Distortional effects of separate accounting and formula apportionment on factor allocation - Ortmann, Regina; Pummerer, Erich (Journal of Business Economics)
Abstract We examine distortions caused by tax base allocation systems–separate accounting (SA) or formula apportionment (FA)–with respect to the allocation of assets and workforce within multinational entities (MNEs). The effects of both systems are intensively debated by EU Member States as they are striving to implement a European tax system. Its introduction would lead to a switch from SA to FA. Moreover, Pillar One of the recent global tax reform includes a mix of both tax base allocation systems. We find that, against the claims of the EU, FA does not necessarily create lower distortions of the factor allocation. Decisive for that assessment is the level of profit shifting under SA. Our results indicate that, in tendency, the factor allocation is more severely distorted by FA when the profit shifting possibilities were rather low under SA. In contrast to former studies, we highlight the importance of analyzing the status quo under the recently applied system (SA) in order to be able to assess the consequences of a switch from SA to FA. Our results are interesting for policy-makers as they help anticipating reactions of MNEs to a change in the applied tax base allocation system and for companies as a basis for future tax planning.
Keywords: Economics and Econometrics; Business and International Management

Distribution Network Optimization: Predicting computation times to design scenario analysis for network operators - Burmeister, Sascha Christian; Schryen, Guido (Energy Systems)

Do People Recover from Algorithm Aversion? An Experimental Study of Algorithm Aversion over Time - Leffrang, Dirk; Bösch, Kevin; Müller, Oliver (Hawaii International Conference on System Sciences)
Optimal decision making requires appropriate evaluation of advice. Recent literature reports that algorithm aversion reduces the effectiveness of predictive algorithms. However, it remains unclear how people recover from bad advice given by an otherwise good advisor. Previous work has focused on algorithm aversion at a single time point. We extend this work by examining successive decisions in a time series forecasting task using an online between-subjects experiment (N = 87). Our empirical results do not confirm algorithm aversion immediately after bad advice. The estimated effect suggests an increasing algorithm appreciation over time. Our work extends the current knowledge on algorithm aversion with insights into how weight on advice is adjusted over consecutive tasks. Since most forecasting tasks are not one-off decisions, this also has implications for practitioners.
Keywords: Algorithm aversion; Time series; Decision making; Advice taking; Forecasting

Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features - Halimeh, Haya; Caron, Matthew; Müller, Oliver (Hawaii International Conference on System Sciences)
Clinical depression is a serious mental disorder that poses challenges for both personal and public health. Millions of people struggle with depression each year, but for many, the disorder goes undiagnosed or untreated. Over the last decade, early depression detection on social media emerged as an interdisciplinary research field. However, there is still a gap in detecting hesitant, depression-susceptible individuals with minimal direct depressive signals at an early stage. We, therefore, take up this open point and leverage posts from Reddit to fill the addressed gap. Our results demonstrate the potential of contemporary Transformer architectures in yielding promising predictive capabilities for mental health research. Furthermore, we investigate the model’s interpretability using a surrogate and a topic modeling approach. Based on our findings, we consider this work as a further step towards developing a better understanding of mental eHealth and hope that our results can support the development of future technologies.
Keywords: Social Media and Healthcare Technology; early depression detection; liwc; mental health; transfer learning; transformer architectures

Emotional Debiasing Explanations for Decisions in HCI - Schütze, Christian; Lammert, Olesja; Richter, Birte; Thommes, Kirsten; Wrede, Britta (Artificial Intelligence in HCI)

Empirical Analysis in Markets for OTF Services - Elrich, Alina; Kaimann, Daniel; Fahr, René; Kundisch, Dennis; Mir Djawadi, Behnud; Müller, Michelle; Poniatowski, Martin; Schäfers, Sabrina; Frick, Bernd (On-The-Fly Computing -- Individualized IT-services in dynamic markets)

Employer Branding - Wie Arbeitgeber strategisch gegen den Arbeitskräftemangel vorgehen. - Schneider, Martin; Radermacher, Katharina (Die Politische Meinung)

Entwurfsmuster: Fachsensible wissenschaftliche Begleitung - Sloane, Hannah Sabrina; Heidebrecht, Jana

Erlebnisorientiert Lehren und Lernen in der beruflichen Bildung. Entwicklung eines didaktischen Konzepts im Rahmen von designbasierter Forschung. - Volgmann, Simone

Evaluation of product testing programs as an effective marketing tool - Negative and positive effects of rejections in product testing programs - Küpper, K.; Garnefeld, I.; Steinhoff, Lena