Extended Summary: Methdology for IE Research (1ZV60/1ZV00)
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Course
1ZV00 Methodology for IE Research (1ZV60)
Institution
Technische Universiteit Eindhoven (TUE)
This is an extended summary of all lectures for the course Methdology for IE Research (1ZV60/1ZV00). This 56-page document (with a clickable table of contents for easier navigation) summarizes the essence of all topics covered in the course (as far as I could imagine when writing it). It includes a...
Table of contents
What is Industrial Engineering?
Introduction to research methods
Methods & methodology
The role of theory in research
Theoretical reasoning
Philosophical foundations of research methods
The empirical & regulative cycles
Solving problems with the regulative cycle
Defining a business problem (step 1)
Analysis & diagnosis (step 2)
Solution design (step 3)
Intervention (step 4)
Evaluating & learning (step 5)
Research ethics
Developing research questions & writing up research
Literature review (primary)
Academic journals
Secondary analysis
Other literature
Meta-analysis
Critical reviews
Official statistics
Data mining & big data
Types of literature review
Structures
Qualitative research design, sampling & data collection
Qualitative vs. quantitative research
Qualitative research methods
Case study vs. grounded theory
Qualitative study designs & sampling cases
Unit of analysis
Multiple & single-case designs
Two levels of sampling
Data collection
Sources of data
1ZV60 - course summary 1
, Quality criteria in business research
Interviewing
Types of interviews
Interview guideline
Practical aspects
Good & bad practices
Ethical and legal aspects
Qualitative data analysis
Coding interviews
Approaches to coding
Three stages of coding
The Gioia method
Rigor, validity and reliability
Reporting
Methods section
Findings section
Discussion section
Writing up a research project
Variables
Research questions
Hypotheses
Quantitative research designs
Cross-sectional (survey) design
Longitudinal (survey) design
Case-study design
Comparative design
Experimental design (the golden standard)
Causal relations in quantitative research
Experiments, questionnaires & measurement
Experiments
Research/experimental design notation
Types of experimental design
Self-completion questionnaires
Questionnaire bias
Web-based surveys
Diaries
Asking questions
Open-ended & closed questions
Types of questions
Scaling
The nature of quantitative research
Statistical methods
Measurement & sampling
The nature of quantitative research
Measurement errors
Sound measurement
Types of reliability
Types of validity
Types of practicality
Sampling in quantitative research
Types of samples
Sampling theory
1ZV60 - course summary 2
, Designing a research project & choosing the methods
Research proposal
Organization & cost
What is Industrial Engineering?
(based on lecture 7.1)
Business process: activity, or bounded group of interrelated work activities, that adds value to one or
more inputs, and produces an output to an internal or external customer.
Industrial Engineering: aims to engineer/design/control innovative/operational business
processes/systems that improve quality & productivity.
Blend between engineering and (scientific) management
Introduction to research methods
(based on lecture 1.1)
Methods & methodology
Method: systematic established procedure for Methodology: system of methods used in a
approaching something → approaching research. particular area of study, e.g. industrial engineering.
Why methods are important:
Plan and set-up projects
Make informed choices in projects
Get good results and avoid pitfalls
Assess research critically and understand
the limitations
Learn transferable skills that will be useful
in other areas Both fields require a systematic approach to building and
applying knowledge.
The role of theory in research
1ZV60 - course summary 3
, Theory is at the core of research.
Unit of analysis: the instance to which the theory applies → one instance of the sample
Different levels of the unit of analysis.
Domain: all instances to which the theory is expected to apply → too big to do meaningful work on → limit
it to a population.
Population: a sub-set of the domain where the theory can be developed/tested → too big to be studied
→ limit it to a sample.
Sample: the instances from the population that are studied → can be generalized to at least the entire
population. If multiple populations are sampled, it can be generalized to the domain.
Example of a theory with related terminology.
Example of a theory: the Technology Acceptance Model (TAM).
Unit of analysis: a potential user of a new computer technology.
1ZV60 - course summary 4
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