Causal Inference Study on Citizen Runners' Purchase Behavior

Abstract

The runners' population is on the rise due to increased health awareness caused by the outbreak of COVID-19 and the recent popularity of running. In this study, the author conducted a questionnaire survey of citizen runners, not professional runners, in their 20s to 60s living in Japan with the aim of analyzing their behavior regarding running and other daily life. The data have been analyzed using a combination of causal inference and machine learning to determine the impact of runners' behavioral transformation regarding running events on their purchase of wearable devices. Such self-behavioral transformation can be viewed as an intervention in causal inference. This will enable us to propose effective sports marketing measures for the products.