PhD Seminar Series
Qualitative Research Methodology
Defining and conducting case-based
research
Analysing case study data
Klas Eric Soderquist, DBA, Brunel University
ΟΙΚΟΝΟΜΙΚΟ ΠΑΝΕΠΙΣΤΗΜΙΟ ΑΘΗΝΩΝ
ΤΜΗΜΑ ΔΙΟΙΚΗΤΙΚΗΣ ΕΠΙΣΤΗΜΗΣ & ΤΕΧΝΟΛΟΓΙΑΣ
Seminar Outline
• A Case of Case Study Research
• Recalling the Process of Defining the Research Problem
• Defining the Unit of Analysis
• Research Strategy, Relation to Theory, Methodological
Choice
• Data Collection
–
Interviews, Direct observation, Participant observation
–
From research question to interview guide
• Data analysis (case or other qualitative approaches)
–
Open coding
–
Axial coding
–
The paradigm model
–
Validity and Reliability
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
My Case of Case Study Research
Inside the Tier Model: Product Development Organisation
and Strategies in Automotive Expert Supplier Firms
Carmaker
First tier
Second tier
Third and fourth
tier
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Definition of the Research Problem
REAL WORLD
CONTEXT
Match /
Mismatch
Match /
Mismatch
PHILOSOPHICAL
POSITION
Match /
Mismatch
OVERALL
RESEARCH
QUESTIONS
Match
RESEARCH
OBJECTIVE
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
My Real World Context
• Background
– The Lean Production Framework
– The Tier Model
– The Partnership Concept
– Transaction Cost Theory, Strategic
Collaboration Theory, Operational
Coordination Theory
• Research Problem
– Supplier Perspective
– Operational Perspective
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Overall
Research
Questions
Overall Research Questions
• They tell you what you want to focus on and what you want to
know
• They set the rough boundaries of the research: you will study
some issues in some context with some actors
• They are oriented towards action and process
• The way they are (implicitly) formulated will determine
research strategy later on
• They set the vision for the research project and helps focusing
activities
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
My Overall Research Questions
• How does the emergence of new industrial principles take
place in expert supplier firms?
• What is the place and role of expert suppliers in the automotive
supply chain?
• What lean production techniques are used and how are they
adopted for satisfying the needs of the organisation?
• How in practice takes integrated component development
place?
• How are organisations and processes designed to support
integration?
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Research Objective
One can distinguish between mainly three objectives or purposes with a
research project:
• To explain the causality between different observations or
the reasons behind a certain situation concerning the
phenomenon
• To explore a vague problem or a new area of
research
• To describe, i.e., observe and visualise the situation of
certain phenomena
The research objective does not automatically define a quantitative or
qualitative logic
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Research Objective
The research questions implicitly determine the research objective, and together
they indicate quantitative vs. qualitative research:
• WHAT questions of descriptive nature in the sense “how
much” or “how many” call for a quantitative approach
• WHAT questions of explanatory or exploratory nature call for
a qualitative approach
• HOW questions and WHY questions call for a qualitative
approach
Qualitative research is needed when we want to come to terms with the meaning,
not the “right” or “wrong” with the phenomena under investigation
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
DEFINITION OF THE RESEARCH PROBLEM
REAL WORLD
“Full“
Process
Model of
Methodological
Choice
CONTEXT
Match /
Mismatch
Match /
Mismatch
Match /
Mismatch OVERALL
RESEARCH
QUESTIONS
PHILOSOPHICAL
POSITION
Match
RESEARCH
OBJECTIVE
UNIT OF
ANALYSIS
Match / Mismatch
Mismatch
Mismatch
Match
RESEARCH
STRATEGY
Match / Mismatch
Mismatch
Mismatch
Match
RELATION TO THEORY
Deduction
Induction
Mismatch
Predefinition and test of
Determination of theory
a theoretical model.
from observations.
THEORY EXTENSION
THEORY DEVELOPMENT
Match / Mismatch
Match
Methodological choice
Qualitative
Deductive Logic
Qualitative
Inductive Logic
Quantitative
Deductive Logic
Quantitative
Inductive Logic
Data collection and data
analysis methods, appropriate
for the chosen methodology
Unit of Analysis – What is the Case?
It is the Research Object – or unit in the real world context
that you will observe
It can be:
•
•
•
•
•
•
An individual,
A role
A group
A process
An organisational entity
An organisation
Or any other definable and observable unit
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Unit of Analysis – Example
Units of analysis in change management research:
• Change efforts (e.g., installing new technology, downsizing, a particular
restructuring, effort to change corporate culture…)
• Change events (e.g. a crises);
• The leaders of change (i.e., the individuals that drive through "corporate
revolutions" with research focus on their personal traits, leadership
styles and leadership levers);
• Sectors undergoing change (i.e., comparative studies of different
business sectors in search of similarities and specificities basically in the
content of change)
•
Employees facing change and acting in change processes.
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
My Unit of Analysis
• Could be a component development project
• Could be the supplier interface
• Could be the product development project
I did chose the Product Development Process in each
studied firm because studying the PDP would enable
answering all the questions (at least in theory)
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
DEFINITION OF THE RESEARCH PROBLEM
REAL WORLD
“Full“
Process
Model of
Methodological
Choice
CONTEXT
Match /
Mismatch
Match /
Mismatch
Match /
Mismatch OVERALL
RESEARCH
QUESTIONS
PHILOSOPHICAL
POSITION
Match
RESEARCH
OBJECTIVE
UNIT OF
ANALYSIS
Match / Mismatch
Mismatch
Mismatch
Match
RESEARCH
STRATEGY
Match / Mismatch
Mismatch
Mismatch
Match
RELATION TO THEORY
Deduction
Induction
Mismatch
Predefinition and test of
Determination of theory
a theoretical model.
from observations.
THEORY EXTENSION
THEORY DEVELOPMENT
Match / Mismatch
Match
Methodological choice
Qualitative
Deductive Logic
Qualitative
Inductive Logic
Quantitative
Deductive Logic
Quantitative
Inductive Logic
Data collection and data
analysis methods, appropriate
for the chosen methodology
Research Strategy
Five Basic Strategies:
• Experiment
• Survey
• Archival Analysis
• History
• Case Study
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Case Study Research Strategy
Selecting the Case Study Organization: Criterion Sampling
• Purposive rather than random samples
• Samples can evolve as research moves on
• Identify theory driven criteria in order to frame the research
• Inclusive or contradictory samples
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Case Study Research Strategy
My Criterion Sampling
Case Study Organisations should:
• Have a good record for internally generated innovation.
• Innovation has a high profile in the organization.
• Have established links with research laboratories.
• Have an explicit strategy for R&D and R&D driven organizational
development
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
DEFINITION OF THE RESEARCH PROBLEM
REAL WORLD
“Full“
Process
Model of
Methodological
Choice
CONTEXT
Match /
Mismatch
Match /
Mismatch
Match /
Mismatch OVERALL
RESEARCH
QUESTIONS
PHILOSOPHICAL
POSITION
Match
RESEARCH
OBJECTIVE
UNIT OF
ANALYSIS
Match / Mismatch
Mismatch
Mismatch
Match
RESEARCH
STRATEGY
Match / Mismatch
Mismatch
Mismatch
Match
RELATION TO THEORY
Deduction
Induction
Mismatch
Predefinition and test of
Determination of theory
a theoretical model.
from observations.
THEORY EXTENSION
THEORY DEVELOPMENT
Match / Mismatch
Match
Methodological choice
Qualitative
Deductive Logic
Qualitative
Inductive Logic
Quantitative
Deductive Logic
Quantitative
Inductive Logic
Data collection and data
analysis methods, appropriate
for the chosen methodology
Relation to Theory
INDUCTION
DEDUCTION
Application
of theory
Construction
of theory
Theory
Theoretical work
Empirical work
Theoretical work
Empirical
Generalizations
Test
Hypotheses
Empirical work
Observations
INDUCTION
Theory Development
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
DEDUCTION
Theory Extension
Methodological Choice
Methodological choice
Qualitative
Qualitative
Deductive Logic
Inductive Logic
Quantitative
Quantitative
Deductive Logic
Inductive Logic
Data collection and data
analysis methods, appropriate
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
for the chosen methodology
Data Collection Methods
Case-Based Research
• Participant Observation – longitudinal presence
The researcher is part of the organisation on a contractual basis and has a
contextual professional role and reporting responsibility
• Direct Observation – (longitudinal) presence
The researcher is present in the organisation as an external observer
• Interviews – occasional visits (can be longitudinal)
• Documentary Analysis - background info and event analysis
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Data Collection
From Research Question to Interview Guide
• The overall research questions starts broadly and are gradually
narrowed by asking sub questions and sub-sub questions
• Research questions should be asked «crude» to managers and
experts in an exploratory phase: Pilot interviews or pilot case
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Data Collection through Interviews
From Research Question to Interview Guide (I)
The process of generating more detailed questions
Exploratory Data
(Real World)
Researcher‘s
Sub, sub-sub…
Research
Questions
Overall Research
Questions
Personal Experience
(Real World)
Mental Processing
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Data Collection through Interviews
From Research Question to Interview Guide (II)
My Interview Guide (minor extract). Semi-structured, open ended
• How are organisations and processes designed to support integration?
•What coordination activities exist in the product development process?
• When and how is manufacturing staff involved in new development projects?
• What are the benefits of their involvement?
• What are the drawbacks?
• How is coordination with customers organised?
• How is coordination with suppliers organised?
•What communication structures exist in the product development process?
• Who talks to who in the process?
• What channels are used?
• Frequency of communication between different players?
• How does communication support coordination?
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Data Collection through Interviews
Basic Interview Techniques
• Not too active, not too passive - The guide serves as a tool for
navigating the interviews
• Use of the critical incident technique to start out the interviews
or enter into new subjects.
It is efficient when managers have difficulties in articulating answers to
specific questions and consists of asking the interviewee to describe specific
events that have had a critical impact on the way a specific issue has been
managed
• Use re-launch questions:
- Could you tell me more about this?
- Could you specify further?
- What are you thinking about in particular?
It is important in such cases not to give any suggestions to
interviewees
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Between Collection and Analysis
Interview (or observation) Transcripts
• For serious research, tape record interviews!
• Always keep supportive notes
• Proceed to immediate transcript
• Transcript should reflect the interview at 100 percent
• Ask for feed-back on transcripts
• Fill in uncertainties with a second (phone) interview
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Data Analysis / Coding
Basics
• If we talk about case research, we will have at least
multiple interviews, possibly a mix of interviews and field
notes
• Our analytical problem is that of analysing a mass of text
• Analysis / Coding represents the operations by which data
are:
– Broken down
– Conceptualized,
– Put back together in new ways
• The objective is to build theory from data – a “Grounded
Theory” approach
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Data Analysis / Coding
Open Coding (I)
• Labelling events: Consists of placing conceptual labels on
discrete happenings, events and instances in data
Data are broken down and conceptualized by taking apart an observation, a
sentence, a paragraph and giving each separate incident, idea or event a name
that represents a phenomenon. Incident after incident in the field notes are
compared in order to give similar events the same name -conceptual label- and
nuance and enrich each concept.
The process involves asking questions to the data so as to identify properties
and dimensions of the incidents
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Data Analysis / Coding
Open Coding (II)
• Categorising: Consists of grouping conceptual labels into
categories
Concepts that seem to pertain to the same phenomena are then regrouped categorized- and given a name that should be more abstract than that given
during labeling.
Categories have conceptual power because they are able to pull together
around them groups of concepts.
Practically, categorising consists of going through all concepts and asking
questions such as 'What is this concept about?' or 'Is this concept similar or
different from the one before or after?'
In this way, categories are discovered when concepts are compared against one
another, and concepts become characteristic components of a category - so
called subcategories.
If a concept seems not to pertain to an already identified category, it is left
aside and might become the entry to a new category as data analysis goes on.
• Categorising can be bottom-up or top-down
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Data Analysis / Coding
Axial Coding
• Condensation of data, i.e., regrouping and linking
categories to each other
Open coding fractures the data and allows the researcher to identify
some categories, their properties and dimensions. Axial coding puts
these data back together in new ways by making connections between
categories.
• The objective is to identify the core category (basically
derived from the unit of analysis) and to logically relate
other main categories to the core
• The “Paradigm Model” structures the axial coding process
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
The Paradigm
Model
PHENOMENON
CAUSAL CONDITIONS
INTERVENING
CONDITIONS
CONTEXT
CONSEQUENCES
1. Identify the phenomenon to be studied (activity, business process...).
2. Identify the conditions of directive nature, influencing the phenomenon (driving forces,
objectives...).
3. Specify the context in which the phenomenon takes place (organization, information....).
4. Identify the conditions of shaping nature that intervene in carrying out and managing the i
phenomenon (reactions from stakeholders, cognitive processes, continuous improvement...).
5. Identify the outcomes related to the phenomenon - predictable/intended or not (competences,
ressources, knowledge, know-how...).
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Data Analysis / Coding
An Iterative
Process
1993
Initial literature review,
development of research
proposal and topic guide
1994
My Research
Process
Pilot interviews, testing
of topic relevance
Suppliers 1, 2, 3 and 4
Final version of
the topic guide
1995
Formal interviews
with general managers
Suppliers 3 and 4
First case study
Supplier 3
Formal interviews with
product development managers
Suppliers 3 and 4
Data analysis:
open coding
Data analysis: open coding,
data reduction and development of case study topic guide
1996
Second case study
Supplier 4
Data analysis: open coding,
data reduction and comparishon
of concepts with case study one
Data analysis:Axial coding,
comparison of findings
with relevant literature
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Second series of formal
interviews (product development
managers) Suppliers 5, 6, 7 and 8
Data Analysis / Coding
My Open Coding
Sentence extracted from interview:
«We need performance measurements that enhance the
value of inter-functional problem solving»
Category: Problem Solving
Sub categories: Objectives, Efficiency, Support Structures
Properties of “Efficiency”: Nature of Topic, Nature of Participation
Dimensions of “Nature of Topic”: Problems, Problems & Causes,
Problems, Causes & possible le actions
Dimensions of “Nature of Participation”:
Participant Driven
Management Driven
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Data Analysis / Coding
My Axial Coding (I)
Core Category: Operational Design
The analysis of the category “Problem Solving” led to the
identification of four distinctive levels of operational design
Systemic work
Project work
Group work
Individual work
Intrafunctional between design
technicians and engineers
Interfunctional within the
supplier company
Involving customers, interface suppliers
and lower-tier suppliers
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Data Analysis / Coding
My Axial Coding (II)
Causal Conditions: Means of Guidance
Intra-company, inter-functional learning
– Guiding Visions, Performance Measurements
Context: Design Support Structures
Process
Engineering
Purchasing
Sales
– Specifications, Information transmission
support technology,
technology scanning, knowledge repositories
Intervening Conditions
– Learning dynamics,
learning model
Intra-company,
intra-functional learning
Design
function in
customer
firms
Design
function in
interfacing
sup. firms
Inter-company, intra-functional learning
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Data Analysis / Coding
My Axial Coding (II)
Causal Conditions: Means of Guidance
CORE
CAPABILITIES
– Guiding Visions, Performance Measurements
S
Context: Design Support Structures
H
Adequation with customer needs
Differentiation from competitors
A
– Specifications, Information transmission
support technology,
R
technology scanning, knowledge
repositories
E
Intervening Conditions
D
– Learning dynamics,
learning model
V
A
L
U
E
S
Consequences
– Model of the process of
building core capabilities
Strategic
Objectives
Management
Systems
Means
of
Guidance
Skills
Basic Resources
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Technological
Development
Collective
Learning
Data Analysis / Coding
Selective Coding and «Story»
• The narrative about the core category must identify and
define the basic content of the other categories
• Narrative about each category, crossing the results of axial
coding with research questions
• Theoretical sampling: Strengthen weak relationships
between categories inductively and integrate literature
relevant for the results emerging
• Specify action / interaction strategies for how the holistic
model or theory operates
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Example: The answer to one of the research questions emerges from the
narratives about the core category, the context category and the intervening
conditions category
How are organisations and processes designed to support integration?
SUPPLIER
CARMAKER
Component
design
Product
planning
Problem solving 1*
Product
engineering
Process
engineering
Running
Production /
Minor
modifications
Design
Project 1
Design
technician S1
technician C1
Problem solving 2*
Design
technician S2
Design
technician S3
Design
Project 2
Problem solving 3*
Problem solving 4*
technician C2
Design
technician C3
Project 3
Project 4
Design
technician C4
Transfer of learning
through formal and
Transfer of learning
through formal and
informal group work,
organizational routines
and support structures
informal group work,
organizational routines
and support structures
* Transfer through supplier - customer
problem solving cycles
Shared knowledge base
Transfer of experience
Reliability and Validity (I)
• Reliability consists of demonstrating that the operations of a
study -such as the data collection procedures- can be
repeated, with the same results
• It is a question of documenting the research procedure
• Reliability is ensured by keeping data in different forms:
- Directly
taken field notes - from interviews and observations,
- Expanded typed notes made as soon as possible after the field work
(this includes comments on problems and ideas that arise during each
stage of the fieldwork and that will guide further research),
- A running record of analysis and interpretation (open coding and axial
coding).
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Reliability and Validity (II)
• Construct validity means establishing correct operational
measures for the concepts being studied. It is ensured
through:
- The use of multiple sources of evidence,
- The establishment of a chain of evidence,
- Letting key informants review draft result reports
• External validity means establishing the domain to which a
study's findings can be generalized. It is ensured through
the use of a replication logic “Analytical Generalisation”
- Relate case findings to existing or emerging bodies of literature, part
of which will have been analysed in the literature section of the thesis
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist
Sources
• Easterby-Smith, M., Thorpe, R., Lowe, A., (1991), Management Research, An Introduction,
London: Sage Publications.
• Dey, I. (1993), Qualitative Data Analysis. A User-Friendly Guide for Social Scientists,
London: Routledge.
• Miles, M. B. & Huberman, A. M., (1994), Qualitative Data Analyses, An Expanded
Sourcebook, Thousand Oaks, CA: Sage Publications.
• Pras, B. & Tarondeau, J-C., (1979), "Typologie de la recherche en gestion" (Typology of
Management Research, in French), Enseignement et Gestion, Nouveau Serie no. 9, p. 5-11
• Silverman, D., (1993), Interpreting Qualitative Data, Methods for Analysing Talk, Text and
Interaction, London: Sage Publications.
• Strauss, A., & Corbin, J., (1990), Basics of Qualitative Research, Grounded Theory
Procedures and Techniques, Newbury Park CA: Sage Publications
• Van Maanen, J., Dabbs, J.M., Faulkner, R.R. (1982), Varieties of Qualitative Research.
Beverley Hills, CA: Sage Publications
• Van Maanen, J., (1983), Qualitative Methodology, Beverley Hills, CA: Sage Publications.
• Yin, R., K., (2003), Case Study Research, Design and Methods, 3rd edition, Newbury Park,
CA: Sage Publications.
PhD Seminar Series. Qualitative Research Methodology
K.E. Soderquist