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Summary of the course 'Research & Skills for MSc BA'

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Summary of the required literature for the midterm exam of the course 'Research & Skills for MSc BA', given in the MSc program 'Business Administration' at the University of Groningen. The summary contains notes of all lectures and lecture videos, including the three training modules about data management, privacy, and ethics

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Contents
Course literature:............................................................................................................................1
Lecture 1a – Introduction and theory building...............................................................................2
Lecture 1b – Research ethics..........................................................................................................3
Lecture 2a – Quantitative Methods................................................................................................6
Lecture 2b – Qualitative research.........................................................................................................11
Lecture 3 – Exam training.............................................................................................................18
Privacy, Ethics and Data Management Modules...........................................................................19
Lecture 1a – Introduction and theory building.......................................................................................2
Lecture 1b – Research ethics..................................................................................................................3
Lecture 2a – Quantitative Methods........................................................................................................6
Lecture 2b – Qualitative research.........................................................................................................11
Lecture 3 – Exam training.....................................................................................................................18
Privacy, Ethics and Data Management Modules..................................................................................18
1. Data management...................................................................................................................18
2. Privacy & Security in student research....................................................................................21
3. Research ethics........................................................................................................................23


Course literature:
Lecture 1a + b

- Sutton, R. I., & Staw, B. M. 1995. What theory is not. Administrative Science Quarterly, 40(3):
371-384.

Lecture 2a

- Tisdell, E.J., Merriam, S.B. & H.L. Stuckey-Peyrot (2025). What is qualitative research?
Chapter 1 in: Tisdell, E.J., Merriam, S.B. & H.L. Stuckey-Peyrot (2025). Qualitative research: a
guide to design and implementation. Hoboken (New Jersey): John Wiley & Sons.
- Tisdell, E.J., Merriam, S.B. & H.L. Stuckey-Peyrot (2025). Six common qualitative research
designs. Chapter 2 in: Tisdell, E.J., Merriam, S.B. & H.L. Stuckey-Peyrot (2025). Qualitative
research: a guide to design and implementation. Hoboken (New Jersey).
- Johnson, J.L., Adkins, D., & S. Chauvin (2020). Qualitative research in pharmacy education: A
review of the quality indicators of rigor in qualitative research. American Journal of
Pharmaceutical Education, 84(1), 138-146.
- Gioia, D. A., Corley, K. G., & A.L. Hamilton (2013). Seeking qualitative rigor in inductive
research: Notes on the Gioia methodology. Organizational Research Methods, 16(1), 15-31.

Lecture 2b




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, - Bamberger, P., & Ang, S. (2016). The Quantitative Discovery: What is it and How to Get it
Published. Academy of Management Discoveries, 2(1), 1–6.
https://doi.org/10.5465/amd.2015.0060
- Field, A. (2009). Discovering statistics using SPSS.(3rd ed.). SAGE Publications.
- Swanson, R. A., & Holton, E. F. (2005). Research in organizations : foundations and methods
of inquiry. San Francisco, Calif.: Berrett-Koehle. – Part II
- Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental
designs for generalized causal inference. Houghton Mifflin.
- Research and Skills Pre MSc reader: https://opentextbooks.rug.nl/rspremsc/

Lecture 1a – Introduction and theory building
Definition of theory:

- Theory is the answer to queries of why (Kaplan, 1964; Merton, 1967).
- Theory is about the connections among phenomena, a story about why acts, events structure
and thoughts occur, and the nature of causal relationships identifying what coms first as well
as the timing of such events (Sutton & Staw, 1995).
- Theory is the description (what, how) and explanation (why) of the social phenomena of
interest, as well as their generalizability (who, where, when) (Whetten, 1989).

What theory is not:

 References  listing references to existing theories or mentioning their names is not theory.
You need to make arguments by explaining and linking concepts and causal logic references.
 Example: this pattern is consistent with findings that aggression provokes the ‘fight’
response (Frijda, 1986) and that anger is a contagious emotion (Schacter & Singer,
1968).
 Data  prior findings cannot by themselves motivate hypotheses, and the reporting of
results cannot substitute for logical reasoning. You need to explain reasons why particular
findings occurred in the past or why certain empirical relationships are expected in the
future.
 Example: Hammer (1978) has investigated the relationship between union strength
and construction workers’ reactions to their work. She found that union strength
(operationalized in terms of workers’ relative wages) was positively related to both
pay satisfaction and perceived job security.
 Constructs and variables  are important parts of theory but do not, alone, constitute
theory, because simply listing a set of antecedents does not make a theoretical argument.
You need to explain why these constructs or variables come about and why they are
connected.
 Diagrams  diagrams or research modes (boxes and arrows) can be a valuable part of
theory but, by themselves, rarely constitute theory, because they rarely explain why the
proposed connection will be observed. The logic underlying the portrayed relationships
needs to be spelled out; verbal explanation about the reasons why a phenomenon occurs or
why it unfolds in a particular manner cannot be replaced by a diagram.
 Hypotheses/predictions of theory  are important parts of theory as crucial bridges
between theory and data by making explicit how the variables and relationships will be
operationalized. However, hypotheses presented without underlying causal logic do not
constitute theory. Hypotheses are concise statements about what is expected to occur, not



2

, why it is expected to occur, and therefore do not contain logical arguments about why
empirical relationships are expected to occur.

A strong and complete theory contains four essential elements:

 What  what factors (concepts, constructs, variables) should be logically considered as part
of the explanation of the social phenomena of interest? (completeness vs. parsimony)
 How  how are these factors related? (causality)
 Why  what are the underlying social mechanisms and dynamics that justify the selection of
factors and the proposed causal relationships? (logic/rationale)
 Who, Where, When  what are the conditions placing the limits and boundaries of
generalizability? (context)

Signaling theory = explains how two parties deal with information asymmetry. The informed party
sends a "signal" (a credible, often costly, action or attribute ) to convey quality, reducing uncertainty
for the receiver. It ensures trust in markets, like job candidates using degrees to signal ability.

There are two ways of thinking for theory building:

 Observational thinking based on practice (inductive thinking)  observation leads to theory
formation (developing a theory)
o More common: qualitative research.
 Conceptual thinking based on literature or logic (deductive thinking)  analysis of data
leads to testing of theory (literature and logical reasoning)
o More common: quantitative approach

Lecture 1b – Research ethics
Ethic = a moral principle or a code of conduct which governs what people do. It is concerned with the
way people act or behave.

Ethics = the moral principle, guiding conduct, which are held by a group or even a profession
(through there is no logical reason why individuals should not have their own ethical code).

Ethics is also known as a moral philosophy = a branch of philosophy that involves systemizing,
defending, and recommending concepts of right and wrong behavior.

There are two types of ethics:

 Business ethics  a form of applied ethics or professional ethics focusing on ethical
problems that arise in business environments.
 Research ethics  focuses on ethical dilemmas and integrity in scientific research.

Ethics is the moral distinction between right and wrong.

Not everything that is legal is also ethical (and vice versa).

Ethical
Yes No
Tax avoidance
Legal Yes Stick to the speed limit
Certain forms of scientific misconduct
No Hide refugees during the war Tax evasion




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