Automation Enables Specialization: Field Evidence

Jie Gong () and I. P. L. Png ()
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Jie Gong: Faculty of Business and Economics, The University of Hong Kong, Pokfulam, Hong Kong
I. P. L. Png: National University of Singapore Business School, National University of Singapore, 119245 Singapore

Management Science, 2024, vol. 70, issue 3, 1580-1595

Abstract: Becker and Murphy proposed that task specialization raises productivity but is limited by the costs of coordinating workers. We propose that automation enables workers to specialize without coordination costs. To the extent that the cost of effort exhibits increasing differences, workers increase effort in nonautomated tasks and productivity. The proposition is supported by a field experiment among supermarket cashiers. Conventionally, supermarket cashiers perform two tasks: scanning purchases and collecting payment. Cashiers exhibited increasing differences in the cost of effort: when they scanned faster, they took longer to collect payments. We rotated cashiers between the conventional job design and one in which they specialized in scanning. The new job design increased cashier productivity in scanning by more than 10%. The faster scanning was not due to customer sorting or cashier learning. The proposition is also validated by a survey of taxi drivers. Drivers who reported that difficulties in finding their way affected their driving were more likely to use map apps.

Keywords: automation; job design; task specialization; productivity (search for similar items in EconPapers)
Date: 2024
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