Themen für Bachelorarbeiten

Beschreibung: Machiavellisten glauben an die Leichtgläubigkeit anderer, aber nehmen keine Rücksicht darauf, sondern nutzen diese bewusst zu ihrem eigenen Vorteil aus. Narzissten haben eine überzogene Selbstwahrnehmung und neigen zu Grössenwahn, so dass sie sich gerne im Zentrum der Aufmerksamt selbst darstellen können. Psychopathen scheren sich nicht um das Wohl anderer oder gesellschaftliche Normen und weisen somit die Tendenz auf, anderen zu schaden. Derartige Charakterzüge mag wohl kaum jemand in seinem Umfeld haben und so hat jeder schon einmal entsprechende Exemplare von dem gesehen, was Paulhus und Williams (2002) als sog. dunkle Triade der Persönlichkeit beschrieben haben. Diese Triade der Persönlichkeit hat über die Jahre grosse Aufmerksamkeit in der arbeits- und organisationspsychologischen Forschung erfahren (e.g., Ellen et al., 2021; O?Boyle et al., 2012, 2015) und wird mit allerlei arbeitsrelevanten Konstrukten in Verbindung gebracht (z.B. Leistung am Arbeitsplatz, Führung von Mitarbeitenden). Das Konstrukt resp. seine Anwendung in der Forschung sind allerdings nicht unumstritten (e.g., DeShong et al., 2015, 2017; Miller et al., 2019).

Vor diesem Hintergrund ist es das Ziel der Literaturarbeit (1) einen theoretischen und messtheoretischen Überblick über die dunkle Triade zu geben, (2) empirische Arbeiten bzgl. der Vorhersagekraft der dunklen Triade am Arbeitsplatz zu identifizieren und zu beschreiben, sowie (3) diese Befunde kritisch-vergleichend zu diskutieren.

Initiale Literatur:
DeShong, H. L., Grant, D. M., & Mullins-Sweatt, S. N. (2015). Comparing models of counterproductive workplace behaviors: The five-factor model and the dark triad. Personality and Individual Differences, 74, 55?60. https://doi.org/10.1016/j.paid.2014.10.001
DeShong, H. L., Helle, A. C., Lengel, G. J., Meyer, N., & Mullins-Sweatt, S. N. (2017). Facets of the dark triad: Utilizing the five-factor model to describe machiavellianism. Personality and Individual Differences, 105, 218?223. https://doi.org/10.1016/j.paid.2016.09.053
Ellen, B. P., Alexander, K. C., Mackey, J. D., McAllister, C. P., & Carson, J. E. (2021). Portrait of a workplace deviant: A clearer picture of the big five and dark triad as predictors of workplace deviance. Journal of Applied Psychology, 106(12), 1950?1961. https://doi.org/10.1037/apl0000880
Miller, J. D., Vize, C., Crowe, M. L., & Lynam, D. R. (2019). A critical appraisal of the dark-triad literature and suggestions for moving forward. Current Directions in Psychological Science, 28(4), 353?360. https://doi.org/10.1177/0963721419838233
O?Boyle, E. H., Forsyth, D. R., Banks, G. C., & McDaniel, M. A. (2012). A meta-analysis of the dark triad and work behavior: A social exchange perspective. Journal of Applied Psychology, 97(3), 557?579. https://doi.org/10.1037/a0025679
O?Boyle, E. H., Forsyth, D. R., Banks, G. C., Story, P. A., & White, C. D. (2015). A meta-analytic test of redundancy and relative importance of the dark triad and five-factor model of personality. Journal of Personality, 83(6), 644?664. https://doi.org/10.1111/jopy.12126
Paulhus, D. L., & Williams, K. M. (2002). The dark triad of personality: Narcissism, machiavellianism, and psychopathy. Journal of Research in Personality, 36(6), 556?563. https://doi.org/10.1016/S0092-6566(02)00505-6
Kontakt: Martin Götz, E-Mail

Beschreibung: When people cooperate to obtain a common goal (e.g., group homework), it is often observed that some people invest less effort than others, but nonetheless benefit from the results (e.g., getting a good grade). In the fields of behavioral economics and psychology, this behavior is defined as free-riding, or defection
(Nowak, 2006). One common solution to this problem is to introduce costly punishment: At a cost for the person enacting it, a sanction can be imposed on the free-rider (e.g., reprimanding). Punishment is an effective deterrent (Fehr & Gächter, 2000), but it introduces a new dilemma: Who in the group is punishing defectors at a cost to themselves? When enforcing cooperation norms in groups is costly, people may shy away from doing so (e.g., not reprimanding), free-riding on those who are willing to enforce such norms in their group. This behavior is defined as second-order free-riding (Henrich & Boyd, 2001). Hence, while punishment can solve the first-order free-rider problem, in theory, it also creates a second-order free-rider problem. Thus, questions arise, such as (1) how do groups actually solve this second-order free-rider problem, (2) how is solving the second-order problem different from solving the first-order free-rider problem, and (3) do people perceive first- and second-order free-riding differently (e.g., Dreber et al., 2008; Mathew, 2017; Raihani & Bshary, 2011).

The aim of the proposed literature review is (1) to provide an overview of empirical and theoretical research on second-order free-riding, (2) to explore distinctions with first-order free-riding, and (3) to discuss the findings and identify directions for future research.

Initial literature:
Dreber, A., Rand, D. G., Fudenberg, D., & Nowak, M. A. (2008). Winners don?t punish. Nature, 452(7185), 348?351. https://doi.org/10.1038/nature06723
Fehr, E., & Gächter, S. (2000). Cooperation and punishment in public goods experiments. American Economic Review, 90(4), 980?994. https://doi.org/10.1257/aer.90.4.980
Henrich, J., & Boyd, R. (2001). Why people punish defectors: Weak conformist transmission can stabilize costly enforcement of norms in cooperative dilemmas. Journal of Theoretical Biology, 208(1), 79?89. https://doi.org/10.1006/jtbi.2000.2202
Mathew, S. (2017). How the second-order free rider problem is solved in a small-scale society. American Economic Review, 107(5), 578?581. https://doi.org/10.1257/aer.p20171090
Nowak, M. A. (2006). Five rules for the evolution of cooperation. Science, 314(5805), 1560?1563. https://doi.org/10.1126/science.1133755
Raihani, N. J., & Bshary, R. (2011). The evolution of punishment in N-player public goods games: A volunteer?s dilemma. Evolution, 65(10), 2725?2728. https://doi.org/10.1111/j.1558-5646.2011.01383.x
Kontakt: Filippo Toscano, E-Mail

Beschreibung: Altruism is broadly defined as a behavior that benefits others but brings about personal costs to the individual performing it (Kerr et al., 2004). Different theories have been proposed to explain such altruistic behavior (Nowak, 2006). One example is kin selection: By helping a genetic relative, one might increase the chances to pass down the genes that both have in common, even when this has a cost to the actor (Foster et al., 2006). Another example is direct reciprocity, where altruistic behavior is exchanged between individuals that expect to receive it back at a later point in time (Trivers, 1971). Lastly, people may act altruistically when they are observed by others, because it may provide reputational benefits for them in the future (Wedekind & Milinski, 2000). However, humans also frequently help unrelated individuals, strangers that they will not meet again, and in situations where they are not observed. This suggests that kin selection, reciprocity and reputation are insufficient to fully explain this behavior (Fehr & Gächter, 2002; Vlerick, 2021). The questions thus still stands: How can we resolve this puzzle and explain altruistic acts in such situations?

The aim of the proposed literature review is (1) to provide an overview of possible mechanisms that explain altruistic behavior, (2) to review research that documents altruism among strangers, and (3) provide some explanations of such behavior based on existing theoretical and empirical work.

Initial literature:
Fehr, E., & Gächter, S. (2002). Altruistic punishment in humans. Nature, 415(6868), 137?140. https://doi.org/10.1038/415137a
Foster, K., Wenseleers, T., & Ratnieks, F. (2006). Kin selection is the key to altruism. Trends in Ecology & Evolution, 21(2), 57?60. https://doi.org/10.1016/j.tree.2005.11.020
Kerr, B., Godfrey-Smith, P., & Feldman, M. W. (2004). What is altruism? Trends in Ecology & Evolution, 19(3), 135?140. https://doi.org/10.1016/j.tree.2003.10.004
Nowak, M. A. (2006). Five rules for the evolution of cooperation. Science, 314(5805), 1560?1563. https://doi.org/10.1126/science.1133755
Trivers, R. L. (1971). The evolution of reciprocal altruism. The Quarterly Review of Biology, 46(1), 35?57. https://doi.org/10.1086/406755
Vlerick, M. (2021). Explaining human altruism. Synthese, 199(1?2), 2395?2413. https://doi.org/10.1007/s11229-020-02890-y
Wedekind, C., & Milinski, M. (2000). Cooperation through image scoring in humans. Science, 288(5467), 850?852. https://doi.org/10.1126/science.288.5467.850
Kontakt: Filippo Toscano, E-Mail

Beschreibung: Nudging ist eine verhaltensökonomische Intervention, um das Verhalten von Menschen "anzustupsen" resp. es ohne Verbote und Gebote oder irgendwelche ökonomischen Anreize zum Guten zu verändern (e.g., Benartzi et al., 2017; Liebe et al., 2021; Ruggeri et al., 2020; Thaler, 2018; Thaler & Sunstein, 2008). Exemplarisch hat das Elektrizitätswerk der Stadt Zürich den Status Quo des Stromtarifs seiner Kund:innen auf nachhaltige Produktion angepasst ? während Kund:innen sich früher explizit für nachhaltigen Strom entscheiden mussten, müssen sie sich nun aktiv dagegen entscheiden. Es gibt diverse weitere Beispiele, wo Nudging in der Realität eingesetzt wurde (z.B. Organspende). Gemessen an den mitunter beeindruckenden empirischen Ergebnissen zu Nudging scheint die Verhaltensökonomie ein Wundermittel zur kostengünstigen und gewinnbringenden Verhaltensänderung von Menschen gefunden zu haben.
Vor diesem Hintergrund ist es das Ziel der Literaturarbeit (1) einen theoretischen Überblick über Nudging zu geben, (2) empirische Belege der Funktion oder des Scheiterns von Nudging in realen Settings zu identifizieren und zu beschreiben, sowie (3) diese Befunde kritisch-vergleichend zu diskutieren.

Initiale Literatur:
Benartzi, S., Beshears, J., Milkman, K. L., Sunstein, C. R., Thaler, R. H., Shankar, M., Tucker-Ray, W., Congdon, W. J., & Galing, S. (2017). Should governments invest more in nudging? Psychological Science, 28(8), 1041?1055. https://doi.org/10.1177/0956797617702501
Liebe, U., Gewinner, J., & Diekmann, A. (2021). Large and persistent effects of green energy defaults in the household and business sectors. Nature Human Behaviour, 5(5), 576?585. https://doi.org/10.1038/s41562-021-01070-3
Ruggeri, K., Folke, T., Benzerga, A., Verra, S., Büttner, C., Steinbeck, V., Yee, S., & Chaiyachati, K. (2020). Nudging New York: Adaptive models and the limits of behavioral interventions to reduce no-shows and health inequalities. BMC Health Services Research, 20(1), 363. https://doi.org/10.1186/s12913-020-05097-6
Thaler, R. H. (2018). From cashews to nudges: The evolution of behavioral economics. American Economic Review, 108(6), 1265?1287. https://doi.org/10.1257/aer.108.6.1265
Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. Yale University Press.
Kontakt: Martin Götz, E-Mail