Inductive Approach (Inductive Reasoning)
Inductive approach, also known in inductive reasoning, starts with the
observations and theories are proposed towards the end of
the research process as a result of observations[1]. Inductive research
“involves the search for pattern from observation and the development
of explanations – theories – for those patterns through series of
hypotheses”[2]. No theories or hypotheses would apply in inductive
studies at the beginning of the research and the researcher is free in
terms of altering the direction for the study after the research process
had commenced.
It is important to stress that inductive approach does not imply
disregarding theories when formulating research questions and
objectives. This approach aims to generate meanings from the data set
collected in order to identify patterns and relationships to build a
theory; however, inductive approach does not prevent the researcher
from using existing theory to formulate the research question to be
explored.[3] Inductive reasoning is based on learning from experience.
Patterns, resemblances and regularities in experience (premises) are
observed in order to reach conclusions (or to generate theory).
Application of Inductive Approach
(Inductive Reasoning) in Business
Research
Inductive reasoning begins with detailed observations of the world,
which moves towards more abstract generalisations and ideas[4].
When following an inductive approach, beginning with a topic, a
researcher tends to develop empirical generalisations and identify
preliminary relationships as he progresses through his research. No
hypotheses can be found at the initial stages of the research and the
researcher is not sure about the type and nature of the research
findings until the study is completed.
As it is illustrated in figure below, “inductive reasoning is often referred
to as a “bottom-up” approach to knowing, in which the researcher uses
observations to build an abstraction or to describe a picture of the
phenomenon that is being studied”[5]
Here is an example:
My nephew borrowed $100 last June but he did not pay back until
September as he had promised (PREMISE). Then he assured me that
he will pay back until Christmas but he didn’t (PREMISE). He also failed
in to keep his promise to pay back in March (PREMISE). I reckon I have
to face the facts. My nephew is never going to pay me back
(CONCLUSION).
Generally, the application of inductive approach is associated
with qualitative methods of data collection and data analysis,
whereas deductive approach is perceived to be related to quantitative
methods. The following table illustrates such a classification from a
broad perspective:
Concepts associated with Concepts associated with
quantitative methods qualitative methods
Deduction Induction
Objectivity Subjectivity
Causation Meaning
Type of reasoning
Pre-specified Open-ended
Outcome-oriented Process-oriented
Type of question
Numerical estimation Narrative description
Statistical inference Constant comparison
Type of analysis
However, the statement above is not absolute, and in some instances
inductive approach can be adopted to conduct a quantitative research
as well. The following table illustrates patterns of data analysis
according to type of research and research approach.
Qualitative Quantitative
Inductive Grounded theory Exploratory data analysis
Deductive Qualitative comparative analysis Structural equation modeling
When writing a dissertation in business studies it is compulsory to
specify the approach of are adopting. It is good to include a table
comparing inductive and deductive approaches similar to one
below[6] and discuss the impacts of your choice of inductive approach
on selection of primary data collection methods and research process.
Attribute Deductive Inductive
Direction “Top-Down” “Bottom-Up”
Prediction changes,
validating theoretical Understanding
construct, focus in “mean” dynamics, robustness,
behaviour, testing emergence, resilience,
assumptions and focus on individual
hypotheses, constructing behaviour, constructing
Focus most likely future alterative futures
Single Multiple
(one landscape, one (multiple landscape, one
resolution) resolution)
Spatial scales
Multiple Multiple
(deterministic) (stochastic)
Temporal scales
Multiple
Single (heterogeneous
(homogenous preferences) preferences)
Cognitive scales
Aggregation scales Single Single or multiple
(core aggregation scale) (one or more
aggregation scales)
High – Low Low-High
Predictive vs. Stochastic (one likely future) (many likely futures)
accuracy
High
Low (individual or group
(group or partial attributes) attributes)
Data intensity
My e-book, The Ultimate Guide to Writing a Dissertation in Business
Studies: a step by step assistance contains discussions of theory and
application of research approaches. The e-book also explains all stages
of the research process starting from the selection of the research
area to writing personal reflection. Important elements of dissertations
such as research philosophy, research design, methods of data
collection, data analysis and sampling are explained in this e-book in
simple words.
John Dudovskiy
