7S
MSIN0014
Refining Your
Research Question
?
Behavioural Science
Your research
question!
The necessity of a focused approach
Big ideas are great! BUT, you can’t test them all at once
A simple research proposal you can actually test > a complex
research proposal that you can’t test
Think of the simplest, most basic, “baby step” way of approaching
your research question
A lot of decisions need to be made and a lot of details need to be
crystal clear
Section 1 – Introduction
What are you trying to accomplish?
Why does it matter to managers?
Why does it matter to scholars?
Focus on the most important and compelling arguments.
1a. Research question
Pick an outcome (just one!)
Most students find it easiest to look at a quantifiable outcome (i.e., conduct
quantitative research).
Examples: number of emails sent in a day, responses to a questionnaire
about job satisfaction, total number of sales, etc.
Pick a predictor (just one!)
Most students find it easiest to propose a simple two-condition experimental
design
Examples: sending employees an informational email (vs. not), giving
employees a monetary reward (vs. not), asking managers to read an article
about your research focus (vs. an article about something else)
1a. Research question
Be as specific as possible! Revisit 2S slides for guidance on how to refine
For example, “productivity” isn’t a great outcome variable because there are a
million ways to conceptualize and measure productivity
“How do bonuses impact productivity?” -> “Does giving a £10 gift card (vs. not)
to baristas before a shift increase the average speed of coffee making during
that shift?”
“How does awareness of implicit bias impact discrimination in hiring?” -> “Does
asking hiring managers in tech to read an academic article about implicit racial
bias (vs. an academic article about road traffic) decrease discrimination on a
fictitious hiring exercise afterwards?”
1b. Managerial relevance and impact
Why does this matter? Hopefully, this will be obvious, but state it
plainly and clearly
If you are situating your research in a specific context (e.g., industry
or profession; this helps with overall specificity), make that clear here
If you feel you’re forced to study something less important than your
original idea, that’s normal, remember this is just a first step!
1c. Literature review
What are the “headlines” from the existing literature?
Length may vary, but it will be a fraction of a standard lit review
If you used a particular paper or several as inspiration, how is your
approach different and how does that add value beyond what we
know?
Section 2 – Theoretical model
What are the variables you’ll be testing?
How are these variables related theoretically?
2a. Outcome
Briefly describe your outcome variable
Ensure it meets the SMART criteria (see 2S slides)
Ensure it’s clear how you would measure this
Offer more detail than in your research question, but you can save
fine-grain specifics (e.g., individual survey questions) for 3b
(Methods)
2b. Predictor
Briefly describe your predictor and why (theoretically) it should impact your
outcome variable
If doing an experiment (most students), how would you manipulate this?
Having a simple experimental design will allow you to rule out confounds,
but you should note if there are any you can’t avoid
Offer more detail than in your research question, but you can save finegrain specifics (e.g., verbatim examples of manipulations) for 3b
(Methods)
2c. Mechanism (Mediator variable)
What is a plausible mediator (i.e., what answers the question “Why
should your predictor impact your outcome?”)
Briefly explain your reasoning
You may think of multiple mediators, but you’ll probably only have
space to write about one
2d. Moderator variable
What is a plausible moderator (i.e., what answers the question
“When or for whom should your predictor impact your outcome?”)
Briefly explain your reasoning
You may think of multiple moderators , but you’ll probably only have
space to write about one
Section 3 – Research plan
What exactly would your proposed study look like in practice?
Again, the simpler the design, the more likely it is you can actually
test it!
3a. Hypotheses
Present both your null (there is no effect of your predictor on your
outcome) & alternate (there is an effect of your predictor on your
outcome) hypotheses (see 2L for examples)
Most (basically all) proposals won’t have space to tackle more than
this one set of hypotheses
3b. Methods
What would your study look like in practice?
Is your description clear enough that someone would be able to
conduct your research without returning to you for clarification?
Don’t worry about specifying sample size or the exact statistical tests
you would need to run
3c. Feasibility and limitations
How confident are you that you could run your study as proposed?
What might go wrong? Conduct a “pre-mortem”
What tradeoffs have you made (e.g., sacrificing realism for control
and simplicity)?
What questions should you research next? (e.g., your big ideas)
Overarching advice
The necessary length of each section will vary case by case
Aim to write using as few words as you possibly can -> Be concise
Be ruthless in your editing
When in doubt, take the simpler route
Peer feedback
Pair up and take turns sharing your progress so far
If you don’t understand exactly what your discussion partner is
talking about, push them for more detail
Looking ahead
Next lecture – Ethics in Behavioural Science
Read “A New Model for Ethical Leadership” & “The Ethics of Nudging”
and watch “Is There a Reproducibility Crisis in Science?”
Next seminar – Module Wrap-Up
Individual Research Proposal due March 23rd at 1 pm
This seminar’s attendance code: [INSERT HERE]
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