Minimizing Learning in Repeated Real-Effort Tasks

Journal article
(Original article)


Publication Details

Author(s): Benndorf V, Rau HA, Sölch C
Journal: Journal of Behavioral and Experimental Finance
Publication year: 2019
ISSN: 2214-6350
Language: English


Abstract


In this paper, we introduce a new real-effort task which mitigates learning behavior in repeated real-effort tasks. In our task, participants need to encode three-letter words into numbers. The task is based on Erkral et al. (2011), however, in our version a double-randomization mechanism is applied to minimize learning. Existing experiments using repeated real-effort tasks report an increase of 15-30% in subjects' performance in the course of the experiment. By contrast, we find that when comparing performance in the first period with the last period, our task mitigates learning behavior down to 8%. The difference between the first and second half of the experiment is only about 3%.


FAU Authors / FAU Editors

Sölch, Christian
Lehrstuhl für Volkswirtschaftslehre, insbesondere Wirtschaftstheorie


External institutions with authors

Georg-August-Universität Göttingen
Goethe-Universität Frankfurt am Main


Research Fields

Experimental Economics
Lehrstuhl für Volkswirtschaftslehre, insbesondere Wirtschaftstheorie


How to cite

APA:
Benndorf, V., Rau, H.A., & Sölch, C. (2019). Minimizing Learning in Repeated Real-Effort Tasks. Journal of Behavioral and Experimental Finance. https://dx.doi.org/10.1016/j.jbef.2019.04.002

MLA:
Benndorf, Volker, Holger Andreas Rau, and Christian Sölch. "Minimizing Learning in Repeated Real-Effort Tasks." Journal of Behavioral and Experimental Finance (2019).

BibTeX: 

Last updated on 2019-02-05 at 17:08