Samenvatting
Samenvatting - Business Research Techniques (BRT) voor PreMaster TISEM (320087-B-6)
deze samenvatting omvat alle stof van BRT, met alle modules die in 2022 zijn weergegeven.
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Voorbeeld 4 van de 64 pagina's
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BUSINESS RESEARCH TECHNIQUES FOR PMModule 1: The Research Process
Chapter 1: Why business research?
1.1 What is business research
Business research can be defined as ‘a systematic process of testing hypotheses through carefully
executed data analyses that are aimed to help a manager solve, avoid, or minimize a problem’
Business research is a systematic process
Business research consists of several distinct but highly interrelated stages. It is systematic because
these stages are universally agreed upon
Business research tests hypothesis
Business research involves constructing testable hypotheses. Whether a study start with or without
constructing hypotheses, it produces the same empirical findings. In a study without hypotheses,
however, these findings could be a mere coincidence, rather than contribute to the understanding of
the problem.
Business research entails colleting and analyzing data
Business research is empirical. Data can be collected in various ways, e.g. through surveys,
experiments, extraction from companies internal databases (e.g., customer account information) or
government databases (e.g., Centraal Bureau voor de statistiek), web scraping, interviews, or
observations.
Business research is meant to help managers make better decisions
Better decisions are evidence-based decisions: decisions that rely on a thorough and painstaking
assessment of empirical data.
1.2 How about managerial intuition?
Why are managers better off when they base their decisions on research? Do the best managers not
make decisions based on their intuition? Is intuition not a reliable (and less time-consuming)
alternative to data gathering and analysis?
Intuition should never be a substitute for research. While intuition has its place in managerial
decision-making (you should not ignore your instincts any more than your conscience), detached
from rigorous data gathering and analysis, intuition can lead us to make less effective decisions. And
while some people have argued that intuition becomes more valuable in highly complex and
changeable environments, the opposite is true. The more unprecedented the challenges you face,
the less you should rely on intuition and the more on evidence/research.
Why can managers' intuition be so wrong?
Managers (like all humans) are prone to cognitive biases. Cognitive biases are unconscious thinking
errors. They are an attempt of our brain to simplify the complex world and speed up decision-
making. These biases lead managers to misinterpret information. They negatively affect the
rationality and accuracy of their decisions. Every day, we are subject to these cognitive biases that
speed up our decision-making. A simple example on the next page illustrates our point.
,1.3 In total, there are over 100 cognitive biases that affect how we process information. Three of
the most common cognitive biases that may affect managers decisions are:
- Confirmation bias
- Availability bias
- What-You-See-Is-All-There-Is (WYSIATI) bias
1.3.1 Confirmation bias
Confirmation bias refers to the tendency to only consider information that
agrees with ("confirms") your preexisting beliefs. You cherry-pick the
information you consider: you look for only the evidence that supports
what you are already thinking and disregard the rest. As such, you may
become a prisoner of your own prejudices.
A business example:
In the investing world, confirmation bias may lead investors to cling to
preconceived notions about their investments, while discounting
information that contradicts these ideas. For example, investors whose
holdings are concentrated in a specific sector may only absorb good news
and ignore bad news regarding this sector. This may lead them to
overinvest in a particular sector. Please read this article for additional
business examples of how managers' confirmation bias may reduce business profits.
1.3.2 Availability bias
Availability bias (also known as the availability heuristic) refers to a cognitive bias in which you make
a decision based on readily available information, even though it may not be the best information to
inform your decision.
Information that is more easily recalled (i.e., is more available because it is more vivid or recent) is
assumed to reflect more frequent and more probable events, while information that is more difficult
to bring to mind (i.e., less available because it is less vivid or recent) is assumed to reflect less
frequent and less probable events. The availability bias thus leads you to overestimate events.
A business example:
The availability bias permeates investment decisions. The availability bias magnifies stock market
volatility because investors tend to overreact to the latest news and buzz. The availability bias helps
explain how a group of users on Reddit could game the stock market by creating social media buzz to
drive the stock of Gamestop (a struggling brick-and-mortar gaming retailer) from a price of $17 at the
beginning of January to a record high of $469 (!) at the end of January. Investors assumed that
because Gamestop was garnering buzz, it must be important, but did not question the
trustworthiness of the information. This led to an overreaction.
1.3.3 What-You-See-Is-All-There-Is (WYSIATI) bias
When deciding whether there is a relationship between an event and an outcome, we tend to notice
what is present but we often forget to consider what is absent. This tendency is referred to as What-
You-See-Is-All-There-Is. Because of this cognitive bias, managers adopt opinions, structure
businesses, and make decisions without examining all the data, which can easily lead to suboptimal
decisions.
A business example:
In a business context, managers tend to notice the times when both a decision (e.g., running an
advertising campaign for a brand) and the desired outcome (e.g., increased brand sales) are present
but are less likely to notice the times when they did not make that decision; however, the outcome
,was still present (e.g., they did not run an advertising campaign for a brand and brand sales increased
anyway).
Consider this 2x2 matrix with the numbers in each cell representing the number of cases (brands).
Managers are more likely to focus on the red number, when both the event and the outcome are
present, rather than on the total picture. For the numerical example in this matrix, they would
conclude that their decision is booming (if they only focus on the red cell).
Sounds great... but reality tells a different tale . In reality, they would be better off doing nothing.
After all, 45% [45/(45+55)] of the instances when doing nothing are linked with better outcomes,
whereas only 20% [10/(10+40)] of the instances with the decision. Suddenly, the decision does don't
seem like a great idea after all.
1.4 How to evaluate research evidence
As future managers, you should follow an evidence-based approach to decision-making, rather than
an intuition-based approach, which may be biased. To base your decisions on empirical evidence, you
will need to read research studies. Unfortunately, not every research study is equally sound. So, how
do you evaluate how much confidence to have in a study that you retrieved? The goal of this course
is to give you the tools to critically evaluate research studies so that you are not misled.
1.4.1 Judging academic-journal quality
Just because you find an academic article through an online search does not mean you should use it
in your decision-making. In fact, while some journals are legitimate, others are predatory. Their sole
purpose is to make money: they ask authors to publish for a fee without providing a peer review (the
independent evaluation of the work by experts). They publish almost everything they receive, even
complete nonsense articles.
How can you evaluate whether a journal is worthy of being considered?
You can check whether the articles in the journal are peer-reviewed. If they are not, the
journal is likely to be predatory.
You can look up the impact factor. While this is not a perfect measure, a journal with an
impact factor of at least 1.0 is more likely to be legitimate.
In the field of business, you can consult the list of quality journals compiled by TISEM.
1.4.2. Judging article quality within peer-reviewed journals
Within peer-reviewed journals, article quality can still vary. Many people firmly believe that a study is
worthless if it is not based upon a very large, random sample of the population. However, a large
sample is not always the first priority; other characteristics of a study may be more important.
1.4.3. Judging popular-press articles
Science journalists translate the findings of academic articles for a wider audience. Hence, in your
future jobs, you may not only read business research in academic articles, but you may also
encounter popular-press articles that interest you.
Most science journalists do a good job. However, sometimes a popular-press article is unreliable
because it is based on flawed academic research. Do you recall the article "Chocolate Causes Weight
Loss" that was published in a predatory journal? It got picked up in the popular press in more than 20
countries!
, In other instances, a popular-press article is unreliable because it did not describe the underlying
academic article accurately; it did not get the story right.
Summary
You should be knowledgeable about business research:
1. To be able to EVALUATE business research.
You should be able to judge to what extent academic and popular press articles can be trusted as
a basis for your decisions.
2. To be able to DELEGATE business research.
You should be able to interact effectively with your firm's in-house research department and/or
external research agencies that will conduct research studies for you. If you cannot steer
business research, you may end up with great answers from external researchers but to the
wrong questions.
3. To be able to PERFORM business research.
You should be able to perform research studies yourself to solve the smaller problems that you
will encounter in your future jobs.
Chapter 2: The stages of the research process
2.1 Deductive vs. inductive research
Deductive and inductive research are two research
approaches.
When using an inductive research approach, researchers
first collect data. Next, they try to find a pattern in these
data, after which they develop a theoretical framework
based on this pattern.
When using a deductive research approach, researchers
first hypothesize relationships between variables based on theory. These hypotheses are then tested
using data. Thus, while inductive research aims at developing a theory, deductive research aims at
testing a theory. These two research approaches are not mutually competing. They are sometimes
used in combination, within a single research study.
2. The 7-step deductive research process
How do you set up a deductive research study?
The figure on the right shows the seven steps in a deductive research study.
These seven steps form the guiding framework along which this course is
structured.
Summary
Deductive research starts with a theory and then tests this
theory using data.
Inductive research starts with collecting data and then
develops a theoretical framework based on the data.
The seven steps in the deductive research process are: (1) defining a problem, (2)
formulating research questions, (3) developing a theoretical framework, (4) choosing a
research strategy, (5) collecting the data, (6) analyzing the data, and (7) writing a report
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