Slower searching yields higher efficiency: A case study of taxi drivers

Abstract

The movement patterns of animals while searching for food have been studied extensively in recent decades. However, although human search behavior has existed since the beginning of civilization, not much is known about human search patterns, particularly regarding strategies that yield higher efficiency. Although most humans no longer need to gather and hunt in the wild, human searching remains prevalent in modern times. A common example of human searching is performed by taxi drivers looking for passengers in a city. Here, we analyze GPS data of taxi drivers in three major cities over different time periods and find that when drivers search for passengers, the higher is their efficiency, the slower is their searching, and they tend to make more short-distance turns during the search. Our study further indicates that individuals are characterized by a specific level of efficiency, and thus, efficient drivers are consistently efficient across different days as they follow their own search strategies. Interestingly, only about 10% of drivers adopt the most efficient strategy, earning nearly 20% more than the average driver. Our findings shed light on human search behavior, a fundamental aspect of human decision-making in competitive and fast-paced environments.