Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/282537 
Year of Publication: 
2023
Series/Report no.: 
CESifo Working Paper No. 10849
Publisher: 
Center for Economic Studies and ifo Institute (CESifo), Munich
Abstract: 
We study the interaction between algorithmic advice and human decisions using high-resolution hotel-room pricing data. We document that price setting frictions, arising from adjustment costs of human decision makers, induce a conflict of interest with the algorithmic advisor. A model of advice with costly price adjustments shows that, in equilibrium, algorithmic price recommendations are strategically biased and lead to suboptimal pricing by human decision makers. We quantify the losses from the strategic bias in recommendations using as structural model and estimate the potential benefits that would result from a shift to fully automated algorithmic pricing.
Subjects: 
advice
algorithmic recommendations
human decisions
adjustment cost
delegation
JEL: 
D22
D83
L13
Document Type: 
Working Paper
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