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Summary - Research Clinic (BMRCSE-SM) - readings + lectures

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This summary contains all three lectures and all six mandatory readings. Mandatory Readings Bacharach, S.(1989). Organizational Theories – Some Criteria for Evaluation. Academy of Management Review, 14 (4):496-515. Bono, J.E., & McNamara, G. (2011). Publishing in AMJ—Part 2: Research Design. Academy of Management Journal, 54(4), 657-660. Dorobantu, S., Gruber, M., Ravasi, D., & Wellman, N. (2024). The AMJ Management Research Canvas: A Tool for Conducting and Reporting Empirical Research. Academy of Management Journal, 67(5), . Graebner, M. E., Martin, J. A., & Roundy, P. T. (2012). Qualitative data: Cooking without a recipe. Strategic Organization, 10(3), 276-284. Lange, D., Pfarrer, M. (2017). Sense and Structure – The Core Building Blocks of an AMR Article. Academy of Management Review, 42 (3): 407-416 Sparrowe, R.T., & Mayer, K.L. (2011). Publishing in AMJ—Part 4: Grounding Hypotheses. Academy of Management Journal, 54(6), .

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December 14, 2024
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Session 1

Types of research:
1. Conceptual research
2. Empirical research
a. Inductive
b. Deductive

Theory = a statement of relations among concepts within a set of boundary assumptions and
constraints. A function of a theory is that of preventing the observer from being dazzled by the
full-blown complexity of natural or concrete events.

Components of a theory:
1. Constructs = may be applied or even
defined on the basis of the observations,
not observational.
2. Variables = an observable entity which
is capable of assuming two or more
values.

Statements of relations:
1. Hypotheses = concrete and operational
statements built from specific variables
– formulated and tested in quantitative
research.
2. Propositions = more abstract – often
formulated as outcome of qualitative research.

Session 2

Qualitative vs quantitative research:
- Qualitative research
o Data are typically in textual, visual, or audio form. Analyses are more verbal /
rhetorical in nature.
o Tend to be process focused.
o Heavy on the focus why or how; deep, embedded understanding of the
phenomenon of interest.
- Quantitative research
o Data are typically in numerical form. Analyses are inferential in nature.
Regression-based; explaining variation.
o Obtain statistical evidence to support or reject hypotheses.
o Focus on the strength of relationships between concepts. The mechanisms are
theorized, but often not explicitly tested.



1

, Dependability = explain and justify methodological choices and / or interpretations in detail.
Confirmability = neutrality – results should not be caused by researcher bias, motivation, or
interest.
Credibility = confidence in the ‘truth’ of he results.

Data

Population = the total set of observations of interest to your study.
Sample = the subset of the population that you empirically study.
Sampling = the process of selecting units (e.g., people, organizations) from a population.
Unit of analysis = the major entity that is being analysed.

Two fallacies:
- Ecological fallacy = drawing conclusions about individuals based on group data.
- Exception fallacy = drawing conclusions about a group based on exceptional cases.

Different types of data:
- Primary data = data that is hand-collected specifically for your research.
- Secondary data = pre-existing data that can be used for your research.
- Cross-sectional data = a sample taken at a single point in time.
- Longitudinal = observations over time.
o Repeated / pooled cross-sections = new cross-sections every time.
o Time series = observations of a variable over time (underlying sample may
change; common in finance).
o Panel data = time-series for each cross-sectional member. Often seen as the gold
standard.

Validity

Validity = the approximate truth of propositions, inferences, or conclusions.

Internal validity = the extent to which a piece of evidence supports a claim about cause and
effect, within the context of a particular study.

External validity = the degree to which the conclusions in your study would hold for other
persons in other places and at other times.

Construct validity = the degree to which inferences can legitimately be drawn from the
operationalizations in your study to the theoretical constructs on which those
operationalizations were based. The operationalisation should capture the construct, the whole
construct, and nothing but the construct.




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