Indoor Air Quality and Strategic Decision Making

Abstract

Decision making on the job is becoming increasingly important in the labor market, in which there is an unprecedented rise in demand for workers with problem-solving and critical-thinking skills. This paper investigates how indoor air quality affects the quality of strategic decision making based on data from official chess tournaments. Our main analysis relies on a unique data set linking the readings of air-quality monitors inside the tournament room to the quality of 30,000 moves, each of them objectively evaluated by a powerful artificial intelligence–based chess engine. The results show that poor indoor air quality hampers players’ decision making. We find that an increase in the indoor concentration of fine particulate matter (PM[Formula: see text]) by 10 [Formula: see text] (corresponding to 75% of a standard deviation in our sample) increases a player’s probability of making an erroneous move by 26.3%. The decomposition of the effects by different stages of the game shows that time pressure amplifies the damage of poor air quality to the players’ decisions. We implement a number of robustness checks and conduct a replication exercise with analogous move-quality data from games in the top national league showing the strength of our results. The results highlight the costs of poor air quality for highly skilled professionals faced with strategic decisions under time pressure. This paper was accepted by Prof. Yan Chen, behavioral economics and decision analysis. Funding: The authors gratefully acknowledge the financial support from the Graduate School of Business and Economics at Maastricht University as well as the Institute of Labor Economics Bonn. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2022.4643 .