Strategic Responses to Algorithmic Recommendations: Evidence from Hotel Pricing

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CESifo Working Paper ; No. 10849

Classification and Topics

• Classification: Wirtschaft ; Firm Behavior: Empirical Analysis ; Search; Learning; Information and Knowledge; Communication; Belief; Unawareness ; Oligopoly and Other Imperfect Markets
• Subject: advice ; algorithmic recommendations ; human decisions ; adjustment cost ; delegation

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Garcia, Daniel ; Tolvanen, Juha ; Wagner, Alexander K.
• Event: Veröffentlichung
• (who): Center for Economic Studies and ifo Institute (CESifo)
• (where): Munich
• (when): 2023

Further information

• Handle: http://hdl.handle.net/10419/282537
• Last update: 10.03.2025, 11:42 AM CET