Losses Never Sleep - The Effect of Tax Loss Offset on Stock Market Returns during Economic Crises - Koch, Reinald; Holtmann, Svea; Giese, Henning

Marginal College Wage Premium under Selection into Employment - Westphal, Matthias; Kamhöfer, Daniel A.; Schmitz, Hendrik (Economic Journal)

May I have your attention, please? Analyzing the effects of attention screening mechanisms on crowdworking platforms - Laux, Florian; Poniatowski, Martin; Kundisch, Dennis

Methoden zum Design digitaler Plattformen, Geschäftsmodelle und Service-Ökosysteme - Robra-Bissantz, Susanne; Lattemann, Christoph; Laue, Ralf; Leonhard-Pfleger, Raphaela; Wagner, Luisa; Gerundt, Oliver; Schlimbach, Ricarda; Baumann, Sabine; Vorbohle, Christian; Gottschalk, Sebastian; Kundisch, Dennis; Engels, Gregor; et al. (HMD Praxis der Wirtschaftsinformatik)

Methodenverliebt am Markt vorbei? - Rebert, Tobias; Tomin, Slawa; Wach, Bernhard; Kabst, Rüdiger (Intrapreneurship)

Mit dem SREL-Training unternehmerische Selbstkompetenzen entwickeln - Büker, Ronja; Jenert, Tobias; Fust, Alexander Paul; Fahrbach, Manuel; Bellwald, Noah; Winkler, Christoph (Erziehung & Unterricht)

Modeling Business Models: A cross-disciplinary Analysis of Business Model Modeling Languages and Directions for Future Research - Szopinski, Daniel; Massa, Lorenzo; John, Thomas; Kundisch, Dennis; Tucci, Christopher (Communications of the Association for Information Systems)

Modelling artificial intelligence in economics - Gries, Thomas; Naudé, Wim (Journal for Labour Market Research)
Abstract We provide a partial equilibrium model wherein AI provides abilities combined with human skills to provide an aggregate intermediate service good. We use the model to find that the extent of automation through AI will be greater if (a) the economy is relatively abundant in sophisticated programs and machine abilities compared to human skills; (b) the economy hosts a relatively large number of AI-providing firms and experts; and (c) the task-specific productivity of AI services is relatively high compared to the task-specific productivity of general labor and labor skills. We also illustrate that the contribution of AI to aggregate productive labor service depends not only on the amount of AI services available but on the endogenous number of automated tasks, the relative productivity of standard and IT-related labor, and the substitutability of tasks. These determinants also affect the income distribution between the two kinds of labor. We derive several empirical implications and identify possible future extensions.
Keywords: General Medicine

Möglichkeiten und Grenzen der Messung, Kontrolle und Sicherung der Qualität logistischer Prozesse - Hrnjadovic, Damir (Aktuelle Fragestellungen zu Produktion, Logistik und Controlling)

Moment or Movement – An Empirical Analysis of the Heterogeneous Impact of Media Attention on Charitable Crowdfunding Campaigns - Seutter, Janina; Müller, Michelle; Müller, Stefanie Jutta Marianne; Kundisch, Dennis (Proceedings of the 55th Hawaii International Conference on System Sciences (HICSS))

Network Disruption and the Common-Enemy Effect - Hoyer, Britta; De Jaegher, Kris (International Journal of Game Theory)

Online Reviews in B2B Markets: A Qualitative Study of Underlying Motivations - Seutter, Janina (Proceedings of the 30th European Conference on Information Systems (ECIS))

Online Reviews in B2B Markets: A Qualitative Study on the Underlying Motives - Seutter, Janina

Overcoming Silos: A Review of Business Model Modeling Languages for Business Ecosystems - Vorbohle, Christian; Kundisch, Dennis (Proceedings of the 30th European Conference on Information Systems (ECIS))

Pay for Tax Certainty? Advance Tax Rulings for Risky Investment under Multi-Dimensional Tax Uncertainty - Chen, An; Hieber, Peter; Sureth-Sloane, Caren

Peer-To-Peer Rentals, Regulatory Policies, And Hosts’ Cost Pass-Throughs - Müller, Michelle; Neumann, Jürgen; Kundisch, Dennis (Journal of Management Information Systems)

Perception of Society’s Trust in Care Robots by Public Opinion Leaders - Hoppe, Julia Amelie; Melkas, Helinä; Pekkarinen, Satu; Tuisku, Outi; Hennala, Lea; Johansson-Pajala, Rose-Marie; Gustafsson, Christine; Thommes, Kirsten (International Journal of Human–Computer Interaction)
Keywords: Computer Science Applications; Human-Computer Interaction; Human Factors and Ergonomics

Perception of Society’s Trust in Care Robots by Public Opinion Leaders - Hoppe, Julia Amelie; Melkas, Helinä; Pekkarinen, Satu; Tuisku, Outi; Hennala, Lea; Johansson-Pajala, Rose-Marie; Gustafsson, Christine; Thommes, Kirsten (International Journal of Human–Computer Interaction)
Keywords: Computer Science Applications; Human-Computer Interaction; Human Factors and Ergonomics

Perception of Society’s Trust in Care Robots by Public Opinion Leaders - Hoppe, Julia Amelie; Melkas, Helinä; Pekkarinen, Satu; Tuisku, Outi; Hennala, Lea; Johansson-Pajala, Rose-Marie; Gustafsson, Christine; Thommes, Kirsten (International Journal of Human–Computer Interaction)
Keywords: Computer Science Applications; Human-Computer Interaction; Human Factors and Ergonomics

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.

Procrastination in the Looking Glass of Self-Awareness: Can Gamified Self-Monitoring Reduce Academic Procrastination? - Klingsiek, Katrin; John, Thomas; Kundisch, Dennis (die hochschullehre)

Regulierung der Vergütungspraxis hochrangiger Mitarbeiter im Finanzdienstleistungssektor. Anmerkung zu EuGH, Urt. v. 01.08.2022 - C-352/20 - Bartlitz, David (Europäische Zeitschrift für Wirtschaftsrecht (EuZW))

Risk allocation through securitization – Evidence from non-performing loans - Wengerek, Sascha Tobias; Hippert, Benjamin; Uhde, André (The Quarterly Review of Economics and Finance)
Employing a unique and hand-collected sample of 648 true sale loan securitization transactions issued by 57 stock-listed banks across the EU-12 plus Switzerland over the period from 1997 to 2010, this paper empirically analyzes the relationship between true sale loan securitization and the issuing banks’ non-performing loans to total assets ratios. Overall, we provide evidence for a negative impact of securitization on NPL exposures suggesting that banks predominantly used securitization as an instrument of credit risk transfer and diversification. In addition, the analysis at hand reveals a time-sensitive relationship between securitization and NPL exposures. While we observe an even stronger NPL-reducing effect through securitization during the non-crisis periods, the effect reverses during and after the global financial crisis suggesting that banks were forced to provide credit enhancement and employ securitization as a funding management tool. Along with the results from a variety of sensitivity analyses our study provides important implications for the recent debate on reducing NPL exposures of European banks by revitalizing the European securitization market.
Keywords: European Banking; Non-performing Loans; Securitization

Rollercoaster of Emotions – A Semantic Analysis of Fundraising Campaigns over the Course of the Covid-19 Pandemic - Grieger, Nicole; Seutter, Janina; Kundisch, Dennis (Tagungsband der 17. Internationalen Tagung Wirtschaftsinformatik 2022)

Same Different but not Same Same: Ethnic Discrimination in Application Procedures in the German Public Sector - Auer, Thorsten Fabian; Ekemen, Helin; Hagedorn, Carolin; Heise, Chantal; Rese, Christine (Empirical Economics Letters)
Regulations to prevent ethnic discrimination in accessing the labor market are implemented most thoroughly in the public sector. However, it remains to be assessed if these regulations are internalized. We conducted a field experiment to examine ethnic discrimination when applying for internships in German municipalities by unsolicited inquiries. We compared responses in German cities to Turkish, Italian, and German applicants in two periods, and find consistent disadvantages for the Turkish and Italian applicants as well as differences related to gender. Thus, the likelihood for ethnic discrimination rises when applying for positions in public institutions that are not subject to regulations.
Keywords: Ethnic Discrimination; Public Sector; Field Experiment; Application Procedure

Seizing the Opportunity for Automation—How Traffic Density Determines Truck Drivers' Use of Cruise Control - Hoffmann, Christin; Thommes, Kirsten (IEEE Transactions on Human-Machine Systems)
Keywords: Artificial Intelligence; Computer Networks and Communications; Computer Science Applications; Human-Computer Interaction; Signal Processing; Control and Systems Engineering; Human Factors and Ergonomics

Semiparametric GARCH models with long memory applied to Value at Risk and Expected Shortfall - Letmathe, Sebastian; Feng, Yuanhua; Uhde, André (Journal of Risk)
In this paper new semiparametric generalized autoregressive conditional heteroscedasticity (GARCH) models with long memory are introduced. A multiplicative decomposition of the volatility into a conditional component and an unconditional component is assumed. The estimation of the latter is carried out by means of a data-driven local polynomial smoother. According to the revised recommendations by the Basel Committee on Banking Supervision to measure market risk in the banks’ trading books, these new semiparametric GARCH models are applied to obtain rolling one-step ahead forecasts for the value-at-risk and expected shortfall (ES) for market risk assets. Standard regulatory traffic-light tests and a newly introduced traffic-light test for the ES are carried out for all models. In addition, model performance is assessed via a recently introduced model selection criterion. The practical relevance of our proposal is demonstrated by a comparative study. Our results indicate that semiparametric long-memory GARCH models are a meaningful substitute for their conventional, parametric counterparts.
Keywords: long memory; generalized autoregressive conditional heteroscedasticity (GARCH) models; value-at-risk (VaR); expected shortfall (ES); traffic-light test; backtesting

Semiparametric GARCH models with long memory applied to Value at Risk and Expected Shortfall - Letmathe, Sebastian; Feng, Yuanhua; Uhde, André (Journal of Risk)
In this paper new semiparametric GARCH models with long memory are in- troduced. The estimation of the nonparametric scale function is carried out by an adapted version of the SEMIFAR algorithm (Beran et al., 2002). Recurring on the revised recommendations by the Basel Committee to measure market risk in the banks' trading books (Basel Committee on Banking Supervision, 2013), the semi- parametric GARCH models are applied to obtain rolling one-step ahead forecasts for the Value at Risk (VaR) and Expected Shortfall (ES) for market risk assets. In addition, standard regulatory traffic light tests (Basel Committee on Banking Supervision, 1996) and a newly introduced traffic light test for the ES are carried out for all models. The practical relevance of our proposal is demonstrated by a comparative study. Our results indicate that semiparametric long memory GARCH models are an attractive alternative to their conventional, parametric counterparts.
Keywords: Semiparametric; long memory; GARCH models; forecasting; Value at Risk; Expected Shortfall; traffic light test; Basel Committee on Banking Supervision

Servitization in the manufacturing industry: Where do we stand? Where do we come from? - Akalan, R.; Böhm, Eva; Eggert, A. (Journal of Service Management Research)

Shifting ML value creation mechanisms: A process model of ML value creation - Shollo, Arisa; Hopf, Konstantin; Thiess, Tiemo; Müller, Oliver (The Journal of Strategic Information Systems)
Keywords: Information Systems and Management; Information Systems; Management Information Systems

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.

Should manufacturers publish online reviews in their own online shops? - Kessing, K.; Garnefeld, I.; Böhm, Eva (EMAC Annual Conference, Budapest, Hungary)

Since Albert and Whetten: the dissemination of Albert and Whetten’s conceptualization of organizational identity - Knorr, Karin; Hein-Pensel, Franziska (Management Review Quarterly)
Abstract Since the seminal work of Albert and Whetten, the organizational identity concept has become ubiquitous and highly relevant in various fields. This study systematically reviews how Albert and Whetten’s concept of organizational identity has been disseminated in different research areas. It employs quantitative (topic modeling) and qualitative text analysis, as well as a network analysis to examine a sample of 1,041 papers published between 1985 and mid-2022 that cite Albert and Whetten’s seminal work. Using this method of systematic literature analysis, the current study investigates the criteria of the basic definition and hypotheses mentioned in their work that contribute to its increasing significance, and those with the potential to become substantial aspects of future organizational identity research. Accordingly, Albert and Whetten’s conceptualization of organizational identity is often partially adopted in the literature. Thus, this study contributes to organizational identity research by unveiling further research questions on the evolving character of organizational identity, research methodology, and quantitative operationalization, on the basis of Albert and Whetten’s organizational identity conceptualization.
Keywords: Strategy and Management; Business; Management and Accounting (miscellaneous)

Smart cities and smart governance models for future cities - Nastjuk, I.; Trang, S.; Papageorgiou, E. (Electronic Markets)

Smart Service für die prädiktive Instandhaltung zentraler Komponenten des Mittelspannungs-Netzes - zur Heiden, Philipp; Priefer, Jennifer; Beverungen, Daniel (Forum Dienstleistungsmanagement)

Speaking of Performance: Evaluating Team Members’ Performance with Open-Ended Audio Comments - Gutt, Jana Kim; Thommes, Kirsten (Academy of Management Proceedings)
Keywords: Microbiology

Speaking of Performance: Evaluating Team Members’ Performance with Open-Ended Audio Comments - Gutt, Jana Kim; Thommes, Kirsten (Academy of Management Proceedings)
Keywords: Microbiology

Start-up-Gründung mit Schwierigkeiten - Bartlitz, David (Juristische Schulung (JuS))

Steuerliche Maßnahmen als Anreiz für Investitionen? - Sureth-Sloane, Caren (Die Presse)

Steuerpolitische Perspektiven der neuen Legislaturperiode - Chancen und Herausforderungen - Sureth-Sloane, Caren (FinanzRundschau)

Strategic emphasis on service-based business models during the corona crisis: Are customer solutions a curse or blessing for manufacturing firms? - Akalan, R.; Eggert, A.; Böhm, Eva (Journal of Service Management Research)

Strategische Erfolgsplanung für Produktinnovationen - Betz, Stefan (Aktuelle Fragestellungen zu Produktion, Controlling und Logistik)

Systematizing the lexicon of platforms in information systems: a data-driven study - Bartelheimer, Christian; zur Heiden, Philipp; Lüttenberg, Hedda; Beverungen, Daniel (Electronic Markets)
Abstract While the Information Systems (IS) discipline has researched digital platforms extensively, the body of knowledge appertaining to platforms still appears fragmented and lacking conceptual consistency. Based on automated text mining and unsupervised machine learning, we collect, analyze, and interpret the IS discipline’s comprehensive research on platforms—comprising 11,049 papers spanning 44 years of research activity. From a cluster analysis concerning platform concepts’ semantically most similar words, we identify six research streams on platforms, each with their own platform terms. Based on interpreting the identified concepts vis-à-vis the extant research and considering a temporal perspective on the concepts’ application, we present a lexicon of platform concepts, to guide further research on platforms in the IS discipline. Researchers and managers can build on our results to position their work appropriately, applying a specific theoretical perspective on platforms in isolation or combining multiple perspectives to study platform phenomena at a more abstract level.
Keywords: Management of Technology and Innovation; Marketing; Computer Science Applications; Economics and Econometrics; Business and International Management

Systematizing the lexicon of platforms in information systems: a data-driven study - Bartelheimer, Christian; zur Heiden, Philipp; Lüttenberg, Hedda; Beverungen, Daniel (Electronic Markets)
While the Information Systems (IS) discipline has researched digital platforms extensively, the body of knowledge appertaining to platforms still appears fragmented and lacking conceptual consistency. Based on automated text mining and unsupervised machine learning, we collect, analyze, and interpret the IS discipline’s comprehensive research on platforms—comprising 11,049 papers spanning 44 years of research activity. From a cluster analysis concerning platform concepts’ semantically most similar words, we identify six research streams on platforms, each with their own platform terms. Based on interpreting the identified concepts vis-à-vis the extant research and considering a temporal perspective on the concepts’ application, we present a lexicon of platform concepts, to guide further research on platforms in the IS discipline. Researchers and managers can build on our results to position their work appropriately, applying a specific theoretical perspective on platforms in isolation or combining multiple perspectives to study platform phenomena at a more abstract level.
Keywords: Platform; Text mining; Machine learning; Data communications; Interpretive research; Systems design and implementation

Tackling Crises Together? – An Econometric Analysis of Charitable Crowdfunding During the COVID-19 Pandemic - Althaus, Maike; Poniatowski, Martin; Kundisch, Dennis (Proceedings of the 43rd International Conference on Information Systems (ICIS))

Tackling Crises Together? - An Econometric Analysis of Charitable Crowdfunding During the COVID-19 Pandemic - Althaus, Maike; Poniatowski, Martin; Kundisch, Dennis

Tackling the Accuracy–Interpretability Trade-off: Interpretable Deep Learning Models for Satellite Image-based Real Estate Appraisal - Kucklick, Jan-Peter; Müller, Oliver (ACM Transactions on Management Information Systems)
Deep learning models fuel many modern decision support systems, because they typically provide high predictive performance. Among other domains, deep learning is used in real-estate appraisal, where it allows to extend the analysis from hard facts only (e.g., size, age) to also consider more implicit information about the location or appearance of houses in the form of image data. However, one downside of deep learning models is their intransparent mechanic of decision making, which leads to a trade-off between accuracy and interpretability. This limits their applicability for tasks where a justification of the decision is necessary. Therefore, in this paper, we first combine different perspectives on interpretability into a multi-dimensional framework for a socio-technical perspective on explainable artificial intelligence. Second, we measure the performance gains of using multi-view deep learning which leverages additional image data (satellite images) for real estate appraisal. Third, we propose and test a novel post-hoc explainability method called Grad-Ram. This modified version of Grad-Cam mitigates the intransparency of convolutional neural networks (CNNs) for predicting continuous outcome variables. With this, we try to reduce the accuracy-interpretability trade-off of multi-view deep learning models. Our proposed network architecture outperforms traditional hedonic regression models by 34% in terms of MAE. Furthermore, we find that the used satellite images are the second most important predictor after square feet in our model and that the network learns interpretable patterns about the neighborhood structure and density.
Keywords: Interpretability; Convolutional Neural Network; Accuracy-Interpretability Trade-Of; Real Estate Appraisal; Hedonic Pricing; Grad-Ram

Tax Avoidance and Vertical Interlocks within Multinational Enterprises - Giese, Henning; Koch, Reinald; Gamm, Markus

Tax Misperception and Its Effects on Decision Making - Literature Review and Behavioral Taxpayer Response Model - Blaufus, Kay; Chirvi, Malte; Huber, Hans-Peter; Maiterth, Ralf; Sureth-Sloane, Caren (European Accounting Review)
Previous accounting research shows that taxes affect decision making by individuals and firms. Most studies assume that agents have an accurate perception regarding their tax burden. However, there is a growing body of literature analyzing whether taxes are indeed perceived correctly. We review 128 studies on the measurement of tax misperception and its behavioral implications. The review reveals that many taxpayers have substantial tax misperceptions that lead to biased decision making. We develop a Behavioral Taxpayer Response Model on the impact of provided tax information on tax perception. Besides individual traits, characteristics of the tax information and the decision environment determine the extent of tax misperception. We discuss opportunities for future research and methodological limitations. While there is much evidence on tax misperception at the individual level, we hardly find any research at the firm level. Little is known about the real effects of managers’ tax misperception and on how tax information is strategically managed to impact stakeholders. This research gap is surprising as a large part of the accounting literature analyzes decision making and disclosure of firms. We recommend a mixed-method approach combining experiments, surveys, and archival data analyses to improve the knowledge on tax misperception and its consequences.

The “black box” of social commerce platforms-a closer look at users’ activities - Meydani, Elnaz; Düsing, Christoph; Fedrau, Annamaria; Trier, Matthias

The ambivalent role of monetary sales incentives in service innovation selling - Alavi, Sascha; Böhm, Eva; Habel, Johannes; Wieseke, Jan; Schmitz, Christian; Brüggemann, Felix (Journal of Product Innovation Management)
Keywords: Management of Technology and Innovation; Strategy and Management

The Black Box of Social Commerce Platforms - A Closer Look at Users’ Activities - Meydani, Elnaz; Düsing, Christoph; Trier, Matthias (Wirtschaftsinformatik 2022 Proceedings)

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

The dark triad and corporate sustainability: An empirical analysis of personality traits of middle managers - Pelster, Matthias; Schaltegger, Stefan (Business Ethics, the Environment & Responsibility)

The Impact of Product Differentiation on Retail Bundling in a Vertical Market - Endres-Fröhlich, Angelika Elfriede; Hehenkamp, Burkhard; Heinzel, Joachim
We study the effects of product differentiation on the bundling incentives of a two-product retailer. Two monopolistic manufacturers each produce a differentiated good. One sells it to both retailers, while the other only supplies a single retailer. Retailers compete in prices. Retail bundling is profitable when the goods are close substitutes. Only then is competition so intense that the retailer uses bundling to relax competition both within and across product markets, despite an aggravation of the double marginalization problem. Our asymmetric market structure arises endogenously for the case of close substitutes. In this case, bundling reduces social welfare.
Keywords: Retail bundling; upstream market power; double marginalization; product differentiation

The Market for Belief Systems: A Formal Model of Ideological Choice - Gries, Thomas; Müller, Veronika; Jost, John T. (Psychological Inquiry)
Keywords: General Psychology

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.)

The smoots Package in R for Semiparametric Modeling of Trend Stationary Time Series - Feng, Yuanhua; Gries, Thomas; Letmathe, Sebastian; Schulz, Dominik (The R Journal)
Keywords: Statistics; Probability and Uncertainty; Numerical Analysis; Statistics and Probability

Theorizing Marketplace Solidarity Systems: From Consumer–Firm Dyads to Structures of Mutual Support - Alberternst, B.; Steinhoff, Lena; Eggert, A.; Giesler, M. (2022 AMA Summer Marketing Educators’ Conference Proceedings, Chicago)

Three Layers of Abstraction—A Conceptual Framework for Theorizing digital Multi-Sided Platforms - Poniatowski, Martin; Lüttenberg, Hedda; Beverungen, Daniel; Kundisch, Dennis (Information Systems and e-Business Management, Special Issue on Platform Business Models and Platform Strategies)

Towards a model- and data-focused taxonomy of XAI systems - Kucklick, Jan-Peter (Wirtschaftsinformatik 2022 Proceedings)
Explainable Artificial Intelligence (XAI) is currently an important topic for the application of Machine Learning (ML) in high-stakes decision scenarios. Related research focuses on evaluating ML algorithms in terms of interpretability. However, providing a human understandable explanation of an intelligent system does not only relate to the used ML algorithm. The data and features used also have a considerable impact on interpretability. In this paper, we develop a taxonomy for describing XAI systems based on aspects about the algorithm and data. The proposed taxonomy gives researchers and practitioners opportunities to describe and evaluate current XAI systems with respect to interpretability and guides the future development of this class of systems.
Keywords: Explainable Artificial Intelligence; XAI; Interpretability; Decision Support Systems; Taxonomy

Towards a Process Model for Social Media Marketing - Arslan, Kader; Trier, Matthias (Proceedings of the 33rd Australasian Conference on Information Systems (ACIS 2022))
Keywords: Social media; Social media marketing process; Social media strategy; Social media management; Guidelines

Towards a Reliable & Transparent Approach to Data-Driven Brand Valuation - Caron, Matthew; Bartelheimer, Christian; Müller, Oliver (Proceeding of the 28th Americas Conference on Information Systems (AMCIS))
Now accounting for more than 80% of a firm's worth, brands have become essential assets for modern organizations. However, methods and techniques for the monetary valuation of brands are still under-researched. Hence, the objective of this study is to evaluate the utility of explanatory statistical models and machine learning approaches for explaining and predicting brand value. Drawing upon the case of the most valuable English football brands during the 2016/17 to 2020/21 seasons, we demonstrate how to operationalize Aaker's (1991) theoretical brand equity framework to collect meaningful qualitative and quantitative feature sets. Our explanatory models can explain up to 77% of the variation in brand valuations across all clubs and seasons, while our predictive approach can predict out-of-sample observations with a mean absolute percentage error (MAPE) of 14%. Future research can build upon our results to develop domain-specific brand valuation methods while enabling managers to make better-informed investment decisions.

Towards an Amended Arm's Length Principle - Tackling complexity and implementing destination rules in transfer pricing - Greil, Stefan; Overesch, Michael; Rohlfing-Bastian, Anna; Schreiber, Ulrich; Sureth-Sloane, Caren

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.

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

Using Geolocated Text to Quantify Location in Real Estate Appraisal - Heuwinkel, Tim; Kucklick, Jan-Peter; Müller, Oliver (55th Annual Hawaii International Conference on System Sciences (HICSS-55))
Accurate real estate appraisal is essential in decision making processes of financial institutions, governments, and trending real estate platforms like Zillow. One of the most important factors of a property’s value is its location. However, creating accurate quantifications of location remains a challenge. While traditional approaches rely on Geographical Information Systems (GIS), recently unstructured data in form of images was incorporated in the appraisal process, but text data remains an untapped reservoir. Our study shows that using text data in form of geolocated Wikipedia articles can increase predictive performance over traditional GIS-based methods by 8.2% in spatial out-of-sample validation. A framework to automatically extract geographically weighted vector representations for text is established and used alongside traditional structural housing features to make predictions and to uncover local patterns on sale price for real estate transactions between 2015 and 2020 in Allegheny County, Pennsylvania.
Keywords: Real Estate Appraisal; Text Regression; Natural Language Processing (NLP); Location Intelligence; Wikipedia

Utilizing Geographic Information Systems for Condition-Based Maintenance on the Energy Distribution Grid - zur Heiden, Philipp; Priefer, Jennifer; Beverungen, Daniel (Proceedings of the 55th Hawaii International Conference on System Sciences)

Visual Interpretability of Image-based Real Estate Appraisal - Kucklick, Jan-Peter (55th Annual Hawaii International Conference on System Sciences (HICSS-55))
Explainability for machine learning gets more and more important in high-stakes decisions like real estate appraisal. While traditional hedonic house pricing models are fed with hard information based on housing attributes, recently also soft information has been incorporated to increase the predictive performance. This soft information can be extracted from image data by complex models like Convolutional Neural Networks (CNNs). However, these are intransparent which excludes their use for high-stakes financial decisions. To overcome this limitation, we examine if a two-stage modeling approach can provide explainability. We combine visual interpretability by Regression Activation Maps (RAM) for the CNN and a linear regression for the overall prediction. Our experiments are based on 62.000 family homes in Philadelphia and the results indicate that the CNN learns aspects related to vegetation and quality aspects of the house from exterior images, improving the predictive accuracy of real estate appraisal by up to 5.4%.
Keywords: Explainable Artificial Intelligence (XAI); Regression Activation Maps; Real Estate Appraisal; Convolutional Block Attention Module; Computer Vision

Wage Bargaining and Employment Revisited: Separability and Efficiency in Collective Bargaining - Haake, Claus-Jochen; Upmann, Thorsten; Duman, Papatya (Scandinavian Journal of Economics)
We analyse the two-dimensional Nash bargaining solution (NBS) by deploying the standard labour market negotiations model of McDonald and Solow (1981). We show that the two-dimensional bargaining problem can be decomposed into two one-dimensional problems, such that the two solutions together replicate the solution of the two-dimensional problem if the NBS is applied. The axiom of Independence of Irrelevant Alternatives is shown to be crucial for this type of decomposability. This result has significant implications for actual negotiations because it allows for the decomposition of a multi-dimensional bargaining problem into one-dimensional problems---and thus helps to facilitate real-world negotiations.
Keywords: Labour market negotiations; efficient bargains; Nash bargaining solution; sequential bargaining; restricted bargaining games

Wait-and-see-ism as partial adoption of management practices: The rise and stall of integrated reporting - Endenich, Christoph; Hahn, Rüdiger; Reimsbach, Daniel; Wickert, Christopher (Strategic Organization)
Integrated reporting has widely been promoted as the next evolutionary step in corporate disclosure, which would soon replace traditional reporting practices. Embedded in a zeitgeist that favors sustainability, this outlook would suggest high integrated reporting adoption rates among reporting organizations. Our analysis of integrated reporting in Germany from 2008 to 2019 shows, however, that organizations approached integrated reporting with a wait-and-see mentality. This approach cannot be described adequately by the existing conceptualizations of (partial) practice adoption. We therefore develop the notion of wait-and-see-ism, defined as the deliberate and potentially long-lasting postponement of a decision to adopt a practice while its further development is monitored silently. We see limited, though continuous, efforts to prepare for the prospect of adopting the practice of integrated reporting quickly at a later stage. Wait-and-see-ism expands on prior work on partial adoption by emphasizing its temporal dimension. This adds an important yet undertheorized option that organizations can employ to respond to ambiguous institutional demands, thus explaining the stalling of promising management practices.
Keywords: Strategy and Management; Industrial relations; Education; Business and International Management

What to do after a data breach? Examining apology and compensation as response strategies for health service providers - Masuch, K.; Greve, M.; Trang, S. (Electronic Markets)

When do individuals choose care robots over a human caregiver? Insights from a laboratory experiment on choices under uncertainty - Hoppe, Julia Amelie; Tuisku, Outi; Johansson-Pajala, Rose-Marie; Pekkarinen, Satu; Hennala, Lea; Gustafsson, Christine; Melkas, Helinä; Thommes, Kirsten (Computers in Human Behavior Reports)
Keywords: Artificial Intelligence; Cognitive Neuroscience; Computer Science Applications; Human-Computer Interaction; Applied Psychology; Neuroscience (miscellaneous)

When do individuals choose care robots over a human caregiver? Insights from a laboratory experiment on choices under uncertainty - Hoppe, Julia Amelie; Tuisku, Outi; Johansson-Pajala, Rose-Marie; Pekkarinen, Satu; Hennala, Lea; Gustafsson, Christine; Melkas, Helinä; Thommes, Kirsten (Computers in Human Behavior Reports)
Keywords: Artificial Intelligence; Cognitive Neuroscience; Computer Science Applications; Human-Computer Interaction; Applied Psychology; Neuroscience (miscellaneous)

When do individuals choose care robots over a human caregiver? Insights from a laboratory experiment on choices under uncertainty - Hoppe, Julia A.; Tuisku, Outi; Johansson-Pajala, Rose-Marie; Pekkarinen, Satu; Hennala, Lea; Gustafsson, Christine; Melkas, Helinä; Thommes, Kirsten (Computers in Human Behavior Reports)
Keywords: Artificial Intelligence; Cognitive Neuroscience; Computer Science Applications; Human-Computer Interaction; Applied Psychology; Neuroscience (miscellaneous)

Who has the future in mind? Gender, time perspectives, and pro-environmental behaviour - Hoffmann, Christin; Hoppe, Julia Amelie; Ziemann, Niklas (Environmental Research Letters)
Abstract An individual’s relation to time may be an important driver of pro-environmental behaviour. We studied whether young individual’s gender and time-orientation are associated with pro-environmental behaviour. In a controlled laboratory environment with students in Germany, participants earned money by performing a real-effort task and were then offered the opportunity to invest their money into an environmental project that supports climate protection. Afterwards, we controlled for their time-orientation. In this consequential behavioural setting, we find that males who scored higher on future-negative orientation showed significantly more pro-environmental behaviour compared to females who scored higher on future-negative orientation and males who scored lower on future-negative orientation. Interestingly, our results are completely reversed when it comes to past-positive orientation. These findings have practical implications regarding the most appropriate way to address individuals in order to achieve more pro-environmental behaviour.
Keywords: Public Health; Environmental and Occupational Health; General Environmental Science; Renewable Energy; Sustainability and the Environment

Wissenschaften in der Coronavirus-Pandemie - Erkenntnisse, Wissens- und Handlungslücken sowie Schlussfolgerungen für die Vorbereitung auf künftige Pandemien - Interdisziplinäre Kommission für Pandemieforschung, DFG; Sureth-Sloane, Caren

Wissenschaftliches Publizieren als Grundlage und Gestaltungsfeld der Wissenschaftsbewertung - Deutsche Forschungsgemeinschaft | AG Publikationswesen, (DFG); Sureth-Sloane, Caren
Academic publishing represents one of the core functions of scientific activity and thus of the research system. The Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) is committed to the adequate communication of research results and the maintenance of a functioning publication system as a basic requirement of the research system. Ensuring that academic publishing serves foremost the purposes of publicising, quality review and documenting scientific findings should be an essential goal of responsible science administration and promotion. The position paper therefore analyses the central background of the current situation in scientific publishing, identifies challenges and points out possible fields of action. With this positioning, the DFG contributes to the further development of the publication system in a way that is appropriate for science and research.

Wissenschaftsdidaktik als Verständigung über wissenschaftliches Handeln – eine Auslegeordnung - Jenert, Tobias; Scharlau, Ingrid (Wissenschaftsdidaktik I: Einführung)
Im Zentrum Beitrags steht die Frage nach dem Spezifischen einer Didaktik im Wissenschafts- bzw. Hochschulkontext. Dabei hat die Organisation des Wissenschaftssystems in Disziplinen bzw. disziplinäre Gemeinschaften eine besondere Bedeutung. Disziplinen entwickeln spezifische Praktiken, die das Handeln ihrer Angehörigen prägen und sich in Fachkulturen zeigen. Diese Praktiken werden insbesondere an kommunikativen Artefakten sichtbar. Für Personen außerhalb einer disziplinären Gemeinschaft und ganz besonders für jene, die keinen direkten Bezug zum Wissenschaftssystem haben, sind disziplinäre Praktiken häufig schwer zu erschließen. Unsere Konzeption von Wissenschaftsdidaktik lenkt den Blick auf die impliziten Praktiken wissenschaftlicher Disziplinen. Aufgabe von Wissenschaftsdidaktik ist es dem- nach, erstens die impliziten disziplinären Sinnstrukturen, die hinter bestimmten Prak- tiken stehen und in kommunikativen Handlungen und Artefakten verschlüsselt sind, zu entschlüsseln. Zweitens ist es notwendig, die Wahrnehmung disziplinärer Praktiken durch die Studierenden zu analysieren und Differenzen zum Sinnverstehen von Wissenschaftler:innen zu identifizieren. Ausgehend davon kann dann drittens auf eine Verständigung über die Praktiken und deren Sinngehalt hingearbeitet werden. Der Beitrag formuliert die Grundzüge einer Wissenschaftsdidaktik, welche Verständigung über die Praktiken wissenschaftlicher Disziplinen zu einem Kernbestandteil akademischer Lehre macht. Dazu gehört auch ein Moment von Wissenschaftskritik, das auf die Disziplinen und deren Praktiken selbst zurückwirkt. Wissenschaftsdidaktik in diesem Sinne verlangt, den Blick Dritter auf die Praktiken der eigenen Disziplin einzunehmen. Dazu gehör auch, sich einzugestehen, wenn Praktiken keinen Sinn für wissenschaftliche Erkenntnisprozesse (mehr) aufweisen bzw. diesen verloren haben.
Keywords: Wissenschaftsdidaktik; Fachsozialisation; Wissenschaftskritik; Verständigung; Fachkultur; akademische Praktiken; Unterrichtsfach Psychologie

Wissenschaftskommunikation als Verständigung: Chance für die Hochschulentwicklung?! - Jenert, Tobias; Scharlau, Ingrid (Zeitschrift für Hochschulentwicklung)

Zusatzkosten der Besteuerung – Eine Analyse des steuerlichen Verwaltungsaufwands und der subjektiv wahrgenommenen Steuerbelastung (An Empirical Analysis of Firms’ Hidden Cost of Taxation) - Fochmann, Martin; Heinemann-Heile, Vanessa; Huber, Hans-Peter; Maiterth, Ralf; Sureth-Sloane, Caren
Keywords: General Earth and Planetary Sciences; General Environmental Science

§ 2 eWpG (Elektronisches Wertpapier) - Bartlitz, David (eWpG - Gesetz über elektronische Wertpapiere - mit weiterführenden Vorschriften - Kommentar)

“I will survive”: Online streaming and the chart survival of music tracks - Kaimann, Daniel; Tanneberg, Ilka; Cox, Joe (Managerial and Decision Economics)

”Sorry, Too Much Information” Designing Online Review Systems that Support Information Search and Processing - Kutzner, K.; Stadtländer, M.; Seutter, Janina; Kundisch, Dennis; Knackstedt, R. (Proceedings of the 29th European Conference on Information Systems (ECIS))

"Timing is Everything" — An Empirical Analysis of the Timing of Online Review Elicitation - Poniatowski, Martin; Seutter, Janina; Kundisch, Dennis (Proceedings of the 42nd International Conference on Information Systems (ICIS))

“What’s the Point of the Task?” Exploring the Influence of Task Meaning on Creativity in Crowdsourcing - Görzen, Thomas (International Journal of Innovation Management)

2020 Global MNC Tax Complexity Survey - Harst, Simon; Schanz, Deborah; Siegel, Felix; Sureth-Sloane, Caren

A common weights model for investigating efficiency-based leadership in the russian banking industry - Kazemi, Sajad; Tavana, Madjid; Toloo, Mehdi; Zenkevich, Nikolay A. (RAIRO - Operations Research)

A Comparison of Multi-View Learning Strategies for Satellite Image-based Real Estate Appraisal - Kucklick, Jan-Peter; Müller, Oliver (The AAAI-21 Workshop on Knowledge Discovery from Unstructured Data in Financial Services)

A Dynamic Decision Support System for Sustainable Supplier Selection in Circular Economy - Alavi, Behrouz; Tavana, Madjid; Mina, Hassan (Sustainable Production and Consumption)

A fuzzy maturity-based method for lean supply chain management assessment - Soares, Gabriela Pereira; Tortorella, Guilherme; Bouzon, Marina; Tavana, Madjid (International Journal of Lean Six Sigma)

A fuzzy weighted influence non-linear gauge system with application to advanced technology assessment at NASA - Tavana, Madjid; Mousavi, Hossein; Khalili Nasr, Arash; Mina, Hassan (Expert Systems with Applications)

A grey-DEMATEL approach for analyzing factors critical to the implementation of reverse logistics in the pharmaceutical care process - de Campos, Elaine Aparecida Regiani; Tavana, Madjid; ten Caten, Carla Schwengber; Bouzon, Marina; de Paula, Istefani Carísio (Environmental Science and Pollution Research)

A joint chance-constrained data envelopment analysis model with random output data - Khanjani Shiraz, Rashed; Tavana, Madjid; Fukuyama, Hirofumi (Operational Research)

A location-inventory-routing model for green supply chains with low-carbon emissions under uncertainty - Tavana, Madjid; Tohidi, Hamid; Alimohammadi, Milad; Lesansalmasi, Reza (Environmental Science and Pollution Research)

A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries - Tavana, Madjid; Govindan, Kannan; Nasr, Arash Khalili; Heidary, Mohammad Saeed; Mina, Hassan (Annals of Operations Research)

A new non-radial directional distance model for data envelopment analysis problems with negative and flexible measures - Tavana, Madjid; Izadikhah, Mohammad; Toloo, Mehdi; Roostaee, Razieh (Omega)

A note and new extensions on “interval efficiency measures in data envelopment analysis with imprecise data” - Ebrahimi, Bohlool; Tavana, Madjid; Charles, Vincent (Operational Research)

A novel fuzzy multi-objective circular supplier selection and order allocation model for sustainable closed-loop supply chains - Khalili Nasr, Arash; Tavana, Madjid; Alavi, Behrouz; Mina, Hassan (Journal of Cleaner Production)

A Procedure Model for Enhancing Ideation in the Collaborative Development of Business Ecosystems - Vorbohle, Christian; Gottschalk, Sebastian; Kundisch, Dennis; Engels, Gregor; Wünderlich, Nancy (Tagungsband der contribution at: 17. Internationale Tagung Wirtschaftsinformatik 2022 (WI))