Summary Notes of all knowledge clips - Academic Project 2020

Knowledge Clips Academic Project
Week 1
1.1 – Foundation research, Research as a language, What is (Business and Management)
research
What characterizes the scientific mindset?
 Research is about producing new and valid knowledge
 How do we know which knowledge to trust?
 Rene Descartes  “Cignito ergo sum” = I think/doubt, therefore I am.
 Iedereen moet dezelfde methodes gebruiken om onderzoek te doen

The nature of management research
Research:
- Purposeful (altijd een doel)
- Systematic (telkens zelfde)
- Empirical (collect data from environment)
- Public (gaat niks verbeteren)
- Cumulative (voortbouwen op ouder onderzoek, uitbreiden)
- Critical of itself (zelf kritisch zijn, peer-reviewen)

Business and management research
- Transdisciplinary (moet toepasbaar/duidelijk zijn in alle vakgebieden)
- Double hurdle (theoretical and practical impact)  het moet ook in de praktijk
uitvoerbaar zijn
- Science-practice gap / translational research  bedrijven willen vaak geen langdurig
onderzoek, maar snel een oplossing
- Evidence Based Management  managers gaan vaak op hun intuitie af, maar als je
bewijs hebt is het beter

1.2 – The structure of research & the Hourglass model
 Eerst de literatuur induiken, het van een breder
perspectief bekijken, verwachtingen stellen
 Operationaliseren = iets meetbaar maken
 Data collection = Observe
 Analyze
 Conclusion and generalize to a broader population

,  meeste artikelen hebben deze opbouw
 Research reports typically take the form of an hourglass
 The hourglass is useful for:
o Efficiently finding that information you are after
o Structuring your own report
o A research proposal is essentially a good first draft of the introduction and
method of the final report

1.3 – Types of research (and demands on design)




 Basic research = satisfies curiosity
 Applied research = find answers to ‘real life’ problems
 Stronger evidence requires tougher designs

Types of studies
 By evidence:
o Descriptive studies  beschrijven van de ‘algemene’ populatie
o Relational studies  tussen verschillende variabelen
o Explanatory / causal studies  oorzaak-gevolg (moet je wel een longitudinaal
onderzoek doen)
 By time:
o Cross-sectional (all data collected at one time). Cross-sectional studies cannot
be used to identify causal relationships
o Longitudinal (data collected over time)
 Repeated measures (<20 measurement waves)
 Time series (>20 measurement waves)

 Qualitative data (‘build theory)
o Data that are in the form of text, pictures, sounds, etc.
o E.g. ‘friendly’, ‘outgoing’, ‘extraverted’, ‘interested’, ‘hardworking’
 Quantitative data (‘test theory’)
o Data that is in numeric form
o A 3.79 on an extraversion scale ranging from 1 to 5 and a 9.35 on a job
performance scale ranging from 1 to 10.

,1.4 – The relationship between theory and data
The importance of Theory  Good theory includes a plausible,
coherent, parsimonious explanation for why certain cause and
effect relationships should be expected. Or more prosaically it is
that which we think we know about a particular phenomenon
 Soms loopt de rits vast
 Je weet nooit iets zeker, maar er is wel een waarheid

Ockham’s razor: “all things being equal, the simplest solution tends to be the best one”

Inductive reasoning:
Observation  Pattern  Tentative hypothesis  Theory
o Observeren/ondervragen: bijv van medewerkers, waarom ze ziek zijn
o Patroon: veel medewerkers lopen tegen hetzelfde probleem aan
o We can use inductive reasoning to generate theory

Deductive reasoning:
Theory  Hypothesis  Observation  Confirmation
o Hypotheses door theorieën, daarna pas testen
o Eerst het probleem, dan kijken hoeveel mensen dit probleem hebben
o We can use deductive reasoning to test theory

Hypotheses
 A specific statement of prediction
 Alternative hypothesis = a specific statement of prediction stating what you expect
will happen in your study
 Null hypothesis = a specific statement that predicts there will be no effect of a
program, treatment, or other independent variable you are studying (deze testen we
altijd, niet de alternatieve hypothese)




0= geen effect
1= sterk effect
+= positief effect
-= negatief effect

, 1.5 – Introduction to causality
Causality as the ‘holy grail’ of research
 Quantitative variable
o The numerical representation of some object (e.g. extraversion, job
performance)
 Attribute
o A specific value of a variable (e.g. male for the variable gender)
o A simplified way of thinking about a quantitative variable is that all attributes
are known and coded with a number prior to data collection (e.g. 0- female, 0
– male)
 Independent variable
o The variable that you manipulate (the cause) (e.g. training 0-No 1-Yes)
 Dependent variable
o The variable that is affected by the independent variable (the effect) (e.g.) job
performance)
 Unit of Analysis
o The entitles about which we want to draw conclusions (e.g. person)

Causal Relationships as a special type of relationship
 Not all relationships that we observe are causal
o Reversed causality (andersom), third variable, chance
 We can design our research in such a way that we can rule out these alternative
explanations
o Isolation
o Temporal precedence (cause precedes the effect)  oorzaak gaat vooraf aan
gevolg

1.6 – Introduction to conclusion, internal, construct, and external I
Validity: no study is perfect!




- Conclusion: is dat er een relatie is,
- Interne validiteit: is er een causale relatie?
- Construct validiteit: meet je wat je wilt meten? Gebruik je het juiste
meetinstrument?