Brm unit 3-dr. shriram dawkhar

BRM :Unit-3: Data & Measurement
( As per revised MBA SPPU Syllabus- 2019)
Dr. Shriram S. Dawkhar
M. Sc.(B.I.), MBA(Mktg.), M. Com. (Bus. Admin),
Ph. D., FDPM (IIM Ahmadabad)
Associate Professor- Sinhgad Institute of
Management, (SIOM) Vadgaon, Pune.
ssdawkhar@gmail.com
@ Shriram Dawkhar, April-2021 1

Unit-3 : Data & Measurement ( Syllabus)
• Meaning of data, Need for data. Secondary Data: Definition,
Sources, Characteristics, Advantages and disadvantages over
primary data, Quality of secondary data - Sufficiency, adequacy,
reliability and consistency. Primary Data: Definition, Advantages
and disadvantages over secondary data.
• Measurement: Concept of measurement, What is measured?
Problems in measurement in management research - Validity and
Reliability, Levels of measurement - Nominal, Ordinal, Interval,
Ratio.
• Attitude Scaling Techniques: Concept of Scale – Rating Scales viz.
Likert Scales, Semantic Differential Scales, Constant Sum Scales,
Graphic Rating Scales – Ranking Scales – Paired Comparison &
Forced Ranking - Concept and Application.
• Questionnaire: Questionnaire Construction - Personal Interviews,
Telephonic survey Interviewing, Online questionnaire tools
Dr. Shriram S. Dawkhar, SIOM.
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• Data can be viewed as collection of facts (number,
words, measurement, observation, etc)
• Data means raw facts and figures (plural of Datum)
• Data comprise of building blocks of information.
• Data is represented in the form of alphabets,
numbers, pictures etc.
What is Data?
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• Data is a set of values of subjects with respect
to qualitative or quantitative variables.
• Data is raw, unorganized facts that need to be
processed. Data can be something simple and
seemingly random and useless until it is
organized.
• When data is processed, organized, structured
or presented in a given context so as to make
it useful, it is called information.
What is Data?
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Secondary Data
Dr. Shriram Dawkhar
Dr. Shriram S. Dawkhar, SIOM. 6

• Provides information & knowledge
• Helpful in analysis & interpreting the results
• It makes the research accurate
• More reliable in work of research
• Convenient method of getting information
• For making reports
• Findings & conclusion of research
• Decision making person
Need of Data Collection
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Secondary Data
• The data collected by other than researcher is
known as secondary data.
• It is the data, which has been previously gathered
by someone other than researcher and /or for
some purpose other than the research project at
hand.
• Based on its source, secondary data may be
classified as Internal and external Secondary data.
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Features / Characteristics of
secondary data
• 1) Recorded / Published Data
• 2) Easy to collect
• 3) Compressive
• 4) Availability
• 5)Less Time consuming
• 6) Less Expensive / Economical
• 7)Can be used without processing
• 8) Not original in character
• 9) Relates to past
• 10) Collected from secondary sources
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Sources of Secondary Data
There are two key sources of secondary data:
The Company Itself
(Internal Databases)
Other Organizations or
Persons
(External Databases)
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Internal sources of secondary data
• Internal sources of secondary information (Internal
secondary data) refer to reports generated by various
departments during the ordinary course of business.
• These reports are submit to the higher authorities by the
executives.
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• The purpose of these reports definitely is
that of keeping records , or keeping track
of operation, or for operation
management such as inventory
management, stores management,
production management etc, but these
reports are useful as secondary data.
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• A) Accounts department:
• The internal data generated by this department may comprise of
• Procedures manual,
• Management accounts,
• Cost sheets ,
• balance sheets ,
• financial data,
• Accounting polices,
• Tax details,
• Working Capital,
• audit report, etc.
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• B) Sales and marketing Department :
• The internal data generated by this department may comprise of-
• Sales report by region,
• Sales by customer,
• Sales by producer,
• Competitor intelligence,
• Market prospects and reports,
• Customer complaints,
• Marketing research reports,
• Brand Strategy and values ,
• Distribution chains.
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• C) Production and operation :
• Operations data
• Stock statements,
• inventory control reports,
• Efficiency and capacity details,
• Process flow charts,
• Detailed product costing ,
• Input prices,
• Supply chain members and reports pertaining to them.
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• D)Human Resources:
• attendance reports,
• salary statements,
• provident fund statements,
• performance appraisal reports,
• requirement details of employees,
• Number of employees,
• Recruitment procedures,
• Training programs,
• Staff turnover details,
• Details of pay, hr inventory etc.
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External sources of secondary data
• Paper-based sources –
• books,
• journals,
• periodicals,
• abstracts,
• indexes,
• directories,
• research reports,
• conference papers,
• market reports,
• annual reports,
• internal records of other organizations,
• newspapers and magazines
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• Electronic sources–
• CD-ROMs,
• on-line databases,
• Internet,
• videos and
• broadcasts
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• Reports ,balance sheets, published by Government ministries
and agencies :
• Government agencies are the good source of economic and other
statistical information.
• Most countries have an agency that provides national statistics.
• This varies significantly from country to country in terms of what is
produced and the format, but you should be able to find
• Economic data
• Social data census
• Market data
• Regulatory bodies and industry association
• Internet sources
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• Unofficial or general business sources
• trade associations
• trade and other journals
• private research publishers
• stock broking firms
• large company market reports
• local authorities
• professional bodies
• academic institutions.
• International sources
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Using secondary information
• Secondary information is used in many business situations and
not just in academic research .
• Secondary information
• 1) Can provide a backdrop to primary information
• 2) Can act as substitute for field research
• 3)Can be used as a technique in itself
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Uses of secondary data
• Secondary data may actually provide enough
information to resolve the problem being
investigated.
• Secondary data can be a valuable source of new ideas
that can be explored later through primary research.
• Secondary data is of use in collecting primary data.
• Secondary data also helps to define the population,
select the sample in primary information collection,
and define the parameters of primary research.
• Secondary data can also serve as a reference base
against which to compare the validity or accuracy of
primary data.
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Advantages of Secondary data
• It is economical. It saves efforts and expenses.
• It is time saving.
• It helps to make primary data collection more specific since
with the help of secondary data, we are able to make out what
are the gaps and deficiencies and what additional information
needs to be collected.
• It helps to improve the understanding of the problem.
• It provides a basis for comparison for the data that is collected
by the researcher.
• Some information can be obtained only through secondary data
• Longitudinal studies may be possible.
• Sometime more accurate than primary data
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Limitations of Secondary Data
• Fit & Relevancy : Collected for some other purpose
• No control over data collection
• May not be very accurate
• May be outdated
• May not meet data requirements
• Assumptions have to be made
• Availability
• Bias
• Statistical accuracy
• Sufficiency
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Golden Rule
• THE GOLDEN RULE USING THE
SECONDARY DATA IS “ USE ONLY
MEANINGFUL INFORMATION ”
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Issues Related to Secondary Data:
1) Sufficiency
• Sufficient data should be available. i.e. as per requirement
& should not be insufficient.
• Sufficiency is an adequate amount of something,
especially of something essential.
• Secondary data many times is not Sufficient. Since it is
collected by other person / researcher for some other
purpose.
• For using secondary data researcher must check
sufficiency of data in order to do successful research.
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2) Adequacy
• Adequate data should be available.
• Adequacy is the state of being sufficient for the
purpose concerned.
• The data will also be considered inadequate, if they are
related to an area which may be either narrower or wider
than the area of the present enquiry.
• Since secondary data is collected by other purpose it may
not be adequate.
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3)Reliability
• The researcher must check reliability of the data by asking
following questions.
• Who collected the data ?
• What were the sources of data ?
• Were they collected by using proper method ?
• At what time were they collected ?
• Was there any bias of the complier ?
• What level of accuracy was desired & Was it achieved?
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4)Consistency
• As Secondary data may not in the same format / size
sometimes it may not be consistent.
• So before using secondary data consistency must be checked.
• Uniformity to be checked.
• Consistency is the quality or fact of staying the same at
different times.
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Primary Data
Dr. Shriram Dawkhar
Dr. Shriram S. Dawkhar, SIOM. 31

Concept…
• Primary data is one, which is collected by the investigator
himself for the purpose of a specific inquiry or study.
• Such data is original in character
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Common types of primary data
• Demographic and socioeconomic characteristics
• Psychological and lifestyle characteristics
• Attitudes and opinions
• Awareness and knowledge
• Intentions
• Motivation Behavior
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Types of Primary Data
• Demographic/Socioeconomic
• Age, Sex, Income, Marital Status, Occupation
• Psychological/Lifestyle
• Activities, Interests, Personality Traits
• Attitudes/Opinions
• Preferences, Views, Feelings, inclinations
• Awareness/Knowledge
• Facts about product, features, price, uses
• Intentions
• Planned or Anticipated Behavior
• Motivations
• Why People Buy (Needs, Wants, Wishes)
• Behavior
• Purchase, Use, Timing, Traffic Flow
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METHODS OF COLLECTING
PRIMARY DATA
▪ Observation
▪ Interview
▪ Questionnaire
▪ Schedule
Other methods include:
• Warranty cards
• Distributor audits
• Pantry audits
• Consumer panels
• Using mechanical
devices
• Projective techniques
• Depth interviews and
• Content analysis
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Advantages of primary data over
secondary data
• The primary data are original and relevant to the topic of
the research study so the degree of accuracy is very high.
Whereas secondary data are borrowed from other and may
be less or partially relevant to the problem under study.
• Primary data is that it can be collected from a number of
ways like interviews, telephone surveys, focus groups etc It
can be also collected across the national borders through
emails and posts. where as secondary data is already collected
and you have to retrieve or borrow from others.
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secondary data
• Moreover, primary data is current and it can better give
a realistic view to the researcher about the topic under
consideration where as secondary data is past / old.
• Reliability of primary data is very high because these
are collected by the concerned and reliable party where as
secondary data is less reliable.
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secondary data (Control)
• One of the main advantages of collecting primary
data is the amount of control the researchers have.
• This allows them to determine the type of method
they will use in collecting the data and how long it
will take them to get the data, thus enabling them to
focus on specific aspects of their research where as
secondary data has no any control.
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secondary data (Focus on issue in hand)
• The other main advantage is the fact that a primary data
collection focuses on the specific issues, unlike secondary
data which may contain details that are not needed by the
researcher.
• This means that the researchers will only set out to find
more information about specific issues that matters to the;
what’s more they have different methodologies to use,
ranging from focus groups to email.
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secondary data
• The best thing about using primary collection
methods is the researchers will be presented with
original and unbiased data.
• Unlike the secondary collection methods, the
researchers will directly interact with the source of
information and get the data that is original and not
analyzed to suit specific premises.
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Disadvantages over secondary data
Time & Efforts:
For primary data collection more time and efforts are required where as
since secondary data is already available less time and efforts are
required.
Expensive : Primary data is more expensive than secondary
data because you have to collect by yourself.
Not immediately available : unlike secondary data primary
data takes time to define problem, sampling frame, method
and analysis.
Not as readily accessible : Secondary data is readily
accessible than primary data
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Measurement
Dr. Shriram Dawkhar
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Measurement
Measurement means assigning numbers or other
symbols to characteristics of objects according to
certain pre specified rules.
• One-to-one correspondence between the numbers and the
characteristics being measured.
• The rules for assigning numbers should be standardized and applied
uniformly.
• Rules must not change over objects or time.
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• Measurement in research consists of assigning numbers to
empirical events, objects or properties, or activities in
compliance with a set of rules.
• This definition implies that measurement is a three-part process:
• Selecting observable empirical events.
• Developing a set of mapping rules where a scheme for
assigning numbers or symbols to represent aspects of the
event being measured and
• Applying the mapping rule(s) to each observation of that event
Measurement
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Measurement
To collect data, you need to have something to measure
Measurement is the process of
assigning numbers or scores to
characteristics or attributes of the
objects or people of interest
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Measurements Will Vary Over Time
“The only man who behaved sensibly was
my tailor; he took my measurement a new
every time he saw me, while all the rest
went on with their old measurements and
expected them to fit me.”
George Bernard Shaw
playwright and essayist
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• 1)Steven (1951) defines measurement as 'the assignment of
numerals to objects or events according to rules.’
• 2) Campbell (1952) defines measurement as 'the assignment
of numbers to objects to represent properties.’
• 3) Torgerson (1959) has defined measurement as 'the
assignment of numbers to objects to represent amounts or
degrees of a property possessed by all of the objects.'
Measurement ( Definitions)
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RESEARCHERS ENGAGE IN USING THE MEASUREMENT
PROCESS
BY
ASSIGNING
EITHER NUMBERS
OR LABELS
TO
PEOPLE’S THOUGHTS,
FEELINGS,
BEHAVIORS,
AND CHARACTERISTICS
THE FEATURES OR ATTRIBUTES OF OBJECTS
THE ASPECTS OF CONCEPTS / IDEAS
Measurement
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What Is Measured
• Variables being studied in research may be classified as objects or as
properties.
• Objects include :
• the concepts of ordinary experience, such as tangible items like
furniture,
• laundry detergent,
• people, or automobiles.
• Objects also include things that are not as concrete, such as
genes,
• attitudes, and
• peer-group pressures.
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What Is Measured
• Properties are the characteristics of the object.
• A person’s physical properties may be stated in terms
of weight, height, and posture among others.
• Psychological properties include attitudes and
intelligence.
• Social properties include leadership ability, class affiliation,
and status.
• These and many other properties of an individual can
be measured in a research study.
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What Is Measured
• In a literal sense, researchers do not measure objects or
properties—they measure indicants of the properties
or objects.
• It is easy to observe that A is taller than B and that C
participates more than D in a group process.
• Or, suppose you are analyzing members of a sales
force to learn what personal properties contribute to
sales success.
• The properties are age, years of experience, and
number of calls made per week.
• The indicants in these cases are so accepted that one
considers the properties to be observed directly.
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• In contrast, it is not easy to measure properties of
constructs like “lifestyles,” “opinion leadership,”
“distribution channel structure,” and
“persuasiveness.”
• Since each property cannot be measured directly,
one must infer its presence or absence by observing
some indicant or pointer measurement.
What Is Measured
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Sources of error/errors in measurement
• Measurement should be precise and unambiguous in
an ideal research study.
• However many times this objectives does not meet
due to some errors in measurement.
• The researcher must aware about the sources of
errors in the measurement.
• Some possible sources of error are mentioned above.
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Sources of
error/errors in
measurement
1) Respondent
Associated
errors
4) Measurer as a
source of errors
3) Situational
errors
2) Instrument
Associated errors
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A) Respondent Associated errors:
• A majority of research studies relay on eliciting information
from respondents.
• If the researcher is able to obtain the cooperation of the
respondents and elicit truthful responses from them, the
survey can easily achieve its targets.
• However when there are two types of error arise then the
researcher will not obtain the information as stated above.
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Respondent
Associated Errors
Non Response
Error
Response Bias
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• 1) Non-response errors:
• Arise when the survey does not include one or
more pieces of information from the unit that has
to be the part of the study.
• Non response errors include failure to respond
completely or failure to respond to one or more
question of the surveyor.
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• 1) Non-response errors:
• The reason for non responding to some questions
may be
• a) Lack of knowledge. Or
b) The respondent don’t want to answer
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• 2) Response bias:
• When the respondents consciously or unconsciously
misrepresent the truth then it amounts to response
bias.
• Sometimes respondents deliberately mislead
researcher by giving false answer so as not to reveal
their ignorance or to avoid embarrassment and so on.
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Errors in measurement
B) Instrument Associated errors
• Error may arise because of the defective measuring
instrument.
• Instrument errors occur due to
• 1) Poor questionnaire design
• 2) Improper selection of samples
• 3) Use of complex words
• 4) Ambiguous meaning
• 5) Poor printing
• 6) Inadequate space to reply.
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C) Situational errors
• The respondent may not provide proper response if
the third person is present during the interview or
sometimes third person might himself participate in
the interview process without any invitation leading to
inappropriate response.
• Location of the interview – public place or home.
• If researcher is not able to convey that the response
data will be confidential.
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D) Measurer as a source of errors
• Measurer errors due to:
• 1) the interviewer can distort responses by rewording or
reordering the questions.
• 2) his behaviour, style, and looks may encourage or discourage
certain replies from respondents.
• 3) Careless nature
• 4) inappropriate/ wrong recording of responses.
• 5) inappropriate coding and tabulation & data analysis error
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Evaluating Measurement Tools
Criteria
Validity
Practicality Reliability
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Tests of sound measurement
• Sound measurement must meet the
• Tests of validity : Refers to the fact that the instrument
is able to measure what it is designed for.
• Reliability : Means every time the instrument is used it
should give the same result
• Practicality : Means that the instrument is very easy &
practical to use.
• These are three major considerations one
should use in evaluating a measurement tool.
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1) Test of Validity
• Validity refers to the extent to which a test measures what we
actually wish to measure.
• Validity is the most critical criterion and indicates the degree
to which an instrument measures what it is supposed to
measure.
• Validity can also be thought of as utility.
• In other words validity is the extent to which differences
found with a measuring instrument reflect true differences
among those being tested.
• Validity is the degree to which the researcher actually
measures what he or she is trying to measure.
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Validity Determinants
Content
Construct
Criterion
There are three major forms of validity: content, construct,
and criterion
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Types / forms of validity: 1) Content
• Content validity refers to the extent to which
measurement scales provide adequate coverage of
the investigative questions.
• If the instrument contains a representative sample of the
universe of subject matter of interest, then content validity is
good.
• To evaluate content validity, one must first agree on what
elements constitute adequate coverage.
• To determine content validity, one may use one’s own
judgment and the judgment of a panel of experts.
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Content Validity / Measuring Customer
loyalty as a construct
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e.g. -2) Customer satisfaction for website
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Increasing Content Validity
Content
Literature
Search
Expert
Interviews
Group
Interviews
Question
Database
Etc.
Types / forms of validity: 1) Content

• Criterion-related validity reflects the success of measures
used for prediction or estimation.
• There are two types of criterion-related validity: concurrent and
predictive.
• These differ only on the time perspective.
• An attitude scale that correctly forecasts the outcome of a
purchase decision has predictive validity.
• An observational method that correctly categorizes families by
current income class has concurrent validity.
Types / forms of validity: 2) Criterion
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Types / forms of validity: 3)Construct validity
• Construct validity refers to the validity of inferences that
measurement tools actually represent or measure the
construct being investigated.
• In lay terms, construct validity examines the question:
• Does the measure behave like the theory says a measure
of that construct should behave?
• Constructs are abstractions that are deliberately created by
researchers in order to conceptualize the latent variable ,
which is the cause of scores on a given measure (although
it is not directly observable).
• Construct validity is essential to the perceived overall
validity of the test.
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• Construct validity is a measurement scale that demonstrates
both convergent validity and discriminant validity.
• In attempting to evaluate construct validity, one considers both the
theory and measurement instrument being used.
• For instance, suppose we wanted to measure the effect of trust in
relationship marketing. We would begin by correlating results
obtained from our measure with those obtained from an
established measure of trust.
• To the extent that the results were correlated, we would have
indications of convergent validity.
• We could then correlate our results with the results of known
measures of similar, but different measures such as empathy and
reciprocity.
• To the extent that the results are not correlated, we can say we
have shown discriminant validity
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• A test has construct validity if it demonstrates an association
between the test scores and the prediction of a theoretical
trait.
• Intelligence tests are one example of measurement
instruments that should have construct validity.
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Summary of Validity Estimates
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Reliability
• A measure is reliable to the degree that it
supplies consistent results.
• Reliability is a necessary contributor to validity but is not a
sufficient condition for validity.
• It is concerned with estimates of the degree to which a
measurement is free of random or unstable error.
• Reliable instruments are robust and work well at different times
under different conditions. This distinction of time and condition
is the basis for three perspectives on reliability – stability,
equivalence, and internal consistency.
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Reliability Estimates
Stability
Internal
Consistency
Equivalence

Reliability
• 1) Stability: A measure is said to possess stability if you can secure
consistent results with repeated measurements of the same person
with the same instrument.
• 2) Equivalence :A second perspective on reliability considers how
much error may be introduced by different investigators (in
observation) or different samples of items being studied (in
questioning or scales). Thus, while stability is concerned with personal
and situational fluctuations from one time to another, equivalence is
concerned with variations at one point in time among observers and
samples of items.
• 3) Internal consistency : A third approach to reliability uses only one
administration of an instrument or test to assess the internal
consistency or homogeneity among the items. The split-half technique
& Cronbach’s Alpha can be used when the measuring tool has many
similar questions or statements to which the participant can respond.
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Practicality
Economy Interpretability
Convenience

• Levels of measurement, also called scales
of measurement, tell you how precisely
variables are recorded.
• In scientific research, a variable is anything
that can take on different values across your
data set (e.g., height or test scores)
Levels of Measurement
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Primary Scales/ Levels of Measurement
7 11 3
Scale
Nominal Numbers
Assigned to
Runners
Ordinal Rank Order of
Winners
Third
Place
Second
Place
First
Place
Interval Performance
Rating on a 0 to
10 Scale
8.2 9.1 9.6
Ratio Time to Finish in
Seconds 152 141 134
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Levels of Measurement : 1) Nominal Scale
• The numbers serve only as labels or tags for identifying and
classifying objects.
• When used for identification, there is a strict one-to-one
correspondence between the numbers and the objects.
• The numbers do not reflect the amount of the characteristic
possessed by the objects.
• The only permissible operation on the numbers in a nominal
scale is counting.
• Only a limited number of statistics, all of which are based on
frequency counts, are permissible, e.g., percentages, and mode.
86

Q.1) Sex : answer ---male / Female
Q.2) Marital status
Q.3) Job Type: Executive, Technical, Clerical
Nominal scale- Examples
Coded as “1” Coded as “2”
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➢classifies nominal data
according to some order or rank
E.g. names ordered alphabetically
➢With ordinal data, it is fair to
say that one response is greater or
less than another.
➢E.g. if people were asked to rate
the hotness of 3 chili peppers, a
scale of "hot", "hotter" and
"hottest" could be used. Values of
"1" for "hot", "2" for "hotter"
and "3" for "hottest" could be
assigned.
➢The gap between the
items is unspecified.
Levels of Measurement : 2) Ordinal Scale
Ordinal scales permit the use of
statistics based on centiles, e.g.,
percentile, quartile, median.
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ORDINAL SCALE
PLEASE RANK THE SOFT DRINKS ON THE FOLLOWING LIST
ACCORDING TO YOUR DEGREE OF LIKING FOR EACH,
ASSIGNINIG MOST PREFERRED DRINK RANK=1 AND YOUR
LEAST PREFERRED DRINK RANK=6
❑COKE
❑THUMS UP
❑MOUNTAIN DEW
❑PEPSI
❑SEVEN UP
❑SPRTIE
Levels of Measurement : 2) Ordinal Scale
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➢assumes that the measurements are made in
equal units.
➢i.e. gaps between whole numbers on the scale are
equal.
➢e.g. Fahrenheit and Celsius temperature scales
➢an interval scale does not have to have a true zero.
e.g. A temperature of "zero" does not mean that
there is no temperature...it is just an arbitrary zero
point.
➢Permissible statistics: count/frequencies, mode,
median, mean, standard deviation
Levels of Measurement : 3) Interval Scale
90

PLEASE RATE EACH BRAND IN TERMS OF ITS
OVERALL PERFORMANCE
BRAND RATING (CIRCLE ONE)
VERY POOR VERY GOOD
MONT BLANC 1 2 3 4 5 6 7 8 9 10
PARKER 1 2 3 4 5 6 7 8 9 10
LUXOR 1 2 3 4 5 6 7 8 9 10
Levels of Measurement : 3) Interval Scale
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• Possesses all the properties of the nominal, ordinal, and
interval scales.
• It has an absolute zero point.
• It is meaningful to compute ratios of scale values.
• All statistical techniques can be applied to ratio data.
Levels of Measurement : 4) Ratio Scale
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0
1
2
3
4
5
6
7
➢height, weight, age,
➢Length
➢time
➢Income
➢Market share
1.What is your height.
_______ feet
2. How far is your workplace
from home? _____ Km
Levels of Measurement : 4) Ratio Scale examples
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APPROXIMATELY HOW MANY TIMES IN THE
LAST MONTH HAVE YOU PURCHASED ANY
THING OVER Rs.1000 IN VALUE AT NANZ
STORE?
0 1 2 3 4 5 MORE ( SPECIFY_ )
Levels of Measurement : 4) Ratio Scale examples
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Comparison of Measurement Scales
Label Order Distance Origin
Nominal scale Yes No No No
Ordinal scale Yes Yes No No
Interval scale Yes Yes Yes No
Ratio scale Yes Yes Yes Yes
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Comparison of Measurement Scales
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Attitude Scaling
Techniques
Dr. Shriram Dawkhar
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CONCEPT OF SCALE
• The word scale or scaling is generally used for
measuring something.
• It is in fact a device through which we measure
various things.
• It is easy to apply scales in the field of physical
science for measurement of physical
phenomena.
• For example, for measuring the fluctuations of
the weather, we use barometer. Thermometer is
used for measurement of heat.
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• Scaling is the branch of measurement that
involves the construction of an instrument
that associates qualitative constructs with
quantitative metric units.
• Scaling evolved out of efforts in
psychology and education to measure
"unmeasurable" constructs like
authoritarianism and self esteem.
CONCEPT OF SCALE
100

• In many ways, scaling remains one of
the most arcane and misunderstood
aspects of social research
measurement.
• And, it attempts to do one of the most
difficult of research tasks -- measure
abstract concepts
CONCEPT OF SCALE
101

• Attitudes defined:
➢Expressions of inner feelings that reflect whether a
person is favorably or unfavorably predisposed to some
object --- a brand, a brand name, a service, a service
provider, a retail store, a company, an
advertisement, in essence, any marketing stimuli.
➢Opinions :
➢A large amount of questions in marketing research are
designed to measure attitudes
➢Marketing managers want to understand consumers’
attitudes in order to influence their behavior
Attitudes Scaling
102

IMPORTANCE OF THE STUDY OF
ATTITUDE
• IMPORTANCE OF THE STUDY OF ATTITUDE
• Study of Attitude helps in formulation of business
ideas:
• Knowledge of Attitude facilitates market surveys
• It helps in business forecasting:
• It helps in maintaining economic order
103

MEASUREMENT OF ATTITUDES
• The nature and characteristics of attitudes reveal that it is
rather difficult to measure.
• For instance, the emotions and feelings involved in attitudes
cannot be measured.
• Thus attitudes can be measured only indirectly by
approximately applying guess-work about them.
• Attitudes being internal systems, do not possibly admit of
any measurement, but because the individual's external
behaviour is produced by inner tendencies and so attitudes
can be measured from external behaviour.
104

➢Measuring Attitude is a frequent undertaking in business
research
➢Attitude may be defined as an enduring disposition to
consistently respond in a given manner to various aspects
➢Attitude has three dimensions:
Affective
Component
Cognitive
Component
Behavioural
Component
Three Components of Attitudes
105

The ABCs of attitudes:
➢ The Affective Component (based on feelings or
overall evaluation) Feelings of like or dislike
➢The Behavioral Component (likely action toward
object; e.g. from a consumer behavior point of view,
the consumer’s intention to buy a product) Intentions
to behave
➢The Cognitive Component (based on beliefs; what
you think about a marketing stimulus) – Information
possessed.
Three Components of Attitudes
106

Rating Scale & Ranking Scale
Scales
Rating Scales
Likert Scale
Semantic
Differential Scale
Ranking Scale
Forced Ranking
Graphic Rating
Scale
Paired
Comparisons
107

Rating Scale & Ranking Scale
• A rating scale is used when participants score an
object or indicant without making a direct
comparison to another object or attitude.
• Ranking scales constrain the study participant
to making comparisons and determining order
among two or more properties (or their indicants) or
objects.
108

Definitions of Rating Scale & Ranking
Scale
• A rating scale is a measuring instrument that
requires the person doing the rating to assign the
person or object being rated to the point along the
continuum or in one of the ordered set of
categories.
• Ranking Scale : A respondent directly compare
two or more objects and makes choice among
them.
109

Rating Scale : Example
• To evaluate any overall performance (a speaker, a worker, a
seminar, a laptop):
• 1 = Poor
2 = Fair
3 = Good
4 = Very Good
5 = Excellent
• When deciding which of several factors should be included in a
major decision, rate each factor as: (e.g.: Time)
• 1 = Unimportant
2 = Slightly important
3 = Important
4 = Very important
5 = Critical
110

Likert scale
• The Likert scale was developed by Rensis Likert and is the
most frequently used variation of the summated rating scale.
• Summated rating scales consist of statements that
express either a favorable or unfavorable attitude
toward the object of interest.
• The participant is asked to agree or disagree with
each statement.
• Each response is given a numerical score to reflect its
degree of attitudinal favorableness and the scores
may be summed to measure the participant’s overall
attitude.
• Likert-like scales may use 3/5/ 7 or 9 scale points.
111

6.
5.
4.
3.
2.
1.
________
________
________
________
________
The auction site support
system is confusing
________
________
________
________
________
The auction site is not
careful with personal
information
________
________
________
________
________
The auction site responds
to complaints quickly
________
________
________
Agree
________
________
________
Strongly
Agree
________
________
________
The auction site
commission
is reasonable
________
________
________
User registration
is complex at this site
________
________
________
The online auction site
contains an abundance of
exhibits
Neither
Agree
nor
Disagree
Disagree
Strongly
Disagree
Likert Scale Items
112

Likert scale
Source : Thesis ( Ph. D.) of Dr. Shriram S. Dawkhar
113

114
Likert Scale
The Internet is superior to traditional libraries for
comprehensive searches.
❑ Strongly disagree
❑ Disagree
❑ Neither agree nor disagree
❑ Agree
❑ Strongly agree

Advantage: Likert scale
• The Likert scale have following advantage:
• i) It is easy and simple to construct
• ii) It is more reliable and provides more
information
• iii) It can easily be used in respondent
centered and stimulus centered studies.
• iv) It takes less time in construction
• V)This scale produces interval data.
115

Disadvantages: Likert scale
• Limitations: The Limitations of Likert Scale are as
follows:
• i) It does not give the intensity comparison of responses.
• ii) It is noticed often that the total score of a respondent
has little clear meaning since a given score can be scored
by a variety of answer patterns.
116

Semantic Differential Scales
• The semantic differential scale measures the psychological
meanings of an attitude object using bipolar adjectives.
• Researchers use this scale for studies of brand and
institutional image, employee morale, safety, financial
soundness, trust, etc.
• The method consists of a set of bipolar rating scales,
usually with 7 points, by which one or more participants rate
one or more concepts on each scale item.
117

• The semantic differential has several advantages.
• It is an efficient and easy way to secure attitudes from a large
sample.
• Attitudes may be measured in both direction and intensity.
• The total set of responses provides a comprehensive picture
of the meaning of an object and a measure of the person
doing the rating.
• It is a standardized technique that is easily repeated but
escapes many problems of response distortion found with
more direct methods.
• It produces interval data
Semantic Differential Scales
118

119
Semantic Differential Scales : Example

120

Adapting Semantic Differential Scales
Convenience of Reaching the Store from Your Location
Nearby ___: ___: ___: ___: ___: ___: ___: Distant
Short time required to reach
store
___: ___: ___: ___: ___: ___: ___: Long time required to reach store
Difficult drive ___: ___: ___: ___: ___: ___: ___: Easy Drive
Difficult to find parking place ___: ___: ___: ___: ___: ___: ___: Easy to find parking place
Convenient to other stores I
shop
___: ___: ___: ___: ___: ___: ___: Inconvenient to other stores I shop
121

The constant-sum scale
• The constant-sum scale helps researchers to discover
proportions.
• The participant allocates points to more than one attribute or
property indicant, such that they total a constant sum, usually
100 or 10.
• Participant precision and patience suffer when too many stimuli
are proportioned and summed.
• A participant’s ability to add may also be taxed.
• Its advantage is its compatibility with percent and the fact
that alternatives that are perceived to be equal can be so
scored.
• This scale produces interval data.
122

Constant-Sum Scales : Example
123

Instructions
Below are eight attributes of bathing soaps. Please allocate 100 points among the attributes so
that your allocation reflects the relative importance you attach to each attribute. The more
points an attribute receives, the more important the attribute is. If an attribute is not at all
important, assign it zero points. If an attribute is twice as important as some
other attribute, it should receive twice as many points.
Form
AVERAGE RESPONSES OF THREE SEGMENTS
Attribute Segment I Segment II Segment III
1. Mildness 8 2 4
2. Lather 2 4 17
3. Shrinkage 3 9 7
4. Price 53 17 9
5. Fragrance 9 0 19
6. Packaging 7 5 9
7. Moisturizing 5 3 20
8. Cleaning Power 13 60 15
Sum 100 100 100
Constant-Sum Scales : Example
124

Graphic rating scale
• The graphic rating scale was originally created to enable researchers to
distinguish fine differences.
• Theoretically, an infinite number of ratings is possible if participants
are sophisticated enough to differentiate and record them.
• They are instructed to mark their response at any point along a
continuum.
• Usually, the score is a measure of length from either endpoint.
• The results are treated as interval data.
• The difficulty is in coding and analysis.
• Graphic rating scales use pictures, icons, or other visuals to
communicate with the rater and represent a variety of data types.
• Graphic scales are often used with children.
125

Graphic rating scale : Example
126

The Wong-Baker faces pain scale is a common scale used to assess
patient discomfort.
127

128

Ranking Scales
• In ranking scales, the participant directly compares two or
more objects and makes choices among them.
• Frequently, the participant is asked to select one as the
“best” or the “most preferred.”
• When there are only two choices, this approach is
satisfactory, but it often results in ties when more than
two choices are found.
• Paired-comparison
• Forced ranking scale
129

Paired-comparison scale
• Using the paired-comparison scale, the participant can express
attitudes unambiguously by choosing between two objects.
• The number of judgments required in a paired comparison is
[(n)(n-1)/2], where n is the number of stimuli or objects to be
judged.
• Paired comparisons run the risk that participants will tire to the
point that they give ill-considered answers or refuse to continue.
• Paired comparisons provide ordinal data.
130

131
Paired-Comparison Scale

Paired-Comparison Scale
132

133

Paired Comparison Scaling: Example
Instructions
We are going to present you with ten pairs of shampoo brands. For each pair, please
indicate which one of the two brands of shampoo in the pair you would prefer for
personal use.
Recording Form
A 1 in a particular box means that the brand in that column was preferred over the
brand in the corresponding row. A 0 means that the row brand was preferred over the
column brand.
B The number of times a brand was preferred is obtained by summing the 1s in each
column.
Clinic-plus
Vatika
Nyle
Head & Shoulders
Patanjali
Number of times
preferred
Clinic-plus Vatika Nyle Head & Shoulders Patanjali
0
1
0
1
2
3 0 4
0
0
0
0
1
1
1
1
1
1
0
1
0
0
0
0
1
134

Forced Ranking Scale
• The forced ranking scale lists attributes that are ranked
relative to each other.
• This method is faster than paired comparisons and is usually
easier and more motivating to the participant.
• With five item, it takes ten paired comparisons to complete the task, but
the simple forced ranking of five is easier.
• A drawback of this scale is the limited number of stimuli
(usually no more than 7) that can be handed by the participant.
• This scale produces ordinal data.
135

136

137

Source: Thesis of Dr. Shriram S. Dawkhar
138

Questionnaire
Dr. Shriram Dawkhar
139

Data Collection
• Two basic methods of collection
• Ask them or Observe them
• Questioning & Observation
• Questioning: Less expensive, Quick, Versatile
• Observation: Expensive, Difficult to set up, Time
consuming
• Observation Data are more Valid & Reliable than
Questioning
140

Why a Questionnaire is needed?
• To standardize the process of data collection –
helps in analysis
• To achieve speed & accuracy in collection &
recording
• To achieve speed & accuracy in handling data
within & between offices for analyses
141

Situations suitable for Questioning
• Knowledge, opinion, motivation, intension
etc. are not open for observation
• Past events (like time & quantity of last
purchase) can be studied only by
questioning
142

Questionnaire Design Steps
143
1) Survey
Objectives
2) Data
Collection
Methods
3) Determine
Content
4) Types of
Question
5) Decide
Wording
6) Decide
Sequence
7) Pre-Code
& Obtain
Approval
8) Decide
Layout
9) Pre Test
10) Revise &
Implement

10 Steps of Questionnaire Construction
1. Specify objectives: List of needed information
2. Decide method of data collection
3. Determine content of individual questions
4. Determine type of questions to use
5. Decide wording of the questions
6. Decide question sequence
7. Pre-Code & Obtain approval
8. Decide layout
9. Pre Test: Pilot survey
10. Revise & Implement
144

Steps 1 & 2: Specify objectives &
Decide method of data Collection
• Specify survey objectives:
• Focused, Outcomes measurable & Within available resources
• Objectives will determine the list of needed information
• Must be comprehensive
• Methods of Data Collection:
Personal Interview, Mail, Phone, Internet
145

Step 3: Determine Contents of
Individual Questions
• Is the question necessary: Check with objective
• Does respondent have the information
• Is the Question asked within respondent’s
experience
• Can he remember: we may use aided recall
• Will the respondent give the info
• Are several questions needed to replace one
146

Step 4: Determine the type of Questions
147

1)Dichotomous /Alternate response types
148

Advantages & Disadvantage Dichotomous
questions
• Dichotomous questions: questions with only two
possible answers
• Advantages
• Easy to answer
• No interviewer bias
• Easy to tabulate & analyze
• Disadvantages
• Not all questions lend themselves to such a format
149

2) Multiple choice questions
150

• Multiple choice
• Advantages
• Eliminates interviewer bias
• Quick and easy to answer
• Easy to tabulate & analyze
• Disadvantages
• Introduces ordering bias
151
Advantages & Disadvantage: Multiple choice

3) Multiple Response Questions
152

4) Ranking Type
153

5) Rating Type
154

6) Open Ended
155

Advantages & Disadvantage: Open Questions
• Open Questions
• Advantages
• Good as first question
• Involves respondents
• Every one can answer
• Disadvantages
• Long answer
• Difficult to analyze: Brings too much variety
• Introduces Interviewer bias 156

Step 5: Decide wording
• Define the issue: Who, What, When, Why, Where &
How?
• Subjective versus objective
• Positive or negative
• Use simple words
• Avoid ambiguous words e.g., Which brand of toothpaste
do you use regularly?
• Questions about personal information need to be
buffered with an explanation
157

Step 6: Decide question sequence
• Opening questions must win respondent’s interest
• Easy to difficult
• Logical order
• No cross referencing
• Demographic questions
158

Step 7: Pre code & Obtain approval
• Each questionnaire must contain a code to help in
tracing up to the source.
• To facilitate data entry & analysis, assign codes to
each question & its possible answers
• Develop a systematic approach about analyses
• Analysis can be done even with cross referencing
(AND & OR concepts of Wenn Diagram) of
questions
159

Step 8: Decide layout
• Layout should be such that
• Secures acceptance
• Easy to control
• Easy to handle
• Font size used should be easy to read
• Easy to fill with minimum effort on respondents’ part
• Should not appear to be bulky
• Should withstand the wear & tear of handling by
multiple people
160

Steps 9 & 10: Pre test, Revise & Implement
• Pre-testing is a must
• Faults in wording, sequence, layout etc. can be identified &
eliminated
• Revise
• Implement
161

Interview Methods/ Types
Interview
1) Personal
interview 3) Computer assisted
personal interview
2) Telephone
interview
162

1) Personal interview
• This method requires a person known as the
interviewer asking questions generally in a face to
face contact to the other person or persons.
163

Methods of conducting an Personal Interview
• A personal interview involves a lot of preparation. Generally
an personal interview should go through the following
five/5 stages.
1) Rapport
Building
2) Introduction
3)Probing
4)Recording
5)Closing
164

Advantages of personal Interview
• Good cooperation from participants.
• Interviewer can answer questions about survey, probe for
answers, use follow-up questions, and gather information by
observation.
• Special visual aids and scoring devices can be used.
• Illiterate and functionally illiterate participants can be reached.
• Interviewer can prescreen participant to ensure he or she fits the
population profile.
• CAPI—computer-assisted personal interviewing: Responses can
be entered into a portable microcomputer to reduce error and
cost.
165

Disadvantages of Personal Interview
• High costs.
• Need for highly trained interviewers.
• Longer period needed in the field collecting data.
• May be less wide geographic dispersion.
• Follow-up is labor-intensive.
• Not all participants are available or accessible.
• Some participants are unwilling to talk to strangers in their
homes.
• Some neighborhoods are difficult to visit.
166

2) Telephone interview
• This method of collecting information consists in
contacting respondent on the telephone itself.
• It is not a very widely used method, but plays an
important part in industrial surveys, particularly in
developed regions.
167

Advantages of Telephonic Interview
• Lower costs than personal interview.
• Expanded geographic coverage without dramatic increase in
costs.
• Uses fewer, more highly skilled interviewers.
• Reduced interviewer bias.
• Fastest completion time.
• Better access to hard-to reach participants through repeated
callbacks.
• Can use computerized random dialing.
168

Disadvantages of Telephonic Interview
• Response rate is lower than for personal interview.
• Higher costs if interviewing geographically dispersed sample.
• Interview length must be limited.
• Many phone numbers are unlisted or not working, making
directory listings unreliable.
• Some target groups are not available by phone.
• Responses may be less complete.
• Illustrations cannot be used.
169

3) Computer-assisted personal interview
• Interviewer visits the respondents with a laptop/
computer/ tablet which has a entire questionnaire
loaded on it.
170

Conditions for successful interview
• A) Availability of information
with the respondent:
- First the respondent must have the information
which is sought by the interviewer.
- he may forgotten or repressed due to some
emotional stress.
171

• B) Cognition:
- Second the respondent should understand what is required
and expected from him.
- he should be in a position to decide what information he
should give, how much he should give and in what manner he
should give.
172

• C) Motivation:
- Finally the respondents should feel motivated to
answer question accurately.
- He should be cooperative right from begging to end
of the interview.
173

The interviewers task
• 1) Locating the Respondents.
• 2) Obtaining the interviews.
• 3) Asking the question
• 4) Recording the answers.
174

Web/Online survey
• Online (Internet) surveys are becoming an essential research
tool for a variety of research fields, including marketing,
social and official statistics research.
• According to ESOMAR online survey research accounted
for 20% of global data-collection expenditure in 2006, which
likely to grow in future. .
• They offer capabilities beyond those available for any other
type of self-administered questionnaire.
• Online consumer panels are also used extensively for
carrying out surveys but the quality is considered inferior
because the panelists are regular contributors and tend to be
fatigued.
175

Web/ Online Survey
176

Web/ Online Survey: Few examples
• Google Forms :
• SurveyMonkey:
• Freeonlinesurvey.com
• KwikSurveys
• http://www.surveypie.com/
• Survey Legend :
• Poll daddy:
• Survey Planet :
• Survey Nuts:
• Zoho Survey:
177

Google Forms
Surveys: Unlimited
Questions: Unlimited
Respondents: Unlimited
Custom design options: Yes
Data export options: Yes
178

Surveys: Unlimited
Questions: 10
Respondents: 100
Custom design
options: No
Data export options:
No
SurveyMonkey
179

180
SurveyMonkey :
https://www.surveymonkey.com/

181

182

http://freeonlinesurveys.com/
183

http://www.kwiksurveys.com
• About KwikSurveys
• KwikSurveys is a free to use online survey builder, which
has been specifically designed so that it is quick and easy
to use for people of all experience levels.
• No compromise on customer support? That is why we
offer you a chance to upgrade to premium support. Since
Kwik Surveys was founded in 2008 it has rapidly
expanded ever since to attract many international clients.
184

185

http://www.surveypie.com/intro
186

Advantages
• Web surveys are faster,
• simpler and cheaper.
• Short turnaround of results; results are tallied as participants
complete surveys.
• Ability to use visual stimuli.
• Ability to do numerous surveys over time.
• Ability to attract participants who wouldn’t participate in
another research project, including international participants.
• Participants feel anonymous.
• Shortened turnaround from questionnaire draft to execution of
survey.
187

188

Disadvantages : Web Survey
• Recruiting the right sample is costly and time-consuming; unlike phone
and mail sample frames, no lists exist and must be built.
---(Firms like Toluna and Survey Samples Inc. now provide samples built
from panels of Internet users who have indicated an interest in
participating in online surveys.)
• Converting surveys to the Web can be expensive. -----
---(Firms like Qualtric Labs with its SurveyPro software and Apian with
its Perseus software for wireless surveys and intranet surveys have made
the process of going from paper to Internet much easier.)
• It takes technical as well as research skill to field a Web survey.
---(Numerous fi rms now offer survey hosting services, e.g.,
SurveyMonkey.com.)
• While research is more compatible with numerous browsers, the
technology isn’t perfect.
-----(Some survey hosting services use initial survey screen questions that
identify the browser and system specifications and deliver the survey in
the format most compatible with the participant’s system.)
189

190

191

References
• 1) Business Research Methods, Donald Cooper & Pamela Schindler,
TMGH.
• 2. Business Research Methods, Alan Bryman & Emma Bell, Oxford
University Press
• 3) Research Methods: The Basics, Nicholas S. R. Walliman, Nicholas
Walliman, Routledge,
• 4) https://www.surveymonkey.com/
• 5) http://www.kwiksurveys.com
• 6) http://www.surveypie.com/intro
• 7) Primary vs Secondary Data: Difference between them with
definition and comparison chart – YouTube
192

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