Title of the Article : Humans Are Not Machines: The Behavioral Impact of Queueing Design on Service Time
Author Information : Julie Niederhoff (Whitman School of Management, Syracuse University) Masha Shunko (Foster School of Business, University of Washington) Yaroslav Rosokha (Krannert School of Management, Purdue University)
Year of Publication : Management Science (Forthcoming)
Summary of Findings : We find experimental support to show that workers in a single-queue setting (where customers wait in one long line and go to the next available server and all servers share that queue) work more slowly than workers in parallel-queue settings (where customers wait in line for a specific server and each server has his or her own queue), and we disentangle the impact of feedback and felt-responsibility as reasons for this slowdown.
Research Questions : 1. Does the structure of the queue affect the performance of workers? 2. If workers do not perform equally in each setting, how is this driven by the reduced felt-responsibility and feedback of the single-line queue? 3. How are these results affected by the number of customers in the system and payment structure, and how does learning develop over time?
What we know : Analytical work typically analyzes these systems from the customer's perspective but assumes steady worker effort; or assumes worker speed is driven by the number of customers in the system. One might intuitively assume that workers would perform differently under single-queue systems compared to parallel-queue systems, but there has not yet been a study to determine this, nor a study of the degree of difference and/or what behavioral factors drive this.
Novel Findings : Building on social loafing theory, group dynamics and system dynamics, we find key drivers include felt-responsibility (due to task interdependence) and feedback about the line movement (due to poor visibility). By manipulating the visibility and the payment structure, we find that when parallel queues have equally poor visibility and both have high incentive to work fast due to payment structure, we find no significant difference between parallel and single queues.
Novel Methodology : We use experimental simulations in the Whitman Behavioral Lab at Syracuse University. Subjects worked as servers in a simulated setting as retail cashiers. We manipulated customer arrival rate, payment structure, visibility of the queue and queue structure to collect a rich data set of worker performance over a ten-minute work period.
Implications for Practice : We find that parallel queues always work faster than single-line queues, but that performance incentives such as pay-per-customer coupled with clear feedback on the number of customers in line and how quickly they are moving will motivate workers in both settings. Feedback is particularly important, as much if not more than financial incentives.
Implications for Policy: Managers looking to move to single-queue policies for the benefits perceived by customers (e.g. fairness), may find that their employees work more slowly. This could reduce customer experience ratings. This slowdown can be mitigated by managing the employees' view of the line and providing incentives, but the overall productivity would still be lower than a comparable setting with parallel queues.
Implications for Society: Slower workers do not always hurt a system. Medical professionals and security screenings may be more effective under reduced pressure to work quickly. In other situations, speed is a vital part of customer satisfaction. Managers should understand the implication of the queue structure on the overall experience for customers and employees.
Implications on Research: Future work is considering the impact of larger group sizes, competitive or team-oriented work groups, and the impact on customer satisfaction. We are also analyzing prior analytical models to understand the theoretical impact of this worker slowdown.
Full Citations : Shunko, M., J. Niederhoff, Y. Rosokha. 2016. Humans Are Not Machines: The Behavioral Impact of Queueing Design on Service Time. Management Science, forthcoming
Abstract : Using behavioral experiments, we study the impact of queue design on worker productivity in service systems that involve human servers. Specifically, we consider two-queue design features: queue structure, which can either be parallel queues (multiple queues with a dedicated server per queue) or a single-queue (a pooled queue served by multiple servers); and queue-length visibility, which can provide either full or blocked visibility. We find that 1) the single-queue structure slows down the servers, illustrating a drawback of pooling; and 2) poor visibility of the queue-length slows down the servers; however, this effect may be mitigated, or even reversed, by pay schemes that incentivize the servers for fast performance. We provide additional managerial insights by isolating two behavioral drivers behind these results-task interdependence and saliency of feedback.
New research shows when customers wait in one long line and go to the next available server, those servers work more slowly than when servers each have their own queue.