Measurement and Scaling - Business Research.pdf
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Aug 27, 2025
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About This Presentation
In business research, measurement is the systematic process of observing and recording characteristics or attributes of objects, individuals, or events by assigning numbers or symbols according to established rules, while scaling involves creating a continuum upon which these measurements can be loc...
Slide Content
RECAP
Measurement and Scaling
•Measurement The process of describing some property of a phenomenon of interest,
usually by assigning numbers in a reliable and valid way.
•Operationalization:: The process of identifying scales that correspond to variance in
a concept to be involved in a research process.
•Scales : Itis a tool or mechanism by which individuals are distinguished as to how
they differ from one another on the variables of interest to our study.
usually by assigning numbers in a reliable and valid way.
•Operationalization:: The process of identifying scales that correspond to variance in
a concept to be involved in a research process.
•Scales : Itis a tool or mechanism by which individuals are distinguished as to how
they differ from one another on the variables of interest to our study.
Levels of Scale measurement
•Nominal scale
• Ordinal scale
• Interval scale
• Ratio scale
•Nominal scale
• Ordinal scale
• Interval scale
• Ratio scale
Nominal Scale
•Represent the most elementary level of
measurement in which values are assigned to
an object for identification or classification
purposes only.
•Nominal scaling is arbitrary.
•Example : with respect to the variable of
gender, respondents can be grouped into two
categories –male and female.
•These two groups can be assigned code
numbers 1 and 2.
•These numbers serve as simple and convenient
category labels with no intrinsic value, other
than to assign respondents to one of two
nonoverlapping, or mutually exclusive,
categories.
•Represent the most elementary level of
measurement in which values are assigned to
an object for identification or classification
purposes only.
•Nominal scaling is arbitrary.
•Example : with respect to the variable of
gender, respondents can be grouped into two
categories –male and female.
•These two groups can be assigned code
numbers 1 and 2.
•These numbers serve as simple and convenient
category labels with no intrinsic value, other
than to assign respondents to one of two
nonoverlapping, or mutually exclusive,
categories.
Ordinal Scale
•Ranking scales allowing things to be arranged based
on how much of some concept they possess.
•It is a ranking scale.
•Example: When class rank for high school students
is determined, we have used an ordinal scale.
•Participants often are asked to rank things based on
preference. So, preference is the concept, and the
ordinalscale lists the options from most to least
preferred, or vice versa.
•Five objects can be ranked from 1–5 (least preferred
to most preferred) or 1–5 (most preferred to least
preferred) with no loss of meaning.
•Ranking scales allowing things to be arranged based
on how much of some concept they possess.
•It is a ranking scale.
•Example: When class rank for high school students
is determined, we have used an ordinal scale.
•Participants often are asked to rank things based on
preference. So, preference is the concept, and the
ordinalscale lists the options from most to least
preferred, or vice versa.
•Five objects can be ranked from 1–5 (least preferred
to most preferred) or 1–5 (most preferred to least
preferred) with no loss of meaning.
Interval Scale
•Scales that have both nominal and ordinal properties,
but that also capture information about differences in
quantities of a concept from one observation to the
next.
•Asales manager know that a particularsalesperson
outperformed a colleague, information that would be
available with an ordinal measure, but the manager
would know by how much.
•Thisscaleallowsustoperformcertainarithmetical
operationsonthedatacollectedfromtherespondents.
•Scales that have both nominal and ordinal properties,
but that also capture information about differences in
quantities of a concept from one observation to the
next.
•Asales manager know that a particularsalesperson
outperformed a colleague, information that would be
available with an ordinal measure, but the manager
would know by how much.
•Thisscaleallowsustoperformcertainarithmetical
operationsonthedatacollectedfromtherespondents.
Ratio Scale
Representthehighestformof
measurementinthattheyhaveallthe
propertiesofintervalscaleswiththe
additionalattributeofrepresenting
absolutequantities;characterizedbya
meaningfulabsolutezero.
Representthehighestformof
measurementinthattheyhaveallthe
propertiesofintervalscaleswiththe
additionalattributeofrepresenting
absolutequantities;characterizedbya
meaningfulabsolutezero.
FOUR LEVELS OF DATA MEASUREMENT
Techniques for Measuring Attitudes
•Ranking: A measurement task that requires respondents to rank order a small number
of stores, brands, or objects on the basis of overall preference or some characteristic
of the stimulus.
•Ranking scales are used to tap preferences between two or among more objects or
items
•Rating: A measurement task that requires respondents to estimate the magnitude of a
characteristic or quality that a brand, store, or object possesses.
•Ranking: A measurement task that requires respondents to rank order a small number
of stores, brands, or objects on the basis of overall preference or some characteristic
of the stimulus.
•Ranking scales are used to tap preferences between two or among more objects or
items
•Rating: A measurement task that requires respondents to estimate the magnitude of a
characteristic or quality that a brand, store, or object possesses.
Measurement Scales
•Actual tools,
instruments, or rating
scales used to
measure variables.
•Actual tools,
instruments, or rating
scales used to
measure variables.
Single-Item Scales
•Single-item scales measure only one item as a construct
•Single-item scales measure only one item as a construct
Multiple-Choice Scale
•The researcher poses a single question with multiple response alternatives.
•For a mere quantification reason, a researcher assigns 1 to the first response, 2 to the
second response, and so on.
•It is important to note that the numbers provide only the nominal information.
Example:
Que. (1) Do you own a car?
Yes (1) No (2)
Que. (2) You belong to which region?
Andhra Pradesh (1) Chhattisgarh (2) Madhya Pradesh (3) Gujarat (4) Punjab (5)
Bihar (6)
Que. (3) In the previous month, which brand of toothpaste you have purchased?
Colgate (1) Pepsodent (2) Babool(3) Close-up (4)
•The researcher poses a single question with multiple response alternatives.
•For a mere quantification reason, a researcher assigns 1 to the first response, 2 to the
second response, and so on.
•It is important to note that the numbers provide only the nominal information.
Example:
Que. (1) Do you own a car?
Yes (1) No (2)
Que. (2) You belong to which region?
Andhra Pradesh (1) Chhattisgarh (2) Madhya Pradesh (3) Gujarat (4) Punjab (5)
Bihar (6)
Que. (3) In the previous month, which brand of toothpaste you have purchased?
Colgate (1) Pepsodent (2) Babool(3) Close-up (4)
Forced-Choice Ranking
•In forced-choice ranking scaling
technique, the respondents rank different
objects simultaneously from a list of
objects presented to them.
•This scaling technique is known as the
forced choice because the items or objects
on the scale are decided by the scale
designer, and the respondent is almost
forced to provide his or her ranking from
the list of brands included by the scale
designer.
•This scaling technique is also referred as
rank-order scaling and results in
generating ordinal-level data.
•In forced-choice ranking scaling
technique, the respondents rank different
objects simultaneously from a list of
objects presented to them.
•This scaling technique is known as the
forced choice because the items or objects
on the scale are decided by the scale
designer, and the respondent is almost
forced to provide his or her ranking from
the list of brands included by the scale
designer.
•This scaling technique is also referred as
rank-order scaling and results in
generating ordinal-level data.
Paired-Comparison Technique
•Arespondent is presented a pair of objects or stimulus or brands and the respondent is
supposed to provide his or her preference of the object from a pair.
•Arespondent is presented a pair of objects or stimulus or brands and the respondent is
supposed to provide his or her preference of the object from a pair.
Constant-Sum Scales
•The respondents allocate points to
more than one stimulus objects or
object attributes or object properties,
such that the total remains a constant
sum of usually 10 or 100
•The respondents allocate points to
more than one stimulus objects or
object attributes or object properties,
such that the total remains a constant
sum of usually 10 or 100
Direct Quantification Scale
•Thesimplestformofobtaining
informationistodirectlyaska
questionrelatedtosome
characteristicsofinterestresulting
inratioscaleddata.
•Thesimplestformofobtaining
informationistodirectlyaska
questionrelatedtosome
characteristicsofinterestresulting
inratioscaleddata.
Q-Sort Scales
•The objective of the Q-sort scaling
technique is to quickly classify a large
number of objects.
•The respondents are presented with a set
of statements, and they classify it on the
basis of some predefined number of
categories (piles).
•Example:National City Corporation, a
banking company, has used sorting as part of
its research into the design of its Web site.
•Consumers participating in the research were
given a set of cards describing various parts
of processes that they might engage in when
they are banking online.
•The participants were asked to arrange the
cards to show their idea of a logical way to
complete these processes.
•This research method shows the Web site
designers how consumers go about doing
something—sometimes very differently from
the way bankers expect
•The objective of the Q-sort scaling
technique is to quickly classify a large
number of objects.
•The respondents are presented with a set
of statements, and they classify it on the
basis of some predefined number of
categories (piles).
•Example:National City Corporation, a
banking company, has used sorting as part of
its research into the design of its Web site.
•Consumers participating in the research were
given a set of cards describing various parts
of processes that they might engage in when
they are banking online.
•The participants were asked to arrange the
cards to show their idea of a logical way to
complete these processes.
•This research method shows the Web site
designers how consumers go about doing
something—sometimes very differently from
the way bankers expect
Multi-item scaling
•Multi-item scaling techniques
generally generate some interval
type of information.
•In interval scaling technique, a
scale is constructed with the
number or description associated
with each scale position.
•Therefore, the respondent’s rating
on certain characteristics of interest
is obtained.
•Multi-item scaling techniques
generally generate some interval
type of information.
•In interval scaling technique, a
scale is constructed with the
number or description associated
with each scale position.
•Therefore, the respondent’s rating
on certain characteristics of interest
is obtained.
The Likert Scales
•The Likert scale is designed to examine how
strongly subjects agree or disagree with
statements on a five-point scale.
•Each item response has five rating categories,
“strongly disagree” to “strongly agree” as two
extremes with “disagree,” “neither agree nor
disagree,” and “agree” in the middle of the
scale. Typically, a 1-to 5-point rating scale is
used.
•Scores are obtained from the respondents, and
the sum is obtained across the scale items.
•After summing, an average is obtained for all
the respondents.
•The summated approach is widely used,
which is why the Likert scale is also referred
as the summated scale.
•The Likert scale is designed to examine how
strongly subjects agree or disagree with
statements on a five-point scale.
•Each item response has five rating categories,
“strongly disagree” to “strongly agree” as two
extremes with “disagree,” “neither agree nor
disagree,” and “agree” in the middle of the
scale. Typically, a 1-to 5-point rating scale is
used.
•Scores are obtained from the respondents, and
the sum is obtained across the scale items.
•After summing, an average is obtained for all
the respondents.
•The summated approach is widely used,
which is why the Likert scale is also referred
as the summated scale.
Semantic Differential Scales
•The semantic differential scale is used
to assess respondents’ attitudes toward a
particular brand, advertisement, object,
or individual.
•The responses can be plotted to obtain a
good idea of their perceptions.
•The semantic differential scale consists
of a series of bipolar adjectival words or
phrases placed on the two extreme points
of the scale.
•The semantic differential scale is used
to assess respondents’ attitudes toward a
particular brand, advertisement, object,
or individual.
•The responses can be plotted to obtain a
good idea of their perceptions.
•The semantic differential scale consists
of a series of bipolar adjectival words or
phrases placed on the two extreme points
of the scale.
Staple Scales
•The staple scale is generally presented vertically with a single adjective or phrase in
the centreof the positiveand negative ratings.
•The staple scale is generally presented vertically with a single adjective or phrase in
the centreof the positiveand negative ratings.
Numerical Scales
•Numerical scales provide equal intervals separated by numbers, as scale points to the
respondents.
•Thesescales are generally 5-or 7-point rating scales
•Numerical scales provide equal intervals separated by numbers, as scale points to the
respondents.
•Thesescales are generally 5-or 7-point rating scales
Continuous Rating Scales
•Inacontinuousratingscale,the
respondentsratetheobjectbyplacinga
markonacontinuumtoindicatetheir
attitude.
•Inthisscale,thetwoendsof
continuumrepresentthetwoextremes
ofthemeasuringphenomenon.
•Thisscaleisalsoreferredasagraphing
ratingscaleandallowsarespondentto
selecthisorherownratingpoint
insteadoftheratingpointspredefined
bytheresearcher.
•Therespondent’sscoresaremeasured
inlengthfromoneendofthescaleto
themarkplacedbytherespondent
•Inacontinuousratingscale,the
respondentsratetheobjectbyplacinga
markonacontinuumtoindicatetheir
attitude.
•Inthisscale,thetwoendsof
continuumrepresentthetwoextremes
ofthemeasuringphenomenon.
•Thisscaleisalsoreferredasagraphing
ratingscaleandallowsarespondentto
selecthisorherownratingpoint
insteadoftheratingpointspredefined
bytheresearcher.
•Therespondent’sscoresaremeasured
inlengthfromoneendofthescaleto
themarkplacedbytherespondent
FACTORS IN SELECTING AN APPROPRIATE
MEASUREMENT SCALE
MEASUREMENT SCALE
In-class Exercise
Understanding Employee and Consumer Preferences at BrewTechLtd
•BrewTechLtd.,acompanyspecializing
incraftbeerproduction,isconductinga
marketresearchstudytobetter
understandconsumerbehavior,
employee demographics,and
organizationalpolicies.
•Theresearchteamneedstodesign
appropriatemeasurementinstruments
tocollectandanalyzedata
•The company aims to:
1.Identify which beer brands are most
popular among consumers.
2. Assess agreement levels on the company’s
new accounting policy among finance
employees.
3. Measure employee satisfaction with the
existing work-from-home policy.
4. Collect demographic data on employee age
for workforce planning.
•BrewTechLtd.,acompanyspecializing
incraftbeerproduction,isconductinga
marketresearchstudytobetter
understandconsumerbehavior,
employee demographics,and
organizationalpolicies.
•Theresearchteamneedstodesign
appropriatemeasurementinstruments
tocollectandanalyzedata
•The company aims to:
1.Identify which beer brands are most
popular among consumers.
2. Assess agreement levels on the company’s
new accounting policy among finance
employees.
3. Measure employee satisfaction with the
existing work-from-home policy.
4. Collect demographic data on employee age
for workforce planning.
As a business research consultant, you
have been hired to develop the right
measurement instruments for BrewTech
Ltd.
For each research objective, identify:
• The type of measurement scale (Nominal,
Ordinal, Interval, or Ratio).
• A suitable measuring instrument (survey,
checklist, HR database, etc.).
• A sample question or method to collect
the required data.
1. How would you design a survey
question to determine which brands of
beer are consumed by individuals?
2. What kind scale could be used to assess
agreement with the accounting policy?
3. How would you measure satisfaction
with an organizational policy?
4.How should employee age be recorded
to ensure accurate analysis?
have been hired to develop the right
measurement instruments for BrewTech
Ltd.
For each research objective, identify:
• The type of measurement scale (Nominal,
Ordinal, Interval, or Ratio).
• A suitable measuring instrument (survey,
checklist, HR database, etc.).
• A sample question or method to collect
the required data.
1. How would you design a survey
question to determine which brands of
beer are consumed by individuals?
2. What kind scale could be used to assess
agreement with the accounting policy?
3. How would you measure satisfaction
with an organizational policy?
4.How should employee age be recorded
to ensure accurate analysis?
1.How would you design a survey
question to determine which brands of
beer are consumed by individuals?
•Which of the following beer brands do
you consume? (Select all that apply)
o ☐Kingfisher
o ☐Budweiser
o ☐Corona
o ☐Heineken
o ☐Others (Please specify)
2. What kind scale could be used to assess
agreement with the accounting policy?
•“Accounting principles ensure financial
transparency.” Please indicate your level
of agreement.
•o☐Strongly Disagree (1)
•o☐Disagree (2)
•o☐Neutral (3)
•o☐Agree (4)
•o☐Strongly Agree (5)
question to determine which brands of
beer are consumed by individuals?
•Which of the following beer brands do
you consume? (Select all that apply)
o ☐Kingfisher
o ☐Budweiser
o ☐Corona
o ☐Heineken
o ☐Others (Please specify)
2. What kind scale could be used to assess
agreement with the accounting policy?
•“Accounting principles ensure financial
transparency.” Please indicate your level
of agreement.
•o☐Strongly Disagree (1)
•o☐Disagree (2)
•o☐Neutral (3)
•o☐Agree (4)
•o☐Strongly Agree (5)
3. How would you measure satisfaction
with an organizational policy?
•How much do you like the current
remote work policy?
o ☐Not at all
o ☐Slightly
o ☐Moderately
o ☐Very much
o ☐Extremely
4.How should employee age be recorded
to ensure accurate analysis?
•What is your age? __ years
with an organizational policy?
•How much do you like the current
remote work policy?
o ☐Not at all
o ☐Slightly
o ☐Moderately
o ☐Very much
o ☐Extremely
4.How should employee age be recorded
to ensure accurate analysis?
•What is your age? __ years
FinTech Solutions, a rapidly growing financial technology company, wanted to measure
employee engagement. The HR team conducted an annual survey to assess job
satisfaction, motivation, and work-life balance.
Survey Questions & Measurement Scales Used:
1.Job Satisfaction:
1.Question: "Are you satisfied with your job?"
Scale: Dichotomous Scale (Yes/No)
2.Work-Life Balance Perception:
1.Question: "How well do you balance work and personal life?"
Scale: Likert Scale (1 = Very Poor, 5 = Excellent)
3.Motivation & Productivity:
1.Question: "How often do you stay late to complete your tasks?"
Scale: Direct Quantification (Number of days per month)
4.Overall Engagement:
1.Question: "Rank the following factors in order of importance: Salary, Work Environment, Growth
Opportunities, Team Collaboration, Job Security."
Scale: Rank-Order Scale
What concerns can you identify in this survey?
employee engagement. The HR team conducted an annual survey to assess job
satisfaction, motivation, and work-life balance.
Survey Questions & Measurement Scales Used:
1.Job Satisfaction:
1.Question: "Are you satisfied with your job?"
Scale: Dichotomous Scale (Yes/No)
2.Work-Life Balance Perception:
1.Question: "How well do you balance work and personal life?"
Scale: Likert Scale (1 = Very Poor, 5 = Excellent)
3.Motivation & Productivity:
1.Question: "How often do you stay late to complete your tasks?"
Scale: Direct Quantification (Number of days per month)
4.Overall Engagement:
1.Question: "Rank the following factors in order of importance: Salary, Work Environment, Growth
Opportunities, Team Collaboration, Job Security."
Scale: Rank-Order Scale
What concerns can you identify in this survey?
Concers:
•The Yes/No question on job satisfaction did not
capture nuance. Employees who were somewhat
satisfied had no way to express it.
•Work-life balance was measured subjectively—
two employees with the same number of working
hours may perceive balance differently.
•Staying late was assumed to indicate motivation,
but some employees stayed late due to
inefficiency, not engagement.
•Ranking engagement factors forced employees to
choose, but in reality, multiple factors influence
engagement simultaneously.
•Survey Questions & Measurement Scales Used:
1.Job Satisfaction:
1.Question: "Are you satisfied with your job?"
Scale: Dichotomous Scale (Yes/No)
2.Work-Life Balance Perception:
1.Question: "How well do you balance work
and personal life?"
Scale: Likert Scale (1 = Very Poor, 5 = Excellent)
3.Motivation & Productivity:
1.Question: "How often do you stay late to
complete your tasks?"
Scale: Direct Quantification (Number of days per
month)
4.Overall Engagement:
1.Question: "Rank the following factors in order
of importance: Salary, Work Environment,
Growth Opportunities, Team Collaboration,
Job Security."
Scale: Rank-Order Scale
•The Yes/No question on job satisfaction did not
capture nuance. Employees who were somewhat
satisfied had no way to express it.
•Work-life balance was measured subjectively—
two employees with the same number of working
hours may perceive balance differently.
•Staying late was assumed to indicate motivation,
but some employees stayed late due to
inefficiency, not engagement.
•Ranking engagement factors forced employees to
choose, but in reality, multiple factors influence
engagement simultaneously.
•Survey Questions & Measurement Scales Used:
1.Job Satisfaction:
1.Question: "Are you satisfied with your job?"
Scale: Dichotomous Scale (Yes/No)
2.Work-Life Balance Perception:
1.Question: "How well do you balance work
and personal life?"
Scale: Likert Scale (1 = Very Poor, 5 = Excellent)
3.Motivation & Productivity:
1.Question: "How often do you stay late to
complete your tasks?"
Scale: Direct Quantification (Number of days per
month)
4.Overall Engagement:
1.Question: "Rank the following factors in order
of importance: Salary, Work Environment,
Growth Opportunities, Team Collaboration,
Job Security."
Scale: Rank-Order Scale
Customer Satisfaction Measurement at StarMart Retail StarMart, a leading retail chain,
conducted a study to measure customer satisfaction.
They used the following tools:
1. Customer Experience Score (CES):
•Question: "How would you rate your experience today?"
•Scale: Likert Scale (1–5, with 1 = Very Poor and 5 = Excellent)
2. Purchase Likelihood:
•Question: "Would you shop at StarMart again?"
•Scale: Dichotomous Scale (Yes/No)
3. Net Promoter Score (NPS):
•Question: "On a scale of 0–10, how likely are you to recommend StarMart to a friend?"
•Scale: Interval Scale
4.Product Quality vs. Pricing Evaluation:
•Question: "Which factor matters more in your shopping decision?"
•Scale: Forced-Choice Scale (Product Quality / Price / Store Location / Brand Reputation)
What concerns can you identify in this survey?
conducted a study to measure customer satisfaction.
They used the following tools:
1. Customer Experience Score (CES):
•Question: "How would you rate your experience today?"
•Scale: Likert Scale (1–5, with 1 = Very Poor and 5 = Excellent)
2. Purchase Likelihood:
•Question: "Would you shop at StarMart again?"
•Scale: Dichotomous Scale (Yes/No)
3. Net Promoter Score (NPS):
•Question: "On a scale of 0–10, how likely are you to recommend StarMart to a friend?"
•Scale: Interval Scale
4.Product Quality vs. Pricing Evaluation:
•Question: "Which factor matters more in your shopping decision?"
•Scale: Forced-Choice Scale (Product Quality / Price / Store Location / Brand Reputation)
What concerns can you identify in this survey?
1. Customer Experience Score (CES):
•Question: "How would you rate your experience
today?“
•Scale: Likert Scale (1–5, with 1 = Very Poor and 5
= Excellent)
2. Purchase Likelihood:
•Question: "Would you shop at StarMart again?“
•Scale: Dichotomous Scale (Yes/No)
3. Net Promoter Score (NPS):
•Question: "On a scale of 0–10, how likely are you
to recommend StarMart to a friend?“
•Scale: Interval Scale
4.Product Quality vs. Pricing Evaluation:
•Question: "Which factor matters more in your
shopping decision?“
•Scale: Forced-Choice Scale (Product Quality /
Price / Store Location / Brand Reputation)
•Concerns:
•Customers who gave a score of ‘4’ in experience
might still have complaints, but the scale does not
explain why.
•Asking "Would you shop again?" in Yes/No format
does not capture frequency. A "Yes" could mean
once a month or once a year.
•NPS assumes recommendation likelihood predicts
loyalty, but some customers may love StarMart but
never recommend it for personal reasons.
•Forced-choice for product quality vs. price is
flawed—many shoppers consider both, not just
one.
•Question: "How would you rate your experience
today?“
•Scale: Likert Scale (1–5, with 1 = Very Poor and 5
= Excellent)
2. Purchase Likelihood:
•Question: "Would you shop at StarMart again?“
•Scale: Dichotomous Scale (Yes/No)
3. Net Promoter Score (NPS):
•Question: "On a scale of 0–10, how likely are you
to recommend StarMart to a friend?“
•Scale: Interval Scale
4.Product Quality vs. Pricing Evaluation:
•Question: "Which factor matters more in your
shopping decision?“
•Scale: Forced-Choice Scale (Product Quality /
Price / Store Location / Brand Reputation)
•Concerns:
•Customers who gave a score of ‘4’ in experience
might still have complaints, but the scale does not
explain why.
•Asking "Would you shop again?" in Yes/No format
does not capture frequency. A "Yes" could mean
once a month or once a year.
•NPS assumes recommendation likelihood predicts
loyalty, but some customers may love StarMart but
never recommend it for personal reasons.
•Forced-choice for product quality vs. price is
flawed—many shoppers consider both, not just
one.
THE CRITERIA FOR GOOD MEASUREMENT
Validity
Validity is the ability of an instrument to measure what is designed to measure.
A researcher captures behavior of employees to measure consumer satisfaction in a big
shopping mall.
Is it a valid scale?
Evaluation of the validity is dealt with the three basic approaches: content validity, criterion
validity, and construct validity
Validity is the ability of an instrument to measure what is designed to measure.
A researcher captures behavior of employees to measure consumer satisfaction in a big
shopping mall.
Is it a valid scale?
Evaluation of the validity is dealt with the three basic approaches: content validity, criterion
validity, and construct validity
Construct validity Exists when a measure reliably measures and truthfully
represents a unique concept; consists of several components including face validity,
content validty, criterion validity, convergent validity, and discriminant validity
(Does the instrument measure what it claims to measure?)
Face Validity: A scale’s content logically appears to reflect what was intended to be
measured.
(Does it appear to measure what it should?)
Content validity: The degree that a measure covers the breadth of the domain of
interest.
(Does the test cover all aspects of the concept?)
represents a unique concept; consists of several components including face validity,
content validty, criterion validity, convergent validity, and discriminant validity
(Does the instrument measure what it claims to measure?)
Face Validity: A scale’s content logically appears to reflect what was intended to be
measured.
(Does it appear to measure what it should?)
Content validity: The degree that a measure covers the breadth of the domain of
interest.
(Does the test cover all aspects of the concept?)
Customer
loyalty.
I prefer to purchase my groceries at Delavan Fine
Foods.
I am very satisfied with my purchases from
Delavan Fine Foods.
Delavan Fine Foods offers very good value.
loyalty.
I prefer to purchase my groceries at Delavan Fine
Foods.
I am very satisfied with my purchases from
Delavan Fine Foods.
Delavan Fine Foods offers very good value.
•Criterion validity: The ability of a measure to correlate with other standard measures
of similar constructs or established criteria addresses the question, “How well does
my measure work in practice?”
•Criterion validity may be classified as either depending on the time sequence in which
the new concurrent validity or predictive validity measurement scale and the criterion
measure are correlated.
•Eg: In a business setting, participants in a training seminar might be given a test to
assess their knowledge of the concepts covered, establishing concurrent validity.
Personnel managers may give potential employees an exam to predict if they will be
effective salespeople (predictive validity).
•While face validity is a subjective evaluation, criterion validity provides a more
rigorous empirical test.
(Does the measure correlate with an external standard?)
of similar constructs or established criteria addresses the question, “How well does
my measure work in practice?”
•Criterion validity may be classified as either depending on the time sequence in which
the new concurrent validity or predictive validity measurement scale and the criterion
measure are correlated.
•Eg: In a business setting, participants in a training seminar might be given a test to
assess their knowledge of the concepts covered, establishing concurrent validity.
Personnel managers may give potential employees an exam to predict if they will be
effective salespeople (predictive validity).
•While face validity is a subjective evaluation, criterion validity provides a more
rigorous empirical test.
(Does the measure correlate with an external standard?)
•Convergent validity:A convergent validity is established when the new measure
correlates or converges with the other similar measures.
•Discriminant validity: Represents how unique or distinct is a measure; a scale
should not correlate too highly with a measure of a different construct
correlates or converges with the other similar measures.
•Discriminant validity: Represents how unique or distinct is a measure; a scale
should not correlate too highly with a measure of a different construct
Job Satisfaction vs. Organizational Commitment
•A company conducts a survey to measure Job Satisfaction and Organizational Commitment among employees.
Constructs Measured:
1.Job Satisfaction – How happy employees are with their job.
1."I enjoy the tasks I perform at work." (1 = Strongly Disagree, 7 = Strongly Agree)
2."I feel valued for the work I do." (1 = Strongly Disagree, 7 = Strongly Agree)
2.Organizational Commitment – How loyal employees feel to the company.
1."I feel emotionally attached to my organization." (1 = Strongly Disagree, 7 = Strongly Agree)
2."I would feel guilty if I left this company now." (1 = Strongly Disagree, 7 = Strongly Agree)
If the correlation between Job Satisfaction and Organizational Commitment is too high (e.g., > 0.80), it
suggests low discriminant validity (i.e., they are measuring the same thing).
•A company conducts a survey to measure Job Satisfaction and Organizational Commitment among employees.
Constructs Measured:
1.Job Satisfaction – How happy employees are with their job.
1."I enjoy the tasks I perform at work." (1 = Strongly Disagree, 7 = Strongly Agree)
2."I feel valued for the work I do." (1 = Strongly Disagree, 7 = Strongly Agree)
2.Organizational Commitment – How loyal employees feel to the company.
1."I feel emotionally attached to my organization." (1 = Strongly Disagree, 7 = Strongly Agree)
2."I would feel guilty if I left this company now." (1 = Strongly Disagree, 7 = Strongly Agree)
If the correlation between Job Satisfaction and Organizational Commitment is too high (e.g., > 0.80), it
suggests low discriminant validity (i.e., they are measuring the same thing).
Reliabiltity
•A measure is said to be reliable when it elicits the same response from the same person
when the measuring instrument is administered to that person successively in similar or
almost similar circumstances.
•A researcher can adopt three ways to handle the issue of reliability: test–retest reliability,
equivalent forms reliability, and internal consistency reliability.
•To execute test–retest reliability, the same questionnaire is administered to the same
respondents to elicit responses in two different time slots.
•In equivalent forms reliability two equivalent forms are administered to the subjects at
two different times. To measure the desired characteristics of interest, two equivalent
forms are constructed with different sample of items. Both the forms contain the same type
of questions and the same structure with some specific difference. On applying the forms
of the measurement device, they may be given one after the other or after a specified time
interval, depending on the investigator’s interest in stability over time (Green et al., 1999).
•The reliability is established by computing the correlation coefficient of the results
obtained from the two equivalent forms.
•A measure is said to be reliable when it elicits the same response from the same person
when the measuring instrument is administered to that person successively in similar or
almost similar circumstances.
•A researcher can adopt three ways to handle the issue of reliability: test–retest reliability,
equivalent forms reliability, and internal consistency reliability.
•To execute test–retest reliability, the same questionnaire is administered to the same
respondents to elicit responses in two different time slots.
•In equivalent forms reliability two equivalent forms are administered to the subjects at
two different times. To measure the desired characteristics of interest, two equivalent
forms are constructed with different sample of items. Both the forms contain the same type
of questions and the same structure with some specific difference. On applying the forms
of the measurement device, they may be given one after the other or after a specified time
interval, depending on the investigator’s interest in stability over time (Green et al., 1999).
•The reliability is established by computing the correlation coefficient of the results
obtained from the two equivalent forms.
•Internal consistency reliability is used to assess the reliability of a summated scale by
which several items are summed to form a total score.
•Split-half technique: In this technique, the items are divided into equivalent groups. This
division is done on the basis of some predefined aspects as odd versus even number
questions in the questionnaire or split of items randomly. After division, responses on items
are correlated.
•High correlation coefficient indicates high internal consistency, and low correlation
coefficient indicates low internal consistency.
•The coefficient alpha or Cronbach’s alpha is actually a mean reliability coefficient for all
the different ways of splitting the items included in the measuring instruments.
•Coefficient alpha varies from 0 to 1, and a coefficient value of 0.6 or less is considered to
be unsatisfactory.
•Scales with a coefficient between 0.70 and 0.80 are considered to have good reliability,
and a value between 0.60 and 0.70 indicates fair reliability.
which several items are summed to form a total score.
•Split-half technique: In this technique, the items are divided into equivalent groups. This
division is done on the basis of some predefined aspects as odd versus even number
questions in the questionnaire or split of items randomly. After division, responses on items
are correlated.
•High correlation coefficient indicates high internal consistency, and low correlation
coefficient indicates low internal consistency.
•The coefficient alpha or Cronbach’s alpha is actually a mean reliability coefficient for all
the different ways of splitting the items included in the measuring instruments.
•Coefficient alpha varies from 0 to 1, and a coefficient value of 0.6 or less is considered to
be unsatisfactory.
•Scales with a coefficient between 0.70 and 0.80 are considered to have good reliability,
and a value between 0.60 and 0.70 indicates fair reliability.
•Sensitivity: A measurement instrument’s ability to accurately measure variability in
stimuli or responses.
•Sensitivity is the ability of a measuring instrument to measure the meaningful
difference in the responses obtained from the subjects included in the study.
Cronbach’s α = 0.86
stimuli or responses.
•Sensitivity is the ability of a measuring instrument to measure the meaningful
difference in the responses obtained from the subjects included in the study.
Cronbach’s α = 0.86
The flawed measurement scales in the Employee Engagement Survey at FinTech Solutions
can be improved:
Job Satisfaction Measurement
Flawed Scale: Dichotomous (Yes/No)
Better Scale: Semantic Scale (Ordinal or
Interval Scale)
New Question:
"On a scale of 1 to 7, how satisfied are you
with your job?"
(1 = Very Dissatisfied, 7 = Very Satisfied)
Validity Concern Fixed:
•Concern: The Yes/No scale lacks
construct validity—it does not capture
varying levels of satisfaction.
Work-Life Balance Perception
Flawed Scale: Subjective Likert Scale (1–5)
Better Scale: Multi-Item Scale (Behavior-Based Questions)
New Measurement Items:
"How often do you engage in the following activities?"
•Leave work on time (Never / Rarely / Sometimes / Often /
Always)
•Work after office hours (Never / Rarely / Sometimes / Often
/ Always)
•Take at least one full day off per week (Never / Rarely /
Sometimes / Often / Always)
Concern: Subjective self-reporting can lead to low criterion
validity (perception vs. reality).
can be improved:
Job Satisfaction Measurement
Flawed Scale: Dichotomous (Yes/No)
Better Scale: Semantic Scale (Ordinal or
Interval Scale)
New Question:
"On a scale of 1 to 7, how satisfied are you
with your job?"
(1 = Very Dissatisfied, 7 = Very Satisfied)
Validity Concern Fixed:
•Concern: The Yes/No scale lacks
construct validity—it does not capture
varying levels of satisfaction.
Work-Life Balance Perception
Flawed Scale: Subjective Likert Scale (1–5)
Better Scale: Multi-Item Scale (Behavior-Based Questions)
New Measurement Items:
"How often do you engage in the following activities?"
•Leave work on time (Never / Rarely / Sometimes / Often /
Always)
•Work after office hours (Never / Rarely / Sometimes / Often
/ Always)
•Take at least one full day off per week (Never / Rarely /
Sometimes / Often / Always)
Concern: Subjective self-reporting can lead to low criterion
validity (perception vs. reality).
Motivation & Productivity
Flawed Scale: Direct Quantification (Number
of days staying late)
Better Scale: Likert-Based Motivation Scale
New Question:
"How strongly do you agree with the
following statement: ‘I stay late at work
because I am motivated to complete my
tasks’?"
(1 = Strongly Disagree, 7 = Strongly Agree)
Concern: Staying late might indicate
inefficiency rather than motivation (low
construct validity).
Employee Engagement Factors
Flawed Scale: Rank-Order Scale (Forcing a single priority)
Better Scale: Multi-Item Rating Scale (Semantic Differential or
Likert Scale)
New Measurement Format:
"How important are the following factors for your
engagement at work?"
(1 = Not Important at All, 7 = Extremely Important)
•Salary
•Work Environment
•Growth Opportunities
•Team Collaboration
•Job Security
Concern: Rank-order scales assume that employees value only
one factor over others, which reduces construct validity.
Flawed Scale: Direct Quantification (Number
of days staying late)
Better Scale: Likert-Based Motivation Scale
New Question:
"How strongly do you agree with the
following statement: ‘I stay late at work
because I am motivated to complete my
tasks’?"
(1 = Strongly Disagree, 7 = Strongly Agree)
Concern: Staying late might indicate
inefficiency rather than motivation (low
construct validity).
Employee Engagement Factors
Flawed Scale: Rank-Order Scale (Forcing a single priority)
Better Scale: Multi-Item Rating Scale (Semantic Differential or
Likert Scale)
New Measurement Format:
"How important are the following factors for your
engagement at work?"
(1 = Not Important at All, 7 = Extremely Important)
•Salary
•Work Environment
•Growth Opportunities
•Team Collaboration
•Job Security
Concern: Rank-order scales assume that employees value only
one factor over others, which reduces construct validity.
The flawed measurement scales in StarMart Retail’s Customer Satisfaction
Study can be improved, along with validity concerns addressed:
Customer Experience Score (CES)
Flawed Scale: Likert Scale (1–5: Very Poor to
Excellent)
Better Scale: Likert Scale with Anchors & Follow-Up
Question
New Measurement:
"On a scale of 1 to 7, how would you rate your
overall shopping experience today?"
(1 = Very Poor, 7 = Excellent)
Follow-Up Question:
"What specific factors influenced your rating?"
(Open-ended)
Concern: A 5-point Likert scale may not capture
finer differences in satisfaction (low discriminant
validity).
Purchase Likelihood
Flawed Scale: Dichotomous Scale (Yes/No: “Would you shop
again?”)
Better Scale: Interval Scale (Probability Rating Scale)
New Measurement:
"How likely are you to shop at StarMart again within the next
3 months?"
(1 = Not Likely at All, 7 = Extremely Likely)
Concern: Yes/No response lacks predictive validity—a "Yes"
could mean once a month or once a year.
Study can be improved, along with validity concerns addressed:
Customer Experience Score (CES)
Flawed Scale: Likert Scale (1–5: Very Poor to
Excellent)
Better Scale: Likert Scale with Anchors & Follow-Up
Question
New Measurement:
"On a scale of 1 to 7, how would you rate your
overall shopping experience today?"
(1 = Very Poor, 7 = Excellent)
Follow-Up Question:
"What specific factors influenced your rating?"
(Open-ended)
Concern: A 5-point Likert scale may not capture
finer differences in satisfaction (low discriminant
validity).
Purchase Likelihood
Flawed Scale: Dichotomous Scale (Yes/No: “Would you shop
again?”)
Better Scale: Interval Scale (Probability Rating Scale)
New Measurement:
"How likely are you to shop at StarMart again within the next
3 months?"
(1 = Not Likely at All, 7 = Extremely Likely)
Concern: Yes/No response lacks predictive validity—a "Yes"
could mean once a month or once a year.
Net Promoter Score (NPS)
Flawed Scale: Interval Scale (0–10: Likelihood to
Recommend)
Better Scale: NPS + Open-Ended Justification
New Measurement:
"On a scale of 0 to 10, how likely are you to
recommend StarMart to a friend?"
(0 = Not at All Likely, 10 = Extremely Likely)
Follow-Up Question:
"What is the main reason for your score?" (Open-
ended)
Concern: NPS assumes recommendation likelihood
directly correlates with loyalty (questionable
predictive validity).
Product Quality vs. Pricing Evaluation
Flawed Scale: Forced-Choice Scale (Customers must choose
one factor: Price vs. Product Quality vs. Location vs. Brand
Reputation)
Better Scale: Likert Scale (Importance of Each Factor)
New Measurement:
"How important are the following factors in your shopping
decisions?"
(1 = Not Important at All, 7 = Extremely Important)
•Product Quality
•Pricing
•Store Location
•Brand Reputation
Concern: Forced-choice assumes customers prioritize only
one factor, reducing construct validity.
Flawed Scale: Interval Scale (0–10: Likelihood to
Recommend)
Better Scale: NPS + Open-Ended Justification
New Measurement:
"On a scale of 0 to 10, how likely are you to
recommend StarMart to a friend?"
(0 = Not at All Likely, 10 = Extremely Likely)
Follow-Up Question:
"What is the main reason for your score?" (Open-
ended)
Concern: NPS assumes recommendation likelihood
directly correlates with loyalty (questionable
predictive validity).
Product Quality vs. Pricing Evaluation
Flawed Scale: Forced-Choice Scale (Customers must choose
one factor: Price vs. Product Quality vs. Location vs. Brand
Reputation)
Better Scale: Likert Scale (Importance of Each Factor)
New Measurement:
"How important are the following factors in your shopping
decisions?"
(1 = Not Important at All, 7 = Extremely Important)
•Product Quality
•Pricing
•Store Location
•Brand Reputation
Concern: Forced-choice assumes customers prioritize only
one factor, reducing construct validity.
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