Multitasking can be a problem

By Paul Walker 27/11/2013


One thing theory tells us about multitasking is that you can get into trouble if some of the things you want people to do are easier to measure than other things. What you would expect is that the people will put more effort into the well measured things than the less well measured things. For example, teaching is harder to measure well than research so you would expect to see more effort placed on research than teaching in academia. And, by and large, you do.

But according to a new NBER working paper it’s not just academics who respond to such incentives.

Testing the Theory of Multitasking: Evidence from a Natural Field Experiment in Chinese Factories
Fuhai Hong, Tanjim Hossain, John A. List, Migiwa Tanaka
NBER Working Paper No. 19660
Issued in November 2013

A well-recognized problem in the multitasking literature is that workers might substantially reduce their effort on tasks that produce unobservable outputs as they seek the salient rewards to observable outputs. Since the theory related to multitasking is decades ahead of the empirical evidence, the economic costs of standard incentive schemes under multitasking contexts remain largely unknown. This study provides empirical insights quantifying such effects using a field experiment in Chinese factories. Using more than 2200 data points across 126 workers, we find sharp evidence that workers do trade off the incented output (quantity) at the expense of the non-incented one (quality) as a result of a piece rate bonus scheme. Consistent with our theoretical model, treatment effects are much stronger for workers whose base salary structure is a flat wage compared to those under a piece rate base salary. While the incentives result in a large increase in quantity and a sharp decrease in quality for workers under a flat base salary, they result only in a small increase in quantity without affecting quality for workers under a piece rate base salary.