2-Lectures Ch 13 Introduction to Measurement

8/12/2019 2-Lectures Ch 13 Introduction to Measurement

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King Fahd University of Petroleum & Minerals

Department of Management and Marketing

MKT 345 Marketing Research

Dr. Alhassan G. Abdul-Muhmin

Introduction to Measurement

Reference: Zikmund, Chapter 13


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Learning Objectives

At the end of this discussion you should be able to:

1. define measurement and explain its importance inmarketing research

2. list and explain the requirements for effectivemeasurement in marketing research

3. list and explain the different types ofmeasurement scales

4. know how to form an index or compositemeasure

5. list and explain the criteria used to evaluate thequality of index measures

6. Perform basic assessment of scale reliability andvalidity


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THE NATURE OF MEASUREMENT

1. The process of assigning numbers or scores toattributes of people or objects.

2. The process of describing some property of aphenomenon of interest by assigning numbers in a

reliable and valid wayPrecise measurement requires:

a) Careful conceptual definitioni.e. careful definition ofthe concept (e.g. loyalty) to be measured

b) Operational definition of the conceptc) Assignment rules by which numbers or scores are

assigned to different levels of the concept that anindividual (or object) possesses.


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1. Conceptual Definition

Concept- A generalized idea about a class ofobjects, attributes, occurrences, or processes. Examples: Gender, Age, Education, brand

loyalty, satisfaction, attitude, market orientation

Construct- A concept that is measured withmultiple variables. Examples: Brand loyalty, satisfaction, attitude,

market orientation, socio-economic status

Variable- Anything that varies or changesfrom one instance to another; can exhibitdifferences in value, usually in magnitude orstrength, or in direction.


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1. Conceptual Definition

Concepts must be precisely defined for effective

measurement.

E.g. consider the following definitions of brandloyalty:

1. The degree to which a consumer consistentlypurchases the same brand within a productclass. (Peter & Olson)

2. A favorable attitude toward, and consistent

purchases of, a particular brand. (Wilkie, p.276)

The two definitions have different implications formeasurementthey imply differentoperationalizations of the concept of brand loyalty


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2. Operational Definition/Operationalization

Operational definition- A definition that gives meaning to aconcept by specifying what the researcher must do (i.e. activities

or operations that should be performed) in order to measure theconcept under investigation.

Operationalization- The process of identifying scales thatcorrespond to variance in a concept.

For example: Conceptual definition # 1 for brand loyalty in the previous slide

implies that in order to measure loyalty for brand A (operationaldefinition), you will need to:

1) Observe consumers brand purchases over a period of time, and

2) Compute the percent of purchases going to brand A

For conceptual definition # 2 you will need to:

1) Observe consumers brand purchases over a period of time,

2) Compute the percent of purchases going to brand A, and

3) Ask consumers questions to determine their attitudes towardbrand A


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3. Rules of Measurement

Guidelines established by the researcher for assigningnumbers or scores to different levels of the concept (orattribute) that different individuals (or objects) possess

The process is facilitated by the operational definition. For example, if you operationalized brand loyalty as purchase

sequences (conceptual definition # 1), then you may establish the

following rules for assigning scores: If consumer purchased brand A:

90% or more> loyalty for brand A = 1 (Extremely loyal)

80 - 89% > loyalty for brand A = 2 (Very loyal)

70 - 79% > loyalty for brand A = 3 (Loyal)

Etc.

In this case, we have assigned the numbers 1, 2, 3 to different

levels of loyalty toward brand A. We have measured loyalty

for brand A.


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MEASUREMENT SCALES

To effectively carry out any measurement (whetherin the physical or social sciences) we need to usesome form of a scale.

A scaleis any series of items (numbers) arranged

along a continuous spectrum of values for the purposeof quantification(i.e. for the purpose of placingobjects based on how much of an attribute theypossess)

E.g. the thermometer consists of numbers arrangedin a continuous spectrum to indicate the magnitudeof heat possessed by an object.


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Three Meanings of Scale in Marketing Research

There are three ways in which the word scale is used in

marketing research1) The level at which a variable is measured (Level of scale

measurement) the arithmetical properties implied by the numbers assigned to levels

of an attribute possessed by an object (i.e. the unit of analysis)

Discussed in this chapter

2) An index, or composite measure of a construct Multiple statements used to measure a construct (also called a multi-

item measure of the construct)

Discussed in this chapter

3) The response categories provided for a close-ended questionin a questionnaire, e.g.

Subjects expressed their agreement / disagreement on a 5-pointcategory scale or on a 5-point semantic differential scale.

Will be discussed in chapter 14


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(1) LEVELS OF SCALE MEASUREMENT

Numbers assigned in measurement can take on different

levels of meaning depending on one of four mappingcharacteristics possessed by the numbers:

1. Classification- The numbers are used only to group orsort responses. No order exists

2. Order - The numbers are ordered. One number is greaterthan, less than, or equal to another

3. Distance- Differences between the numbers are ordered.The difference between any pair of numbers is greaterthan, less than, or equal to the difference between any

other pair of numbers4. Origin- The number series has a unique origin indicated

by the number zero

The type of mapping characteristic assumed depends on the

properties of the attribute (or construct) being measured


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The Four Characteristics of Mapping Rules

1. ClassificationThe numbers are used only togroup or sort responses. No order exists

2. OrderThe numbers are ordered. Onenumber is greater than, less than, or equal toanother

3. DistanceDifferences between the numbersare ordered. The difference between any pairof numbers is greater than, less than, or equalto the difference between any other pair ofnumbers

4. OriginThe number series has a uniqueorigin indicated by the number zero


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The Four Levels of Scale Measurement

Four levels of scale measurementresult from this mapping

1. Nominal Scale: a scale in which the numbers or letters assignedto an object serve only as labels for identification orclassification, e.g. Gender (Male=1, Female=2)

2. Ordinal Scale: a scale that arranges objects or alternativesaccording to their magnitude in an ordered relationship, e.g.

Academic status (Sophomore=1, Freshman=2, Junior=3, etc3. Interval Scale: a scale that both arranges objects according to

their magnitude, distinguishes this ordered arrangement in unitsof equal intervals, but does not have a natural zero representingabsence of the given attribute, e.g. the temperature scale (40oC

is not twice as hot as 20oC)4. Ratio Scale: a scale that has absolute rather than relative

quantities and an absolute (natural) zero where there is anabsence of a given attribute, e.g. income, age.


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Nominal, Ordinal, Interval, and Ratio Scales Provide Different Information


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Characteristics of Different Levels of Scale Measurement

Type of

Scale

Data

Characteristics

Numerical

Operation

Descriptive

StatisticsExamples

Nominal Classification but no

order, distance, or

origin

Counting Frequency in each

category

Percent in each

category

Mode

Gender (1=Male,

2=Female)

Ordinal Classification and

order but no

distance or unique

origin

Rank ordering Median

Range

Percentile ranking

Academic status

(1=Freshman,

2=Sophomore,

3=Junior,

4=Senior)

Interval Classification, order,

and distance but no

unique origin

Arithmetic

operations that

preserve order and

magnitude

Mean

Standard deviation

Variance

Temperature in

degrees

Satisfaction on

semanticdifferential scale

Ratio Classification, order,

distance and unique

origin

Arithmetic

operations on

actual quantities

Geometric mean

Coefficient of

variation

Age in years

Income in Saudi

riyals

Note: All statistics appropriate for lower-order scales (nominal being lowest) are appropriate forhigher-order scales (ratio being the highest)


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(2) INDEX OR COMPOSITE MEASURES

Both index and composite measures use combinations (or collection) ofseveral variables to measure a single construct (or concept); they aremulti-item measures of constructs.

However, for index measures, the variables need not be stronglycorrelated with each other, whilst for composite measures, the variablesare typically strongly correlated as they are all assumed to be measuringthe construct in the same way

Example 1:Index Measure

Construct: Social class

Measures: Linear combination (index) of occupation, education, income.

Social class = 1Education + 2Occupation + 2Occupation

Example 2: Composite Measure

Construct: Attitude Toward Brand AMeasures: Extent of agreement/disagreement with multiple statements:

a) I like Brand A very much

b) Brand A is the best in the market

c) I always buy Brand A

Statements a), b), c), constitute a scale to measure attitudes toward brand A


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Computing Scale Values for Composite Scales

Summated Scale

A scale created by simply summing (adding

together) the response to each item making up the

composite measure.

Reverse CodingMeans that the value assigned for a response is

treated oppositely from the other items.


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CRITERIA FOR GOOD MEASUREMENT

Three criteria are commonly used to assess thequality of measurement scales in marketingresearch:

1. Reliability2. Validity

3. Sensitivity


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RELIABILITY

The degree to which a measure is free fromrandom error and therefore gives consistentresults.

An indicator of the measures internalconsistency


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Reliability

Internal

Consistency

Stability(Repeatability)

Equivalent

forms

Splittinghalves

Test-Retest


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Assessing Stability (Repeatability)

Stabilitythe extent to which resultsobtained with the measure can be reproduced.

1. Test-Retest Method

Administering the same scale or measure to the same

respondents at two separate points in time to test forstability.

2. Test-Retest Reliability Problems

The pre-measure, or first measure, may sensitize the

respondents and subsequently influence the results ofthe second measure.

Time effects that produce changes in attitude or other

maturation of the subjects.


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Assessing Internal Consistency

Internal Consistency: the degree of homogeneity

among the items in a scale or measure

1. Split-half Method

Assessing internal consistency by checking the results of one-half of a set of scaled items against the results from the other

half.

Coefficient alpha ()

The most commonly applied estimate of a multiple itemscales reliability.

Represents the average of all possible split-half reliabilitiesfor a construct.

2. Equivalent forms

Assessing internal consistency by using two scales designed tobe as equivalent as possible.


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VALIDITY

The accuracy of a measure or the extent towhich a score truthfully represents a concept.

The ability of a measure (scale) to measure whatit is intended measure.

Establishing validity involves answers to the ff:

Is there a consensus that the scale measures what itis supposed to measure?

Does the measure correlate with other measures ofthe same concept?

Does the behavior expected from the measurepredict actual observed behavior?


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Validity

PredictiveConcurrent

ConstructValidity

CriterionValidity

Face orContent

ASSESSING VALIDITY


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ASSESSING VALIDITY

1. Face or content validity: The subjective agreementamong professionals that a scale logically appears tomeasure what it is intended to measure.

2. Criterion Validity:the degree of correlation of ameasure with other standard measures of the same

construct. Concurrent Validity: the new measure/scale is taken atsame time as criterion measure.

Predictive Validity: new measure is able to predict a futureevent / measure (the criterion measure).

3. Construct Validity: degree to which a measure/scaleconfirms a network of related hypotheses generatedfrom theory based on the concepts.

Convergent Validity.

Discriminant Validity.


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Relationship Between Reliability & Validity

1. A measure that is not reliable cannot bevalid, i.e. for a measure to be valid, it mustbe reliableThus, reliability is a necessarycondition for validity

2. A measure that is reliable is not necessarilyvalid; indeed a measure can be but not validThus, reliability is not a sufficient

condition for validity3. Therefore, reliability is a necessary but not

sufficient condition for Validity.


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Reliability and Validity on Target


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SENSITIVITY

The ability of a measure/scale to accurately measure

variability in stimuli or responses;

The ability of a measure/scale to make fine distinctionsamong respondents with/objects with different levels of

the attribute (construct). Example - A typical bathroom scale is not sensitive enough to be used to

measure the weight of jewelry; it cannot make fine distinctions amongobjects with very small weights.

Composite measures allow for a greater range ofpossible scores, they are more sensitive than single-itemscales.

Sensitivity is generally increased by adding moreresponse points or adding scale items.

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2-Lectures Ch 13 Introduction to Measurement