Project Website

OeNB Anniversary Fund Project

Project Number 18878

Recommendation and Price Update

“Human-Algorithm Interactions in Economic Decision Making”

Project description

Human-algorithm interactions are increasingly shaping the economic behavior of consumers, firms, and therefore society as a whole.  This project aims to advance our understanding of the fundamental changes that human-AI collaborations bring to economic decision-making by investigating AI-supported human decision-making in two important economic domains: pricing decisions and demand planning decisions. This will allow us to gain insights into the potential benefits and pitfalls of AI-based decision making in both non-strategic and strategic settings. The impact of AI-supported decision making is not only to the involved consumers and firms, but are also a key policy concern, as AI-supported decision making can impact price formation, consumer welfare, firm competitiveness, market regulation, discrimination, and productivity.

Project 1 focuses on AI-supported pricing in the service industry. We investigate the strategic interaction between an AI algorithm that provides price recommendations and a human manager that makes pricing decisions in the context of dynamic hotel room pricing. We study experimentally and empirically how AI-supported pricing changes pricing when the human decision maker faces adjustment costs due to limited attention. In project 2 we study human-AI collaboration in demand planning in the high-tech industry. We focus on the interaction between algorithmic forecasts and human forecasters who provide predictions about uncertain demand to a human decision maker. We develop a model of information transmission (communication) between forecasters and decision makers, taking into account the possible effects of misaligned incentives and limited cognition of human economic agents. The two projects are expected to provide important insights into the effects AI-supported decision making has on price formation (project 1) and demand planning (project 2) and their underlying microeconomic mechanisms.

Funding

Austrian National Bank (OeNB) Anniversary Fund Project 18878 for the years 2023-2027.

Project team

Alexander K. Wagner (Principal Investigator, PLUS), Daniel Garcia (U Vienna), Juha Tolvanen (U Tor Vergata Rome) and James Tremewan (U Tor Vergata Rome)

Results

Garcia, Daniel, Juha Tolvanen, and Alexander K. Wagner. “Strategic Responses to Algorithmic Recommendations: Evidence from Hotel Pricing.” Management Science, 2024.   doi 

Picture taken from Garcia Tolvanen and Wagner (2024)