Improving Scheduling in Entry-Level Retail Jobs: A Workplace-Based Experiment

Awarded Scholars:
Julia R. Henly, University of Chicago
Susan J. Lambert, University of Chicago
Project Date:
Nov 2005
Award Amount:
Project Programs:
Future of Work

The Foundation sparked much debate with the release of Low-Wage America, which suggested that firms employing "high-road" employment strategies could be just as successful as firms that relied mainly on low-cost, low-quality labor. Some critics have suggested that high-road firms may benefit from unobserved advantages that make it possible for them to compete despite their higher wage costs. The best way to test this claim is through an experimental design. Therefore, the Foundation is supporting a research project by Julia R. Henly and Susan J. Lambert.


Henly and Lambert have persuaded a chain of clothing stores to systematically vary the amount of advanced notice that store managers give to employees about work schedules. They predict that scheduling working hours four weeks in advance, instead of the current practice of scheduling one week in advance, will reduce collisions between family and work commitments, make it possible for workers to arrange for higher quality childcare, reduce stress, cut absenteeism, and improve worker attitudes and productivity. The advanced notice system will also increase the degree to which work schedules are responsive to employee preferences, allowing workers greater flexibility and control in managing their time. Information about sales volume, labor costs, absenteeism, and turnover will be obtained from administrative data at each store to test the hypothesis that advanced scheduling and increased employee flexibility will have a positive impact on the bottom line. Henly and Lambert will also conduct telephone surveys of workers at both control and experimental stores to gauge their opinion of their work schedules. The results of the project will be published in a set of papers that target academic, policy, and employer audiences.


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