Understanding How OB Research Is Done
Learning Objectives
- Learn the terminology of research.
- Understand the different types of OB research methods used.
OB Research Methods
OB
researchers have many tools they use to discover how individuals,
groups, and organizations behave. Researchers have working hypotheses
based on their own observations, readings on the subject, and
information from individuals within organizations. Based on these ideas,
they set out to understand the relationships among different variables.
There are a number of different research methods that researchers use,
and we will discuss a few of these below. Imagine that your manager has
asked you to find out if setting goals will help to make the employees
at your company more productive. We will cover the different ways you
could use research methods to answer this question, impress your boss,
and hopefully get a promotion.
Surveys
Surveys
are one of the primary methods management researchers use to learn
about OB. A basic survey involves asking individuals to respond to a
number of questions. The questions can be open-ended or close-ended. An
example of an open-ended question that could be used to address your
manager's question would be to ask employees how they feel about goal
setting in relation to productivity, then summarize your findings. This
might work if you have a small organization, but open-ended surveys can
be time consuming to summarize and hard to interpret at a glance. You
could get more specific by asking employees a series of close-ended
questions in which you supply the response key, such as a rating of 1 to
5. Today it is easy to create online surveys that quickly compile the
results automatically. There are even several free survey tools
available online such as http://freeonlinesurveys.com/ and
http://www.surveygizmo.com/, or you can use paper-and-pencil surveys.
Sample Survey About the Effectiveness of Goal Setting
Instructions:
We would like to gather your opinions about different aspects of work.
Please answer the following three questions using the scale below:
Response Scale:
1=Strongly disagree
2=Disagree
3=Neither agree nor disagree
4=Agree
5=Strongly agree
Setting goals at work helps me to focus |
1 |
2 |
3 |
4 |
5 |
Goal setting is effective in improving performance |
1 |
2 |
3 |
4 |
5 |
I get more done when I use goal setting |
1 |
2 |
3 |
4 |
5 |
Regardless
of the method you choose to collect your information, the next step is
to look at the average of the responses to the questions and see how the
responses stack up. But this still wouldn't really answer the question
your boss asked, which is whether using goal setting would help
employees be more effective on the job. To do this, you would want to
conduct a field study.
Field Studies
Field
studies are also effective ways to learn about what is truly going on
within organizations. There are survey field studies like the one above,
but more compelling evidence comes from field studies that employ an
experimental design. Here you would assign half the employees at your
company to the goal setting condition and the other half to the control
group condition. The control group wouldn't get any information on goal
setting but the treatment group would. If you found that the treatment
group was more effective than the control group, you could tell your
boss that goal setting works.
Laboratory Studies
OB
researchers are often interested in basic research questions such as
"Can we show that goal setting increases performance on a simple task?"
This is how research on goal setting started, and it is also how we can
establish the conditions under which it works more or less effectively.
Again, to address this, researchers may conduct a lab study in which one
group is assigned one condition and the other group is assigned the
control condition (generally the control condition involves no change at
all). You may even have been involved in a lab study during your time
at your university. One of the most important concepts to understand
with lab studies is that they give the researcher a great deal of
control over the environment they are studying but do so in a less
"realistic" way, since they are not studying real employees in real work
settings. For example, in a lab study, a researcher could simulate
hiring and firing employees to see if firing some employees affected the
goal-setting behavior of the remaining employees. While this wouldn't
be legal or ethical to do in a real organization, it could be a
compelling lab study. At the same time, however, firing someone in a lab
setting does not necessarily carry the same consequences as it would in
real life.
Case Studies
Case
studies are in-depth descriptions of a single industry or company. Case
writers typically employ a systematic approach to gathering data and
explaining an event or situation in great detail. The benefits of case
studies are that they provide rich information for drawing conclusions
about the circumstances and people involved in the topics studied. The
downside is that it is sometimes difficult to generalize what worked in a
single situation at a single organization to other situations and
organizations.
Meta-Analysis
Meta-analysis
is a technique used by researchers to summarize what other researchers
have found on a given topic. This analysis is based on taking observed
correlations from multiple studies, weighting them by the number of
observations in each study, and finding out if, overall, the effect
holds or not. For example, what is the average relationship between job
satisfaction and performance? Research shows that, looking across 300
studies, the relationship is moderately strong. This is useful information because
for years people had thought that the relationship did not exist, but
when all the studies to date were examined together, the original
beliefs about the satisfaction–performance relationship deteriorated.
The advantage of meta-analysis is that it gives a more definitive answer
to a question than a single study ever could. The downside is that
meta-analysis is only possible if sufficient research has been done on
the topic in question.
Measurement Issues in OB
Another
important thing to understand is the difference between
reliability and
validity. Imagine you own a trucking company. A major component in
trucking is managing the weight of different cargo. If you had a scale
that gave you the same weight three times, we would say that was a very
reliable scale. But, if it turns out the weights given are in kilograms
instead of pounds, it would not be a valid measure if you charge for
delivery by the pound.
Finally,
much of management research addresses correlations between two concepts
rather than actual causation. Correlation simply means that two things
co-vary. For example, it would be inaccurate to assume that because 99%
of the people who died this year also drank water, consuming water kills
people. Yet many people claim their product caused a positive outcome
when, in fact, the data do not support their claim any more than the
water example. This brings up something that confuses even seasoned
researchers. When you have only one observation it is called a datum.
When you use the word data, it refers to multiple observations, so it is
always plural.
Key Takeaway
OB
researchers test hypotheses using different methods such as surveys,
field studies, case studies, and meta-analyses. Reliability refers to
consistency of the measurement while validity refers to the underlying
truth of the measurement. It is important to recognize the difference
between correlation and causation.
Exercises
-
Create a hypothesis about people at work. Now that you have one in
mind, which method do you think would be most effective in helping you
test your hypothesis?
- Have you used any of the OB research methods before? If not, what can you do to become more familiar with them?
- Give an example of a reliable measure.
- Give an example of a valid measure.
- How can you know if a relationship is causal or correlational?