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Business Research Methods Quantitative Summary
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Business Research Methods QuantitativeLecture 1:
Business Research:
“A series of well-thought-out and carefully executed activities that enable the manager to
know how organizational problems can be solved, or at least considerably minimized” -
Sekaran & Bougie (2016, p. 2)
Hallmarks of scientific research
1. Purposiveness: Knowing “the why” of your research
2. Rigor: Ensuring a sound theoretical base and methodological design
3. Testability: Being able to test logically developed ideas based on data
4. Replicability: Finding the same results if the research is repeated in similar circumstances
5. Precision & Confidence: Drawing accurate conclusions with a high degree of confidence
6. Objectivity: Drawing conclusions based on facts (rather than on subjective ideas)
7. Generalizability: Being able to apply research findings in a wide variety of different
settings
8. Parsimony: Shaving away unnecessary details, explaining a lot with a little
Research process:
,Stage 1: Problem identification
Stage 2: Research approach development
A theoretical framework consists of:
Description of all relevant variables and their definitions
o Motivate why these are important
Hypotheses (i.e. expected relationships between variables)
o Based on existing theory, testable, and unambiguous
Conceptual model (i.e. a graphical representation)
Theoretical framework summarized:
Conceptual model –graphical representation
Covers all variables and relationships
Variable definitions
Define all variables
Motivate why these variables are important to include
Hypotheses –relationships between variables
Provide a logical justification / backing
Based on theory
Research design: “A framework or plan for conducting a [...] research project. It details the
procedures necessary for obtaining the information needed to structure or solve [...]
research problems. ” –Malhotra, Nunan& Birks (2017, p. 61)
,Research design classification:
Explanatory research:
A flexible and evolving approach to understand phenomena that are inherently
difficult to measure
Often required when prior theory is absent and an in-depth understanding is
required
Aim is to develop new theory since phenomenon is new or previously uninvestigated
Result -> theory
Examples:
Conclusive research:
Characterized by clearly defined phenomena that can be measured by means of
quantitative data
Descriptive: testing the correlational relationship between two or more variables
(e.g. by means of a survey or archival data)
Causal: testing the causal relationship between two or more variables by means of a
(laboratory of field) experiment
, Useful R-commands:
Lecture 2:
Total error: Variation between true mean value in the population of the variable of interest
and the observed value
Random sampling errors: Error because the selected sample is an imperfect representation
of the population of interest
Non-sampling errors: Error that can be attributed to sources other than sampling and that
can be random or non-random
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