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Summary Research Skills Slides

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Summary Research Skills slides with more elaboration from Sekaran and Bougie (2016), Research Methods for Business. The following is discussed in the summary: 1) Content of the course 2) Problem definition: problem identification - problem statement - research questions 3) Research design - theoretical framework - data collection 4) Data analysis 5) Solutions and recommendations 6) Questions Pitch2Peer

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Research Skills Master Supply Chain Management
Slides Author: Andreas S. Melisse

Week 1 – Lecture 1

Content of the course
Learning goals
• Define an adequate and relevant research problem and devise the accompanying problem
identification, problem statement and research questions.
• Devise a conceptual model that indicates the relevant concepts to study and serves as a guideline for
literature study and data analysis.
• Develop a research design taking into account scientific criteria such as validity and reliability.
• Choose a suitable sampling method to perform data collection.
• Analyze the data so that an in-depth understanding of the company problem is achieved.
• Discuss findings and use these findings to develop an adequate solution for the business problem.

This course aims to improve the research skills that you will need to successfully conduct a research for your MSc
Thesis project.

Deductive: testing of a theory; theory → hypothesis → observation → confirmation.
Inductive: developing a theory; observation → pattern → proposition → theory.

In your Master Thesis, you are expected to contribute to existing theory (when choosing inductive research) you
will not only use empirical data to look for patterns, but you will also study literature about equivalent/similar
problems already studied by other SCM researchers. In general, it will not be possible to develop a new theory.
Path: observation and theory → pattern → conclusion → recommendations.

When choosing deductive research, start using academic literature to define a problem and to define hypotheses,
then collecting the data to test the hypotheses and test these hypotheses. You study the average behaviour of a
large population, e.g. companies in a certain industry or employees in a large company.

Content of the course
Theory supported inductive research, most commonly associated with case study research: start in defining a
practical problem (e.g. company problem), then study the literature about similar problems already investigated.
Use this literature to collect relevant data: qualitative + quantitative data, methods: observations + interviews
are important, but also secondary data, measurements, and questionnaires, then data collection with analysis:
no fixed recipe, lastly, data with literature is used to understand the problem and draw conclusions and give
recommendations. You study a specific situation (no average behaviour).

A good research topic for your MSc thesis
It is very important that there is a good match between you and your
research topic. You are a person with specific characteristics: knowledge,
skills, personal preferences, MSc student of a specific MSc program.
Feasibility is an important issue, you should have access to the data
needed, have enough time and the costs are reasonable. From research
idea to a good research topic is an challenging and time-consuming
process. It is linked with writing the research proposal.

Research proposal
A research proposal is important to structure and guide your research,
and to evaluate the feasibility of your research. A research proposal describes:
- What you will research
- Why this is interesting and relevant
- How you will conduct your research
- Why this is the adequate way to conduct your research.

What + Why → problem identification, problem statement, and research questions.
How + Why → research design, data collection, data analysis, and reliability and validity.

1

, Research Skills Master Supply Chain Management
Slides Author: Andreas S. Melisse

Week 2 – Lecture 2: Problem definition

Requirements for good theory supported inductive research




Problem identification – Step 1
Problem definition: problem identification + problem statement + research questions. Important tool:
conceptual model. What is the topic of your research is the problem of the organization. Why is this topic
interesting? Motivation of empirical relevance/urgency is the why is it important for the organization. Motivation
of theoretical relevance (more important for deductive research) is less important. What is the main objective to
achieve? What does the organization want. Connection to theory: use conceptual model.

Problem identification
Step 1: Description of the empirical problem.
- Story in the language of the company. Systematic from broad to narrow. Intro 40% and problem 60%.
Do not forget to describe the company and the process you want to research. Describe symptoms of
the problems, how can the company see that there is a problem. One clear objective, what does the
company wants to achieve. (almost) no literature study, connection to theory is step 2.
- It is about the problem. Write to-the-point: problem-based not knowledge based. Stick to the facts, do
not invent anything. Clear line of reasoning. Does not contain solutions. In general, the problem can be
represented by a relation: phenomenon → (un)desired effect.
Step 2: Conceptualization (=connection to the theory), which results in a conceptual model.

Problem identification – Step 2 Making a conceptual model
Step 1: Description of the empirical problem.
- Empirical problem: phenomenon → (un)desired effect.
Step 2: Conceptualization (=connection to the theory), which results in a conceptual model.
- Transform a practical problem to a conceptual model: (delayed) transfer of CVA-patients (in the TsZ to
the nursing homes De Wever, Volckaert and Eikendonk) → (wrong) bed days (at the neurology dept of
the TsZ). Becomes: (disrupted) patient flow → bed/capacity utilization in hospitals.
- Conceptual model: concept 1 → concept 2.
- Conceptual model describes the relevant concepts to study (quantitative study: the constructs). The
empirical problem and the conceptual model have to fit together: concept validity. The conceptual
model is the basis for your theoretical framework. The conceptual model strongly influences your data
collection and data analysis.
- A good conceptual model: leads you to articles about a similar problem (concept validity), leads you to
the right literature (SCM), and leads you to the right amount of literature.
- Use both concepts of the conceptual model for your search, use relevant journals. Very few or no
articles: try broader concepts, try alternatives, try one of the concepts separately. Enormous amount of
articles: narrow the concepts.

Problem identification – What if no company..
What if you do not have a company assignment → you can always do a deductive study.
Step 1: Literature study → conceptual model.
Step 2: Test with empirical data.
Also here theory and practice have to be connected in the right way.



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