scholarly journals A Game-Theoretic Study on Non-monetary Incentives in Data Analytics Projects with Privacy Implications

Author(s):  
Michela Chessa ◽  
Jens Grossklags ◽  
Patrick Loiseau
2014 ◽  
Vol 30 (2) ◽  
pp. 215-240 ◽  
Author(s):  
Verena Utikal ◽  
Urs Fischbacher

A series of studies in experimental philosophy have revealed that people blame others for foreseen negative side effects but do not praise them for foreseen positive ones. In order to challenge this idea, also called the Knobe effect, we develop a laboratory experiment using monetary incentives. In a game-theoretic framework we formalize the two vignettes in a neutral way, which means that we abstain from the use of any specific language terms and can easily control and vary the economic parameters of the situation. We confirm the Knobe effect in one situation and present situations in which the effect vanishes or even reverses. Our results are in line with a theoretical approach where the assessment of intention is not based on the action itself but on the underlying motive – as modelled in Levine (1998).


Author(s):  
Thomas Kleinsorge ◽  
Gerhard Rinkenauer

In two experiments, effects of incentives on task switching were investigated. Incentives were provided as a monetary bonus. In both experiments, the availability of a bonus varied on a trial-to-trial basis. The main difference between the experiments relates to the association of incentives to individual tasks. In Experiment 1, the association of incentives to individual tasks was fixed. Under these conditions, the effect of incentives was largely due to reward expectancy. Switch costs were reduced to statistical insignificance. This was true even with the task that was not associated with a bonus. In Experiment 2, there was a variable association of incentives to individual tasks. Under these conditions, the reward expectancy effect was bound to conditions with a well-established bonus-task association. In conditions in which the bonus-task association was not established in advance, enhanced performance of the bonus task was accompanied by performance decrements with the task that was not associated with a bonus. Reward expectancy affected mainly the general level of performance. The outcome of this study may also inform recently suggested neurobiological accounts about the temporal dynamics of reward processing.


2017 ◽  
pp. 120-130
Author(s):  
A. Lyasko

Informal financial operations exist in the shadow of official regulation and cannot be protected by the formal legal instruments, therefore raising concerns about the enforcement of obligations taken by their participants. This paper analyzes two alternative types of auxiliary institutions, which can coordinate expectations of the members of informal value transfer systems, namely attitudes of trust and norms of social control. It offers some preliminary approaches to creating a game-theoretic model of partner interaction in the informal value transfer system. It also sheds light on the perspectives of further studies in this area of institutional economics.


2018 ◽  
pp. 114-131
Author(s):  
O. Yu. Bondarenko

his article explores theoretical and experimental approach to modeling social interactions. Communication and exchange of information with other people affect individual’s behavior in numerous areas. Generally, such influence is exerted by leaders, outstanding individuals who have a higher social status or expert knowledge. Social interactions are analyzed in the models of social learning, game theoretic models, conformity models, etc. However, there is a lack of formal models of asymmetric interactions. Such models could help elicit certain qualities characterizing higher social status and perception of status by other individuals, find the presence of leader influence and analyze its mechanism.


2019 ◽  
Vol 54 (5) ◽  
pp. 20
Author(s):  
Dheeraj Kumar Pradhan

2020 ◽  
Vol 49 (5) ◽  
pp. 11-17
Author(s):  
Thomas Wrona ◽  
Pauline Reinecke

Big Data & Analytics (BDA) ist zu einer kaum hinterfragten Institution für Effizienz und Wettbewerbsvorteil von Unternehmen geworden. Zu viele prominente Beispiele, wie der Erfolg von Google oder Amazon, scheinen die Bedeutung zu bestätigen, die Daten und Algorithmen zur Erlangung von langfristigen Wettbewerbsvorteilen zukommt. Sowohl die Praxis als auch die Wissenschaft scheinen geradezu euphorisch auf den „Datenzug“ aufzuspringen. Wenn Risiken thematisiert werden, dann handelt es sich meist um ethische Fragen. Dabei wird häufig übersehen, dass die diskutierten Vorteile sich primär aus einer operativen Effizienzperspektive ergeben. Strategische Wirkungen werden allenfalls in Bezug auf Geschäftsmodellinnovationen diskutiert, deren tatsächlicher Innovationsgrad noch zu beurteilen ist. Im Folgenden soll gezeigt werden, dass durch BDA zwar Wettbewerbsvorteile erzeugt werden können, dass aber hiermit auch große strategische Risiken verbunden sind, die derzeit kaum beachtet werden.


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