Hawthorne effect – definition and meaning

The Hawthorne effect is an observation that recognition and show of concern affect employees significantly. In fact, they affect workers’ productivity by at least as much as or more than their work conditions. It is a type of reactivity in which people modify an aspect of their behavior when they know that somebody is observing them. Some say the term refers to our tendency to work harder and perform better when we are participating in an experiment.

We also refer to it as the observer effect.

In other words, people may alter their behavior due to the attention they are receiving rather than because of better conditions. Specifically, the attention workers are receiving comes from the researchers in an experiment.

VeryWell.com says the following regarding the term:

“The Hawthorne effect is a term referring to the tendency of some people to work harder and perform better when they are participants in an experiment.”

“Individuals may change their behavior due to the attention they are receiving from researchers rather than because of any manipulation of independent variables.”

Since the 1930s, psychologists have been writing extensively about the Hawthorne effect. The theme is common in industrial and organizational psychology textbooks and journals.

Hawthorne Effect - definition and images
Ever since the middle of the last century, experts have been criticizing the Hawthorne effect. Richard Nisbett, a social psychology professor at the University of Michigan at Ann Arbor, described it as a ‘glorified anecdote.’

Hawthorne effect – George Elton Mayo

Productivity researcher George Elton Mayo (1880-1949) first observed the effect at the Hawthorne (Illinois) plant of Western Electric Company. Mayo also pioneered the treatment of shell-shock, i.e., post traumatic stress disorder or PTSD.

Productivity refers to how much each worker produces per hour, day, week, etc.

He observed the Hawthorne effect while assessing the effects of working conditions from 1927 to 1933.

Mayo reported that the performance of workers improved when management showed concern for their problems. In fact, when that concern was evident, their productivity increased regardless of their working conditions.

Mayo’s research and experiments marked a sea change in thinking about productivity and work.

Mayo’s experiments

Mayo initially wanted to carry out experiments to determine the effects of physical conditions on worker productivity.

His study participants, i.e., his guinea pigs, were placed into one of two groups.

In one group, he improved the lighting in their work area significantly. In the other group, however, the lighting remained the same. He called the second group the control group.

Mayo and colleagues found that productivity improved considerably more in the ‘better-lighting’ group than in the control group.

The researchers subsequently changed other features of their working conditions. For example, they changed their working hours, rest breaks, etc.

Every time a change was made, there was an improvement in productivity. However, when conditions returned to how they were initially, productivity at the plant continued to be very high. In fact, it was higher than it had ever been. Absenteeism, for example, had plummeted.

Mayo and colleagues concluded that researcher concern for the workers was the driving factor behind the productivity increase. The changes in physical conditions were not the main drivers of improvement.

Mayo wrote:

“The desire to stand well with one’s fellows, the so-called human instinct of association, easily outweighs the merely individual interest and the logic of reasoning upon which so many spurious principles of management are based.”

Researcher Henry A. Landsberger first described the effect in the 1950s after analyzing Mayo’s experiments. In fact, Landsberger coined the term ‘Hawthorne effect.’

Video – Hawthorne effect

This Motion 71 video explains what the Hawthorne effect is and the implications for productivity. It also discusses when monitoring is useful and when it is not.


 

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