Automation Enables Specialization: Field Evidence
通过超市收银员实地实验和出租车司机调查，发现自动化使工人无需协调成本即可专业化，从而提升非自动化任务的生产率。
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. This paper was accepted by Alfonso Gambardella, business strategy. Funding: This work was supported by the Singapore Ministry of Education [MOE2016-SSRTG-059]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4760 .