Lecture 1, Introduction
Business research: a series of well-thought out activities and carefully executed data analyses that
help a manager to avoid, solve, or minimize a problem
- Intuition without research leads to losses. See the example of coca cola c2. They wanted to
make a male version of the diet coke but they didn’t ask the public what they wanted and
failed with their cola c2.
- Experience without research leads to losses. In the US people want to clean fast, so products
that make cleaning easier do pretty well. In Italy they don’t care about cleaning fast, but
about cleaning properly. So the Swiffer Wet doesn’t fit the needs of the Italian customer
o Us cleans 4 hours a week
o Italy cleans 21 hours a week
The book mentions 8 points for good research, however the ones we have to know are:
- Purposiveness, knowing ‘the why’ of your research e.g. dissatisfied employees
- Rigor, ensuring a sound theoretical base. Ensuring a sound methodological design (the way
you are going to gather your data).
o Representative sample
o Unbiased questions
- Objectivity, drawing conclusions based on facts
- Parsimony, shaving away unnecessary details. So keep it simple, explaining a lot with a little
- Replicability, finding the same results if the research is repeated in similar circumstances. So
describe your study design in detail!
- Generalizability, being able to apply the research findings in a wide variety of different
settings
o Should hold for fundamental research
o …. But much less so for a[plied research
Applied research:
- To solve a current problem faced by a manager
- Applies to a specific company
- Within firms or research agencies
Fundamental/basic research:
- To generate new knowledge about how problems that occur in several firms can be solved
- Applies to several organizational settings
- Mainly within universities and knowledge institutes
➔ Fundamental research is often used in applied research
Deductive research: you look into literature and you distinguish theories and develop hypothesis.
You will test these hypotheses by gathering data. So you are testing a theory.
• If it rains, everything outside becomes wet.
• It rains.
• The car is outside.
→The car will become wet
We start with a general theory and then we see in practice what happens
Inductive research: ‘data’ are observations. There is a higher chance of error, that the theory
doesn’t work out. Inductive research is often tested via a deductive method. Through inductive
research you try to build a theory.
• The first duck in the park is brown.
• The second duck in the park is brown.
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, • The third duck in the park is brown.
→Every duck in the park is brown
We only have 3 different observations and based on these observations we develop a theory
The seven-step deductive research process
Inductive research process
Notice that step 3 and 7 are different from the deductive method
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,Lecture 2, The research process
Stated as a question
Stated as a question
Not stated as a question
Business problem occurs when there is a gap between the actual status of a company and the
desired status of the company. There are two types:
So there might be a serious problem
or an opportunity for growth
Examples:
- Problem where the actual state of a company is seriously wrong: Suppose you are Unilever,
and Albert Heijn boycotts your products. Albert Heijn refuses to sell your products. Unilever
needs to solve this problem asap because they are losing a lot of sales due to this boycott.
- The actual situation is not seriously wrong but it can be further improved: Suppose you are
Pfizer (a company which among others sells medicines and vaccines). You are making good
profits, but you may want to make more profits. And you wonder whether you can do so by
having your sales reps approach doctors and pharmacists differently.
What makes a good business problem?
- Feasibility, is it doable?
- Relevance, there should be a party interested in your research
Feasibility
- Have a good demarcation. It needs to be specific but not too specific. Use specific terms not
only use the words ‘methods’ and ‘how should we do this’. You should include a clear
relationship with variables you can research. BUT don’t have too much variables, you should
narrow it down to a group of specific variables.
- Should be expressible in variables. A good variable is a variable that can vary; the variable
should at least be able to have two different levels
o E.g. gender: female, male
o Revenue: very from 0 to millions of dollars
- Are you able to gather the required data?
o Existing data, data that the company you work for owns ór purchases from data-
providing companies
o New data for example through surveys or through interviews
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, Examples of infeasible business problems
ABN Amro would like to increase its profits.
- it is way too big. There’s zillions of ways to improve profits, and no-one can study them all.
Hence, the problem is not well demarcated
- This business problem cannot be expressed in variables, as there are hundreds of variables
that may increase profits
- Finally, if the list of variables is endless, [CLICK] then it is also unlikely that you will be able to
gather the required data
Philips would like to know whether running price promotions on their products can reduce the
profitability of their competitors’ new products
- This business problem is well demarcated
- It can also be expressed in variables. The variables are
o Price promotions on Philips’ products
o Profitability of competitors’ new products
- The issue here is that you cannot get access to the required data to research this problem.
Profit information is not available for competitors’ products. You can buy data that capture
the sales of your competitors’ products – through market research agencies– but you cannot
buy profit data for your competitors’ products
Relevance
- Managerial relevance, someone should actually benefit from having the problem solved
- Academic relevance, The problem should not have been solved before in academic research
Managerial relevance: Who benefits from having the problem solved?
- Managers
o Of one company
o Of one industry
o Of multiple industries
- End users (consumers, tax payers, stock buyers, investors…)
- Public policy makers (government, EU, …)
There are a lot of situations where it is relevant for multiple stakeholders.
Academic relevance: Solving a business problem can contribute in various ways to extant knowledge
- Completely new topic
o No research available, although the topic is important (e.g. research drone delivery)
o However, maybe the topic has not been researched because it is unimportant in the
first place. So, you also need to argue why that topic is important.
- New context
o Prior research is available but not in the same context
▪ Do the research in company X instead of company B
▪ A lot of research has been done on private labels in grocery stores. If you
apply this research to the fashion industry you apply it to a new context
- Integrate scattered research
o Different studies have focused on different IVs/moderators; consequently, their
relative importance is not clear
- Reconcile contradictory research
o Solve the contradictions through introducing one or more moderators
▪ For example, one study may have concluded that outsourcing increases
company profitability, whereas another study may have concluded the exact
opposite. You can introduce variables that explain under which conditions
the effect of outsourcing is positive versus negative.
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