Quantitative Research Summary
Gregory Rutbell
25 September 2013
Embry-Riddle Aeronautical University - Worldwide
Campus
Quantitative research attempts precise measurement of
something. In business research, quantitative methodologies usually measure
consumer behavior, knowledge, opinions, or attitudes. Such methodologies answer
questions related to how much, how often, how many, when, and who. Although the
survey is not the only methodology of the quantitative researcher, it is
considered a dominant one. (Cooper & Schindler, 2014)
Besides the purpose of the research, this process sets up
several key distinctions between qualitative and quantitative research,
elaborated in Exhibit 1, including the level of researcher involvement;
sampling methodology and size; data collection processes; including participant
preparation and researcher and research sponsor involvement; data type and
preparation; data analysis and timing; processes for reaching insights and
meaning; time frame of insight discovery; and the level of data security. (Cooper
& Schindler, 2014)
In the case of
quantitative data, both the researcher and research sponsor have less
significant involvement in collecting and interpreting data compared to
qualitative analysis. With large quantitative studies, the researcher who
interprets the data and draws conclusions from it is rarely the data collector
and often has no contact at all with the participant. In quantitative research,
identical data are desired from all participants, so evolution of methodology
is not acceptable. (Cooper & Schindler, 2014)
Quantitative data often consist of participant responses
that are coded, categorized, and reduced to numbers so that these data may be
manipulated for statistical analysis. One objective is the quantitative tally
of events or opinions, called the frequency of responses. Qualitative data are
all about texts. Detailed descriptions of events, situations, and interactions,
either verbal or visual, constitute the data. Data may be contained within
transcriptions of interviews or video focus groups, as well as in notes taken
during those interactions. But by
definition they generate reams of words that need to be coded and analyzed by
humans for meaning. While computer software is increasingly used for the coding
process in qualitative research, at the heart of qualitative research is the
researcher - and his or her experience - framing and interpreting the data. (Cooper
& Schindler, 2014)
Multimillion-dollar strategies may
lose their power if the competitor acts too quickly. Data security is therefore
of increasing concern. Both group and individual interviewing, the mainstay techniques
of qualitative research, can be conducted in highly secure environments. In
comparison, once a quantitative survey or field observation or experiment is
started, it is quickly common knowledge among a research sponsor's competitors.
Although the data might not be known, the area of inquiry often can be
determined. For example, in a test market - an experimental quantitative design
- a research sponsor 's competitors can often observe and extract insights
right along with the sponsor. In quantitative research, unless a researcher is
collecting his or her own data, interviewers or data collectors are rarely
involved in the data interpretation or analysis stages. Although data
collectors contribute to the accuracy of data preparation, their input is rarely,
if ever, sought in the development of data interpretations. While qualitative
research is being used to increasingly because of the methodologies' ability to
generate deeper understanding, it is still perceived by many senior-level
executives as a stepchild of quantitative data collection. This is primarily
due to qualitative research's use of nonprobability sampling, the smaller
sample sizes involved, and the nonprojectability of the results to a broader,
target population. (Cooper & Schindler, 2014)
Triangulation is the term used to describe the combining of several
qualitative methods or combining qualitative and quantitative methods.
Qualitative studies may be combined with quantitative studies to increase the
perceived quality of the research, especially when a quantitative study follows
a qualitative one and provides validation for the qualitative findings. Four
strategies for combining methodologies are common in business research:
1. Qualitative and quantitative research can be
conducted simultaneously.
2. A qualitative study can be ongoing while
multiple waves of quantitative studies are done, measuring changes in behavior
and attitudes over time.
3. A qualitative study can precede a
quantitative study, and a second qualitative study might then follow the
quantitative study, seeking more clarification.
4. A quantitative study can precede a
qualitative study.
Many researchers recognize that qualitative research compensates for
the weaknesses of quantitative research and vice versa. These forward thinkers
believe that the methodologies complement rather than rival each other. (Cooper
& Schindler, 2014)
Exhibit 1 (Cooper & Schindler,
2014, p. 147)
|
|
Qualitative
|
Quantitative
|
|
Focus
of Research
|
· Understand and interpret
|
· Describe, explain, and predict
|
|
Researcher
Involvement
|
· High - researcher is participant or
catalyst
|
· Limited; controlled to prevent bias
|
|
Research
Purpose
|
· In-depth understanding; theory building
|
· Describe or predict; build and test
theory
|
|
Sample
Design
|
· Nonprobability; purposive
|
· Probability
|
|
Sample
Size
|
· Small
|
· Large
|
|
Research
Design
|
· May evolve or adjust during the course of
the project
·
Often
uses multiple methods simultaneously or sequentially
·
Consistency
is not expected
·
Involves
longitudinal approach
|
·
Determined
before commencing the project
·
Uses
single method or mixed methods
·
Consistency
is critical
· Involves either a cross-sectional or
longitudinal approach
|
|
Participant
Preparation
|
· Pretasking is common
|
· No preparation desired to avoid biasing
the participant
|
|
Data
Type and Preparation
|
· Verbal or pictorial descriptions
·
Reduced
to verbal codes (sometimes with computer assistance)
|
·
Verbal
descriptions
· Reduced to numerical codes for
computerized analysis
|
|
Data
Analysis
|
· Human analysis following computer or human
coding; primarily nonquantitative
·
Forces
researcher to see the contextual framework of the phenomenon being measured -
distinction between facts and judgments less clear
|
·
Computerized
analysis - statistical and mathematical methods dominate
·
Analysis
may be ongoing during the project
· Maintains clear distinction between facts
and judgments
|
|
Insights
and Meaning
|
· Deeper level of understanding is the norm;
determined by type and quantity of free-response questions
·
Researcher
participation in data collection allows insights to form and to be tested
during the process
|
·
Limited
by the opportunity to probe respondents and the quality of the original data
collection instrument
·
Insights
follow data collection and data entry, with limited ability to reinterview
participants
|
|
Research
Sponsor Involvement
|
· May participate by observing research in
real time or via taped interviews
|
· Rarely has either direct or indirect
contact with participant
|
|
Feedback
Turnaround
|
· Smaller sample sizes make data collection
faster for shorter possible turnaround
·
Insights
are developed as the research progresses, shortening data analysis
|
·
Larger
sample sizes lengthen data collection; Internet methodologies are shortening
turnaround but inappropriate for many studies
· Insight development follows data
collection and entry, lengthening research process; interviewing software
permits some tallying of responses as data collection progresses
|
|
Data
Security
|
· More absolute given use of restricted
access facilities and smaller sample sizes
|
· Act of research in progress is often known
by competitors; insights may be gleaned by competitors for some visible,
field-based studies
|
References
Cooper, Donald R. & Schindler,
Pamela S. (2014) Business Research Methods (12th ed). New York, NY: McGraw-Hill/Irwin.
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