications Major limitations refer to the cross-sectional and national sample and the usage of subjective measures. Major implications are the suitability of neo-configurational approaches for future research on HRA, while deeper conceptualizing and researching both the characteristics and outcomes of HRA constitutes a core future task. Originality/value The authors' paper employs an innovative theoretical-methodical approach to explain and analyze conditions that conjuncturally cause decision quality therewith offering much needed empirical evidence on HRA success.
Keywords: Management of Technology and Innovation; Marketing; Organizational Behavior and Human Resource Management; Strategy and Management; Business and International Management

Like It or not: When corporate social responsibility does not attract potential applicants - Jakob, Eva Alexandra; Steinmetz, Holger; Wehner, Marius; Engelhardt, Christina; Kabst, Rüdiger (Journal of Business Ethics)

The case of Mesut Özil: A symbol of (non-) integration? An analysis of German print media discourses on integration - Schmidt, Eva (Discourse & Communication)

Die Erde und die Welt. Wie wir Hannah Arendt in Anthropozän lesen können - Robaszkiewicz, Maria Anna (Anfangen! Politik im Anthropozän. Beiträge der 24. Hannah Arendt Tage 2021)

Georg Brunn/Claus Beisbard [Hg.], Mit Philosophie die Welt verändern, Basel: Schwabe Verlag 2020 - Robaszkiewicz, Maria Anna (Zeitschrift für Didaktik der Philosophie und Ethik)

The broken chain: Evidence against emotionally driven upstream indirect reciprocity - Schnedler, Wendelin (Games and Economic Behavior)
Psychologists claim that being treated kindly puts individuals in a positive emotional state: they then treat an unrelated third party more kindly. Numerous experiments document that subjects indeed ‘pay forward’ specific behavior. For example, they are less generous after having experienced stinginess. This, however, is not necessarily driven by emotions. Subjects may also imitate what they regard as socially adequate behavior. Here, I present an experiment in which imitation is not possible at the next opportunity to act with a stranger: after being given either a fun or an annoying job, subjects have to decide whether to be generous or not. I find that although subjects who are given the annoying job report more negative emotions than those with the fun job, they do not treat an unrelated third person more unkindly in terms of passing on less money.
Keywords: Economics and Econometrics; Finance

Shortcut Learning in Financial Text Mining: Exposing the Overly Optimistic Performance Estimates of Text Classification Models under Distribution Shift - Caron, Matthew (2022 IEEE International Conference on Big Data (Big Data))
In recent years, many cases of deep neural networks failing dramatically when faced with adversarial or real-world examples have been reported. Such failures, which are quite hard to detect, are often related to a generalization problem known as shortcut learning. Yet, with state-of-the-art transformer models now being ubiquitous in financial text mining, one cannot help but wonder how reliable the results conveyed in the ever-growing literature genuinely are. Against this background, we expose, in this work, how vulnerable contemporary financial text mining approaches are to shortcut learning. Focussing on the common learning task of financial sentiment classification, we assess, using two entity-based sampling strategies and our publicly-available dataset, the discrepancies between i.i.d. and o.o.d. performance estimates of four transformer models. Our results reveal that o.o.d. performance estimates are consistently weaker than those of their i.i.d. counterparts, with the error rate increasing by as much as 29.7%, thus, demonstrating how this issue can, when overlooked, lead to misleading evaluations. Moreover, we show how additional preprocessing steps, such as entity removal and vocabulary filtering, can help reduce the effects of shortcut learning by filtering out entity-related linguistic cues.

Towards Automated Moderation: Enabling Toxic Language Detection with Transfer Learning and Attention-Based Models - Caron, Matthew; Bäumer, Frederik S.; Müller, Oliver (55th Hawaii International Conference on System Sciences (HICSS))
Our world is more connected than ever before. Sadly, however, this highly connected world has made it easier to bully, insult, and propagate hate speech on the cyberspace. Even though researchers and companies alike have started investigating this real-world problem, the question remains as to why users are increasingly being exposed to hate and discrimination online. In fact, the noticeable and persistent increase in harmful language on social media platforms indicates that the situation is, actually, only getting worse. Hence, in this work, we show that contemporary ML methods can help tackle this challenge in an accurate and cost-effective manner. Our experiments demonstrate that a universal approach combining transfer learning methods and state-of-the-art Transformer architectures can trigger the efficient development of toxic language detection models. Consequently, with this universal approach, we provide platform providers with a simplistic approach capable of enabling the automated moderation of user-generated content, and as a result, hope to contribute to making the web a safer place.

Commentaries on Relationship Marketing: The Present and Future of Customer Relationships in Services - Steinhoff, Lena; Palmatier, R. W.; Martin, K. D.; Fox, G.; Henderson, C. M.; Saint Clair, J. K.; Yan, S.; Lee, J.-Y.; Perko, T.; Harmeling, C. M. (Journal of Service Management Research)

The Role of Self-Rewarding Behavior in Cashback Loyalty Programs - Becker, M.; Wiegand, N.; Steinhoff, Lena; Baidina, K. (Proceedings of the 51st European Marketing Academy (EMAC) Conference, Budapest.)

Datenbanken - Weber, Jutta (Feministische Studien)

Transfer Pricing Rules for Intangibles: Implementation and Practical Challenges - Safaei, Reyhaneh

Changes in Transfer Pricing Regulations and Corporate Investment Decisions - Shabestari, Mehrzad Azmi; Safaei, Reyhaneh