Competitive Arousal, Temporal Clustering, and Overbidding Dynamics in an Auction Platform

Auctions provide a unique lens through which to study human behavior and decision-making in competitive environments. These scenarios involve complex dynamics and strategic choices, where interactions between bidders lead to financial outcomes. During auctions, individuals must make quick decisions under pressure while navigating conditions such as item scarcity, information asymmetry, and emotional arousal. By examining bid increments and participant engagement across different auction formats, researchers can gain valuable insights into decision-making processes in competitive settings. This paper presents the findings of a preliminary study that analyzed a dataset from a popular online auction platform where users bid on various types of retail products. The study focused on three key aspects: competitive arousal, temporal clustering, and overbidding. The results reveal that nearly half of the bids occur near the closing time due to competitive arousal, and user activity peaks in the evening. However, contrary to expectations, such temporal clustering does not result in higher average item prices. Furthermore, the dataset revealed instances of overbidding, suggesting the presence of irrational behavior that requires further investigation.