In the paper “Slower searching yields higher efficiency: A case study of taxi drivers”, Qiuyue Li examines human search behavior as a fundamental aspect of human decision-making. While animal search patterns have been widely studied, human searching in real urban environments, where attention, speed, and spatial constraints are key, remains less understood. By analyzing over 2.3 billion GPS data points from nearly 40,000 taxi drivers across three major cities, the researchers uncovered a counterintuitive result: slower searching leads to higher efficiency. The most efficient drivers tend to move at lower speeds and make more short-distance turns, demonstrating a more attentive and localized search approach.

To interpret these findings, the study draws on the Lévy walk principle, a theory that describes a natural balance between exploration and exploitation. Instead of searching randomly or directly, the searcher makes mostly short movements while occasionally performing longer relocations. The short movements allow for careful inspection of nearby surroundings, while the longer ones prevent stagnation. These insights challenge the common assumption that speed necessarily improves results, suggesting instead that efficiency can emerge from strategic movement. 

We invite you to explore the complete article and discover how slower searching can lead to smarter efficiency.

Qiuyue Li, Daqing Li, Orr Levy, Shlomo Havlin

DOI: https://doi.org/10.1073/pnas.2502965122