Quantification of deviations from rationality with heavy-tails in human dynamics

TL;DR

This study analyzes human task execution times using large-scale web data, revealing multiple regimes beyond power-law distributions, including exponential and plateau regimes, influenced by user utilization and response strength, with implications for human decision-making and policy design.

Contribution

It uncovers complex regimes in human response times, extending queueing theory beyond power-law assumptions using real-world web data.

Findings

Existence of exponential and plateau regimes in human task timing

Response times depend on user utilization and perturbation strength

Implications for policies and understanding collective human behaviors

Abstract

The dynamics of technological, economic and social phenomena is controlled by how humans organize their daily tasks in response to both endogenous and exogenous stimulations. Queueing theory is believed to provide a generic answer to account for the often observed power-law distributions of waiting times before a task is fulfilled. However, the general validity of the power law and the nature of other regimes remain unsettled. Using anonymized data collected by Google at the World Wide Web level, we identify the existence of several additional regimes characterizing the time required for a population of Internet users to execute a given task after receiving a message. Depending on the under- or over-utilization of time by the population of users and the strength of their response to perturbations, the pure power law is found to be coextensive with an exponential regime (tasks are performed without too much delay) and with a crossover to an asymptotic plateau (some tasks are never performed). The characterization of the availability and efficiency of humans on their actions revealed by our study have important consequences to understand human decision-making, optimal designs of policies such as for Internet security, with spillovers to collective behaviors, crowds dynamics, and social epidemics.