Research Skill Summary
Ghauri, P., Grønhaug, K., & Strange, R. (2020). Research Methods in Business Studies (5th ed.).
Cambridge: Cambridge University Press.
Research Skill Course 325085-M-6
Research in business serves as the bridge between intuition and evidence-based decision-making. This
summary outlines the skills required to navigate the research process, structured across the stages of
conceptualization, design, data collection, analysis, and reporting. It guides the reader through both
qualitative and quantitative pathways, grounded in an ethical and theoretical framework.
The journey begins with Chapter 2, “Research in Business Studies,” and Lecture 1. This section establishes
the philosophical foundations of inquiry, distinguishing "justified true belief" from common sense and
introducing key orientations like positivism and interpretivism. Chapter 3, "The Research Process,"
structures this into an iterative cycle, emphasizing the movement between theory and data through
deduction, induction, and abduction.
Next, Chapter 4, “Research Problems" focuses on converting broad topics into testable questions. It
highlights using literature reviews to identify gaps and define the "real" problem. With the problem defined,
Chapter 5, "Research Design" acts as the project's master plan. It details how to structure inquiry based on
exploratory, descriptive, or causal goals, and introduces crucial validity concepts distinct to qualitative and
quantitative paths.
The text then focuses on qualitative methodologies. Chapter 7, "Data Collection for Qualitative Research,"
outlines tools for gaining deep "insider" understanding, specifically the Case Study method and semi-
structured interviews. This is followed by Chapter 8, "Qualitative Data Analysis," which explains how to
process text data through systematic coding and display to achieve theoretical generalization.
Chapter 14, "Writing the Final Report" connects these efforts to communication. It details the structural
requirements of a master’s thesis ensuring the research is presented logically to convince the reader.
The focus then shifts to the quantitative stream with Chapter 10, "Description and Preliminary Analysis of
Quantitative Data." This chapter covers statistical basics necessary to describe datasets and conduct initial
hypothesis testing using t-tests and correlations. This lays the groundwork for Chapter 11, "Multiple
Regression," which introduces sophisticated tools for predicting outcomes and establishing causality using
Ordinary Least Squares (OLS).
Finally, the text circles back to data inputs. Chapter 6, “Measurements,” enforces the "Garbage In, Garbage
Out" principle, detailing how to operationalize abstract concepts into measurable variables. The summary
concludes with Chapter 9, “Data Collection for Quantitative Research,” providing practical guidelines for
sampling strategies and survey design to ensure the data is robust enough to support analysis.
,Table of Contents
1. CHAPTER 2 “RESEARCH IN BUSINESS STUDIES” AND LECTURE 1.............................................................3
2. CHAPTER 3 "THE RESEARCH PROCESS" AND LECTURE 1.........................................................................6
3. CHAPTER 4 “RESEARCH PROBLEMS" AND LECTURE 1.............................................................................9
4. CHAPTER 5 "RESEARCH DESIGN" AND LECTURE 2................................................................................12
1. CHAPTER 7 "DATA COLLECTION FOR QUALITATIVE RESEARCH" AND LECTURE 2....................................15
2. CHAPTER 8 "QUALITATIVE DATA ANALYSIS" AND LECTURE 3................................................................18
3. CHAPTER 14 "WRITING THE FINAL REPORT" AND LECTURE 4...............................................................21
4. CHAPTER 10: DESCRIPTION AND PRELIMINARY ANALYSIS OF QUANTITATIVE DATA AND LECTURE 5.....24
5. CHAPTER 11: MULTIPLE REGRESSION AND LECTURE 5..........................................................................27
8. CHAPTER 6, “MEASUREMENTS,” AND LECTURE 6.................................................................................30
9. CHAPTER 9, “DATA COLLECTION FOR QUANTITATIVE RESEARCH,” AND LECTURE 6...............................33
10. WEEK 7, COVERING MODERATION, MEDIATION, AND PANEL DATA ANALYSIS....................................36
,1. CHAPTER 2 “RESEARCH IN BUSINESS STUDIES” AND LECTURE 1.
2.1: The Nature of Knowledge Development
This section introduces the philosophical foundation of research: epistemology, or the theory of knowledge.
It explores how we differentiate "knowledge" from "mere opinion". The Western philosophical tradition
defines knowledge as a "justified true belief".
The chapter distinguishes between two types of knowledge:
'A priori' knowledge: Knowledge based on sense, which is hypothetical.
'A posteriori' knowledge: Knowledge based on experience, which is empirical.
Common sense is defined as the beliefs of a group, but this can be corrected or rejected as knowledge
develops.
2.2: Why We Do Research
The fundamental purpose of research is to teach students to work systematically and analyze issues critically
before acting upon them. In a business context, research is essential for making important decisions, such as
launching a new product, entering a new market, or evaluating a merger. It allows managers to move beyond
intuition and systematically investigate relevant information to find solutions to problems. Ultimately, the
goal of research is to understand how and why things happen in an effort to improve social and business life.
2.3: Research versus Common Sense
A central theme of the chapter, and highlighted in Lecture 1, is the relationship between systematic research
and "common sense." While managers often see academic research as abstract and impractical, the book
argues that research is simply a systematic and controlled extension of common sense.
The key difference is that a layperson or manager relying on common sense often uses theories loosely,
accepts explanations that fit their existing beliefs, and does not control for external influences.
In contrast, an academic researcher must be systematic, arguable, and challengeable. As noted in the
lecture, the researcher must systematically explain how data is collected and analyzed, and what the
limitations of the research are.
The book outlines four primary differences :
1. Use of Concepts: Laypersons are loose; scientists build and test theories systematically.
2. Testing Hypotheses: Laypersons seek evidence that confirms their beliefs; scientists test hypotheses
systematically and are careful about their conclusions.
3. Control: Laypersons do not control for external influences or biases; scientists systematically try to
study and control the relations between phenomena.
4. Explanations: Laypersons may accept metaphysical explanations (e.g., "it's God's will"); scientists
are concerned only with things that can be observed, tested, and falsified.
2.4: Different Research Orientations
A researcher's background and beliefs influence their research orientation, which dictates the relationship
between methods, data, and theories.
A core requirement for scientific study is originality, which is also covered in the lecture. This does not
mean finding a topic never studied before. Rather, it means creating a new dimension to existing
knowledge. This can be a "novel twist, fresh perspective," "new hypothesis," or an "innovative method" of
approaching an existing topic.
The chapter presents five key research orientations (Table 2.1):
1. Positivism: Assumes a single, objective truth exists. It relies on observable, measurable facts to
make law-like causal generalizations and predict behavior.
, 2. Critical Realism: Accepts that social interactions are complex and require different methods than
physical facts. It encourages methodological diversity but maintains that the researcher should be as
objective as possible.
3. Pragmatism: Seeks knowledge that is relevant and useful to practice. The research should provide
solutions to practical problems.
4. Interpretivism: Believes that knowledge is subjective and context is important. It aims to present
rich, in-depth understanding and diverse interpretations rather than simple, generalizable laws.
5. Post-modernism: Argues that truth and knowledge are based on dominant ideologies. It encourages
researchers to be reflexive and reveal hidden meanings.
2.5: Induction, Deduction, and Abduction
This section, emphasized heavily in Lecture 1, details the three primary ways of reasoning in research.
1. Induction: This approach is based on empirical evidence. The process moves from observations →
analysis → findings → theory building. Theory is the outcome of the research. This is often
associated with qualitative research, where conclusions are probable but not 100% certain.
2. Deduction: This approach is based on logic. The process moves from theory → hypotheses →
operationalization → empirical testing (acceptance/rejection). Theory comes first and guides the
entire research process. This is often associated with quantitative research.
3. Abduction: This is not merely a combination of the other two. It is a continuous, iterative process
that goes "back and forth between framework, data, and research". It involves a theoretical
interpretation of an empirical puzzle, where unexpected findings force the researcher to modify their
original framework, potentially leading to new theory.
2.6 & 2.7: Theory vs. Data and Knowledge Skills
Section 2.6 notes that while deduction (theory-first) is common, research can also begin with data
(induction), such as when a researcher observes something they cannot explain and aims to "construct
theory". In practice, most research involves an interaction between the two.
Section 2.7 outlines four "ways of knowing": the method of tenacity (it's always been true), the method of
authority (an authority said it's true), the a priori method (it's self-evident), and the method of science.
The scientific method is unique because its conclusions are independent of our opinions and it has self-
correction built into it.
2.8: Why Research Never Stops
Research is a cyclical, never-ending process,
often depicted as "the wheel of research" (Figure
2.2). The conclusions drawn from one study lead
to an "improvement in theory or problem
solving". This new, improved knowledge then
becomes the starting point (the observation or
literature review) for the next researcher, thus
starting the cycle anew.
Ghauri, P., Grønhaug, K., & Strange, R. (2020). Research Methods in Business Studies (5th ed.).
Cambridge: Cambridge University Press.
Research Skill Course 325085-M-6
Research in business serves as the bridge between intuition and evidence-based decision-making. This
summary outlines the skills required to navigate the research process, structured across the stages of
conceptualization, design, data collection, analysis, and reporting. It guides the reader through both
qualitative and quantitative pathways, grounded in an ethical and theoretical framework.
The journey begins with Chapter 2, “Research in Business Studies,” and Lecture 1. This section establishes
the philosophical foundations of inquiry, distinguishing "justified true belief" from common sense and
introducing key orientations like positivism and interpretivism. Chapter 3, "The Research Process,"
structures this into an iterative cycle, emphasizing the movement between theory and data through
deduction, induction, and abduction.
Next, Chapter 4, “Research Problems" focuses on converting broad topics into testable questions. It
highlights using literature reviews to identify gaps and define the "real" problem. With the problem defined,
Chapter 5, "Research Design" acts as the project's master plan. It details how to structure inquiry based on
exploratory, descriptive, or causal goals, and introduces crucial validity concepts distinct to qualitative and
quantitative paths.
The text then focuses on qualitative methodologies. Chapter 7, "Data Collection for Qualitative Research,"
outlines tools for gaining deep "insider" understanding, specifically the Case Study method and semi-
structured interviews. This is followed by Chapter 8, "Qualitative Data Analysis," which explains how to
process text data through systematic coding and display to achieve theoretical generalization.
Chapter 14, "Writing the Final Report" connects these efforts to communication. It details the structural
requirements of a master’s thesis ensuring the research is presented logically to convince the reader.
The focus then shifts to the quantitative stream with Chapter 10, "Description and Preliminary Analysis of
Quantitative Data." This chapter covers statistical basics necessary to describe datasets and conduct initial
hypothesis testing using t-tests and correlations. This lays the groundwork for Chapter 11, "Multiple
Regression," which introduces sophisticated tools for predicting outcomes and establishing causality using
Ordinary Least Squares (OLS).
Finally, the text circles back to data inputs. Chapter 6, “Measurements,” enforces the "Garbage In, Garbage
Out" principle, detailing how to operationalize abstract concepts into measurable variables. The summary
concludes with Chapter 9, “Data Collection for Quantitative Research,” providing practical guidelines for
sampling strategies and survey design to ensure the data is robust enough to support analysis.
,Table of Contents
1. CHAPTER 2 “RESEARCH IN BUSINESS STUDIES” AND LECTURE 1.............................................................3
2. CHAPTER 3 "THE RESEARCH PROCESS" AND LECTURE 1.........................................................................6
3. CHAPTER 4 “RESEARCH PROBLEMS" AND LECTURE 1.............................................................................9
4. CHAPTER 5 "RESEARCH DESIGN" AND LECTURE 2................................................................................12
1. CHAPTER 7 "DATA COLLECTION FOR QUALITATIVE RESEARCH" AND LECTURE 2....................................15
2. CHAPTER 8 "QUALITATIVE DATA ANALYSIS" AND LECTURE 3................................................................18
3. CHAPTER 14 "WRITING THE FINAL REPORT" AND LECTURE 4...............................................................21
4. CHAPTER 10: DESCRIPTION AND PRELIMINARY ANALYSIS OF QUANTITATIVE DATA AND LECTURE 5.....24
5. CHAPTER 11: MULTIPLE REGRESSION AND LECTURE 5..........................................................................27
8. CHAPTER 6, “MEASUREMENTS,” AND LECTURE 6.................................................................................30
9. CHAPTER 9, “DATA COLLECTION FOR QUANTITATIVE RESEARCH,” AND LECTURE 6...............................33
10. WEEK 7, COVERING MODERATION, MEDIATION, AND PANEL DATA ANALYSIS....................................36
,1. CHAPTER 2 “RESEARCH IN BUSINESS STUDIES” AND LECTURE 1.
2.1: The Nature of Knowledge Development
This section introduces the philosophical foundation of research: epistemology, or the theory of knowledge.
It explores how we differentiate "knowledge" from "mere opinion". The Western philosophical tradition
defines knowledge as a "justified true belief".
The chapter distinguishes between two types of knowledge:
'A priori' knowledge: Knowledge based on sense, which is hypothetical.
'A posteriori' knowledge: Knowledge based on experience, which is empirical.
Common sense is defined as the beliefs of a group, but this can be corrected or rejected as knowledge
develops.
2.2: Why We Do Research
The fundamental purpose of research is to teach students to work systematically and analyze issues critically
before acting upon them. In a business context, research is essential for making important decisions, such as
launching a new product, entering a new market, or evaluating a merger. It allows managers to move beyond
intuition and systematically investigate relevant information to find solutions to problems. Ultimately, the
goal of research is to understand how and why things happen in an effort to improve social and business life.
2.3: Research versus Common Sense
A central theme of the chapter, and highlighted in Lecture 1, is the relationship between systematic research
and "common sense." While managers often see academic research as abstract and impractical, the book
argues that research is simply a systematic and controlled extension of common sense.
The key difference is that a layperson or manager relying on common sense often uses theories loosely,
accepts explanations that fit their existing beliefs, and does not control for external influences.
In contrast, an academic researcher must be systematic, arguable, and challengeable. As noted in the
lecture, the researcher must systematically explain how data is collected and analyzed, and what the
limitations of the research are.
The book outlines four primary differences :
1. Use of Concepts: Laypersons are loose; scientists build and test theories systematically.
2. Testing Hypotheses: Laypersons seek evidence that confirms their beliefs; scientists test hypotheses
systematically and are careful about their conclusions.
3. Control: Laypersons do not control for external influences or biases; scientists systematically try to
study and control the relations between phenomena.
4. Explanations: Laypersons may accept metaphysical explanations (e.g., "it's God's will"); scientists
are concerned only with things that can be observed, tested, and falsified.
2.4: Different Research Orientations
A researcher's background and beliefs influence their research orientation, which dictates the relationship
between methods, data, and theories.
A core requirement for scientific study is originality, which is also covered in the lecture. This does not
mean finding a topic never studied before. Rather, it means creating a new dimension to existing
knowledge. This can be a "novel twist, fresh perspective," "new hypothesis," or an "innovative method" of
approaching an existing topic.
The chapter presents five key research orientations (Table 2.1):
1. Positivism: Assumes a single, objective truth exists. It relies on observable, measurable facts to
make law-like causal generalizations and predict behavior.
, 2. Critical Realism: Accepts that social interactions are complex and require different methods than
physical facts. It encourages methodological diversity but maintains that the researcher should be as
objective as possible.
3. Pragmatism: Seeks knowledge that is relevant and useful to practice. The research should provide
solutions to practical problems.
4. Interpretivism: Believes that knowledge is subjective and context is important. It aims to present
rich, in-depth understanding and diverse interpretations rather than simple, generalizable laws.
5. Post-modernism: Argues that truth and knowledge are based on dominant ideologies. It encourages
researchers to be reflexive and reveal hidden meanings.
2.5: Induction, Deduction, and Abduction
This section, emphasized heavily in Lecture 1, details the three primary ways of reasoning in research.
1. Induction: This approach is based on empirical evidence. The process moves from observations →
analysis → findings → theory building. Theory is the outcome of the research. This is often
associated with qualitative research, where conclusions are probable but not 100% certain.
2. Deduction: This approach is based on logic. The process moves from theory → hypotheses →
operationalization → empirical testing (acceptance/rejection). Theory comes first and guides the
entire research process. This is often associated with quantitative research.
3. Abduction: This is not merely a combination of the other two. It is a continuous, iterative process
that goes "back and forth between framework, data, and research". It involves a theoretical
interpretation of an empirical puzzle, where unexpected findings force the researcher to modify their
original framework, potentially leading to new theory.
2.6 & 2.7: Theory vs. Data and Knowledge Skills
Section 2.6 notes that while deduction (theory-first) is common, research can also begin with data
(induction), such as when a researcher observes something they cannot explain and aims to "construct
theory". In practice, most research involves an interaction between the two.
Section 2.7 outlines four "ways of knowing": the method of tenacity (it's always been true), the method of
authority (an authority said it's true), the a priori method (it's self-evident), and the method of science.
The scientific method is unique because its conclusions are independent of our opinions and it has self-
correction built into it.
2.8: Why Research Never Stops
Research is a cyclical, never-ending process,
often depicted as "the wheel of research" (Figure
2.2). The conclusions drawn from one study lead
to an "improvement in theory or problem
solving". This new, improved knowledge then
becomes the starting point (the observation or
literature review) for the next researcher, thus
starting the cycle anew.
