Marketing Research Module 3 Non Comparitive Scaling
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Transcript of Marketing Research Module 3 Non Comparitive Scaling
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Ch apter Ni neMeasurement and Scaling:
Noncomparative Scaling
Techniques
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Ch apter O utl ine1) Overview
2) Noncomparative Scaling Techniques
3) Continuous Rating Scale
4) Itemized Rating Scale
i. Likert Scale
ii. Semantic Differential Scale
iii. Stapel Scale
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Cha pter Ou tl ine5) Noncomparative Itemized Rating Scale Decisions
i. Number of Scale Categories
ii. Balanced Vs. Unbalanced Scales
iii. Odd or Even Number of Categories
iv. Forced Vs. Non-forced Scales
v. Nature and Degree of Verbal Description
vi. Physical Form or Configuration
6) Multi-item Scales
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Cha pter Ou tl ine7) Scale Evaluation
i. Measurement Accuracy
ii. Reliability
iii. Validity
iv. Relationship between Reliability and Validity
v. Generalizability
8) Choosing a Scaling Technique
9) Mathematically Derived Scales
Reliable? Valid?
Generalizable?
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Cha pter Ou tl ine
10) International Marketing Research
11) Ethics in Marketing Research
12) Summary
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Nonc ompa ra ti ve S cali ngTechniques Respondents evaluate only one object at a time, and for
this reason non-comparative scales are often referred to
as monadic scales.
Non-comparative techniques consist of continuous anditemized rating scales.
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Co nti nuous Rati ng S ca leRespondents rate the objects by placing a mark at the appropriate position
on a line that runs from one extreme of the criterion variable to the other.
The form of the continuous scale may vary considerably.
How would you rate Sears as a department store?
Version 1
Probably the worst - - - - - - -I - - - - - - - - - - - - - - - - - - - - - - Probably the best
Version 2
Probably the worst - - - - - - -I - - - - - - - - - - - - - - - - - - - - - --Probably the best
0 10 20 30 40 50 60 70 80 90 100
Version 3
Very bad Neither good Very good
nor bad
Probably the worst - - - - - - -I - - - - - - - - - - - - - - - - - - - - ---Probably the best
0 10 20 30 40 50 60 70 80 90 100
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A rel ativel y new re sea rch too l, the perc ept ion ana ly zer, pr ovidescon tin uou s mea sure me nt of gu t rea ct ion . A gr oup of up to 400re spon de nts is pre sen te d wi th TV or ra dio spot s or adve rt is ing copy .The measuring de vic e con sists of a dia l that con ta in s a 100-poin tra nge . Ea ch pa rt ic ipa nt is giv en a dia l and instru cte d to con tin uouslyre cord his or her re act ion to the mate ria l be in g te ste d ..As th e re spon den ts tu rn th e di als , thein form ation is f ed to a com pu ter , wh ichtabu la tes secon d-by -sec ond re spon sepr ofile s. As the res ult s are re corde d bythe comp uter, they are super im pos ed ona vid eo scr een , enabli ng the res earch erto vie w th e re spon de nts' score sim med ia tel y. The res pon ses are alsostored in a per ma nent da ta file for use infurt her analy sis. The re spon se score sca n be brok en dow n by ca teg orie s, suchas age, in com e, sex , or produ ct usage.
RATE: R api d A na lysi s a ndTest ing En vir on me nt
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Itemi ze d Rati ng Sc ales The respondents are provided with a scale that has a
number or brief description associated with eachcategory.
The categories are ordered in terms of scale position,and the respondents are required to select the specifiedcategory that best describes the object being rated.
The commonly used itemized rating scales are theLikert, semantic differential, and Stapel scales.
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Li kert S ca leThe Li ke rt sca le requires the respondents to indicate a degree of agreement ordisagreement with each of a series of statements about the stimulus objects.
Strongly Disagree Neither Agree Strongly
disagree agree nor agree
disagree
1. Sears sells high quality merchandise. 1 2X 3 4 5
2. Sears has poor in-store service. 1 2X 3 4 5
3. I like to shop at Sears. 1 2 3X 4 5
The analysis can be conducted on an item-by-item basis (profile analysis), or atotal (summated) score can be calculated.
When arriving at a total score, the categories assigned to the negativestatements by the respondents should be scored by reversing the scale.
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Se man ti c Di ffere nti al Sc al eThe seman tic diffe re nt ial is a seven-point rating scale with endpoints associated with bipolar labels that have semantic meaning.
SEARS IS:
Powerful --:--:--:--:-X-:--:--: Weak
Unreliable --:--:--:--:--:-X-:--: ReliableModern --:--:--:--:--:--:-X-: Old-fashioned
The negative adjective or phrase sometimes appears at the leftside of the scale and sometimes at the right.
This controls the tendency of some respondents, particularlythose with very positive or very negative attitudes, to mark theright- or left-hand sides without reading the labels.
Individual items on a semantic differential scale may be scored
on either a -3 to +3 or a 1 to 7 scale.
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A Seman ti c D if ferenti al Sca le f or Me asuri ngSelf - Conc ep ts, Person Conc ept s, and ProductConce pts 1) Rugged :---:---:---:---:---:---:---: Delicate
2) Excitable :---:---:---:---:---:---:---: Calm
3) Uncomfortable :---:---:---:---:---:---:---: Comfortable
4) Dominating :---:---:---:---:---:---:---: Submissive
5) Thrifty :---:---:---:---:---:---:---: Indulgent
6) Pleasant :---:---:---:---:---:---:---: Unpleasant
7) Contemporary :---:---:---:---:---:---:---: Obsolete
8) Organized :---:---:---:---:---:---:---: Unorganized
9) Rational :---:---:---:---:---:---:---: Emotional
10) Youthful :---:---:---:---:---:---:---: Mature
11 Formal :---:---:---:---:---:---:---: Informal
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St apel Sc al eThe Stapel scale is a unipolar rating scale with ten categoriesnumbered from -5 to +5, without a neutral point (zero). This scaleis usually presented vertically.
SEARS
+5 +5
+4 +4+3 +3
+2 +2X
+1 +1
HIGH QUALITY POOR SERVICE
-1 -1
-2 -2-3 -3
-4X -4
-5 -5
The data obtained by using a Stapel scale can be analyzed in the
same way as semantic differential data.
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Scal e Bas ic Charac ter is tics Exampl es Advantages Disadv antagesContinuousRatingScale
Place a mark on acontinuous line
Reaction toTVcommercials
Easy to construct Scoring can becumbersomeunlesscomputerized
Itemized Rating Scales
Likert Scale Degrees ofagreement on a 1(strongly disagree)to 5 (strongly agree)scale
Measurementof attitudes
Easy to construct,administer, andunderstand
Moretime-consuming
SemanticDifferential Seven - point scalewith bipolar labels Brand,product, andcompanyimages
Versatile Controversy asto whether thedata are interval
StapelScale
Unipolar ten - pointscale, - 5 to +5,without a neutralpoint (zero)
Measurementof attitudesand images
Easy to construct,administer overtelephone
Confusing anddifficult to apply
Table 9.1
Basic Nonc omp ara ti ve S ca les
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Summary of Itemized Scale Decisions
Table 9.2
1) N umber of categ ories Although there is no single, optimalnumber,
traditional guidelines suggest that thereshould be between five and nine categories
2) Bal anced vs. unb ala nc ed In general, the scale should be balanced toobtain objective data
3) O dd/even no. o f cate gor ies If a neutral or indifferent scaleresponse is
possible for at least some respondents,an odd number of categories should be used
4) Fo rced vs. non- forced In situations where the respondents areexpected to have no opinion, the accuracy ofthe data may be improved by a non-forcedscale
5) Ve rb al des crip tio n An argument can be made for labeling all ormany scale categories. The categorydescriptions should be located as close tothe response categories as possible
6)Physi cal fo rm A number of options should be tried and thebest selected
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Fig. 9.1
Jovan Musk for Men is: Jovan Musk for Men is:Extremely good Extremely good
Very good Very goodGood Good Bad Somewhat good
Very bad BadExtremely bad Very bad
a ance a n n a an ceScales
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Rati ng S ca le C onfig ura ti ons
-3 -1 0 +1 +2-2 +3
Cheer
Cheer detergent is:Cheer detergent is:1) Very harsh --- --- --- --- --- --- --- Very gentle
2) Very harsh 1 2 3 4 5 6 7 Very gentle
3) . Very harsh.
.
. Neither harsh nor gentle
.
.
. Very gentle
4) ____ ____ ____ ____ ____ ____ ____Very Harsh Somewhat Neither harsh Somewhat Gentle Very
harsh Harsh nor gentle gentle gentle
5)
Very Neither harsh Very
harsh nor gentle gentle
Fig. 9.2
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Thermometer Scale
Instructions: Please indicate how much you like McDonalds hamburgersby coloring in the thermometer. Start at the bottom and color up to the
temperature level that best indicates how strong your preference is.
Form:
Smiling Face Scale
Instructions: Please point to the face that shows how much you like theBarbie Doll. If you do not like the Barbie Doll at all, you would point to Face
1. If you liked it very much, you would point to Face 5.
Form:
1 2 3 4 5
Fig. 9.3
Like very
much
Dislike
very much
100
75
50
25
0
Conf igura tio ns
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Some Co mm on ly U sed Scales inMarketingTable 9.3
CONSTRUCT
SCALE DESCRIPTORS
Attitude
Importance
Satisfaction
Purchase Intent
Purchase Freq
Very Bad
Not all All Important
Very Dissatisfied
Definitely will Not Buy
Never
Bad
Not Important
Dissatisfied
Probably Will Not Buy
Rarely
Neither Bad Nor Good
Neutral
Neither Dissat Nor Satisfied
Might or Might Not Buy
Sometimes
Good
Important
Satisfied
Probably Will Buy
Often
Very Good
Very Important
Very Satisfied
Definitely Will Buy
Very Often
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De velo pm ent of a Mul ti-i tem S ca leDe vel op T he ory
Ge nerat e Ini tial Poo l of It em s: T heory , Sec ond ary Dat a, a ndQual it ative R esea rch
Collec t Dat a fr om a L arg e Pret est Sam pleSt atist ica l A nalysis
Dev elop Puri fi ed Scal eCol lec t More Dat a from a Different Sam ple
Fi na l Scal e
Fig. 9.4
Sel ect a Reduced Set of It em s Based on Quali tat ive Jud geme nt
Eval uat e Scal e Reliab il ity, Vali dity, and Generali zab il ity
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Sca le E va lua ti onFig. 9.5
Discriminant NomologicalConvergent
Test/Retest
AlternativeForms
InternalConsistency
Content Criterion Construct
GeneralizabilityReliability Validity
Scale Evaluation
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Mea su remen t Ac cu ra cyThe true sco re mo del provides a framework forunderstanding the accuracy of measurement.
XO = XT + XS + XR
where
XO
= the observed score or measurement
XT = the true score of the characteristicXS = systematic errorXR = random error
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Mea sure me nt11) Other relatively stable characteristics of the individual that influence
the test score, such as intelligence, social desirability, andeducation.
2) Short-term or transient personal factors, such as health, emotions,and fatigue.
3) Situational factors, such as the presence of other people, noise, anddistractions.
4) Sampling of items included in the scale: addition, deletion, orchanges in the scale items.
5) Lack of clarity of the scale, including the instructions or the itemsthemselves.
6) Mechanical factors, such as poor printing, overcrowding items in thequestionnaire, and poor design.
7) Administration of the scale, such as differences among interviewers.
8) Analysis factors, such as differences in scoring and statisticalanalysis..
Fig. 9.6
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Rel iabi lity Rel iabi l it y can be defined as the extent to which
measures are free from random error, XR. If XR = 0,the measure is perfectly reliable.
In test -ret est rel iab il it y, respondents areadministered identical sets of scale items at twodifferent times and the degree of similarity betweenthe two measurements is determined.
In al te rna tiv e- forms r eli ab il ity , two equivalentforms of the scale are constructed and the samerespondents are measured at two different times,with a different form being used each time.
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Rel iabi lity In ter nal co nsi stency rel ia bi li ty determines the
extent to which different parts of a summated scale areconsistent in what they indicate about the characteristicbeing measured.
In sp li t-ha lf r eli ab il ity , the items on the scale aredivided into two halves and the resulting half scores arecorrelated.
The co efficien t al pha, or Cronbach's alpha, is theaverage of all possible split-half coefficients resultingfrom different ways of splitting the scale items. Thiscoefficient varies from 0 to 1, and a value of 0.6 or lessgenerally indicates unsatisfactory internal consistencyreliability.
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Validity
The vali dity of a scale may be defined as the extent towhich differences in observed scale scores reflect truedifferences among objects on the characteristic beingmeasured, rather than systematic or random error.Perfect validity requires that there be no measurement
error (XO = XT, XR = 0, XS = 0).
Co nten t va li dit y is a subjective but systematicevaluation of how well the content of a scale represents
the measurement task at hand. Cr it eri on va lid it y reflects whether a scale performs as
expected in relation to other variables selected (criterionvariables) as meaningful criteria.
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Validity Co nst ruct v al idi ty addresses the question of what
construct or characteristic the scale is, in fact,measuring. Construct validity includes convergent,discriminant, and nomological validity.
Co nver gen t val idi ty is the extent to which the scalecorrelates positively with other measures of the sameconstruct.
Discr iminan t va li dit y is the extent to which ameasure does not correlate with other constructs fromwhich it is supposed to differ.
Nomological validity is the extent to which thescale correlates in theoretically predicted ways with
measures of different but related constructs.
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Rel ati onsh ip Between Reli abili tyand Va lidi ty If a measure is perfectly valid, it is also perfectly reliable.
In this case XO = XT, XR = 0, and XS = 0. If a measure is unreliable, it cannot be perfectly valid,
since at a minimum XO = XT + XR. Furthermore,systematic error may also be present, i.e., XS0. Thus,unreliability implies invalidity.
If a measure is perfectly reliable, it may or may not beperfectly valid, because systematic error may still bepresent (XO = XT + XS).
Reliability is a necessary, but not sufficient, condition for
validity