Automation, Specialization, and Productivity: Field Evidence

48 Pages Posted: 5 Oct 2020 Last revised: 31 Mar 2022

See all articles by Jie Gong

Jie Gong

National University of Singapore (NUS)

Ivan P. L. Png

National University of Singapore (NUS)

Date Written: March 31, 2022

Abstract

Becker and Murphy (1992) 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 non-automated tasks and productivity. The predicate of increasing differences is supported by a study of taxi drivers: 73 percent of respondents who used map apps reported that, with the app, they could focus on driving and were less tired. The proposition that automation-enabled specialization increases productivity is supported by a field experiment. Conventionally, supermarket cashiers perform two tasks: scanning purchases and collecting payment. 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 over 10 percent.

Keywords: Automation; Job design; Task specialization; Productivity

JEL Classification: D2, O33, J3, J2

Suggested Citation

Gong, Jie and Png, Ivan P. L., Automation, Specialization, and Productivity: Field Evidence (March 31, 2022). Available at SSRN: https://ssrn.com/abstract=3597725 or http://dx.doi.org/10.2139/ssrn.3597725

Jie Gong

National University of Singapore (NUS) ( email )

1E Kent Ridge Road
NUHS Tower Block Level 7
Singapore, 119228
Singapore

Ivan P. L. Png (Contact Author)

National University of Singapore (NUS) ( email )

Singapore, 117543
Singapore
+65 6516-6807 (Phone)

HOME PAGE: http://sites.google.com/site/iplpng/

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