Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/238230 
Year of Publication: 
2020
Series/Report no.: 
Working Papers in Economics and Statistics No. 2020-06
Publisher: 
University of Innsbruck, Research Platform Empirical and Experimental Economics (eeecon), Innsbruck
Abstract: 
Rankings are intended as incentive tools on labor markets. Yet, when agents perform multiple tasks - not all of which can be ranked with respect to performance -, rankings might have unintended side-effects. Based on a dynamic model of multi-tasking, we present an experiment with financial professionals in which we identify hidden ranking costs when performance in one task is ranked while in another prosocial task it is not. We find that subjects lagging behind (leading) in the ranked task devote less (more) effort to the prosocial task. We discuss implications for optimal incentive schemes in organizations with multitasking.
Subjects: 
multi-tasking decision problem
rank incentives
framed field experiment
finance professionals
JEL: 
C93
D02
D91
Document Type: 
Working Paper

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