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Hawthorne Effect: Definition, How It Works, and How to Avoid It

Ayesh Perera

B.A, MTS, Harvard University

Ayesh Perera, a Harvard graduate, has worked as a researcher in psychology and neuroscience under Dr. Kevin Majeres at Harvard Medical School.

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Key Takeaways

• The Hawthorne effect refers to the increase in the performance of individuals who are noticed, watched, and paid attention to by researchers or supervisors.
• In 1958, Henry A. Landsberger coined the term ‘Hawthorne effect’ while evaluating a series of studies at a plant near Chicago, Western Electric’s Hawthorne Works.
• The novelty effect, demand characteristics and feedback on performance may explain what is widely perceived as the Hawthorne effect.
• Although the possible implications of the Hawthorne effect remain relevant in many contexts, recent research findings challenge many of the original conclusions concerning the phenomenon.

The Hawthorne effect refers to a tendency in some individuals to alter their behavior in response to their awareness of being observed (Fox et al., 2007).

This phenomenon implies that when people become aware that they are subjects in an experiment, the attention they receive from the experimenters may cause them to change their conduct.

Hawthorne Studies

The Hawthorne effect is named after a set of studies conducted at Western Electric’s Hawthorne Plant in Cicero during the 1920s. The Scientists included in this research team were Elton Mayo (Psychologist), Roethlisberger and Whilehead (Sociologists), and William Dickson (company representative).

There are 4 separate experiments in Hawthorne Studies:

Illumination Experiments (1924-1927) Relay Assembly Test Room Experiments (1927-1932) Experiments in Interviewing Workers (1928- 1930) Bank Wiring Room Experiments (1931-1932)

The Hawthorne Experiments, conducted at Western Electric’s Hawthorne plant in the 1920s and 30s, fundamentally influenced management theories.

They highlighted the importance of psychological and social factors in workplace productivity, such as employee attention and group dynamics, leading to a more human-centric approach in management practices.

Illumination Experiment

The first and most influential of these studies is known as the “Illumination Experiment”, conducted between 1924 and 1927 (sponsored by the National Research Council).

The company had sought to ascertain whether there was a relationship between productivity and the work environments (e.g., the level of lighting in a factory).

During the first study, a group of workers who made electrical relays experienced several changes in lighting. Their performance was observed in response to the minutest alterations in illumination.

What the original researchers found was that any change in a variable, such as lighting levels, led to an improvement in productivity. This was true even when the change was negative, such as a return to poor lighting.

However, these gains in productivity disappeared when the attention faded (Roethlisberg & Dickson, 1939). The outcome implied that the increase in productivity was merely the result of a motivational effect on the company’s workers (Cox, 2000).

Their awareness of being observed had apparently led them to increase their output. It seemed that increased attention from supervisors could improve job performance.

Hawthorne Experiment by Elton Mayo

Relay assembly test room experiment.

Spurred by these initial findings, a series of experiments were conducted at the plant over the next eight years. From 1928 to 1932, Elton Mayo (1880–1949) and his colleagues began a series of studies examining changes in work structure (e.g., changes in rest periods, length of the working day, and other physical conditions.) in a group of five women.

The results of the Elton Mayo studies reinforced the initial findings of the illumination experiment. Freedman (1981, p. 49) summarizes the results of the next round of experiments as follows:

“Regardless of the conditions, whether there were more or fewer rest periods, longer or shorter workdays…the women worked harder and more efficiently.”

Analysis of the findings by Landsberger (1958) led to the term the Hawthorne effect , which describes the increase in the performance of individuals who are noticed, watched, and paid attention to by researchers or supervisors.

Bank Wiring Observation Room Study

In a separate study conducted between 1927 and 1932, six women working together to assemble telephone relays were observed (Harvard Business School, Historical Collections).

Following the secret measuring of their output for two weeks, the women were moved to a special experiment room. The experiment room, which they would occupy for the rest of the study, had a supervisor who discussed various changes to their work.

The subsequent alterations the women experienced included breaks varied in length and regularity, the provision (and the non-provision) of food, and changes to the length of the workday.

For the most part, changes to these variables (including returns to the original state) were accompanied by an increase in productivity.

The researchers concluded that the women’s awareness of being monitored, as well as the team spirit engendered by the close environment improved their productivity (Mayo, 1945).

Subsequently, a related study was conducted by W. Lloyd Warner and Elton Mayo, anthropologists from Harvard (Henslin, 2008).

They carried out their experiment on 14 men who assembled telephone switching equipment. The men were placed in a room along with a full-time observer who would record all that transpired. The workers were to be paid for their individual productivity.

However, the surprising outcome was a decrease in productivity. The researchers discovered that the men had become suspicious that an increase in productivity would lead the company to lower their base rate or find grounds to fire some of the workers.

Additional observation unveiled the existence of smaller cliques within the main group. Moreover, these cliques seemed to have their own rules for conduct and distinct means to enforce them.

The results of the study seemed to indicate that workers were likely to be influenced more by the social force of their peer groups than the incentives of their superiors.

This outcome was construed not necessarily as challenging the previous findings but as accounting for the potentially stronger social effect of peer groups.

Hawthorne Effect Examples

Managers in the workplace.

The studies discussed above reveal much about the dynamic relationship between productivity and observation.

On the one hand, letting employees know that they are being observed may engender a sense of accountability. Such accountability may, in turn, improve performance.

However, if employees perceive ulterior motives behind the observation, a different set of outcomes may ensue. If, for instance, employees reason that their increased productivity could harm their fellow workers or adversely impact their earnings eventually, they may not be actuated to improve their performance.

This suggests that while observation in the workplace may yield salutary gains, it must still account for other factors such as the camaraderie among the workers, the existent relationship between the management and the employees, and the compensation system.

A study that investigated the impact of awareness of experimentation on pupil performance (based on direct and indirect cues) revealed that the Hawthorne effect is either nonexistent in children between grades 3 and 9, was not evoked by the intended cues, or was not sufficiently strong to alter the results of the experiment (Bauernfeind & Olson, 1973).

However, if the Hawthorne effect were actually present in other educational contexts, such as in the observation of older students or teachers, it would have important implications.

For instance, if teachers were aware that they were being observed and evaluated via camera or an actual person sitting inside the class, it is not difficult to imagine how they might alter their approach.

Likewise, if older students were informed that their classroom participation would be observed, they might have more incentives to pay diligent attention to the lessons.

Alternative Explanations

Despite the possibility of the Hawthorne effect and its seeming impact on performance, alternative accounts cannot be discounted.

The Novelty Effect

The Novelty Effect denotes the tendency of human performance to show improvements in response to novel stimuli in the environment (Clark & Sugrue, 1988). Such improvements result not from any advances in learning or growth, but from a heightened interest in the new stimuli.

Demand Characteristics

Demand characteristics describe the phenomenon in which the subjects of an experiment would draw conclusions concerning the experiment’s objectives, and either subconsciously or consciously alter their behavior as a result (Orne, 2009). The intentions of the participant—which may range from striving to support the experimenter’s implicit agenda to attempting to utterly undermine the credibility of the study—would play a vital role herein.

Feedback on Performance

It is possible for regular evaluations by the experimenters to function as a scoreboard that enhances productivity. The mere fact that the workers are better acquainted with their performance may actuate them to increase their output.

Despite the seeming implications of the Hawthorne effect in a variety of contexts, recent reviews of the initial studies seem to challenge the original conclusions.

For instance, the data from the first experiment were long thought to have been destroyed. Rice (1982) notes that “the original [illumination] research data somehow disappeared.”

Gale (2004, p. 439) states that “these particular experiments were never written up, the original study reports were lost, and the only contemporary account of them derives from a few paragraphs in a trade journal.”

However, Steven Levitt and John List of the University of Chicago were able to uncover and evaluate these data (Levitt & List, 2011). They found that the supposedly notable patterns were entirely fictional despite the possible manifestations of the Hawthorne effect.

They proposed excess responsiveness to variations induced by the experimenter, relative to variations occurring naturally, as an alternative means to test for the Hawthorne effect.

Another study sought to determine whether the Hawthorne effect actually exists, and if so, under what conditions it does, and how large it could be (McCambridge, Witton & Elbourne, 2014).

Following the systemic review of the available evidence on the Harthorne effect, the researchers concluded that while research participation may indeed impact the behaviors being investigated, discovering more about its operation, its magnitude, and its mechanisms require further investigation.

How to Reduce the Hawthorne Effect

The credibility of experiments is essential to advances in any scientific discipline. However, when the results are significantly influenced by the mere fact that the subjects were observed, testing hypotheses becomes exceedingly difficult.

As such, several strategies may be employed to reduce the Hawthorne Effect.

Discarding the Initial Observations :

• Participants in studies often take time to acclimate themselves to their new environments.
• During this period, the alterations in performance may stem more from a temporary discomfort with the new environment than from an actual variable.
• Greater familiarity with the environment over time, however, would decrease the effect of this transition and reveal the raw effects of the variables whose impact the experimenters are observing.

Using Control Groups:

• When the subjects experiencing the intervention and those in the control group are treated in the same manner in an experiment, the Hawthorne effect would likely influence both groups equivalently.
• Under such circumstances, the impact of the intervention can be more readily identified and analyzed.
• Where ethically permissible, the concealment of information and covert data collection can be used to mitigate the Hawthorne effect.
• Observing the subjects without informing them, or conducting experiments covertly, often yield more reliable outcomes. The famous marshmallow experiment at Stanford University, which was conducted initially on 3 to 5-year-old children, is a striking example.

Frequently Asked Questions

What did the researchers, who identified the hawthorne effect, see as evidence that employee performance was influenced by something other than the physical work conditions.

The researchers of the Hawthorne Studies noticed that employee productivity increased not only in improved conditions (like better lighting), but also in unchanged or even worsened conditions.

They concluded that the mere fact of being observed and feeling valued (the so-called “Hawthorne Effect”) significantly impacted workers’ performance, independent from physical work conditions.

What is the Hawthorne effect in simple terms?

The Hawthorne Effect is when people change or improve their behavior because they know they’re being watched.

It’s named after a study at the Hawthorne Works factory, where researchers found that workers became more productive when they realized they were being observed, regardless of the actual working conditions.

Bauernfeind, R. H., & Olson, C. J. (1973). Is the Hawthorne effect in educational experiments a chimera ? The Phi Delta Kappan, 55 (4), 271-273.

Clark, R. E., & Sugrue, B. M. (1988). Research on instructional media 1978-88. In D. Ely (Ed.), Educational Media and Technology Yearbook, 1994. Volume 20. Libraries Unlimited, Inc., PO Box 6633, Englewood, CO 80155-6633.

Cox, E. (2001).  Psychology for A-level . Oxford University Press.

Fox, N. S., Brennan, J. S., & Chasen, S. T. (2008). Clinical estimation of fetal weight and the Hawthorne effect. European Journal of Obstetrics & Gynecology and Reproductive Biology, 141 (2), 111-114.

Gale, E.A.M. (2004). The Hawthorne studies – a fable for our times? Quarterly Journal of Medicine, (7) ,439-449.

Henslin, J. M., Possamai, A. M., Possamai-Inesedy, A. L., Marjoribanks, T., & Elder, K. (2015). Sociology: A down to earth approach . Pearson Higher Education AU.

Landsberger, H. A. (1958). Hawthorne Revisited : Management and the Worker, Its Critics, and Developments in Human Relations in Industry.

Levitt, S. D., & List, J. A. (2011). Was there really a Hawthorne effect at the Hawthorne plant? An analysis of the original illumination experiments. American Economic Journal: Applied Economics, 3 (1), 224-38.

Mayo, E. (1945). The human problems of an industrial civilization . New York: The Macmillan Company.

McCambridge, J., Witton, J., & Elbourne, D. R. (2014). Systematic review of the Hawthorne effect: new concepts are needed to study research participation effects. Journal of Clinical Epidemiology, 67 (3), 267-277.

McCarney, R., Warner, J., Iliffe, S., Van Haselen, R., Griffin, M., & Fisher, P. (2007). The Hawthorne Effect: a randomised, controlled trial. BMC Medical Research Methodology, 7 (1), 1-8.

Rice, B. (1982). The Hawthorne defect: Persistence of a flawed theory. Psychology Today, 16 (2), 70-74.

Orne, M. T. (2009). Demand characteristics and the concept of quasi-controls. Artifacts in behavioral research: Robert Rosenthal and Ralph L. Rosnow’s classic books, 110 , 110-137.

Further Information

• Wickström, G., & Bendix, T. (2000). The” Hawthorne effect”—what did the original Hawthorne studies actually show?. Scandinavian journal of work, environment & health, 363-367.
• Levitt, S. D., & List, J. A. (2011). Was there really a Hawthorne effect at the Hawthorne plant? An analysis of the original illumination experiments. American Economic Journal: Applied Economics, 3(1), 224-38.
• Oswald, D., Sherratt, F., & Smith, S. (2014). Handling the Hawthorne effect: The challenges surrounding a participant observer. Review of social studies, 1(1), 53-73.
• Bloombaum, M. (1983). The Hawthorne experiments: a critique and reanalysis of the first statistical interpretation by Franke and Kaul. Sociological Perspectives, 26(1), 71-88.

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How the Hawthorne Effect Works

Nick David / Getty Images

• Does It Really Exist?

Other Explanations

• How to Avoid It

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.

The term is often used to suggest that individuals may change their behavior due to the attention they are receiving from researchers rather than because of any manipulation of independent variables .

The Hawthorne effect has been widely discussed in psychology textbooks, particularly those devoted to industrial and organizational psychology . However, research suggests that many of the original claims made about the effect may be overstated.

History of the Hawthorne Effect

The Hawthorne effect was first described in the 1950s by researcher Henry A. Landsberger during his analysis of experiments conducted during the 1920s and 1930s.

Why Is It Called the Hawthorne Effect?

The phenomenon is named after the location where the experiments took place, Western Electric’s Hawthorne Works electric company just outside of Hawthorne, Illinois.

The electric company had commissioned research to determine if there was a relationship between productivity and work environments.

The original purpose of the Hawthorne studies was to examine how different aspects of the work environment, such as lighting, the timing of breaks, and the length of the workday , had on worker productivity.

Increased Productivity

In the most famous of the experiments, the focus of the study was to determine if increasing or decreasing the amount of light that workers received would have an effect on how productive workers were during their shifts. In the original study, employee productivity seemed to increase due to the changes but then decreased once the experiment was over.

What the researchers in the original studies found was that almost any change to the experimental conditions led to increases in productivity. For example, productivity increased when illumination was decreased to the levels of candlelight, when breaks were eliminated entirely, and when the workday was lengthened.

The researchers concluded that workers were responding to the increased attention from supervisors. This suggested that productivity increased due to attention and not because of changes in the experimental variables.

Findings May Not Be Accurate

Landsberger defined the Hawthorne effect as a short-term improvement in performance caused by observing workers. Researchers and managers quickly latched on to these findings. Later studies suggested, however, that these initial conclusions did not reflect what was really happening.

The term Hawthorne effect remains widely in use to describe increases in productivity due to participation in a study, yet additional studies have often offered little support or have even failed to find the effect at all.

Examples of the Hawthorne Effect

The following are real-life examples of the Hawthorne effect in various settings:

• Healthcare : One study found that patients with dementia who were being treated with Ginkgo biloba showed better cognitive functioning when they received more intensive follow-ups with healthcare professionals. Patients who received minimal follow-up had less favorable outcomes.
• School : Research found that hand washing rates at a primary school increased as much as 23 percent when another person was present with the person washing their hands—in this study, being watched led to improved performance.
• Workplace : When a supervisor is watching an employee work, that employee is likely to be on their "best behavior" and work harder than they would without being watched.

Does the Hawthorne Effect Exist?

Later research into the Hawthorne effect suggested that the original results may have been overstated. In 2009, researchers at the University of Chicago reanalyzed the original data and found that other factors also played a role in productivity and that the effect originally described was weak at best.

Researchers also uncovered the original data from the Hawthorne studies and found that many of the later reported claims about the findings are simply not supported by the data. They did find, however, more subtle displays of a possible Hawthorne effect.

While some additional studies failed to find strong evidence of the Hawthorne effect, a 2014 systematic review published in the Journal of Clinical Epidemiology found that research participation effects do exist.

After looking at the results of 19 different studies, the researchers concluded that these effects clearly happen, but more research needs to be done in order to determine how they work, the impact they have, and why they occur.

While the Hawthorne effect may have an influence on participant behavior in experiments, there may also be other factors that play a part in these changes. Some factors that may influence improvements in productivity include:

• Demand characteristics : In experiments, researchers sometimes display subtle clues that let participants know what they are hoping to find. As a result, subjects will alter their behavior to help confirm the experimenter’s  hypothesis .
• Novelty effects : The novelty of having experimenters observing behavior might also play a role. This can lead to an initial increase in performance and productivity that may eventually level off as the experiment continues.
• Performance feedback : In situations involving worker productivity, increased attention from experimenters also resulted in increased performance feedback. This increased feedback might actually lead to an improvement in productivity.

While the Hawthorne effect has often been overstated, the term is still useful as a general explanation for psychological factors that can affect how people behave in an experiment.

How to Reduce the Hawthorne Effect

In order for researchers to trust the results of experiments, it is essential to minimize potential problems and sources of bias like the Hawthorne effect.

So what can researchers do to minimize these effects in their experimental studies?

• Conduct experiments in natural settings : One way to help eliminate or minimize demand characteristics and other potential sources of experimental bias is to utilize naturalistic observation techniques. However, this is simply not always possible.
• Make responses completely anonymous : Another way to combat this form of bias is to make the participants' responses in an experiment completely anonymous or confidential. This way, participants may be less likely to alter their behavior as a result of taking part in an experiment.
• Get familiar with the people in the study : People may not alter their behavior as significantly if they are being watched by someone they are familiar with. For instance, an employee is less likely to work harder if the supervisor watching them is always watching.

Many of the original findings of the Hawthorne studies have since been found to be either overstated or erroneous, but the term has become widely used in psychology, economics, business, and other areas.

More recent findings support the idea that these effects do happen, but how much of an impact they actually have on results remains in question. Today, the term is still often used to refer to changes in behavior that can result from taking part in an experiment.

Schwartz D, Fischhoff B, Krishnamurti T, Sowell F. The Hawthorne effect and energy awareness .  Proc Natl Acad Sci U S A . 2013;110(38):15242-15246. doi:10.1073/pnas.1301687110

McCambridge J, Witton J, Elbourne DR. Systematic review of the Hawthorne effect: New concepts are needed to study research participation effects .  J Clin Epidemiol . 2014;67(3):267-277. doi:10.1016/j.jclinepi.2013.08.015

Letrud K, Hernes S. Affirmative citation bias in scientific myth debunking: A three-in-one case study . Bornmann L, ed. PLoS ONE. 2019;14(9):e0222213. doi:10.1371/journal.pone.0222213

McCarney R, Warner J, Iliffe S, van Haselen R, Griffin M, Fisher P. The Hawthorne effect: a randomised, controlled trial .  BMC Med Res Methodol . 2007;7:30. doi:10.1186/1471-2288-7-30

Pickering AJ, Blum AG, Breiman RF, Ram PK, Davis J. Video surveillance captures student hand hygiene behavior, reactivity to observation, and peer influence in Kenyan primary schools . Gupta V, ed. PLoS ONE. 2014;9(3):e92571. doi:10.1371/journal.pone.0092571

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• What Is the Hawthorne Effect? | Definition & Examples

What Is the Hawthorne Effect? | Definition & Examples

Published on September 23, 2022 by Kassiani Nikolopoulou . Revised on November 18, 2022.

The Hawthorne effect refers to people’s tendency to behave differently when they become aware that they are being observed. As a result, what is observed may not represent “normal” behavior, threatening the internal and external validity of your research.

The Hawthorne effect is also known as the observer effect and is closely linked with observer bias .

Like other types of research bias , the Hawthorne effect often occurs in observational and experimental study designs in fields like medicine, organizational psychology, and education.

Table of contents

What is the hawthorne effect, example of the hawthorne effect, criticism of the hawthorne effect, other explanations of the hawthorne effect, how to reduce the hawthorne effect, other types of research bias, frequently asked questions about research bias.

The Hawthorne effect occurs when a participant’s behavior changes as a result of being observed, rather than as a result of an intervention.

In other words, when groups or individuals realize they are being observed, they may change their behavior. This change can be positive or negative, depending on the research context. For example, people participating in a nutrition-related experiment may improve their diet solely because they are taking part in the experiment.

It’s important to note that participants must be aware that they are under observation for this effect to occur. Thus, the Hawthorne effect is a subtype of performance bias. 

Initially, results suggested that productivity improved whenever any changes to those variables were made—including negative changes like reduced lighting. However, any change in productivity disappeared when the experiments stopped.

Changes in behavior attributed to Hawthorne effect can seriously distort your conclusions, especially in terms of any assertions made about causal relationships between variables. This affects the internal validity of the study.

Relatedly, a Hawthorne effect can also compromise your ability to make generalizations. This affects the external validity of your study.

In the follow-up visit, the patient appears worse. The doctor has read many published Alzeheimer’s medication trials where patients who were prescribed active medication (i.e., not a placebo ) often appeared better or more stable. Due to this, the doctor concludes that if the patient is worse, then it has to be a treatment failure. The doctor then decides to stop the medication.

However, the doctor hasn’t taken into account the possible impact of a Hawthorne effect on trial results. People participating in clinical trials often appear to do better than those in routine practice solely because of their participation in the study. In reality, the increased attention and interaction with doctors and nurses at regular intervals may be what leads to their better health outcomes.

Recent research into the original studies at Hawthorne Works has shown that the findings were flawed or overstated. In particular, significant differences between control groups and experimental groups led to the introduction of confounding variables that experimenters were unaware of at the time. It is highly likely that other factors also played a role in the original study.

Ultimately, it may be hard to determine exactly how participant awareness impacts study results. However, researchers must keep this in mind when designing studies or interpreting results with human-centered research.

There are a few other factors to keep in mind that can also explain behavioral changes in study participants. These include:

Performance feedback

Demand characteristics, novelty effect.

Participants who receive feedback may also have improved performance. For instance, in the context of employee productivity, increased attention from researchers can result in increased productivity. In other words, employees with regular access to information about their individual daily output or performance may perform differently to those who don’t.

Demand characteristics are subtle cues that can reveal the study’s research objectives to the participants. This awareness may lead them to change their behavior. For example, participants may feel motivated to please the researcher.

A temporary improvement in performance resulting from participation in a research study for the first time is known as a novelty effect. This improvement can also occur when a new element, technology, feature, or process is introduced into an experimental setting.

Because participants are unfamiliar with the new element, increased interest can result in an initial increase in performance or productivity. For example, students often perform better when a learning experience is new. However, the novelty effect wears off with time.

The Hawthorne effect cannot be entirely avoided in research using participant observation or experimental research . However, there are a few things you can do to reduce it:

• Invest in interpersonal relationships at the study site. Sustaining contact with participants over time reduces participant reactivity and improves the quality of data collection .
• Give participants tasks unrelated to the purposes of the study. This can mask the research objectives from the participants. However, be sure to consider whether this is ethical to do.
• Whenever possible, opt for a naturalistic or covert observation. In this way, you can observe people in their natural surroundings without being seen. The downside here is that your ability to draw conclusions about causal relationships or generalize to other contexts is limited. There are also implications for participant privacy and informed consent here.

Cognitive bias

• Confirmation bias
• Baader–Meinhof phenomenon

Selection bias

• Sampling bias
• Ascertainment bias
• Attrition bias
• Self-selection bias
• Survivorship bias
• Nonresponse bias
• Undercoverage bias
• Hawthorne effect
• Observer bias
• Omitted variable bias
• Publication bias
• Pygmalion effect
• Recall bias
• Social desirability bias
• Placebo effect

There are seven threats to external validity : selection bias , history, experimenter effect, Hawthorne effect , testing effect, aptitude-treatment and situation effect.

Performance bias is a general term describing the effects of unequal treatment between study groups. As a result, study participants alter their behavior. There are two subtypes of performance bias—namely, the Hawthorne (or observer) effect and the John Henry effect.

In research, demand characteristics are cues that might indicate the aim of a study to participants. These cues can lead to participants changing their behaviors or responses based on what they think the research is about.

Demand characteristics are common problems in psychology experiments and other social science studies because they can cause a bias in your research findings .

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Hawthorne Effect (Definition + Examples)

Interested in learning about the Hawthorne Effect for your psychology class, or just because you're curious? You've come to the right place!

What Is The Hawthorne Effect? 

The Hawthorne Effect, also known as the observer-expectancy effect, is the idea that people change or modify their behaviors when they are being observed. Researchers theorize that researchers may skew the results or interpret it incorrectly due to the Hawthorne Effect. The Hawthorne Effect doesn’t just affect participants.

Observation may become a variable of its own that researchers have to account for when setting up or conducting a study.

How was the Hawthorne Effect Discovered?

Say you’re working in a factory. Do you think that increased light throughout the factory would make you more productive? What about decreased light throughout the factory? 

Do you think you would be more productive with  more  working hours in a day? Or would you be more productive with fewer working hours? 

Do you think that longer breaks would make you more productive? Or would shorter breaks make you more productive? 

These are some of the questions that researchers asked themselves in the 1920s. They conducted a study to see whether or not workers in an electric factory would be more productive under certain conditions. And the answers were surprising. No matter how they altered the conditions of the workplace, the workers were more productive. 

This phenomenon became known as the Hawthorne Effect, named after the Hawthorne Works electric factory where the studies were conducted. 

Causes of Hawthorne Effect 

Why does this happen? The answers may vary based on the context of the study. Take productivity studies. During the Hawthorne studies, it’s possible that the workers received feedback on their productivity as part of the study. That extra observation and feedback could play into increased productivity. 

Demand Effect

Another explanation is that the demand effect comes into play. The participants may have wanted to please the experimenters by giving them the results they wanted to see. This means working harder, even when variables like working hours or lighting is changed in ways that might contradict the original hypothesis. 

Yet another explanation may lie in the participants’ explanation for the study in the first place. Throughout the Hawthorne studies, participants started to grow wary of the researchers’ motives. They worried that the study may result in layoffs. This fear could have serious effects on motivation . 

The Clever Hans Effect

One last cause of the Hawthorne Effect involves a study that involves humans and a horse. If the experiments or observers are aware of the desired effect of the study, they might unintentionally skew the results. In the early 1900s, Wilhelm von Osten claimed that his horse, Clever Hans, could answer arithmetic questions. A German psychologist went to study this horse and see if the owner was actually a fraud. While fraud was not involved, the psychologist observed something interesting. If the owner was present or knew the answers to the arithmetic questions, the horse was able to answer correctly 89% of the time. If the owner was not present or didn’t know the answer, the horse only answered correctly 6% of the time. 

Further studies on the Clever Hans effect show that drug-sniffing dogs and humans are likely to produce a certain result if the experimenters, owners, or observers in the room know what result is desired. 

Real-Life Examples of the Hawthorne Effect

There have been many replication studies aimed at proving or disproving the presence of the Hawthorne Effect. Not all of them have confirmed the existence of the Hawthorne Effect, especially to the degree that was described in the original Hawthorne studies. But some studies do give some validity to the Hawthorne Effect and how it may change the results of different research studies. 

Example 1: Studies on Rheumatoid Arthritis

A study from the  American College of Rheumatology showed that the Hawthorne Effect may have played a role in the results of a study on rheumatoid arthritis. Researchers measured the subjects’ conditions before, during, and after the trial. No matter what variables were brought into the study, the conditions of the patients improved. Once the study was over, the conditions worsened. 

This goes to show that while the Hawthorne Effect has been a part of productivity and human behavior studies, it could also affect the results of studies in the medical world. 

Example 2: Cerebral Palsy Patients 

Contradicting data can show the Hawthorne Effect in action. In the 1970s, a study aimed to see whether or not a treatment would reduce motor dysfunction in patients with cerebral palsy. The researchers recorded testimony from the patients about the result of the treatment and quantitative data based on different tests. As it turned out, the qualitative and quantitative data contradicted each other. The patients said that the treatment worked for them, but the results from the tests showed otherwise. This could support the idea that motives, the demand effect, and the compliance bias could all play into the results of a study. 

Example 3: Clinical Trials 

When subjects are recruited for a clinical trial, they may be forbidden from leaving the hospital or research facility where the test is taking place. Some researchers believe that not only does the Hawthorne Effect take place here, but also an effect called the trial effect. In addition to the modifications in behavior caused by the observers, subjects may also be affected by the level of care in the facility. In addition, they may be more likely to comply with the researchers, and that compliance could affect results. 

Example 4: The Hawthorne Effect in League of Legends

On Reddit, u/redditmademeregister shared how they feel the Hawthorne Effect appears in League of Legends: 

"Ten internet meme points to Gryffindor to whomever guessed that someone from Riot was in our game. Just the simple of act of being there and observing the game in all phases eliminated all toxicity that was in abundant and dare I say common in every other game. This reminiscent of how drivers are suddenly on their best behavior when driving around a police office. Changing one's behavior if they are known to be observed is The Hawthorne Effect."

You can read the whole post here .

Why It’s Important to Know About the Hawthorne Effect

In order to study human behavior, researchers often need human subjects. The Hawthorne Effect is a reminder that humans can be complicated to work with. How can researchers prevent subjects from just giving the answers that researchers might want to hear? How can researchers set up a study to best reflect a “normal” environment, including living or working conditions? And how can this all be done ethically?

These are important questions, and there isn’t one definite answer. But the more that you study psychology and understand setting up studies, the easier it will be to question results and search for the truth.

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Module 6: Motivation in the Workplace

The hawthorne effect, learning outcome.

• Explain the role of the Hawthorne effect in management

During the 1920s, a series of studies that marked a change in the direction of motivational and managerial theory was conducted by Elton Mayo on workers at the Hawthorne plant of the Western Electric Company in Illinois. Previous studies, in particular Frederick Taylor’s work, took a “man as machine” view and focused on ways of improving individual performance. Hawthorne, however, set the individual in a social context, arguing that employees’ performance is influenced by work surroundings and coworkers as much as by employee ability and skill. The Hawthorne studies are credited with focusing managerial strategy on the socio-psychological aspects of human behavior in organizations.

The following video from the AT&T archives contains interviews with individuals who participated in these studies. It provides insight into the way the studies were conducted and how they changed employers’ views on worker motivation.

The studies originally looked into the effects of physical conditions on productivity and whether workers were more responsive and worked more efficiently under certain environmental conditions, such as improved lighting. The results were surprising: Mayo found that workers were more responsive to social factors—such as their manager and coworkers—than the factors (lighting, etc.) the researchers set out to investigate. In fact, worker productivity improved when the lights were dimmed again and when everything had been returned to the way it was before the experiment began, productivity at the factory was at its highest level and absenteeism had plummeted.

What happened was Mayo discovered that workers were highly responsive to additional attention from their managers and the feeling that their managers actually cared about and were interested in their work. The studies also found that although financial incentives are important drivers of worker productivity, social factors are equally important.

Practice Question

There were a number of other experiments conducted in the Hawthorne studies, including one in which two women were chosen as test subjects and were then asked to choose four other workers to join the test group. Together, the women worked assembling telephone relays in a separate room over the course of five years (1927–1932). Their output was measured during this time—at first, in secret. It started two weeks before moving the women to an experiment room and continued throughout the study. In the experiment room, they were assigned to a supervisor who discussed changes with them and, at times, used the women’s suggestions. The researchers then spent five years measuring how different variables affected both the group’s and the individuals’ productivity. Some of the variables included giving two five-minute breaks (after a discussion with the group on the best length of time), and then changing to two ten-minute breaks (not the preference of the group).

Changing a variable usually increased productivity, even if the variable was just a change back to the original condition. Researchers concluded that the employees worked harder because they thought they were being monitored individually. Researchers hypothesized that choosing one’s own coworkers, working as a group, being treated as special (as evidenced by working in a separate room), and having a sympathetic supervisor were the real reasons for the productivity increase.

The Hawthorne studies showed that people’s work performance is dependent on social issues and job satisfaction. The studies concluded that tangible motivators such as monetary incentives and good working conditions are generally less important in improving employee productivity than intangible motivators such as meeting individuals’ desire to belong to a group and be included in decision making and work.

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Hawthorne Effect

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• Renee L. Allen 3 &
• Andrew S. Davis 4  

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A widely accepted definition of the Hawthorne Effect refers to the effects of subjects’ awareness of their evaluation as participants of a research study [ 4 ]. Other definitions include the importance of changes in the work environment (e.g., lighting, rest breaks) while some focus on the resilience of the change in performance. Common variables that can be found in the Hawthorne effect definitions include participants’ interpretation of workplace changes being implemented for their benefit, reference to the response of subjects to change, and the presence of reduced worker boredom [ 2 ]. Researchers who support the phenomenon that is known as the Hawthorne Effect have been criticized for failing to differentiate this concept from subject reactivity to experimental conditions or from the issue of confounding variables in experimental research. Indeed, the original research itself has been deemed methodologically flawed and insufficient to suggest such an effect by some [ 5 ].

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Brannigan, A., & Zwerman, W. (2001). The real “Hawthorne Effect”. Society, 38 , 55–60.

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Chiesa, M., & Hobbs, S. (2008). Making sense of social research: How useful is the Hawthorne Effect? European Journal of Social Psychology, 38 , 67–74.

Mayo, E. (1933). The human problems of an industrial civilization . New York: MacMillan.

Merrett, F. (2006). Reflections on the Hawthorne effect. Educational Psychology, 26 , 143–146.

Olson, R., Verley, J., Santos, L., & Salas, C. (2004). What we teach students about the Hawthorne studies: A review of content within a sample of introductory I-O and OB textbooks. The Industrial-Organizational Psychologist, 41 , 23–39.

Roethlisberger, F. J., & Dickson, W. J. (1939). Management and the worker . Cambridge, MA: Harvard University Press.

Further Readings

Gillespie, R. (1991). Manufacturing knowledge: A history of the Hawthorne experiments . Cambridge, MA: Harvard University Press.

Holden, J. D. (2001). Hawthorne effects and research into professional practice. Journal of Evaluation in Clinical Practice, 7 , 65–70.

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Allen, R.L., Davis, A.S. (2011). Hawthorne Effect. In: Goldstein, S., Naglieri, J.A. (eds) Encyclopedia of Child Behavior and Development. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-79061-9_1324

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The Human Relations Movement:

Harvard business school and the hawthorne experiments (1924-1933).

In the 1920s Elton Mayo, a professor of Industrial Management at Harvard Business School, and his protégé Fritz J. Roethlisberger led a landmark study of worker behavior at Western Electric, the manufacturing arm of AT&T. Unprecedented in scale and scope, the nine-year study took place at the massive Hawthorne Works plant outside of Chicago and generated a mountain of documents, from hourly performance charts to interviews with thousands of employees. Harvard Business School’s role in the experiments represented a milestone in the dawn of the human relations movement and a shift in the study of management from a scientific to a multi-disciplinary approach. Baker Library’s exhaustive archival record of the experiments reveals the art and science of this seminal behavioral study—and the questions and theories it generated about the relationship of productivity to the needs and motivations of the industrial worker.

• The Hawthorne Plant
• Employee Welfare
• Illumination Studies and Relay Assembly Test Room
• Enter Elton Mayo
• Human Relations and Harvard Business School
• Women in the Relay Assembly Test Room
• The Interview Process
• Spreading the Word
• The "Hawthorne Effect"
• Research Links
• Baker Library | Historical Collections | Site Credits | Digital Accessibility
• Contact Email: [email protected]

© President and Fellows of Harvard College

Overview of the Hawthorne Effect

The field of organizational behavior is built on a foundation of research and studies that aim to understand the complexities of human behavior within the workplace. One of the most influential studies in this field is the Hawthorne Studies, conducted at the Western Electric Hawthorne Works in Chicago between 1924 and 1932.

Led by a team of researchers from Harvard Business School , these studies revolutionized the understanding of human behavior in a work setting and continue to shape organizational behavior research today.

The Hawthorne Effect, named after the studies that uncovered it, refers to the phenomenon where individuals modify their behavior simply because they are being observed.

• 1 The Context of the Hawthorne Studies
• 2 The Initial Experiments and Findings
• 3 The Significance of the Hawthorne Studies
• 4 The Legacy of the Hawthorne Effect in Organizational Behavior
• 5.1.1 Benefits and Impact
• 5.1.2 Limitations

The Context of the Hawthorne Studies

The Hawthorne Studies were conducted by a team of researchers from Harvard Business School, including Elton Mayo, Fritz Roethlisberger, and William J. Dickson. Elton Mayo , considered the father of the Hawthorne Studies, played a crucial role in shaping the research and interpreting the findings.

The Hawthorne Studies were originally initiated to examine the relationship between lighting levels and worker productivity. The researchers believed that by increasing lighting levels, they could improve worker efficiency.

However, the results of the initial experiments surprised them. Not only did productivity increase when lighting was increased, but it also increased when lighting was decreased. This unexpected finding prompted further investigations into the psychological and social factors that influence worker motivation and performance.

The Initial Experiments and Findings

The initial experiments of the Hawthorne Studies focused on the relationship between lighting levels and worker productivity. The researchers divided the workers into two groups and manipulated the lighting conditions for each group. Surprisingly, both groups showed increased productivity regardless of whether the lighting was increased or decreased. This phenomenon became known as the “Hawthorne Effect” and led the researchers to delve deeper into the factors that influence worker behavior.

Further experiments were conducted to explore factors such as rest breaks, incentives, and supervisory styles. The researchers found that regardless of the specific changes made, productivity tended to increase. This led to the realization that it was not the specific changes themselves that influenced productivity, but rather the attention given to the workers and the social interactions within the workplace.

The Significance of the Hawthorne Studies

The Hawthorne Studies challenged traditional management theories that focused solely on the technical aspects of work. They demonstrated that the human element within organizations plays a crucial role in productivity and job satisfaction.

The studies highlighted the importance of worker attitudes, group dynamics, and social interactions in influencing employee performance. This shift in perspective paved the way for a greater emphasis on creating supportive and collaborative work environments that prioritize employee well-being and engagement.

The findings of the Hawthorne Studies also led to the development of new management practices. The researchers advocated for a more participative management style that encouraged open communication, employee involvement in decision-making, and a focus on developing positive relationships between managers and workers. These practices aimed to create a sense of belonging and foster a positive work culture, ultimately leading to improved performance and job satisfaction.

The Legacy of the Hawthorne Effect in Organizational Behavior

The Hawthorne Studies have left a lasting legacy in the field of organizational behavior. They shifted the focus from a purely technical approach to a more holistic understanding of employee behavior.

The studies highlighted the importance of considering the human element within organizations and recognizing the impact of social interactions and group dynamics on productivity and job satisfaction.

The Hawthorne Studies also paved the way for further research in the field, inspiring subsequent studies that explored topics such as leadership styles, employee motivation, and organizational culture .

Criticisms of the Hawthorne Studies

One criticism is that the studies were c onducted in a specific context – the Hawthorne Works factory – which may limit the generalizability of the findings to other industries or settings.

Some argue that the Hawthorne Effect itself may have influenced the results , as the workers may have changed their behavior due to the awareness of being observed.

Another criticism is that the studies did not take into account external factors that could have influenced productivity, such as changes in technology or market conditions.

And critics argue that the studies focused too heavily on the social and psychological aspects of work , neglecting other important factors that contribute to productivity.

Quick Overview of the Hawthorne Effect

Human Relations Approach : Emphasized the importance of social relations and employee attitudes in the workplace.

Effect of Observation on Behavior : Known as the “Hawthorne Effect,” it suggests that workers modify their behavior in response to being observed.

Increased Productivity : Found that changes in physical work conditions (like lighting) temporarily increased productivity.

Social Factors in Work : Identified the significant role of social groups and norms in the workplace.

Employee Motivation : Highlighted non-economic factors like camaraderie and attention as motivators for workers.

Management Practices : Suggested that more attention to workers’ needs could improve worker satisfaction and productivity.

Benefits and Impact

Humanizes the Workplace : Shifted focus from strict task orientation to considering workers’ social needs and well-being.

Foundation for Modern HR Practices : Influenced the development of employee-centered management and human resource practices.

Importance of Social Dynamics : Emphasized the role of group dynamics, leadership, and communication in work efficiency.

Broader Understanding of Motivation : Contributed to understanding that motivation is not solely driven by pay or working conditions.

Limitations

Methodological Flaws : Critics point out flaws in experimental design, lack of proper controls, and subjective interpretations.

Exaggerated Effects : Some argue that the studies overemphasized the impact of social and psychological factors on productivity.

Overgeneralization : Critics believe that conclusions drawn from the studies were too broad and not universally applicable.

Potential Bias : The presence of researchers may have influenced worker behavior, questioning the validity of the results.

Key Takeaways

• The Hawthorne Studies have had a profound impact on our understanding of human behavior in the workplace.
• These studies revolutionized management theories by highlighting the significance of worker attitudes, group dynamics, and social interactions in influencing productivity and job satisfaction.
• The findings of the studies continue to shape modern-day organizations, emphasizing the value of employee engagement, teamwork, and creating a positive work culture for optimal performance.

What is the Hawthorne Effect?

The Hawthorne Effect refers to the phenomenon where individuals change or improve an aspect of their behavior in response to their awareness of being observed.

How was the Hawthorne Effect identified?

It was identified during the Hawthorne Studies conducted at the Western Electric Hawthorne Works, where changes in work environment led to increased productivity, believed to be due to the workers’ awareness of being observed.

What were the Hawthorne Studies?

The Hawthorne Studies were a series of experiments on worker productivity conducted at the Hawthorne Works of Western Electric Company in Chicago between 1924 and 1932.

Why is the Hawthorne Effect important in research?

In research, the Hawthorne Effect is important because it highlights the need to consider how the presence of researchers or the awareness of being studied can influence participants’ behavior.

Can the Hawthorne Effect affect the outcome of an experiment?

Yes, the Hawthorne Effect can significantly affect the outcome of an experiment as participants might alter their natural behavior due to the awareness of being observed or studied.

Is the Hawthorne Effect only observed in workplace settings?

No, the Hawthorne Effect can occur in various settings, including clinical trials, educational research, and workplace studies, essentially anywhere subjects are aware they are being observed.

How can researchers minimize the Hawthorne Effect?

Researchers can minimize the Hawthorne Effect by using control groups, ensuring anonymity, employing blind or double-blind study designs, and minimizing the intrusion of observation.

Does the Hawthorne Effect have implications for management?

Yes, in management, it suggests that giving attention to employees and making them feel valued can improve productivity and job satisfaction.

What criticisms have been made about the Hawthorne Effect?

Critics argue that the original studies had methodological flaws, and some suggest the effect might be overestimated or not as universal as once thought.

How is the Hawthorne Effect relevant in today’s workplace?

In modern workplaces, understanding the Hawthorne Effect is relevant for designing work environments and management practices that acknowledge the impact of observation and attention on employee behavior and productivity.

About The Author

Geoff Fripp

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What is Hawthorne Experiment? Theory by Elton Mayo, 4 Phases

Hawthorne experiments were designed to study how different aspects of the work environment, such as lighting, the timing of breaks, and the length of the workday, had an on worker productivity. Here in this article, we have explained what is Hawthorne Experiment.

► What is Hawthorne Experiment?

The Hawthorne experiments were first developed in November 1924 at Western Electric Company’s Hawthorne plant in Chicago in Manufactured equipment for the bell telephone system and employed nearly 30,000 workers at the time of experiments.

Although, in all material aspects, this was the most progressive company with pension and sickness benefit schemes along with various recreational and other facilities discontent and dissatisfaction prevailed among the employees.

The initial tests were sponsored by the National Research Council (NRC) of the National Academy of Sciences. In 1927, a research team from Harvard Business School was invited to join the studies after the illumination test drew unanticipated results.

A team of researchers led by George Elton Mayo from the Harvard Business School carried out the studies (General Electric originally contributed funding, but they withdrew after the first trial was completed).

Experiments of Hawthorne effects work were conducted from 1924 to 1932. These studies mark the starting point of the field of Organizational Behaviour.

Initiated as an attempt to investigate how characteristics of the work setting affect employee fatigue and performance. (i.e., lighting) Found that productivity increased regardless of whether illumination was raised or lowered.

◉ Hawthorne Experiments were given by Elton Mayo

In 1927, a gathering of scientists driven by Elton Mayo and Fritz Roethlisberger of the Harvard Business School were welcome to participate in the investigations at the Hawthorne Works of Western Electric Company, Chicago. The usefulness of representatives relies vigorously on the fulfillment of the representatives in their work circumstances.

Mayo’s thought was that legitimate elements were less significant than passionate variables in deciding usefulness effectiveness. Besides, of the relative multitude of human variables impacting representative conduct, the most remarkable were those exuding from the specialist’s investment in gatherings. Accordingly, Mayo inferred that work courses of action as well as meeting the true necessities of creation must simultaneously fulfill the worker’s emotional prerequisite of social fulfillment at his workplace.

The Hawthorne experiment can be divided into 4 significant parts:

• Experiments on Illumination.
• Relay Assembly Experiment.
• Mass Interviewing Program
• Bank Wiring Observation Room.

✔ 1. Illumination Experiment

The examinations in Illumination were an immediate augmentation of Elton Mayo’s previous light analyses done in the material business in 1923 and 1924. This trial started in 1924.

It comprised of a progression of investigations of test bunches in which the degrees of brightening shifted yet the circumstances were held steady. The reason behind it was to look at the connection of the quality and amount of light to the proficiency of laborers.

It was observed that the efficiency expanded to practically a similar rate in both test and control bunches chosen for the examinations. In the last investigation, it was found that result diminished with the diminished brightening level, i.e., moonlight power.

As the analysts didn’t observe a positive and straight connection between brightening and effectiveness of laborers, they inferred that the outcomes were ‘suspicious’ without even a trace of straightforward and direct circumstances and logical results relationship.

One of the critical realities revealed by the review was that individuals act diversely when they are being considered than they could somehow or another act. It is from this the term Hawthorne Effect was authored.

✔ 2. Relay Assembly Test Room Experiment

This stage pointed toward knowing the effect of brightening on creation as well as different variables like the length of the functioning day, rest hours, and other states of being.

In this trial, a little homogeneous work-gathering of six young ladies was established. These young ladies were amicable to one another and were approached to work in an extremely casual environment under the management of a scientist.

Efficiency and resolve expanded significantly during the time of the examination. Usefulness continued expanding and settled at an undeniable level in any event, when every one of the upgrades was removed and the pre-test conditions were once again introduced.

The analysts reasoned that socio-mental factors, for example, the sensation of being significant, acknowledgment, consideration, investment, durable work-bunch, and non-order oversight held the key to higher efficiency.

✔ 3. Mass Interview Program in Hawthorne Experiment

The goal of this program was to make an orderly investigation of the representative’s mentalities which would uncover the significance that their “working circumstance” has for them.

The specialists talked with countless laborers as to their viewpoints on work, working circumstances, and management.

At first, an immediate methodology was utilized by which meetings posed inquiries considered significant by supervisors and scientists.

The analysts say that the answers of the workers were monitored. Consequently, this approach was supplanted by a roundabout method, where the questioner essentially paid attention to what the workers needed to say.

The discoveries affirmed the significance of social elements at work in the absolute workplace.

✔ 4. Bank Wiring Room Study

The last Hawthorne analysis, called the bank wiring room study, was directed to notice and dissect the elements of a working bunch when impetus was presented. With the end goal of tests, a gathering of 14 laborers was utilized on bank wiring.

The work was conveyed between nine wiremen, three weld men, and two reviewers. In the bank wiring room study, the work bunch framed a standard that the gathering would play out a specific pre-chosen amount of work in a day.

The whole work bunch complied with this standard paying little mind to pay, which suggests that gathering rules were more significant for the individuals.

Subsequently, it was recommended to bring the administration and laborer’s goals in line to pursue the shared objectives to improve the association.

Must Read : 14 Principles of Management

► Features of Hawthorne Experiment

The highlight Features of the Hawthorne Experiment are:

1.  A business association is fundamentally a social framework. It isn’t simply a techno-financial framework.

2. The business can be inspired by mental and social needs since its conduct is additionally affected by sentiments, feelings, and perspectives. Consequently, monetary impetuses are by all accounts not the only strategy to propel individuals.

3. The executives should figure out how to foster co-employable mentalities and not depend just on order.

Support turns into a significant instrument in human relations development. To accomplish interest, a successful two-way correspondence network is fundamental.

4. Usefulness is connected with representative fulfillment in any business association. In this way, the board should check out worker fulfillment. Bunch brain research assumes a significant part in any business association.

5. The neo-old style hypothesis stresses that man is a living machine and he is undeniably more significant than the lifeless machine. Subsequently, the way to higher efficiency lies in worker spirit. High confidence brings about higher results.

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Home » Management Principles » Elton Mayo’s Hawthorne Experiment and It’s Contributions to Management

Elton Mayo’s Hawthorne Experiment and It’s Contributions to Management

The term “Hawthorne” is a term used within several behavioral management theories and is originally derived from the western electric company’s large factory complex named Hawthorne works. Starting in 1905 and operating until 1983, Hawthorne works had 45,000 employees and it produced a wide variety of consumer products, including telephone equipment, refrigerators and electric fans. As a result, Hawthorne works is well-known for its enormous output of telephone equipment and most importantly for its industrial experiments and studies carried out.

Hawthorne Experiment by Elton Mayo

In 1927, a group of researchers led by Elton Mayo and Fritz Roethlisberger of the Harvard Business School were invited to join in the studies at the Hawthorne Works of Western Electric Company, Chicago. The experiment lasted up to 1932. The Hawthorne Experiment brought out that the productivity of the employees is not the function of only physical conditions of work and money wages paid to them. Productivity of employees depends heavily upon the satisfaction of the employees in their work situation. Mayo’s idea was that logical factors were far less important than emotional factors in determining productivity efficiency. Furthermore, of all the human factors influencing employee behavior , the most powerful were those emanating from the worker’s participation in social groups. Thus, Mayo concluded that work arrangements in addition to meeting the objective requirements of production must at the same time satisfy the employee’s subjective requirement of social satisfaction at his work place.

• Illumination Experiment.
• Relay Assembly Test Room Experiment.
• Interviewing Programme.
• Bank Wiring Test Room Experiment.

1. Illumination Experiment:

This experiment was conducted to establish relationship between output and illumination. When the intensity of light was increased, the output also increased. The output showed an upward trend even when the illumination was gradually brought down to the normal level. Therefore, it was concluded that there is no consistent relationship between output of workers and illumination in the factory. There must be some other factor which affected productivity.

2. Relay Assembly Test Room Experiment:

3. Mass Interview Programme:

The objective of this programme was to make a systematic study of the employees attitudes which would reveal the meaning which their “working situation” has for them. The researchers interviewed a large number of workers with regard to their opinions on work, working conditions and supervision. Initially, a direct approach was used whereby interviews asked questions considered important by managers and researchers. The researchers observed that the replies of the workmen were guarded. Therefore, this approach was replaced by an indirect technique, where the interviewer simply listened to what the workmen had to say. The findings confirmed the importance of social factors at work in the total work environment.

4. Bank Wiring Test Room Experiment:

• Each individual was restricting output.
• The group had its own “unofficial” standards of performance.
• Individual output remained fairly constant over a period of time.
• Informal groups play an important role in the working of an organization.

Effect of Monotony and Fatigue on Productivity

Using a study group other experiments were conducted to examine what effect of monotony and fatigue on productivity and how to control those using variables such as rest breaks, work hours and incentives.

At normal conditions the work week was of 48 hours, including Saturdays, with no rest pauses. On the first experiment workers were put on piece-work salary where they were paid on each part they produced, as a result the output increased. On the second experiment the workers were given 2 rest pauses of 5 minutes each for 5 weeks and again output went up. The third experiment further increased the pauses to 10 min and the output went up sharply. For the fourth experiments a 6, 5 min breaks were given and output fell slightly as the workers complained that the work rhythm was broken. On the fifth experiments conditions for experiment three were repeated but this time a free hot meal was given by the company and output wen up again.at the sixth experiment, workers were dismissed at 4.30p.m. Instead of 5.00p.m were an output increase was recorded.

Contributions of the Hawthorne Experiment to Management

Elton Mayo and his associates conducted their studies in the Hawthorne plant of the western electrical company, U.S.A., between 1927 and 1930. According to them, behavioral science methods have many areas of application in management. The important features of the Hawthorne Experiment are:

• A business organization is basically a social system . It is not just a techno-economic system.
• The employer can be motivated by psychological and social wants because his behavior is also influenced by feelings, emotions and attitudes. Thus economic incentives are not the only method to motivate people.
• Management must learn to develop co-operative attitudes and not rely merely on command.
• Participation becomes an important instrument in human relations movement. In order to achieve participation , effective two-way communication network is essential.
• Productivity is linked with employee satisfaction in any business organization. Therefore management must take greater interest in employee satisfaction.
• Group psychology plays an important role in any business organization. We must therefore rely more on informal group effort.
• The neo-classical theory emphasizes that man is a living machine and he is far more important than the inanimate machine. Hence, the key to higher productivity lies in employee morale . High morale results in higher output.

A new milestone in organisational behavior was set and Elton Mayo and his team found a way to improve productivity by creating a healthy team spirit environment between workers and supervisors labeling it as The Hawthorne Effect .

Although the Hawthorne effect tends to be an ideal contributor to organizational management, it contains a few flaws which such a study is criticized upon. Having the experiments being conducted in controlled environments, lack of validity may exist as the workers knew they were observed hence produced better performances. The human aspect in the Hawthorne experiments was given too much importance were it alone cannot improve production as other factors are a must. Group decision making might also evolve in a flaw as on occasions individual decision making is vital as it might be the way to prevent failures within a system. Another flaw contributes to the freedom given to the workers by the Hawthorne effect. The important constructive role of supervisors may be lost with excess informality within the groups and in fact such a flaw may result in lowering the performance and productivity.

The Hawthorne experiments marked a significant step forward in human behavior and are regarded as one of the most important social science investigations and said to be the foundations of relations approach to management and the development of organizational behavior. Managers are to be aware of the criticism evolved through years on such a study before adopting it. In my opinion, the Hawthorne effect is a validated theory and could be applied within the organisation, though care is to be taken and a limit is to be set. The use of team groups is acceptable as it creates a caring factor between workers and competitively amongst other teams. Supervisors are to keep their role and limit socializing with staff on the shop floor to always keep their role and hence standards are always kept to the maximum. Team meeting are to be held which allows the worker to give out his opinion and feel important by contributing his ideas to the organisation.

External Links about Hawthorne Experiment:

• A New Vision  (Harvard Business School)
• Elton Mayo  (British Library)

Related posts:

• 4 Phases of Hawthorne Experiment – Explained
• The Hawthorne Studies
• Case Study: Henry Ford’s Contributions to Organizational Behavior and Leadership
• Contingency Approach to Management
• Scientific Management Theory
• Steps in Management by Objectives (MBO) Process
• Comparison of Classical and Behavioral Approaches to Management
• Criticism of Scientific Management Theory (Taylorism)
• The Cultural Web – Johnson and Scholes’s Model of Organizational Culture
• Span of Management -Meaning and Factors Determining

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Article Contents

Introduction, men and machines, the hawthorne wars, a fable for our times.

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The Hawthorne studies—a fable for our times?

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E.A.M. Gale, The Hawthorne studies—a fable for our times?, QJM: An International Journal of Medicine , Volume 97, Issue 7, July 2004, Pages 439–449, https://doi.org/10.1093/qjmed/hch070

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‘The consumer of knowledge can never know what a dicky thing knowledge is until he has tried to produce it’. F.J. Roethlisberger, investigator at Hawthorne

There is a familiar anecdote that relates, with variations, that experiments with improved factory lighting increased the productivity of workers. The outcome seemed clear until someone turned the lighting down to below baseline, whereupon output increased still further. The moral of this tale, referred to as the Hawthorne effect, is that people change their behaviour when they think you are watching it. The story relates to the first of many experiments performed at the Hawthorne works of the Western Electric Company in Chicago from November 1924 onwards. The original aim was to test claims that brighter lighting increased productivity, but uncontrolled studies proved uninterpretable. The workers were therefore divided into matched control and test groups and, to the surprise of the investigators, productivity rose equally in both. In the next experiment, lighting was reduced progressively for the test group until, at 1.4 foot-candles, they protested that they could not see what they were doing. Until then the productivity of both groups had once again risen in parallel. Two volunteers went on to demonstrate that a high output was possible at 0.06 foot-candles, equivalent to moonlight.

The investigators next changed the light bulbs daily in the sight of the workers, telling them that the new bulbs were brighter. The women commented favourably on the change and increased their work-rate, even though the new bulbs were identical to those that had been removed. This and other manoeuvres showed beyond doubt that productivity related to what the subjects believed, and not to objective changes in their circumstances. These at least seem to be the main facts behind the popular legend, although these particular experiments were never written up, the original study reports were lost, and the only contemporary account of them derives from a few paragraphs in a trade journal. 1, 2

Compelling though this fable may be, it conceals something of greater interest. Behind it lies the story of investigators who wanted to make the sweat-shop conditions of factory life in the 1920s more humane and yet more profitable; of the research they ran—research that affected the working conditions of millions of people while generating an academic industry all of its own; of the way in which a particular academic interpretation was imposed upon an untidy reality; of the turf wars that resulted; and of five young women who entered the folklore of sociology because they got faster and faster at making telephone relays. Their work also entered the folklore of medicine, as an ‘effect’ that everyone refers to, but no-one can source or define. The Hawthorne studies deserve more detailed consideration.

At the start of the 20 th century, most people still worked on the land, heirs to a rhythm of life that stretched back unbroken into Neolithic times. Those who moved to the cities found a new sort of work: year-round performance of the same set of tasks with output measured against the clock. A day's work for a day's wages was typically based upon an uneasy pact between the employer, who wanted the maximum output for the minimum wage bill, and the work-force, whose defence against exploitation lay in defining a customary rate of output and penalizing anyone who exceeded it. This became the subject of intense scrutiny by Frederick Winslow Taylor, who possibly did more than anyone else to change the way in which people would work in the 20 th century. 3 His self-appointed mission was to define the most efficient way of carrying out any task performed by human hands, and of enforcing this upon the workplace. The success stories, at least as recounted by him, are remarkable. After examining a factory at which each workman brought his own shovel to work, he worked out the optimal weight for each shovelling task (21 lb) and adjusted shovel size according to the weight of the material being shifted. When he was done, the factory used 15 different shovels, and 140 men performed the work previously done by 600. 4 The views of the other 460 were not recorded. Or again, he found that pig-iron was being moved at a customary rate of 12½ tons per day per man. Calculation showed that the figure should be 47 tons per day. Incredible though this seemed, his slide rule left no room for doubt, and the transition was duly achieved by a combination of subterfuge and judicious extra payment to the most efficient workers. 5 His unsentimental view was that workers should appreciate that the factory ‘exists, first, last and all time, for the purpose of paying dividends to its owners’. 6 Archetype though he was of the man with the clip-board and stop-watch, the most hated person on the shop floor, Taylor knew one big thing: make shoes more cheaply, and people will buy more shoes. Cheaper goods and higher wages make the producer into a consumer, creating the spiral that has sustained us ever since.

The First World War introduced high throughput homicide and other industrial methods into warfare. 7 As whole populations were pitted against one another in the race to produce food and munitions, there was large-scale forced expansion of the factory population, and the role of women was transformed. Munitions workers were initially obliged to work 7 days a week, with one day off per month, and were often found asleep at their lathes. The futility of this approach was brought home by the demonstration that the total output of women producing fuses rose by 13% when working hours were reduced from 75 to 55 h. 8 Physical fatigue became the subject of high-level concern, and the recently formed Medical Research Committee (later Council) was asked to advise an Industrial Fatigue Research Board ( Figure 1 ). Investigators in the US paid close attention to the resulting partnership between academics and industrialists, no doubt noting that ‘sometimes the mere presence of the Institute's investigators and the interest which they have shown in the employees’ work have served to send up output before any actual changes have been introduced’. 6

Measuring industrial fatigue, 1920s style. From Hill AV, Living Machinery .

It became evident that fatigue had many causes, monotony high among them. 9 The sheer mind-numbing monotony of factory work before the introduction of the silicon chip is hard to comprehend. To take one example, assembly of relay R-1498 at the Hawthorne factory required 32 separate operations for each hand. The worker was expected to assemble one of these relays every minute for up to 9 h a day, and for five and a half days per week. 2 Allowing for one week of holiday (later rising to two) and six statutory days off, they were required to work 300 days in the year, with little hope of change or promotion. Studs Terkel, the social historian of Chicago, prefaced his book Working by saying ‘this book being about work is by its very nature about violence—to the spirit as well as to the body. It is, above all, about daily humiliations. To survive the day is triumph enough for the walking wounded … ’. 10 Monotony as penal as this required either incentive or coercion. Economic necessity might provide the incentive, but fatigue, error and carelessness became major problems. Looming behind was the threat of industrial unrest, strikes, and a descent into anarchy.

Few were more aware of this threat than the leaders of the socialist revolution in Russia, who used ruthless discipline in forcing progress towards industrialization and collective farming. Curiously enough, Frederick Winslow Taylor had a big influence upon Lenin, who encouraged Alexei Gastev to carry out experiments at the Central Institute of Labour in which ‘hundreds of identically dressed trainees would be marched in columns to their benches, and orders would be given by buzzes from machines. The workers were trained to hammer correctly by holding a hammer attached to and moved by a hammering machine so that after half an hour they had internalized its mechanical rhythm’. 11 Gastev honestly believed that efficiency would be improved if people were given numbers instead of names, and thus inspired the satire We , written in 1924 by Yevgeny Zamyatin, in which people known only by number lived in glass houses and performed each activity of the day in a mechanical fashion that maximized its efficiency. 12 This dystopian vision, much admired by George Orwell, was banned from the Soviet Union for more than 60 years. While the emerging totalitarian powers in Russia, Italy and Germany would set out to mould their populations into national task forces by discipline, propaganda and the parade ground, the privileged and managerial classes in the democracies viewed the emergence of the working masses with some concern. 13 This was not the deferential working class of before the war. These were people thronging to the dance halls and cinemas, casting votes, banding together in unions and generally threatening to throw the old order into chaos. Worse still, these were the new masters. 14

Chicago was built on the American Dream. It was where immigrants came to become Americans. In the 1920s alone, a wave of immigrants from southern or eastern Europe took its population from 2 701 705 to 3 376 438, 15 yet elderly inhabitants could still remember when prairie wolves would howl in the streets on cold winter nights. 16 One of its most successful industries was the telephone business, effectively monopolized by the American Telephone and Telegraph Company (AT&T). The monopoly supplier of telephone equipment to AT&T was the Western Electric Company, and its main factory in the Chicago suburb of Hawthorne offered employment to some 35 000 people, mainly first- or second-generation immigrants from 60 nationalities. Western Electric was a paternalistic organization that enjoyed the status of a public utility, forbade union membership, and yet led the way with pension schemes and social and sporting facilities for its workers. Their electrical suppliers claimed in the early 1920s that better lighting improved productivity, thus prompting the famous illumination experiments. These experiments were supervised by two company officials, Clarence Stoll and George Pennock, and it was they who dreamed up the next experiment, on the back of which so many academics were to rise to fame. 16

The study was carried out in the relay assembly Test Room. 1 A relay was a switching device activated in the telephone exchange as each number was dialled. Six experienced workers were moved into the area constructed for the illumination experiments in April 1927: five to work on assembly and the sixth to keep them supplied with parts. The young women (invariably referred to as ‘girls’ by the investigators) worked in a row ( Figure 2 ) and each completed relay was dropped into a chute and automatically recorded by a hole punched in a tape. The supervisor sat at a desk directly opposite with his assistants in a row beside him; in further emphasis of the social divide, the clerical and administrative staff entered and left the room by a different door.

The Test Room in 1931. From left to right (upper panel), layout operator, Anna Haug, Wanda Blasejak, Theresa Layman, Jennie Sirchio, Mary Volango.

Rate of production of relays in the Test Room. Note that 50 per hour was the base rate, and that Operators 2 and 4 approached 80 per hour at maximum.

The aim was to examine the effect of changes in working arrangements upon productivity. Pennock and Stoll were engineers, and treated the row of women like an engine in its test bed, tweaking the conditions to achieve maximum output. Output did indeed rise in response to shorter hours and the introduction of rest breaks, but Pennock was puzzled to observe that—with occasional hitches—it continued to rise regardless of any changes he made to the experiment. Most baffling of all, output remained high when he decreed a return to baseline working conditions for 3 months in 1928. By this stage, the women were making 2900 relays per week instead of 2400, rising to 3000 when the most successful innovations were subsequently reintroduced. The company became interested, and brought in academic consultants. One of these was Elton Mayo, an Australian recently appointed to the Harvard Business School. Conservative in his views, he attracted the attention of leading industrialists because he considered industrial unrest and political dissidence to be symptoms of psychopathology brought on by an unsuitable working environment. 2 He first came into the Test Room in April 1928, measured the blood pressures of the women at different times of day, and departed. Only later was he to rescue Pennock from his uninterpretable experiment and himself from academic obscurity by pointing out that the key variable was the attitude of the workers.

Discipline was initially a problem. Accustomed as they were to the classroom atmosphere of the shop floor, the women now found themselves free to work in the way that suited them best. They talked, so much so that the two most challenging (and least productive) women were replaced after 8 months. Jennie Sirchio, known as Operator 2, was one of the replacements. Born of Italian immigrants, she dreamed as a child of working in an office, but left high school early because her family needed the wages. When her mother died, she became the housekeeper, main breadwinner, and financial manager for her father and three brothers, breaking off with her long-established boyfriend to do so. Her fierce loyalty to her family was soon matched by her loyalty to the Test Room, not least because to her the wage of $30 per week (1 cent per relay at group rates) appeared astronomical. Her arrival changed the course of the experiment. She rapidly became the centre of the group, and discipline was no longer a problem. The girls would laugh and talk, sometimes even sing together, but the focus was now firmly on output.

On her left was Mary Volango. Eighteen and born of Polish parents, she aspired to look and behave as much like an American as possible; ‘motion pictures were her chief diversion, and if given the opportunity she talked about them incessantly’. On her right was Theresa Layman, who had lied about her age and was only 15, also with Polish parents. Her mother dominated her husband and six children, and the three wage-earners were obliged to hand over their wage-packets unopened; she was allowed no regular spending money, despite her longing for clothes. Wanda Blazejak, also Polish, lived in a six-room bungalow with her grandmother, parents and six siblings, forming a thrifty, close-knit family group. Her parents ordered her to break off with a boyfriend because he was not Polish. The odd one out was Anna Haug, a 29-year-old from Norway who came to Chicago on her own at the age of 25, and who by some amazing chance ran into her childhood sweetheart at a party. They married while the study was in progress, and planned to save enough money to return to Norway. 1, 2, 16 None of the five spoke English at home, but they adopted American customs which, much to the scandal of their families, included serial boyfriends. During the boom they would buy a new outfit of hat, dress, artificial silk stockings and shoes (at a cost of $10–15) every few weeks; the style would be set by the latest movies and the outfit would be discarded rather than cleaned. For one observer these clothes were symbolic of ‘their desire for another and largely imaginary world peopled by wealthy young men and ‘smart’ women such as could be seen in any movie, where social obligations and routines of behaviour are conspicuous by their absence’. 16

By February 1929, and largely due to the Test Room, the company committed itself to studying its workers. A Division of Industrial Research was formed, and the Test Room supervisor was promoted to department chief. He was assisted by a new test room supervisor, an office boy, a lady who helped with the statistics, and the superintendent of the Inspection Branch (Pennock himself). To this could be added ‘an intermittent stream of other visitors or consultants: industrialists, industrial relations experts, industrial psychologists, and university professors’. 1 All eyes were on the five women as they worked away demurely, each dropping a new relay down the chute every 40–50 seconds, 8 hours a day.

The twenty-first century reader might pause to wonder why the Test Room was considered so interesting. It may seem self-evident that the girls became the centre of a lot of fuss, were accorded unheard-of autonomy and respect, bonded as a group, and gained a whole range of rewards and privileges in return for making relays faster. Why should there be anything surprising in that? The difficulty, or so I believe, lies in our twenty-first century eyes. We have seen too many costume dramas in which people from other times and places think and behave just as we do. They didn’t. Talk to someone who lived through the 1920s, and the strangeness will not at first be apparent—for them the landscape has moved at the same speed as the train—but sooner or later they will say ‘things were very different then’. Things were very different. Let us therefore pause to adjust our focus.

In a book titled (with unintended irony) The Scientific Outlook , and published in 1931, the philosopher Bertrand Russell mused about the future of industry: ‘the pleasantest work, of course’, he wrote, ‘will be that which gives the most control over the mechanism. The posts giving most power will presumably be awarded to the ablest men (sic) as a result of intelligence tests. For entirely inferior work negroes will be employed wherever possible … The society will not be one in which there is equality … ’. 17 In the following year, Aldous Huxley published Brave New World , a satire in which factory workers are cloned, deprived of graded amounts of oxygen during fetal maturation, and classed beta to epsilon according to the technical skills they would require. This classification was not invented by Huxley, but by Robert M Yerkes, Professor of Psychology at Harvard, who produced the first mass tests of intelligence and applied them to 1.75 million US army recruits in World War 1. Those who could read were given a test known as Army Alpha; the remainder were given a pictorial challenge known as Army Beta; all were then graded from A to E according to intellectual capacity. The results of these tests horrified the educated classes, for they showed that the average mental age of White Americans came in at 13.08 years; it was now official that half the population were semi-morons. Needless to say, immigrants from Southern or Eastern Europe came in even lower (10.74 years for Poles), with Black people scoring lowest of all. 18 The inescapable conclusion, or so it seemed, was that the masses were intellectually and biologically inferior to their social superiors. 19 Without firm leadership from above—which democracy could not provide—society was on a one-way trip to the abyss. So at least many right wing thinkers believed. 20 Those of a more liberal disposition set out to study the working class using techniques developed by anthropologists, tried to improve them by education, advised them not to breed too enthusiastically, or aped their speech and manners. The Old Etonian Eric Blair (George Orwell) went on the personal voyage of discovery described in the Road to Wigan Pier and other books. The common factor in all this was that working people were always them , while we—the people who communicated between ourselves about them—were always us .

Seen from this perspective, the excitement of the Hawthorne investigators becomes easier to understand. They had bridged a social abyss and discovered a new alchemy. Treat working people with respect, understand their thinking and group dynamics, reward them appropriately, and they will work better for you. Everyone can be a winner. In the view of one investigator, the invitation to the girls ‘to work like we feel’ had ‘the emotional force of a Magna Charta or of a Declaration of Independence, and unwittingly it inaugurated a revolution in employee and supervisory attitudes’. 16 George Pennock addressed the Personnel Research Federation in New York in this vein on 15 November 1929. Describing the Test Room, he claimed that ‘a relationship of confidence and friendliness has been established with these girls to such an extent that practically no supervision is required. In the absence of any drive or urge whatsoever they can be depended upon to do their best. They say they have no sensation of working faster now than under the previous conditions … they have a feeling that their increased production is in some way related to the distinctly freer, happier, and more pleasant working environment’. 9

While academics began to build their reputations around these findings, the management at Hawthorne was quick to apply them. Rest breaks were introduced across the factory, with a general increase in productivity. The observation that the women worked more freely and effectively when relieved of the ‘apprehension of authority’ prompted a review of supervisory style. The new mood had evidently caught on, for someone soon said ‘why not ask the workers?’ and an ambitious interview programme was launched. A cadre of trained interviewers was recruited, and some 21 000 employees were interviewed between 1928–1930. The interviews were an immediate success, popular both with the employees and the interviewers. Oddly enough (or perhaps not) there was an immediate effect upon the supervisors themselves, even though they were not involved—yet another Hawthorne effect. Before long they too were participating in regular training conferences. At the outset it was assumed that the interviews would generate practical suggestions, but most complaints were found to relate to vaguely expressed personal grievances, some of which had been nursed for years. These were often relieved by being expressed, so that the employee walked out of the interview with considerable lightening of mood. Meanwhile the interviewers ‘felt that they had acquired a new and improved way of understanding and dealing with their fellow men’. 1

After considerable debate, this experience led to a change in interviewing technique. The original direct approach based on a pre-selected list of questions was abandoned in favour of an indirect technique which encouraged the subject to develop and follow his or her own train of thought, with minimal prompting from the interviewer. The interviews now took 90 min, were recorded almost verbatim, and subsequently took up 10 pages of single-spaced typescript. Certain areas of complaint (e.g. about the cafeteria) were no longer treated as facts in themselves, but as pointers to underlying personal or social situations which warranted exploration. What had been learned was ‘that opinions are not detachable. What a worker thinks on a certain subject is a symptom of what he is; his ideas cannot be torn out of their personal context and exhibited as significant’. 9 Only later did the investigators realise that they had rediscovered the psychiatric interview as developed at the Salpêtrière Hospital in Paris and adopted by the psychoanalytic community. The Hawthorne interview did have some influence on the medical consultation, 21 however, and undoubtedly influenced Carl Rogers as he developed non-directive counselling, 22 the basis of modern counselling techniques.

Meanwhile, Hollywood style, the Test Room women had been translated from anonymous drudgery to minor celebrity; 30 000 other Hawthorne workers now enjoyed regular rest breaks because of them. Jennie Sirchio and Wanda Blazejak had become the fastest relay assemblers of all time, each with a distinctive style; Sirchio appeared quite leisurely from across the room, but up close her hands became a blur. Meanwhile, their world was beginning to fall apart. AT&T had more than 15 million telephones in operation in 1929, and became the first company ever to gross $1 billion. The boom ended when Wall Street crashed on Black Thursday, 24 October, and one in ten US phones was disconnected in 1932. Western Electric's takings fell from $411 million in 1929 to $70 million in 1933, and 80% of the workforce lost their jobs. 23 Exploring the intimate feelings of employees was no longer on the company's agenda. The Test Room women received their notice in 1932. An exception was made for Jennie Sirchio, who achieved her ambition of working in an office for a few brief months, before she too was sacked. They tracked her down two years later, earning a bare living as a shop assistant. There was one final question. The phenomenal output of the Test Room girls had fallen for the first time when they were given their notice, although logic dictated that they should have worked flat out to maximize their income over the final weeks. Asked why this happened, Jennie said ‘we lost our pride’. 16

The missing link in most accounts of the Hawthorne studies has been the investigators. 2 As we have seen, the studies were initiated by company officials who approached worker output as if it was a problem in engineering. To do them justice, they were well aware of the human factor, but lacked the vocabulary to describe it. Academics rescued them by transforming a series of poorly performed experiments into a potent myth. The resulting alliance fulfilled the unwritten agenda of all professionals: identifying problems to which they themselves are the solution. The company officials had generated a whole new role for middle management, and the academics now had their feet firmly under the big business table. First on the scene was Elton Mayo, whose somewhat racy account of the doings at Hawthorne was heavily influenced by his reading of Durkheim and the concept of social disorganization. 9 Mayo's disciple J.F. Roethlisberger showed the workforce as a social system , influenced by group interaction, participation and a more relaxed style of supervision. In 1936, he presented these ideas for the first time to an audience of prominent business executives, asking himself ‘were they to remain the robber barons or to become the saviors of our industrial civilisation?’. 24 His talk was well received but no doubt naïve; as a later commentator put it ‘the Goliath of industrial warfare cannot be slain by the David of industrial relations’. 25 There is, after all, a genuine conflict of interest between management and worker that cannot be resolved by psychotherapy, and his account blithely ignores the role of unions. Later and more hard-nosed commentators would derisively label this as the ‘Pet Milk’ concept of industrial relations, after a famous advertising slogan which claimed that ‘ Pet Milk comes from contented cows’, but 20 000 future graduates of the Harvard Business School would nonetheless cut their teeth on the Hawthorne studies.

Hawthorne duly became a locus classicus of industrial relations, the place where every commentator worth his salt came to sharpen his claws. You might imagine that the studies had demonstrated for all time that (a) the behaviour of individuals cannot be abstracted from its personal and social context, and that (b) the observer of a behavioural experiment is also in some way a participant. Not so. One commentator after another jumped straight in with one eye and both feet to offer a reductionist ‘solution’ based around their own personal or academic value system. The performance of the girls has thus been attributed to discipline and firmer supervision (amazingly enough), to kindness and better working conditions, to pay, to feedback and learning curves, to operant conditioning (by the behavioural psychologists), to group interaction and mutual support, and to some intuitive yet undefinable gestalt which incorporates all of the above. 26

Things move on, however, and the behavioural sciences have left Hawthorne behind them. There are, come to that, no more workers for them to study; 27 transformed into technicians, robots or rows of children in some tropical sweat-shop, they are no longer worthy objects of academic investigation. The Harvard Business School lost its human heart long ago, 28 and sociologists would consider the suggestion that their task is to provide the tools with which to construct a better society laughably naïve. Indeed, after doing much to justify Francis Crick's famous quip that any academic discipline with ‘science’ in its title probably isn’t one, 29 the social science represented in some current journals has become an academic exercise in fashionable linguistics, the unreadable in pursuit of the uninterpretable. All that remains of Hawthorne is the name, and the fable.

In spring 1974, Fritz Roethlisberger lay dying in hospital, alert as ever to the nuances of corporate behaviour. ‘The physicians want to be surgeons’, he would say, ‘the nurses want to be physicians, the aides want to be nurses, and no one wants to fluff my pillow’. 30 Fifty years earlier, when the studies that made Roethlisberger famous were under way, the medical practitioner was an isolated professional who sold his skills for whatever the market would bear, and was answerable only to the code of his chosen profession. The time would come when presumed skill with the scalpel or stethoscope would not be enough, and he or she would come to rely increasingly upon expertise and technologies provided by others. Later still, the doctor would evolve into the means by which a complex technology is delivered, 31 within a medical system that has acquired many of the features of an industrial process. Hence the haunting sense of déjà vu within the Hawthorne story. Techniques of management developed on the shop floor in the 1920s have at long last worked their way through to us. Here you will find the same mantras regarding hours of work, rest breaks, group dynamics, personal review, feedback, pay linked to productivity, audits, reports and outcomes, all rebadged and sold as new. And there within our medical factories we will find the older generation of factory hands, deskilled, shaking their heads over the new work practices, resentful of the present, apprehensive of the future, and vaguely aware that something important has been taken from them. You might call it respect.

Meanwhile, the ‘Hawthorne effect’ scored 1940 hits on a recent electronic search of the medical literature. The term ‘effect’ is used in physics to describe a phenomenon that cannot be accounted for within current theory: a stimulus to further endeavour. In medicine it is all too often used to close a door, conveying the impression of understanding where none in fact exists, as in the placebo effect, or (within my own speciality) the now-defunct Somogyi effect. 32 Be that as it may, there are two frequently quoted examples of studies in which control groups changed their behaviour. One involved health professionals: medical residents in a US hospital participated in a trial of two methods, financial incentive or chart discussion, designed to reduce the frequency with which they ordered laboratory tests and X-rays. 33 One third of the residents acted as controls. The upshot was that the chart review group made a 47% reduction, the financial incentive group made a 29% reduction, and the control group made a 36% reduction! The second example comes from the Multiple Risk Factor Intervention Trial. In this, some 12 000 men were selected for an intervention programme on the basis of increased cardiovascular risk, and then randomized to ‘special intervention’ and ‘usual care’ groups. After 7 years, the special intervention group had reached its targets in terms of smoking cessation and reduced diastolic blood pressure, with a less-than-desired but still useful fall in cholesterol, but did not differ from the usual care group in terms of total mortality and incidence of coronary heart disease. Smoking had decreased in the control group from 59% to 46%, and diastolic blood pressure from 91 to 84 mmHg; antihypertensive use rose from 19% to 47%. Oddly, altered behaviour of the controls (or their physicians) was not at the time among the three hypotheses put forward by the investigators to explain the lack of difference between the groups. 34 No doubt many more examples could be found, but let us consider patients as individuals.

Economists have a concept known as ‘economic man’. This is a person whose behaviour can be understood and predicted on the basis of financial self-interest. Less explicitly, health workers assume a ‘health man’ whose behaviour can be understood and predicted in terms of a rational desire for longevity. The limitation of both assumptions is that balanced individuals have many other desires and fears. The undivided pursuit of wealth may result in a knighthood, a prison sentence, or both, but the undivided pursuit of health commands little respect and is generally considered unhealthy. The behaviour of most of us emerges as a compromise between conflicting motives. There may be good reasons for what we do, but they are not rational ones. Instead, they derive from our background and from the situation we find ourselves in. This is why we find it easier to understand and predict the behaviour of someone with whom we can identify reasonably closely. Prediction becomes progressively uncertain with people we know less well, and true strangers are viewed with caution because we have little idea what they will do next.

I specialize in looking after people with diabetes. As such, I operate as a trader in risks and futures, and use the clinical interview as a means of identifying the personal and social context within which to operate. Long term risk is a tricky concept to handle; diabetes can only be lived one day at a time. Change the day, and you change the life. Which brings us back to monotony. Elton Mayo has interesting things to say about this. Some tasks, he observes, are so automatic that the operatives can pass their time day-dreaming or chatting to one another. At the other end of the scale are tasks that are absorbing because they demand skill and full attention. It is the work in between, characterized as ‘semi-automatic’ and combining monotony with constant vigilance and frequent interruptions, that generates the stress and depression. 9 Managing your own diabetes is a semi-automatic activity.

The evidence that behaviour is the dominant element in successful management of diabetes is so overwhelming that we tend to ignore it. It is too much in the foreground, and runs counter to the widespread assumption that we can live pretty much as we please provided we have access to the right pharmaceuticals. Hawthorne does not just provide an occasional academic footnote to the management of diabetes; it is the basis of good management. Let us take some examples. I was involved in the first studies of home blood glucose monitoring for diabetes. Our patients almost invariably improved their control, and we had no hesitation in attributing this to the technique. It took a study in which patients were randomized to blood or urine tests, with equal attention to both, to show that the benefit was unrelated to the intervention. 35 Increased attention is only as useful as the behaviour advocated, however, as was shown in a primary care study in which newly-diagnosed patients with type 2 diabetes were randomized to routine care or more intensive patient-centred consulting. The intensively managed group gained significantly more weight, with associated deterioration in blood pressure and triglyceride levels. Glucose control was unchanged. The depressing but likely explanation was that the intervention group gained weight because they were more conscientious in taking their sulphonylurea medication, since the effect was seen only in this group and could not be accounted for by differences in the amount prescribed. 36

Beneficial non-specific treatment effects are regularly seen in drug trials, which in diabetes are often judged against a rule of thumb used by the US Food and Drug Administration, to the effect that a reduction in HbA1c of 0.5% is clinically useful. Many published trials omit an adequate description of the run-in period on unchanged therapy, but when supplied, it very often demonstrates a clinically useful improvement in control. Every diabetes specialist knows this, but (so far as I know) it has never been the subject of a systematic review. Meanwhile the insulin analogues continue to sweep the market on the basis of benefits demonstrated in unblinded trials, although blinded trials of the rapid-acting analogues suggest that they are virtually indistinguishable from standard insulins. 37

Hawthorne reminds us that there are times when context is more important than science, and that Voltaire may have missed the point when he remarked that the main function of doctors was to keep the patient occupied ‘while the disease ran its inevitable course’. Keeping the patient occupied can be very effective. Studies of weight control, or of glucose control in type 2 diabetes, both behaviour-based therapies, show a tick-shaped response: the greatest fall below baseline is reached within six months or so, and is followed by an inexorable return towards baseline. Good diabetes teams get round the tick phenomenon and the semi-automatic monotony of diabetes by constant introduction of new gadgets or nostrums, thus creating a continuous experiment. Ironically, practitioners of this art almost invariably credit their success to the intervention rather than to the context in which it is offered. This is indeed an essential part of the trick, since the confidence with which the new therapy is offered largely governs its success. No surprise that the literature is replete with conflicting recipes for successful management.

The importance of context can also be overlooked in studies of the efficacy of placebo medication. As good clinical scientists, we will look for evidence that is generally applicable, precisely because it is independent of context. We will be reassured by evidence that under neutral and carefully controlled conditions inert substances used as placebos are virtually (although not quite) free of effect. 38 Should we then conclude that placebos are powerless? Or should we reflect that in human affairs, context is everything? That in 1993 some 45 million Americans paid $13 billion for fraudulent or ineffective remedies? 39 Or that every fake medicine has its passionate advocates, and that Arbuthnot Lane used to exhibit a grateful patient to prove that total colectomy was a wonderful treatment for rheumatoid arthritis? 40 Science lights a lonely path through an irrational world, and follow we must, but not at the cost of excluding the obvious because it is not easy to measure. A clinician is an amphibious creature, trained in the abstractions of science but relied on as a human being. As a scientist, he is detached and reductionist. As a human being, he exists as an element in the situation he is attempting to resolve. Hawthorne showed that to change one element is to change the situation, and that human behaviour never is, never was, and never will be a spectator sport.

I thank George Davey-Smith and Neville Goodman for their encouragement and helpful advice.

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Worth R, Home PD, Johnston DG, Anderson J, Ashworth L, Burrin JM, Appleton D, Binder C, Alberti KGMM. Intensive attention improves glycaemic control in insulin-dependent diabetes without further advantage from home blood glucose monitoring: results of a controlled trial. Br Med J 1982 ; 285 : 1233 –40.

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What Is the Hawthorne Effect?

• How It Works
• Modern Research
• In Medical Practice
• Hawthorne Effect FAQs

Hawthorne Effect Definition: How It Works and Is It Real

Erika Rasure is globally-recognized as a leading consumer economics subject matter expert, researcher, and educator. She is a financial therapist and transformational coach, with a special interest in helping women learn how to invest.

Investopedia / Ellen Lindner

The Hawthorne Effect is the supposed inclination of people who are the subjects of an experiment or study to change or improve the behavior being evaluated only because it is being studied and not because of changes in the experiment parameters or stimulus. It was first identified by organizational researchers in the 1920s.

More recent research suggests that the Hawthorne Effect may not actually be real and that the original study was flawed.

Key Takeaways

• The Hawthorne Effect is when subjects of an experimental study attempt to change or improve their behavior simply because it is being evaluated or studied.
• The term was coined during experiments that took place at Western Electric’s factory in the Hawthorne suburb of Chicago in the late 1920s and early 1930s.
• The Hawthorne Effect is thought to be unavoidable in studies and experiments that use humans as subjects.
• Whether or not the Hawthorne Effect is real remains up for debate.

How the Hawthorne Effect Works

The Hawthorne Effect refers to the fact that people will modify their behavior simply because they are being observed. The effect gets its name from one of the most famous industrial history experiments that took place at Western Electric’s factory in the Hawthorne suburb of Chicago in the late 1920s and early 1930s. However, subsequent analyses of the effect have revealed that the original results were likely overstated along with several flaws in the study's design and execution.

The Hawthorne experiments were originally designed by the National Research Council to study the effect of shop-floor lighting on worker productivity at a telephone parts factory in Hawthorne. However, the researchers were perplexed to find that productivity improved, not just when the lighting was improved, but also when the lighting was diminished. Productivity improved whenever changes were made in other variables such as working hours and rest breaks.

The researchers concluded that the workers’ productivity was not being affected by the changes in working conditions, but rather by the fact that someone was concerned enough about their working conditions to conduct an experiment on it.

The Hawthorne Effect and Modern Research

Research often relies on human subjects. In these cases, the Hawthorne Effect is the intrinsic bias that researchers must take into consideration when studying their findings. Although it can be challenging to determine how a subject's awareness of a study might modify their behavior, researchers should nevertheless strive to be mindful of this phenomenon and adapt accordingly.

While there is no universally agreed-upon methodology for achieving this, experience and keen attention to the situation can help researchers prevent this effect from tarnishing their results.

Although it can be challenging to determine how a subject's awareness of a study might modify their behavior, researchers should nevertheless strive to be mindful of this phenomenon and adapt accordingly.

The Hawthorne Effect in Medical Practice

As an example of the Hawthorne Effect, consider a 1978 study conducted to determine if cerebellar neurostimulators could reduce the motor dysfunction of young cerebral palsy sufferers. The objective testing revealed that the patients in the study claimed that their motor dysfunctions decreased and that they embraced the treatment. But this patient feedback countered the quantitative analysis , which demonstrated that there was scant increased motor function.

Indeed, the increased human interaction with doctors, nurses, therapists, and other medical personnel during these trials had a positive psychological impact on patients, which consequently fostered their illusion of physical improvements to their conditions. When analyzing the results, researchers concluded that the Hawthorne Effect negatively impacted the data, as there was no evidence that the cerebellar neurostimulators were measurably effective.

Is the Hawthorne Effect Real?

While the Hawthorne Effect is taught in business schools and sociology courses around the world, recent scholarship has begun to question its validity. According to Scientific American, out of the first three original experiments, only one showed improved productivity, the second found no improved productivity, and in the third productivity actually worsened. What is suspicious is that the sponsors of the study ordered the destruction of all data, including everything that had been sent to MIT, and for no report to be written. When the original data finally did resurface, several scholars were able to debunk the initial findings. Additionally, modern attempts to replicate the Hawthorne Effect have been inconclusive. Only seven out of 40 such studies found any evidence of the effect.

Why Is It Called the Hawthorne Effect?

The name comes from where the original studies took place: in a factory complex known as the Hawthorne Works, outside of Chicago, IL.

What Were Some of the Flaws of the Original Hawthorne Study?

Scholars have identified several flaws in the studies that led to the Hawthorne Effect. For one, the sample size was very small: just five individual workers. Moreover, the members of the sample changed over time. The researchers conducting the study were not blinded and so could have been biased. The data collected, even if it had been sound, has been further criticized as being misinterpreted.

Scientific American. " The Hawthorne effect: An Old Scientists’ Tale Lingering 'in the Gunsmoke of Academic Snipers' ."

Levitt, Steven D., and John A. List. " Was There Really a Hawthorne Effect at the Hawthorne Plant? An Analysis of the Original Illumination Experiments ." NBER Working Paper Series, National Bureau of Economic Research , No 15016, May 2009, pp. 1–19.

Sparrow, Sara, and Edward Zigler. "Evaluation of a Patterning Treatment for Retarded Children."  Pediatrics , Vol . 62, No. 2. 1978, pp. 137-150.

Liptak, Gregory S. "Complementary and Alternative Therapies for Cerebral Palsy."  Mental Retardation and Developmental Disabilities Research Reviews, Vol. 11, No. 2, 2005, pp. 56-163.

Bk, Dr Sujatha, Dr. Mayurnath T. Reddy, and Dr. Pooja Pathak. "Camouflage in Research‐The Hawthorne Effect."  International Journal of Development Research, Vol. 9, No. 4, 2019, pp. 26996-26999.

The New York Times. " Scientific Myths That Are Too Good to Die ."

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• v.110(38); 2013 Sep 17

The Hawthorne effect and energy awareness

Daniel schwartz.

Departments of a Social and Decision Sciences and

Baruch Fischhoff

b Engineering and Public Policy, and

Tamar Krishnamurti

c Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA, 15213

Fallaw Sowell

Author contributions: D.S., B.F., and T.K. designed research; D.S. performed research; D.S. and F.S. analyzed data; and D.S., B.F., T.K., and F.S. wrote the paper.

Associated Data

The feeling of being observed or merely participating in an experiment can affect individuals’ behavior. Referred to as the Hawthorne effect, this inconsistently observed phenomenon can both provide insight into individuals' behavior and confound the interpretation of experimental manipulations. Here, we pursue both topics in examining how the Hawthorne effect emerges in a large field experiment focused on residential consumers’ electricity use. These consumers received five postcards notifying, and then reminding, them of their participation in a study of household electricity use. We found evidence for a Hawthorne (study participation) effect, seen in a reduction of their electricity use—even though they received no information, instruction, or incentives to change. Responses to a follow-up survey suggested that the effect reflected heightened awareness of energy consumption. Consistent with that interpretation, the treatment effect vanished when the intervention ended.

How to substitute human responsibility for futile strife and hatred—this is one of the most important researches of our time.

Elton Mayo, in Roethlisberger and Dickson ( 1 )

Beginning in 1924, the Western Electric Company Hawthorne plant was the site of some of the most influential studies in the formative years of the social sciences: the illumination experiments, examining the effects of artificial lights on worker behavior. Although workers seemed to increase their productivity when lighting regimes changed, the researchers eventually concluded that those changes actually reflected psychological factors, such as workers’ responses to receiving special attention or being aware of the experiment. Subsequent studies at Hawthorne reached similar conclusions ( 1 ). Such changes came to be called Hawthorne effects ( 2 , 3 ), although, ironically, secondary analyses concluded that there was no effect in the original studies or, more precisely, that the studies’ design was too flawed to establish whether the effect was, in fact, observed there ( 4 – 7 ).

The mythical status of the initial observation notwithstanding, the Hawthorne effect is a fundamental concern for scientists studying any program designed to change human behavior, who must distinguish the effects of the program from the effects of being in the study. As a result, the Hawthorne effect has been examined in many areas, including worker performance ( 8 ), education ( 9 , 10 ), health ( 11 ), and voting ( 12 ). The evidence from these studies is mixed. Some of the variability in their results may reflect differences in how they operationalized the concept of “being in a study.” At one extreme lie such minimal manipulations as telling people no more than that they are in a study. At the other extreme lie treatments known to have their own effects, such as directly monitoring specific behaviors ( 13 ), providing performance feedback ( 14 ), inadvertently communicating research hypotheses ( 15 ), and providing new resources or instruction ( 16 ). Here, we add to the relatively small set of experiments that have examined the effects of study participation per se, with a field experiment examining electricity use of several thousand consumers. Our results reveal evidence of a pure Hawthorne effect, the psychological mechanisms shaping its size, and its implications for field studies of policy interventions.

In addition to its obvious economic and environmental importance, household electricity consumption offers several attractive features as a research domain. It is routinely measured for many households. It is such a small part of most Americans’ budgets that it typically receives little attention, meaning that participating in a study might be enough to make it salient. Finally, most people know how to save electricity—even if they do not always know which ways are most effective ( 17 , 18 ). Thus, if participating in a study increases the salience of electricity consumption, people should know what to do without further instruction—which could confound the pure participation manipulation.

Although there are many studies of interventions seeking to affect energy consumption, few have assessed the impact of Hawthorne (study participation) effects on their results ( 19 ). Among those few, some used an opt-in design eliciting a commitment to participate (hence confounded the mere-participation manipulation), had small samples, used weak manipulations, or omitted essential details in the research report, making it hard to tell what they did and found ( 20 – 22 ). As a measure of the importance of even small changes in energy consumption, states have set goals ranging from 0.1% to 2.25% annual savings ( 23 ).

Our experiment sent five weekly postcards to a random sample of electricity customers, notifying them about their participation in a study about household electricity use. Monthly electricity use was collected before, during, and after the experimental period for the treatment group and for a similarly selected control group. One month after the last postcard was sent, we surveyed a random sample of participants, asking about their response to the study.

Experimental Design

Participants were randomly selected from residential customers of a mid-Atlantic electricity utility to be in treatment or control groups. Households in the treatment group received their first notification a few days before the start date through a postcard stating that they had been selected to be in a 1-mo study about electricity use in their home and that no action was required on their part. They then received four additional weekly postcard reminders about the study. Thus, the study’s sole stated goal was measuring electricity consumption. The control group received nothing. The observation period approximately spanned the interval between successive monthly readings. Table 1 summarizes household characteristics for the treatment and control groups. A subsample received a survey 1 mo after the end of the study period. Methods provides details on the postcards, survey, sampling, and data structure.

Household characteristics for control and treatment groups

The main dependent variable was households’ electricity use. Although meter readings are scheduled for monthly intervals, there is some variability in when they are actually performed. To accommodate this variability, we adjusted each household’s electricity use by the number of days that fell during the postcard treatment period. We used this as our estimator of the intervention’s impact, comparing electricity use in treatment and control households, before and after the treatment period ( Eq. 1 ):

where y it is the log of average daily electricity consumption for household i in month (billing period) t, treatment_group i indicates whether household i is in the treatment (1) or the control group (0), and treatment_period t is the fraction of days in the treatment period included in monthly electricity use for t . X it is the interaction between these two terms, equal to the fraction of days in the treatment period for month t for households in the treatment group and 0 for households in the control group. Because most of the variation in electricity use in this region reflects demand for heating and air conditioning, our statistical model included heating and cooling degree days in each billing period: CDD it and HDD it are the average cooling and heating degrees days for month t , respectively, using the weather station closest to household i . Several household characteristics (e.g., household size and electric heating) were included in the regression and are denoted as η i (see Supporting Information for details). The error term is e it . β 1 is the average treatment effect of the intervention.

We calculated the average treatment effect estimators for the posttreatment period in the same way. We used two posttreatment periods, for the month after the intervention ( Eq. 2 ) and for the following month ( Eq. 3 ), to estimate carry-over effects, perhaps reflecting energy-saving habits that people formed during the intervention, and then maintained afterward.

where the new interaction terms, Y it and Z it , are equal to the fraction of days in the first and second months, respectively, after the intervention ended for households in the treatment group and 0 for households in the control group. β 2 and β 3 are the average treatment effect for the first and second month after the intervention, respectively. As in Eq. 1 , first-month-after_period t and second-month-after_period t indicate use changes, that hold for both control and treatment groups, in each posttreatment period for t .

Table 2 presents ordinary least-squares (OLS) analyses, using robust SEs clustered by household. Models I, II, and III represent the treatment and posttreatment effects specified above, in Eqs. 1 , 2 , and 3 , respectively. The table shows that the average household in the treatment group used 2.7% less electricity during the month of the study (model I, β 1 = −0.027, P = 0.03), compared with the control group. These results are essentially the same when adjusted for observed days within the treatment month, as would be expected given the 97.9% overlap in the periods. As shown in models II and III, there was no posttreatment effect in either the month after the last postcard (model II, β 2 = −0.007, P = 0.45) or in the second month after that (model III, β 3 = −0.005, P = 0.55). Supporting Information shows that these results are highly robust to changes in model specification and that including temperature data and household characteristics markedly improve the fit of the regressions ( 24 ).

OLS regressions and average treatment effects, indicating the percentage change (savings) in the treatment group compared with the control group

Dependent variable (DV) is the log of household's average daily electricity use.* P < 0.10, ** P < 0.05, *** P < 0.01. A log transformation of average daily use produced residuals closer to a normal distribution than did analyses using actual use, suggesting more robust results and inference. Without the transformation, the average treatment effect was −0.998 kW⋅h/d ( P = 0.04), or 2.2% based on the control group’s average daily use of 44.5 kW⋅h/d during the treatment period.

The survey was conducted a month after the field intervention ended. It followed the tailored design method ( 25 ). The analysis focuses on treatment group respondents able to answer questions about the intervention. Most treatment group respondents (68.1%) reported remembering at least one postcard out of the five, with a mean of 3.0 (SD = 1.3). Respondents who could not remember a single postcard may simply have forgotten in the month since the study ended. Or, they may not be the person who got the card—although most did say that they were the person who usually picks up the mail. When asked an open-ended question about the purpose of the study, 30.2% of these respondents cited variants of “save, learn, or be more aware about electricity,” 29.6% offered variants of “study electricity usage” (as stated in the postcards); 20.4% said that they did not know. When asked how the study had affected them, 22.2% agreed or strongly agreed with the statement “the study made me reduce my electricity usage,” where 1 = “Strongly disagree” and 5 = “Strongly agree.” In addition, 36.4% thought that the study had made them more aware of their electricity use and 30.2% that they had learned more about what things use electricity.

As seen in Table 3 , treatment group respondents were more likely to report that they had reduced their electricity consumption when they saw themselves as doing more than their neighbors to save electricity (model 1; β = 0.386, P < 0.01), and when they perceived the study as having heightened their awareness of electricity use (model 3; β = 0.669, P < 0.01). Whether they reported reducing their consumption was not related to whether they expressed concern about privacy with new metering devices that would constantly track their use, which could be seen as another form of awareness. Finally, even though perceived reductions were related to believing that the study was about reducing, learning, or being aware of electricity use (model 2; β = 0.545, P < 0.01), that effect disappeared when reported electricity awareness was added to the model (model 3). Thus, perceived reductions reflect heightened awareness of electricity use as a result of participating, rather than beliefs about the study’s purpose. Additional regression analyses found no relationship between actual use and these survey questions (See Supporting Information for details). However, only 162 respondents reported remembering at least one postcard, limiting the statistical power of this test.

Survey measures associated with reported-use electricity reduction

Of the 162 treatment group respondents who reported remembering at least one postcard, hence could answer questions about the study, 136 answered all of the questions used in this analysis. Unstandardized coefficients. Unless otherwise noted, for all scales 1 = “Strongly disagree” to 5 = ”Strongly agree.” * P < 0.10, ** P < 0.05, *** P < 0.01.

When asked how often they had performed nine energy-saving actions (with “never” = 1 and “always” = 5), treatment group respondents who reported reducing their electricity consumption were also more likely to report turning off their air conditioning, unplugging devices when not in use, and using electrical devices less, compared with respondents in the control group ( P = 0.07, P = 0.01, and P < 0.01, respectively). There were no differences in reports of the other six actions, whether routine (e.g., turning off computers and lights) or sustained (e.g., buying energy-efficient light bulbs or appliances). Comparing all actions reported by treatment group respondents who reported not reducing their electricity use with respondents in the control group revealed only one significant difference: Control group respondents reported using electrical devices less ( P < 0.01).

We find evidence for a “pure” (study participation) Hawthorne effect in electricity use. Residential consumers who received weekly postcards informing them that they were in a study reduced their monthly use by 2.7%—an amount greater than the annual conservation goal currently mandated by any state. A follow-up survey found that participants who reported having responded more to the study also reported greater awareness of their electricity consumption and saw themselves as already doing more than their neighbors. These results suggest that the Hawthorne effect occurred here because participation in the study increased the saliency of the focal behavior—an interpretation supported by the fact that the treatment effect vanished when the intervention ended.

The field study contributes to our understanding of the Hawthorne effect by addressing methodological limitations of previous studies. Namely, our design isolates the effect of participation in a study from potential confounds, such as providing information or feedback. The follow-up survey further clarifies the underlying mechanisms. Our results suggest that participation in a study can change behavior without providing feedback, resources, information, or direct observation. The results also suggest that participants’ interpretation of the study’s purpose was less relevant than their increased awareness of the study’s topic, in a context where attention alone might change behavior—because people already know how to respond. As with any self-reports, these responses may not have reflected participants’ actual behavior or perceptions. According to one well-known account, self-reports are more accurate when the stimulus is salient and the responses plausible ( 26 ). Those conditions should hold for our stimuli (postcards) and focal responses (energy-saving actions). According to another well-known account ( 27 ), retrospective self-reports are less valid than concurrent ones. Ours fall somewhere in between, with participants reporting on the actions that they remember having taken in response to the postcards. Still, it is possible that the relationships that we observed might have been obscured by cases in which participants failed to remember their own actions or succumbed to social desirability bias and reported actions that they had not actually taken. Further clarifying the mechanisms affecting Hawthorne responses is an important topic for future research. Another topic for future research is how the Hawthorne effect varies with the source of the observation or study (neighbors, utility company, a university, or a governmental agency) and how people view (e.g., trust) it.

The Hawthorne effect has long been known as a potential experimental artifact. The present results show the importance of assessing the impact of just being in an electricity-use study, before making inferences about the impact of experimental manipulations. Were people better informed about how best to save energy, then the energy saving might be larger. However, providing guidance regarding effective energy-saving actions ( 28 ) would have confounded our study of Hawthorne effects. These results also suggest how these behavioral changes come about: by heightening awareness of electricity use. That interpretation is consistent with the observation that the effects of sustained energy conservation programs seem to decay between quarterly use reports ( 29 ). Thus, any socially acceptable way of increasing awareness might reduce consumption for those motivated to do so, but only as long as the intervention continues, unless it creates sustained habits or prompts structural changes (e.g., buying efficient air conditioning or upgrading home insulation). We cannot know what effects a sustained Hawthorne intervention (e.g., a steady stream of postcards notifying consumers about new studies) would produce. It is possible that it would lose effect over time, as consumers habituate to the messages, or have increasing effect, as awareness becomes routine and energy-saving behaviors a matter of habit. However, if awareness alone can improve performance in contexts where people require no additional information, we might retire the “Hawthorne effect” in favor of a “Hawthorne strategy” ( 30 ) of reminding people about things that matter to them but can get neglected in the turmoil of everyday life.

Field Experiment Participants.

Participants ( n = 6,350) were randomly selected from a dataset of residential customers who live in one of the regions served by a major mid-Atlantic electricity utility. Customers with scheduled meter reading dates close to July 20, 2011, and August 20, 2011, were eligible for the study. Other eligibility criteria were met by almost all customers: having an individual electricity meter and being a residential customer under a standard (i.e., flat-rate) price-scheme program. From the 45,509 eligible customers, 6,350 were randomly selected and divided between the treatment and control groups. This sample size was determined through statistical power analysis using 2010 electricity-use data, considering effect sizes of previous energy conservation programs and budget constraints.

The intervention lasted from July 20, 2011, to August 20, 2011. Households in the treatment group received postcard notification of participation in the study a few days before its beginning. Then, at weekly intervals, they received three postcards reminding them of their participation and a final postcard notifying them that the study was ending. All material said that the households were participating in a study conducted by researchers at Carnegie Mellon University, but with no explicit goal other than measuring their electricity consumption: “You have been selected to be part of a one-month study of how much electricity you use in your home. This study will start on Wednesday July 20, 2011, close to the day of your meter reading this month. No action is needed on your part. We will send you a weekly reminder postcard about the study. Thank you. This study is being conducted by researchers at Carnegie Mellon University with help from your utility company.” Customers’ names and addresses appeared as well, using the post office format. On the front of the postcard was a picture of a house with appliances connected to an electricity meter and the Carnegie Mellon University logo. The materials were pretested with a sample of people recruited from an online national subject pool, to assess their understanding and interpretations. Postcards were sent out on Fridays, so households would receive them the following Monday or Tuesday and be informed in a timely fashion about the beginning and end of the study. We sent postcards to two households of the study’s service territory but not part of the study, who confirmed their arrival dates. The control group received no experimental material.

The field study used an opt-out design, in which customers (in the treatment group) could call a 1-800 toll-free number or visit a Web site to request not being part of the study and not receiving additional material. None of these communication channels provided more information than that shown on the postcards. Thirty-six (treatment group) participants (1.28%) elected to opt out. Although they received no additional postcards, they were included in the analyses of energy use for two reasons: ( i ) We had intended to treat them and ( ii ) receiving one or two postcards (and actively opting out) may have increased their energy awareness, distinguishing them from the control group. Excluding them did not affect our results.

The sample was selected with 2010 data. By the start of the study (summer 2011), 9.7% of households in the treatment group and 9.3% in the control group had moved or closed their accounts and hence did not receive the materials. Between August and October 2011, an additional 2.1% of households in the treatment group and 2.6% in the control group had moved or closed their accounts. The postcards had a “sender request to be returned” stamp, and most returns indicated that customers had moved. As of October 2011, the final treatment and control groups had 2,802 and 2,796 participants, respectively. There was no significant difference between the treatment and control group in attrition rate [ χ 2 (1) = 0.04, P = 0.84]. Although there are no data on electricity consumption for these households for the study period, there is information about some characteristics, revealing that they had lower baseline electricity consumption and were more likely to be renting than those who received the study materials ( P < 0.05). Thus, participants in the study ( n = 5,598) represented more “settled” households in the area.

Electricity Consumption Data.

All participants had 2 y of prior monthly electricity use (133,545 observations), from November 2009 to October 2011. Of these, 6.7% had monthly electricity bills based on estimates, rather than actual consumption, as a result of scheduled meter readings not being performed, typically owing to weather conditions or meter inaccessibility. They were excluded, as were a few (<0.1%) with zero readings. These exclusions left 124,578 observations in the analysis.

Meter Reading Dates.

Meter readings are not always performed on the scheduled day, meaning that the treatment period did not fully coincide with a single billing cycle of participants. Overall, there was a 97.9% overlap between participants’ bill cycle and the month of the treatment period. For the months before and after the treatment, the overlap was 9.5% and 3.6%, respectively. We adjusted our analyses to consider the days in the monthly billing cycle that overlapped with the study treatment and posttreatment periods.

Weather and Household Data.

Cooling degree days in the billing period for each household were calculated as the sum of the average daily temperature over 65 °F, for a billing period, using the closest weather station to its ZIP code. Heating degree days were calculated similarly for average daily temperatures below 65 °F. Household data were obtained from utility company and 2010 Census data, for which we geo-referenced addresses to block and tract numbers. Supporting Information details all variables.

Survey Respondents.

Participants from the treatment ( n = 600) and control ( n = 370) groups were mailed a survey. Given our interest in how the intervention affected treatment group members, they were oversampled, with the control group’s survey responses used to compare self-reported energy-saving actions (See Supporting Information for details). Sixty-nine participants had moved or closed their accounts, hence did not receive the survey. From the 572 (treatment group) and 329 (control group) participants, the overall response rate was 42.5%, with no significant difference between groups ( P = 0.97). This response rate is greater than the response rate normally reached by the utility company that serves these customers, which is around 10%. See Supporting Information for respondents’ and nonrespondents’ characteristics, using Census and electricity-use information, with a few seemingly minor differences.

Participants received a package containing a cover letter explaining the goal of the survey, a 5-min survey with questions about electricity, a $2 bill, and a postage-paid envelope. One week later, all participants received a thank-you-and-reminder postcard. Participants had the option of answering the survey online. Two-thirds of participants were randomly offered participation in a raffle if they returned the survey before the end of September, as part of our ongoing study of how to increase participation rates (it made no difference.) Supporting Information details all questions included in the survey.

Supplementary Material

Acknowledgments.

We thank W. Bruine de Bruin, D. Caruso, and J. Wang for their help in this study and The Energy and Behavior Group for valuable comments. This material is based upon work supported by the Department of Energy under Awards DE-OE0000300 and DE-OE0000204. This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission. T.D. is a guest editor invited by the Editorial Board.

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1301687110/-/DCSupplemental .