Research methodology BPH 4th year

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RESEARCH METHODOLOGY
A CONCEPTUAL
FRAMEWORK
Bph 4th year

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Research Means
*Systematic and objective
investigation of a subject or a
problem in order to discover
relevant information.

3. Types of Research
1. Fundamental Research
Known as basic or pure research; seeks to expand the boundaries of knowledge in the
given area.
For example
Development of research methods, propagation of new theories, conduction of
academic research studies.
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4. 2. Applied Research
* Known as a decisional research
* Attempts to use existing knowledge for resolving the current problem.
For example
* What consumers will like in next five years
* What are the customer needs, expectations, and problems associated to our
offerings?
* Do they like our after sales services? and so on ...
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5. Academic Research
¤ An academic research may be defined
as a process that involves systematic
design, collection, interpretation and
reporting of information needed to
solve specific problems or take
advantage of functional opportunities,
or find new dimensions in the existing
theories.
¤ Academic research is also referred to
as basic or fundamental research.
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6. ¤ As a whole, an applied research is driven by the objectives of development,
interpretation, and communication of decision-oriented information.
¤ The basic research also serves in a similar fashion so as to facilitate the
development of new theories or principles, or to add new dimensions in the
existing principles or concepts, or challenge them.
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7. OBJECTIVES OF Research
1. Assessment
2. Exploration
3. Evaluation
4. Examination
5. Comparison
6. Estimation
7. Propagation
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8. The Research Process
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Step 1
Defining the
problem and
research
objectives
Step 2
Developing the
research plan
for collecting
information
Step 3
Implementing
the research
plan - collecting
and analyzing
the data
Step 4
Interpreting
and reporting
the findings

9. Research Design
 Specification of methods and procedures for
obtaining the information needed
 A plan or organizing framework for conducting
the study and collecting data
 Blueprint of the detail procedure and
rationale of research project
 An essential part of research methodology
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10. Research Design Answers These Questions
 What is the study all about?
 Why is the study being carried out?
 Where will the study be carried out?
 What type of data are required?
 How much time will the study require?
 What will be the sample design?
 What techniques of data collection will be used ?
 How will the data be analyzed and interpreted?
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11. Importance of Research Design
 Serves as a foundation to formulate and guide the
research study
 Supports in better planning & execution of the
research methodology
 Useful in the estimation of probable research
errors and handling strategies
 Maintains necessary control over the contents of
the study
 Makes the study more systematic, and effective
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12. Tasks of Research Design
 Determine the exploratory, descriptive, or causal phases of the research
 Determine the information needed
 Specify the measurement and scaling procedures
 Construct and pretest appropriate form of data collection
 Specify sampling process and sample size
 Develop a plan of data analysis and presentation
 Develop a monitoring and control mechanism for facilitate the overall research function
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13. Types of Research Designs
On the basis of the study techniques adopted in the research function, the research designs can
primarily be categorized into TWO forms:
1. Exploratory Research Designs
2. Conclusive Research Designs
a. Descriptive Research Designs
b. Causal Research Designs
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Observational
Research
Gathering data
by observing
people, actions
and situations
(Exploratory)
Experimental
Research
Using groups of
people to
determine
cause and
effect
relationships
(Causal)
Survey Research
Asking
individuals
about attitudes,
preferences or
behaviors
(Descriptive)
Three Research Approaches

15. Types of Research Designs
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Exploratory
Research
Descriptive
Research
Causal
Research
Test hypotheses about cause and effect
relationships
X causes Y
Gathers preliminary information to define
the problem and suggest hypotheses
Literature search, expert interviews, focus
groups, case studies, company audits,
qualitative research
Describes things as the market potential of
a product, consumer demographics and
attitudes
Secondary data analysis, surveys, observations,
panels, simulations

16. Research Design Process
Step 1: Define the Research Problem
Step 2: Estimate the value of the information to be provided by the research
Step 3: Select the Data Collection Method
Step 4: Select the Measurement Techniques
Step 5: Select the Sample
Step 6: Select the Analytical Approach
Step 7: Evaluate the Ethics of the Research
Step 8: Specify the Time and Financial Cost
Step 9: Prepare the Research Proposal
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17. Components of a research proposal
1. Problem Definition
2. Study Approach and Designs
3. Population and Sampling Strategies
4. Sources of Data
5. Data Collection Instrumentation
6. Mechanism for Fielding the Study
7. Mechanism for Data Processing and Analysis
8. Confirmation of the Expertise Involved
9. Timeframe of the Study
10. Cost of the Study
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18. Components of a Research proposal
 Focus of the study and gap analysis
 Estimation of required information and its relevance
 Research design and instrumentation
 Methods of data collection, processing and analysis
 Expertise required
 Estimation of research project costs
 Action programs with timeframe
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19. Variables
Meaning
 Known as a property of proposition being studied
 Also known as the constructs of a proposition
 A symbol to which we assign numerals or values
 Numerical value assigned to a variable is based on its properties
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20. Three General Examples of Variables
1. Dichotomous Variables
 These variables are so called because they have TWO values, reflecting presence
or absence of a property.
 For example: pass or fail, exists or does not exist, employed - unemployed, male -
female, yes - no.
 The dichotomous variables can be assigned with a numerical value of ‘0’ or ‘1’ for
analysis purpose.
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21. 2. Discrete Variables
 These are categorical variables.
 For example, the demographic variables race or religion are the examples of
discrete variables.
 Religion: Hindu, Islam, Buddhism, and Jain can be assigned numerical values of 1,
2, 3, and 4 respectively.
 The numerical values assigned to these variables will be of absolute nature; not
like 3.5, or 4.7.
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22. 3. Continuous Variables
 These variables take on values with a given range or, in some cases, an infinite
set.
 For example, test scores may range from 0 - 100, age may be 2.5 years, present
income of a person could be Rs. 15000, you may disclose your property worth more
than Rs. 500,000,000.
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Sample vs. Population
Population = collection of ALL possible
observations
Sample = subset of a population
Random Sample
representative of a population
all observations have equal chance of
being selected

24. Why Do We Use Samples?
 Cost
 Time
 Inaccessibility of the population
 Accuracy
 Destruction of the observations
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25. Steps in Developing a Sampling Plan
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Step 1: Define the
Population of
Interest
Step 2: Choose
Data Collection
Method
Step 3: Choose
Sampling Frames
Step 4: Select a
Sampling Method
Step 5: Determine
Sample Size
Step 6: Develop and
Specify Operational
Plan
Step 7: Execute
Operational Sampling
Plan

26. Sampling Methods
 Probability vs. Nonprobability
 Probability
 members in the population have a known chance (probability) of being selected
into the sample
 Nonprobability
 the probability of selecting members from the population is not known
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27. Sampling Design Process
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Define Population
Determine Sampling Frame
Determine Sampling Procedure
Probability Sampling
Simple Random Sampling
Systematic Random Sampling
Stratified Sampling
Cluster Sampling
Non-Probability Sampling
Convenience
Judgmental
Quota
Snow-ball
Determine Appropriate Sample Size
Execute Sampling Design

28. Classification of Sampling Methods
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Sampling
Methods
Probability
Samples
Simple
Random
Cluster
Systematic Stratified
Non-
probability
QuotaJudgment
Convenience Snowball

29. Data
Meaning
Data are the units, or, numbers, or facts that are generated through observation.
Data can be qualitative as well as quantitative.
Considered as the backbone for the evidence of every findings and decision
alternatives in the research.
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30. Data Objectives
Data objectives are derived from the research objectives and comprise of what we
have observed to be lacking in the example.
Their determination mainly rests on the researcher, to translate what the decision
maker wants into a specific description of the needed data.
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31. General Qualities Required
1. The measurement should be relevant and adequate to the problem faced to provide
key guidance in decision making.
2. The data must be accurate in both;
i. Validity: Measure what they are supposed to, and
ii. Reliability: On repeating the same method, should give the same results.
3. Data should be obtained quickly enough at an affordable cost.
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32. Nature of Data
1. Facts:
* Include the measurements of anything that actually exists or has
existed.
*Facts, generally describe tangible things, they also can be intangibles.
*They generally originate as the demographic, sociological, psychographic, or
behavioral types.
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33. Nature of Data ...
2. Knowledge:
* That is what people know.
*The information true or false, exists or does not exist, etc.
Example
Consumers awareness about a product or a brand.
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34. Nature of Data ...
3. Opinion:
* How people perceive something.
*What they believe about attitudes.
*The mental sets or predisposition to act in some manner.
Example
Consumer perception regarding good or bad.
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35. Nature of Data ...
4. Intentions:
* The acts that people have in mind to do.
*The expectations of their behavior
Example
Consumer interest upon a certain retailer.
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36. Nature of Data ...
5. Motives:
* Internal forces that cause people to behave as they do.
*Motives may be instrumental ideas for identifying the subjects about
which the people will speak freely.
Example
A certain consumer never liking wine.
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37. Functions of Data
1. Causation
2. Pay off
Here, ‘X’ is the causation and ‘Y’ is the pay off.
3. Description: Determination of causal variables in
the sample. E.g.: How many of them are ‘X’.
4. Identification: Identification of the particular
source.
e.g.: The name of person who took an interview, or
made an observation, name, address, and locations
of subjects, etc.
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Y = f(X)
‘X’ Causes ‘Y’

38. Types of Data
1. Primary Vs. Secondary
Primary Data
That originate from primary sources and are based on observation or investigation or
direct questioning.
* Observation Method
* Interview Method
* Questionnaires
* Projective Techniques
* Content Analysis
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39. 1. Primary Vs. Secondary
Secondary Data
That originate from secondary sources.
Data already available, collected and analyzed by someone else.
* Publications
* Books
* Journals
* Magazines and Newspapers
* Reports
* Collateral Materials
* PR Messages
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40. 2. Qualitative Vs. Quantitative
Qualitative Data: Psychological, perceptual, or
conceptual data that is not counted in numbers, rather
coded as ‘good or bad’, ‘interesting or boring’ etc.
Quantitative Data: Number based facts and figures.
Frequency of occurrence.
3. Personal Reporting
Data based on individual observation and reporting.
Can be qualitative as well as quantitative.
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Can be primary/secondary
Always primary

41. Sources of Data
1. Internal
Data developed or gathered, maintained, and preserved by the organization itself.
MIS is the best source for internal records.
MIS comprises of FOUR major components; Management Research Systems (MRS),
Internal Database Systems (IDS), Management Intelligence Systems (MIS), and
Analytical Information Systems (AIS).
Annual reports, collateral materials, press releases etc.
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Primary

42. 2. External
* Data generated from the published reports of various bureaus, and public surveys.
Example:
EDIFY International conducting a salt consumption behavior research study in Nepal,
and the same report findings to be used in other related future researches.
Use of CBS - Nepal reports for various research purposes.
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Secondary

43. Data Collection Methods
1. Literature Reviews
* A secondary method of data collection.
* Facts gathered in the basis of reviews of various publications, articles, journals,
books, collateral materials, reports, etc.
* Useful in providing the evidence to the results of the primary observation.
* Mostly used in understanding the theoretical phenomenon.
* Very essential in qualitative studies.
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44. 2. Census
* Census represents the study of universe.
* Mostly conducted by the governments in long periodical basis.
* Each and every component of the population is the subject of the study.
* Most costly approach of data collection.
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45. 3. Survey
* An alternative to census.
* Sample based study; study/observation through population representation.
* Mostly used by the researchers.
* A primary method of data collection.
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46. 4. Focus Group Observation
* A approach of group observation.
* A source for primary data collection.
* Useful in perceptual studies.
* The groups may comprise of 6 to 10 people.
* The issues are discussed by cross questioning and sharing their views.
* Suitable in case of new product launch and testing.
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Can be direct or
indirect, structured
or unstructured

47. 5. Experiments
* A primary method of data collection.
* Can be field or lab experiment based.
* Mostly conducted by using the control groups.
* Most useful in new product testing.
* May be very costly incase of wrong selection of control groups.
* Sometimes conducted by the help of various physical tests; eye movements, pupil
movements, skin stimuli etc.
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48. 6. Interviews
* A popular method of primary data collection.
* Data collected in the basis of personal interaction with the respondents.
* Can be well-structured or less-structured.
* Useful when small size of observation is enough for data collection.
* The individuals/subjects are the source of study.
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49. Date Reduction and Analysis
Data Reduction Process
Step I: Establishing field controls
Step II: Editing of data
Step III: Coding the data
Step IV: Transcribing
Step V: Creating new variables
Step VI: Calculating and
summarizing statistics
Data Analysis
Descriptive analysis
Bivariate analysis
Multivariate analysis
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50. Presentation of a Report
I. Prefatory Part
Title Page
Signatory Page
Copy Rights
Acknowledgements
Executive Summary
List of Abbreviations
List of Tables and Graphs
Table of Contents
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II. Main Body
Introduction
Review of Literature
Research Methodology
Data Reduction,
Presentation, and Analysis
Summary of Key Findings
Recommendations and
Conclusions
III. Supplementary Part
Bibliography
Annextures
Appendixes

52. Ethical Issues Related to Research Function
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Nature and Content of Ethical Issues
Participant Treatment
Issues
* Purpose shouldn't be
to sell merchandise
* Anonymity must be
protected
----------------------------
Ultraviolet ink
Hidden tape recorders
One-way mirrors
Fake long distance calls
Fake research firm
Right to safety
Right to be informed
Right to privacy
Right to choice
Client Treatment
Issues
* Methods used and
results should be
accurately reported
----------------------------
Confidentiality
Unqualified researcher
Proprietary information
Unnecessary research
Researcher Treatment
Issues
* Should not disseminate
conclusions that are
inconsistent with data
* Should not solicit
designs and deliver to
another for execution
----------------------------
Excessive requests
Reneging on promises
Availability of funds

53. Should Research be
Conducted?
 Relevance of the subject matter
 Nature of the decision
 Availability of existing information
 Time constraints
 Availability of data
 Costs vs. benefits
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