This document provides an overview of qualitative research methods. It discusses various qualitative research techniques including observation studies, interviews, focus groups, and case studies. It also covers topics like developing qualitative research questions, sampling techniques, data collection and analysis strategies, and choosing appropriate qualitative methods.

1. 5
Qualitative Research
McGraw-Hill/Irwin
Business Research Methods, 10e Copyright © 2008 by The McGraw-Hill Companies, Inc. All Rights Reserved.

2. 2
Qualitative Research in Business
 Job Analysis
 Advertising Concept
Development
 Productivity
Enhancement
 New Product
Development
 Benefits Management
 Retail Design
 Process
Understanding
 Union Representation
 Market Segmentation
 Sales Analysis

3. 3
The Roots of Qualitative Research
Psychology
Anthropology
Communication
Sociology
Semiotics
Economics
Qualitative
Research

4. 4
Qualitative
Research
and the
Research Process

5. 5
Formulating
the
Qualitative
Research
Question

6. 6
Qualitative Research Question
 Exploratory foundation
 How? Why?
 Phenomenology
 Essence of experience; affect on meaning and
behavior
 Grounded theory
 Elements of experience; generating models or
theories
Adopt from Dr. John L. Hoffman, CSUF (2012)

7. 7
Qualitative Research Question
 Narrative Inquiry
 Analyzes people’s stories about experience;
creates a collaborative story for a purpose
 Ethnography
 Uses an ethnic group as the unit of analysis
 Case study
 Uses a program, event, or process as the unit
analysis
Adopt from Dr. John L. Hoffman, CSUF (2012)

8. 8
Mixed methods Research question
 Convergent
 In what ways do the quantitative and qualitative
findings complement or contradict one another?
 Explanatory/Exploratory
 Based on an intentional sequence (e.g. QUAN 
QUAL)
 In what ways do the qualitative findings confirm,
disconfirm, and/or extend the quantitative
findings?

9. 9
Focus Groups
Qualitative Research
Ethnography
Observation
Data
Collection
Techniques
IDIs
Case Studies
Action
Research
Grounded
Theory
Group
Interviews

10. 10
Data Sources
People
Organizations
Texts
Environments
Events and
happenings
Artifacts/ media
products

11. 11
Pretasking Activities
Use product in home
Bring visual stimuli
Create collage
Keep diaries
Construct a story
Draw pictures

12. 12
Choosing a Qualitative Method
Types of
participants
Researcher
characteristics
Factors
Schedule
Budget
Topics
Project’s
purpose

13. 13
NonProbability Sampling
Purposive
Sampling
Snowball
Sampling
Convenience
Sampling

14. 14
Qualitative Sampling
General sampling rule:
You should keep conducting
interviews until no new insights are
gained.

15. 15
The Interview Question Hierarchy

16. 16
Interviewer Responsibilities
 Recommends topics and
questions
 Controls interview
 Plans location and
facilities
 Proposes criteria for
drawing sample
 Writes screener
 Recruits participants
 Develops pretasking
activities
 Prepares research
tools
 Supervises
transcription
 Helps analyze data
 Draws insights
 Writes report

17. 17
Elements of a Recruitment Screener
 Heading
 Screening requirements
 Identity information
 Introduction
 Security questions
 Demographic questions
 Behavior questions
 Lifestyle questions
 Attitudinal and
knowledge questions
 Articulation and
creative questions
 Offer/ Termination

18. 18
Interview Formats
Unstructured
Semi-structured
Structured

19. 19
Requirements for
Unstructured Interviews
Distinctions
Developed dialog
Interviewer skill
Probe for
answers
Interviewer
creativity

20. In-depth or semi-structure
 To help you decide whether or not to use in-depth or
semi-structure interview
 Does the purpose of your research suggest to use in-depth or
semi-structure interview?
 Will it help to seek personal contact in terms of gaining access
to participants and their data?
 Are your data collection questions large in number, complex or
open-ended?
 Will there be a need to vary the order and logic of
questioning?
 Will it help to be able to probe interviewees responses to build
on or seek explanation of their answer?
 Will the data collection process with each individual involve a
relatively lengthy period?
20

21. 21

22. 22
The Interview Mode
GroupIndividual

23. 23
IDI vs Group
Individual Interview Group Interview
Research Objective
 Explore life of individual in depth
 Create case histories through repeated
interviews over time
 Test a survey
 Orient the researcher to a field of inquiry and
the language of the field
 Explore a range of attitudes, opinions, and
behaviors
 Observe a process of consensus and
disagreement
Topic Concerns
 Detailed individual experiences, choices,
biographies
 Sensitive issues that might provoke anxiety
 Issues of public interest or common concern
 Issues where little is known or of a
hypothetical nature
Participants
 Time-pressed participants or those difficult to
recruit (e.g., elite or high-status participants)
Participants with sufficient language skills (e.g.,
those older than seven)
 Participants whose distinctions would inhibit
participation
 Participants whose backgrounds are similar or
not so dissimilar as to generate conflict or
discomfort
 Participants who can articulate their ideas
 Participants who offer a range of positions on
issues

24. 24
Types of Research Using IDIs
Cultural
interviews
Sequential
interviewing
Types
Life histories
Critical
incident
techniques
Oral histories
Ethnography

25. 25
Group Interviews
 Dyads
 Triads
 Mini-Groups
 Small Groups (Focus Group)
 Supergroups

26. 26
Determining the Number of Groups
Scope
Number of distinct segments
Desired number of ideas
Desired level of detail
Homogeneity
Level of distinction

27. 27
Group Interview Modes
Teleconference
Online
Videoconference
Face-to-Face

28. 28
Combining Qualitative Methodologies
Action ResearchCase Study

29. 29
Case Study
 Yin (1984:23) defines the case study research method
“as an empirical inquiry that investigates a contemporary
phenomenon within its real-life context; when the
boundaries between phenomenon and context are not
clearly evident; and in which multiple sources of
evidence are used.”
 Through case study methods, a researcher is able to go
beyond the quantitative statistical results and understand
the behavioral conditions through the actor’s
perspective. By including both quantitative and
qualitative data, case study helps explain both the
process and outcome of a phenomenon through
complete observation, reconstruction and analysis of the
cases under investigation (Tellis, 1997).

30. 30
Case Study Design
 single-case  where events are limited to a
single occurrence
 multiple-case design  numerous sources of
evidence through replication
 Generalisation of results from case studies, from
either single or multiple designs, stems on
theory rather than on populations (Yin,1994)

31. 31
Case Study Design
 case study method, through interviews or journal
entries, must be able to prove that:
 it is the only viable method to explore implicit and
explicit data from the subjects
 it is appropriate to the research question
 it follows the set of procedures with proper
application
 a ‘chain of evidence’, either quantitatively or
qualitatively, are systematically
 recorded and archived particularly when
interviews and direct observation by the
researcher are the main sources of data
 the case study is linked to a theoretical framework
(Tellis, 1997)

32. 32
Action Research
 Action research is “learning by doing”: a group of
people identify a problem, do something to
resolve it, see how successful their efforts were,
and if not satisfied, try again. While this is the
essence of the approach, there are other key
attributes of action research that differentiate it
from common problem-solving activities that we
all engage in every day.

33. 33
Action research process

34. 34
Action research process is a spiral

35. QUALITATIVE DATA
COLLECTION
35

36. Data recording - Converting Raw Data to
Computer Files
 Audio Recording
 transcribing all tapes and typing the transcriptions into
computer files
 Before transcription, the tabs on the tapes should be
punched to prevent them from being recorded over.
36

37. 37
Converting Raw Data to Computer Files
 Handwritten field notes: handwritten notes include a
wide range of information:
 casual and structured observations
 verbatim quotes
 paraphrases of participant responses
 interview and focus group backup documentation
 the researcher’s questions
 questions, conclusions, and observations discussed during
the staff debriefing sessions
 Transcription of recordings and typing of field
notes should begin as soon as possible after the
data collection event.

38. 38
Converting Raw Data to Computer
Files
 Use standard conventions for identifying the researcher
and individual participants throughout the transcript.
 These conventions should be detailed in a transcription
protocol which precisely outlines procedures and formats
for transcribing recorded data.
 Transcription protocol you develop for your own study
should reflect any formatting or other requirements of the
software that you will use.

39. Data Analysis Strategies
 Identifying themes
 Begin with big picture and list “themes” that emerge.
 Events that keep repeating themselves
 Coding qualitative data
 Reduce data to a manageable form
 Often done by writing notes on note cards and
sorting into themes.
 Predetermined categories vs. emerging categories

40. EDUC 7741/Paris/Terry
Coding Data
 Open Coding
 Assign a code word or phrase that accurately
describes the meaning of the text segment
 Line-by-line coding is done first in theoretical
research
 More general coding involving larger segments of
text is adequate for practical research (action
research)

41. EDUC 7741/Paris/Terry

42. Systematic Coding
 Categories are created ahead of time
 from existing literature
 from previous open coding
 Code the data just like open coding
Ron Wardell, EVDS 617 course notes

43. How to make coding manageable
 Make photocopies of original data
 Why?
 Read through all of the data.
 Attach working labels to blocks of text
 Cut and paste blocks of text onto index cards.
 Group cards that have similar labels together
 Revisit piles of cards to see if clusters still hold
together.

44. Affinity Diagramming
 Goal: what are the main themes?
 Write ideas on sticky notes
 Place notes on a large wall / surface
 Group notes hierarchically to see main themes
Holtzblatt et al., 2005

45. Example: Calendar Field Study
Neustaedter, 2007
 Families were given a digital calendar to use
in their homes
 Thoughts / reactions recorded:
 Weekly interview notes
 Audio recordings from interviews

46. Example: Calendar Field Study
 Step 1: Affinity Notes
 go through data and write observations down on
post-it notes
 each note contains one idea

47. Example: Calendar Field Study
 Step 2: Diagram Building
 place all notes on a wall / surface

48. Example: Calendar Field Study
 Step 2: Diagram Building
 move notes into related columns / piles

49. Example: Calendar Field Study
 Step 3: Diagram Building
 move notes into related columns / piles

50. Example: Calendar Field Study
 Step 2: Diagram Building
 move notes into related columns / piles

51. Example: Calendar Field Study
 Step 2: Diagram Building
 move notes into related columns / piles

52. Example: Calendar Field Study
 Step 2: Diagram Building
 move notes into related columns / piles

53. Example: Calendar Field Study
 Step 3: Diagram Building
 move notes into related columns / piles

54. Example: Calendar Field Study
 Step 2: Diagram Building
 move notes into related columns / piles

55. Example: Calendar Field Study
 Step 3: Affinity Labels
 write labels describing each group

56. Example: Calendar Field Study
 Step 3: Affinity Labels
 write labels describing each group
Calendar placement
is a challenge

57. Example: Calendar Field Study
 Step 3: Affinity Labels
 write labels describing each group
Calendar placement
is a challenge
Interface visuals
affect usage

58. Example: Calendar Field Study
 Step 3: Affinity Labels
 write labels describing each group
Calendar placement
is a challenge
Interface visuals
affect usage
People check the
calendar when not
at home

59. Example: Calendar Field Study
 Step 4: Further Refine Groupings
Calendar placement
is a challenge
Interface visuals
affect usage
People check the
calendar when not
at home

60. EDUC 7741/Paris/Terry
Why themes?
 It is best to write a qualitative report providing
detailed information about a few themes rather
than general information about many themes
 Themes can also be referred to as Categories

61. EDUC 7741/Paris/Terry
Naming the Themes or Categories
 The names can come from at least three
sources:
 The researcher
 The participants
 The literature
 Most common: when the researcher
comes up with terms, concepts, and
categories that reflect what he or she sees
in the data

62. EDUC 7741/Paris/Terry
Themes should…
 Reflect the purpose of the research
 Be exhaustive--you must place all data in a
category
 Be sensitizing--should be sensitive to what is in
the data
 i.e., “leadership” vs. “charismatic leadership”
 Be conceptually congruent- the same level of
abstraction should characterize all categories
at the same level
 For instance, you wouldn’t have produce,
canned goods, and fruit

63. EDUC 7741/Paris/Terry
Types of themes
 Ordinary: themes a researcher expects
 Unexpected: themes that are surprises and not
expected to surface
 Hard-to-classify: themes that contain ideas that
do not easily fit into one theme or that overlap
with several themes
 Major & minor themes: themes that represent the
major ideas, or minor, secondary ideas in a
database
 Minor themes fit under major themes in the write up

64. 64
Exercise 4 (Group)
 Develop qualitative research question(s) for
your group project
 Design an in-depth interview protocol:
 Interview purpose?
 Interviewee? (any selection criteria?)
 Questions? (screening, leading, probe questions)
 Practice the interview skill

65. McGraw-Hill/Irwin
Business Research Methods, 10e Copyright © 2008 by The McGraw-Hill Companies, Inc. All Rights Reserved.
OBSERVATION
STUDIES

66. 66
Observation and the Research Process

67. 67
Selecting an Observation Data Collection
Approach

68. 68
Research Design
How?
Where?
Task Details
What?
(event or
time)
When?
Who?

69. 69
Content of Observation
Factual Inferential
Introduction/identification of salesperson and
customer.
Credibility of salesperson. Qualified status of
customer.
Time and day of week. Convenience for the customer. Welcoming
attitude of the customer
Product presented. Customer interest in product.
Selling points presented per product. Customer acceptance of selling points of
product.
Number of customer objections raised per
product.
Customer concerns about features and
benefits.
Salesperson’s rebuttal of objection. Effectiveness of salesperson’s rebuttal
attempts.
Salesperson’s attempt to restore controls. Effectiveness of salesperson’s control attempt.
Consequences for customer who prefers
interaction.
Length of interview. Customer’s/salesperson’s degree of
enthusiasm for the interview.
Environmental factors interfering with the
interview.
Level of distraction for the customer.
Customer purchase decision. General evaluation of sale presentation skill.

70. 70
Data Collection
Watching
Listening
Touching
Smelling
Reading

71. 71
Using Observation
Systematic planning
Properly controlled
Consistently dependable
Accurate account of events

72. 72
Observation Classification
Nonbehavioral
 Physical condition
analysis
 Process or Activity
analysis
 Record analysis
Behavioral
 Nonverbal
 Linguistic
 Extra-linguistic
 Spatial

73. 73
 Nonverbal observation is the most prevalent
and refers to recording physical actions or
movements of participants. These behaviors can
be measured with the human eye and with
several mechanical or digital devices.
 Linguistic observation is the observation of
human verbal behavior during conversation,
presentation, or interaction.
 Extra-linguistic observation is the recording of
vocal, temporal, interaction, and verbal stylistic
behaviors of human participants.
 Spatial observation is the recording of how
humans physically relate to one another.

74. 74
Selecting an Observation Data Collection
Approach - Non-behavioral

75. 75
Nonbehavioral Observation
Record
Analysis
Physical Condition
Analysis
Physical Process
Analysis

76. 76
Selecting an Observation
Data Collection Approach…Behavioral

77. 77
Behavioral Observation
 “We noticed people scraping
the toppings off our pizza
crusts. We thought at first
there was something wrong,
but they said, ‘We love it, we
just don’t eat the crust
anymore.”
 Tom Santor, Donatos Pizza

78. 78
Systematic Observation
Encoding
observation
information
Structured
Systematic
Trained
observers
Standardized
procedures
Recording
schedules

79. 79
Flowchart for Checklist Design

80. 80
Mechanical/ Digital Behavioral
Observation
Eye camera
Devices
Audio recorder
Video camera

81. 81
Observer-Participant Relationship
Direct or indirect
observation
Presence is known
or unknown
Observer involved or
not involved in events

82. 82
Extralinguistic Observation
Vocal
Temporal
Interaction
Verbal Stylistic

83. 83
Extralinguistic Observation
 Vocal
 Temporal
 Interaction
 Verbal Stylistic

84. 84
Desired Characteristics for Observers
Concentration
Detail-oriented
Unobtrusive
Experience level

85. 85
Errors Introduced by Observers
Observer DriftHalo Effect

86. 86
Errors Introduced by Observers
 Halo Effect: inexperience can be an advantage if
there is a risk that experienced observers may have
preset convictions about the topic or if prior
observations will influence what is perceived in a
current observation.
 Observer Drift: observers can also introduce error
when fatigued, which can result in observer drift.
Observer drift is error caused by decay in
consistency and accuracy on recorded observations
over time, affecting categorization.

87. 87
Evaluation of Behavioral Observation
Strengths
 Securing information that
is otherwise unavailable
 Avoiding participant
filtering/ forgetting
 Securing environmental
context
 Optimizing naturalness
 Reducing obtrusiveness
Weaknesses
 Enduring long periods
 Incurring higher
expenses
 Having lower reliability of
inferences
 Quantifying data
 Keeping large records
 Being limited on
knowledge of cognitive
processes