How best to structure the work day is an important operational question for organizations. A key structural consideration is the effective use of breaks from work. Breaks serve the critical purpose of allowing employees to recharge, but in the short term, translate to a loss of time that usually leads to reduced productivity. We evaluate the effects of two types of breaks (expected versus unexpected), and two distinct forms of unexpected breaks, and find that unexpected breaks can, under certain conditions, yield immediate post-break performance increases. We test our hypotheses using productivity data from 212 fruit harvesters collected over one harvesting season yielding nearly 250,000 truckloads of fruit harvested over the course of 9,832 shifts. We provide a conceptual laboratory replication of these findings, showing that unexpected breaks lead to increased performance when they allow people to maintain attention on the focal task. Our results suggest that the characteristics of a break can lead the break to be experienced as an interruption, with all consequent negative outcomes, or as a rejuvenating and experience, with positive post-break consequences.

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We estimate the causal effects of responsible scheduling practices on store financial performance at the U.S. retailer Gap, Inc. The randomized field experiment evaluated a multicomponent intervention designed to improve dimensions of work schedules—consistency, predictability, adequacy, and employee control—shown to foster employee well-being. The experiment was conducted in 28 stores in the San Francisco and Chicago metropolitan areas for nine months between November 2015 and August 2016. Intent-to-treat (ITT) analyses indicate that implementing responsible scheduling practices increased store productivity by 5.1%, a result of increasing sales (by 3.3%) and decreasing labor (by 1.8%). Drawing on qualitative interviews with managers and quantitative analyses of employee shift-level data, we offer evidence that the intervention improved financial performance through improved store execution. Our experiment provides evidence that responsible scheduling practices that take worker well-being into account can enhance store productivity by motivating additional employee effort and reducing barriers to employees adhering to the scheduled labor plan. This paper was accepted by David Simchi-Levi, operations management.

Problem definition: We examine the impact of four classes of workplace interruptions on short-term (working hours) and long-term (across-shifts) worker performance in an agribusiness setting. The interruptions are organized in a two-by-two framework in which they result (or do not result) in a physical task requirement and lead to a varying degree of attention shift from the primary task. Academic/practical relevance: Prior operations management literature primarily examines the long-term effects of a single class of interruption that reduces performance. Our study contributes to this literature by examining multiple classes of interruptions that lead to positive and negative outcomes over the short-term in addition to the long-term. Further, our study also contributes to understanding the impact of general task transitions (interruptions) on worker performance, and the interrupting tasks include tasks that are not part of workers’ primary job duties. Our study is relevant to work settings that envelop high manual labor and experience interruptions regularly. Finally, we offer strategies to improve operational performance. Methodology: Using a granular data set on worker productivity from 211 harvesters yielding 117,581 truckloads of fruit harvested for 9,819 worker shifts, we utilize an instrumental variable approach with two-stage residual inclusion estimation on a mix of linear and nonlinear models to examine and quantify the impact of interruptions on both short- and long-term worker productivity. Results: We identify a new interruption class, a pause—interruptions that provide the physical respite and limit the degree of attention shift from the primary task. We find that pauses improve worker productivity in the short- and long-term. Next, we find that scheduled breaks hurt (improve) the worker’s productivity in the short-term (long-term). Finally, we find that harvester breakdown and travel across field interruptions that drain physical resources and cause attention shift hurt worker productivity in the short- and long-term. We quantify the impact (in our field context) of a five-minute increase in each of these work interruptions on average worker productivity. Managerial implications: Our study demonstrates that various work interruptions can have positive or negative effects on workers’ productivity. We suggest that introducing brief pauses in a workday and simultaneously reminding (before initiating the pause) employees about the tasks yet to be completed or goals to be achieved for the rest of the shift can help maintain their focus on the work and yield high-performance benefits. We also suggest strategies that limit the restart costs and increase the predictability of interruptions that hurt performance. For example, in regards to scheduled breaks, planning the break after completing a subtask or reaching a subgoal can limit their adverse effects. Further, informing workers on the possibility of interruption circumstances at the beginning of the work shift can help them plan for these events and improve engagement and performance on the primary job.

Problem definition: We examine the impact of logistics performance metrics such as delivery time and customer’s requested delivery speed on logistics service ratings and third-party sellers’ sales on an e-commerce platform. Academic/practical relevance: Although e-commerce retailers like Amazon have recently invested heavily in their logistics networks to provide faster delivery to customers, there is scant academic literature that tests and quantifies the premise that convenient and fast delivery will drive sales. In this paper, we provide empirical evidence on whether this relationship holds in practice by analyzing a mechanism that connects delivery performance to sales through logistics ratings. Prior academic work on online ratings in e-commerce platforms has mostly analyzed customers’ response to product functional performance and biases that exist within. Our study contributes to this stream of literature by examining customer experience from a service quality perspective by analyzing logistics service performance, logistics ratings, and its impact on customer purchase probability and sales. Methodology: Using an extensive data set of more than 15 million customer orders on the Tmall platform and Cainiao network (logistics arm of Alibaba), we use the Heckman ordered regression model to explain the variation in customers’ rating of logistics performance and the likelihood of customers posting a logistics rating. Next, we develop a generic customer choice model that links the customer’s likelihood of making a purchase to the logistics ratings provided by prior customers. We implement a two-step estimation of the choice model to quantify the impact of logistics ratings on customer purchase probability and third-party seller sales. Results: We surprisingly find that even customers with no promise on delivery speed are likely to post lower logistics ratings for delivery times longer than two days. Although these customers are not promised an explicit delivery deadline, they seem to have a mental threshold of two days and expect deliveries to be made within that time. Similarly, we find that priority customers (those with two-day and one-day promise speed) provide lower logistics ratings for delivery times longer than their anticipated delivery date. We estimate that reducing the delivery time of all three-day delivered orders on this platform (which makeup [Formula: see text] 35% of the total orders) to two days would improve the average daily third-party seller sales by 13.3% on this platform. The impact of delivery time performance on sales is more significant for sellers with a higher percentage of three-day delivered orders and a higher spend per order. Managerial implications: Our study emphasizes that delivery performance and logistics ratings, which measure service quality, are essential drivers of the customer purchase decision on e-commerce platforms. Furthermore, by quantifying the impact of delivery time performance on sales, our study also provides a framework for online retailers to assess if the increase in sales because of improved logistics performance can offset the increase in additional infrastructure costs required for faster deliveries. Our study’s insights are relevant to third-party sellers and e-commerce platform managers who aim to improve long-term online customer traffic and sales.