Hafenbrädl, S. (Sebastian)

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    Rivals without a cause? Relative performance feedback creates destructive competition despite aligned incentives
    (Wiley, 2020) Hafenbrädl, S. (Sebastian); Woike, J.K. (Jan K.)
    Whether people compete or cooperate with each other has consequences for their own performance and that of organizations. To explain why people compete or cooperate, previous research has focused on two main factors: situational outcome structures and personality types. Here, we propose that—above and beyond these two factors—situational cues, such as the format in which people receive feedback, strongly affect whether they act competitively, cooperatively, or individualistically. Results of a laboratory experiment support our theorizing: After receiving ranking feedback, both students and experienced managers treated group situations with cooperative outcome structures as competitive and were in consequence willing to forgo guaranteed financial gains to pursue a—financially irrelevant—better rank. Conversely, in dilemma situations, feedback based on the joint group outcome led to more cooperation than ranking feedback. Our study contributes to research on competition, cooperation, interdependence theory, forced ranking, and the design of information environments.
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    When self-humanization leads to algorithm aversion: What users want from decision support systems on prosocial microlending platforms
    (Springer, 2022-07-01) Pfeiffer, J. (Jella); Hafenbrädl, S. (Sebastian); Heßler, P.O. (Pascal Oliver)
    Decision support systems are increasingly being adopted by various digital platforms. However, prior research has shown that certain contexts can induce algorithm aversion, leading people to reject their decision support. This paper investigates how and why the context in which users are making decisions (for-profit versus prosocial microlending decisions) affects their degree of algorithm aversion and ultimately their preference for more human-like (versus computer-like) decision support systems. The study proposes that contexts vary in their affordances for self-humanization. Specifically, people perceive prosocial decisions as more relevant to self-humanization than for-profit contexts, and, in consequence, they ascribe more importance to empathy and autonomy while making decisions in prosocial contexts. This increased importance of empathy and autonomy leads to a higher degree of algorithm aversion. At the same time, it also leads to a stronger preference for human-like decision support, which could therefore serve as a remedy for an algorithm aversion induced by the need for self-humanization. The results from an online experiment support the theorizing. The paper discusses both theoretical and design implications, especially for the potential of anthropomorphized conversational agents on platforms for prosocial decision-making.
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    Competition and moral behavior: A meta-analysis of forty-five crowd-sourced experimental designs
    (National Academy of Sciences, 2023-06-06) Hafenbrädl, S. (Sebastian); Qin, X. (Xiangdong); Schneider, F. (Florian); Schram, A. (Arthur); Hudja, S. (Stanton); Li, S. (Shuwen); Mak, V. (Vincent); Brütt, K. (Katharina); Isler, O. (Ozan); Jolles, D. (Daniel); Gasiorowska, A. (Agata); Meyers, E.A. (Ethan Andrew); Roth, Y. (Yefim); Lucas, B. (Brian); Dreber, A. (Anna); Hart, E. (Einav); Weitzel, U. (Utz); Yakobi, O. (Ofir); Rincke, J. (Johannes); Abellán, M. (Miguel); Hütter, M. (Mandy); Yilmaz, O. (Onurcan); Ceren-Ay, F. (Fehime); Neyse, L. (Levent); Demiral, E.E. (Elif E.); Holzmeister, F. (Felix); Jeworrek, S. (Sabrina); Barron, K. (Kai); Palumbo, H. (Helena); Delnoij, J. (Joyce); Huber, J. (Jürgen); Schwieren, C. (Christiane); Fiala, L. (Lenka); Zeisberger, S. (Stefan); Khadjavi, M. (Menusch); Theodoropoulou, A. (Andriana); Urbig, D. (Diemo); Cardella, E. (Eric); Schmitz, J. (Jan); Seyhun-Saral, A. (Ali); Soraperra, I. (Ivan); Merkle, C. (Christoph); Mollerstrom, J. (Johanna); Waibel, J. (Joschka); Glogowsky, U. (Ulrich); Pratap-KC, R. (Raghabendra); Juanchich, M. (Marie); Rahal, R.M. (Rima Maria); Sirota, M. (Miroslav); Steimanis, I. (Ivo); Scopelliti, I. (Irene); Grohmann, A. (Antonia); Schudy, S. (Simeon); Kugler, T. (Tamar); Doerflinger, J.T. (Johannes Theodor); Claassen, M.A. (Maria Almudena); Woods, D. (Daniel); Peters, K. (Kim); Pirrone, A. (Angelo); Fries, T. (Tilman); Mechtel, M. (Mario); Handgraaf, M. (Michel); Dimant, E. (Eugen); Campos-Mercade, P. (Pol); Hennig, M. (Max); Nesterov, A. (Alexander); Cornelissen, G. (Gert); Dawson, I.G.J. (Ian G. J.); Ioannidis, K. (Konstantinos); Ronzani, P. (Piero); Nieken, P. (Petra); Sonnemans, J. (Joep); Adayeva, X. (Xeniya); Freddi, E. (Eleonora); Emery, C. (Cécile); Berry, Z. (Zachariah); Rau, H. (Holger); Gorny, P.A.(Paul M.); Bulutay, M. (Muhammed); Hyndman, K. (Kyle); Spantig, L. (Lisa); Huber, C. (Christoph); Zaleskiewicz, T. (Tomasz); Johannesson, M. (Magnus); Steinmetz, J. (Janina); Gretton, J.D. (Jeremy David); Fiedler, S. (Susann); Schweitzer, M.E. (Maurice E.); Vorlaufer, T. (Tobias); Bönte, W. (Werner); Suetens, S. (Sigrid); Dold, M. (Malte); Kirchler, M. (Michael); Hanoch, Y. (Yaniv); Nussberger, A.M. (Anne-Marie)
    Does competition affect moral behavior? This fundamental question has been debated among leading scholars for centuries, and more recently, it has been tested in experimental studies yielding a body of rather inconclusive empirical evidence. A potential source of ambivalent empirical results on the same hypothesis is design heterogeneity—variation in true effect sizes across various reasonable experimental research protocols. To provide further evidence on whether competition affects moral behavior and to examine whether the generalizability of a single experimental study is jeopardized by design heterogeneity, we invited independent research teams to contribute experimental designs to a crowd-sourced project. In a large-scale online data collection, 18,123 experimental participants were randomly allocated to 45 randomly selected experimental designs out of 95 submitted designs. We find a small adverse effect of competition on moral behavior in a meta-analysis of the pooled data. The crowd-sourced design of our study allows for a clean identification and estimation of the variation in effect sizes above and beyond what could be expected due to sampling variance. We find substantial design heterogeneity—estimated to be about 1.6 times as large as the average standard error of effect size estimates of the 45 research designs—indicating that the informativeness and generalizability of results based on a single experimental design are limited. Drawing strong conclusions about the underlying hypotheses in the presence of substantive design heterogeneity requires moving toward much larger data collections on various experimental designs testing the same hypothesis.
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    The transmission game: Testing behavioral interventions in a pandemic-like simulation
    (American Association for the Advancement of Science, 2022-02-25) Hafenbrädl, S. (Sebastian); Woike, J.K. (Jan K.); Kanngiesser, P. (Patricia); Hertwig, R. (Raplh)
    During pandemics, effective nonpharmaceutical interventions encourage people to adjust their behavior in fast-changing environments in which exponential dynamics aggravate the conflict between the individual benefits of risk-taking and its social costs. Policy-makers need to know which interventions are most likely to promote socially advantageous behaviors. We designed a tool for initial evaluations of the effectiveness of large-scale interventions, the transmission game framework, which integrates simulations of outbreak dynamics into large-group experiments with monetary stakes. In two studies (n = 700), we found substantial differences in the effectiveness of five behavioral interventions. A simple injunctive-norms message proved most effective, followed by two interventions boosting participants’ ability to anticipate the consequences of risky behavior. Interventions featuring descriptive norms or concurrent risk information failed to reduce risk-taking.