Strategic Responses to Algorithmic Recommendations: Evidence from Hotel Pricing

Author(s)
Daniel Garcia, Alexander K. Wagner, Juha Tolvanen
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.

Organisation(s)
Department of Economics, Vienna Center for Experimental Economics
Journal
Management Science
ISSN
0025-1909
DOI
https://doi.org/10.1287/mnsc.2022.03740
Publication date
2023
Peer reviewed
Yes
Austrian Fields of Science 2012
502021 Microeconomics, 502058 Digital transformation
Portal url
https://ucrisportal.univie.ac.at/en/publications/01580b8c-4575-4612-b9f0-1be635577bbe