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Theory and Decision
Article . 2014 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
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Recall searching with and without recall

Authors: Tibor Neugebauer; Tibor Neugebauer; Abdolkarim Sadrieh; Carlos Rodríguez-Palmero; Daniela Di Cagno;

Recall searching with and without recall

Abstract

We revisit the sequential search problem by Hey (J Econ Behav Organ 8:137–144, 1987). In a 2 $$\times $$ 2 factorial design, varying fixed and random cost treatments with and without recall, we address open research questions that were originally stated by Hey (1987). Our results provide clear evidence for Hey’s (1987) conjecture that recall negatively affects performance in sequential search. With experience, however, search behavior with and without recall converges toward the optimal reservation rule. We further find that the utilization of optimal reservation rules is independent from the stochastic nature of the search cost.

Keywords

Experiments, Search, Stopping rule, Recall Effect, experiments, jel: jel:D92, jel: jel:C90, jel: jel:D53, jel: jel:G12, jel: jel:G02, jel: jel:G11

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
bronze