1. Chapter Nine Attitude Measurement

2. What is an Attitude A mental state used by individuals to structure the way they perceive the environment and guide the way they respond to it Essence of the ‘human change agent’ – influencing attitudes can influence how you behave Great diagnostic / explanatory value – why consumers buy / don’t buy Overwhelming amount of primary research in marketing deals in measuring attitudes

3. Formation of attitudes (MAAM) Belief about a brand = Attribute x strength of its association with brand Importance of attribute moderates belief strength Sum of moderated beliefs = attitude to brand Interpret the figure according to the direction of the scale Interpret the figure relative to attitude measures for competing brands Multi Attribute Attitude Modeling (MAAM)

4. Multi-Attribute Attitude Models n A b =  b i e i i = 1 A b = attitude toward brand b i = belief about the relationship between brand and attribute i e i = attribute importance weight i n = number of salient attributes

5. Multi-Attribute Attitude Models Example Value Store Store Store Attribute (e i ) X YZ Wide Selection0.3+2+3+3 Low Price0.2+3-2-1 High Quality0.3-1+3+1 Convenient0.2+2+2+3 location b i e i for Store X: (0.3)(+2) + (+3)(0.2) + (-1)(0.3) + (+2)(0.2) = 1.3 b i e i for Store Y: (+3)(0.3) + (-2)(0.2) + (+3)(0.3) + (+2)(0.2) = 1.8 b i e i for Store Z: (+3)(0.3) + (-1)(0.2) + (+1)(0.3) + (+3)(0.2) = 1.6

6. Attitude Research Attitude Action/ Behavior

7. Three Components of Attitude Affective Component Cognitive Component Action Component

8. Attitude components Cognitive component –Awareness of object –Knowledge of attributes of object –Judgments of importance of attributes of object Satisfaction Etc. Affective component –Feelings and emotions Conative component –‘drive’ to act / behave – motivation –Desire Attitude is a three – dimensional construct

9. Ideas, Concepts, Constructs and Variables E.g. “I want to make advertising that is “cool”, “hip” and “edgy” Can you lay down clear boundaries between “cool”, “hip” and “edgy”?

10. Ideas, Concepts, Constructs and Variables E.g. “I want to make advertising that is “contemporary” and “effective” Can you lay down clear boundaries between the two?

11. Ideas, Concepts, Constructs and Variables 1. E.g. “Did you feel that you identified yourself with the characters / situation in the ad?” Not in the least 12345 Completely Variable: E.g. “Did you buy the product when you last went to the store?” Y/N Variable:

12. Construct vs. Variable Construct –An idea / concept which stands on its own –In the conceptual / abstract domain –E.g. attitude, satisfaction, love, romance, commitment, motivation, etc. –May have several dimensions e.g. dimensions of attitude, etc. Variable –The operationalization of the construct –A variable can be measured –E.g. the operationalization of attitude is “liking”; of romance could be “attraction” etc. –If a construct has several dimensions, its variable has several factors e.g. factors of attitude, etc.

13. Measurement and Scaling Measurement – standardized process of assigning numbers / symbols to characteristics of objects according to pre-specified rules –One-to-one correspondence between the number / symbol and the characteristic –Assignment to be invariant over time and objects Scaling – process of creating a continuum on which objects are located according to the amount of the measured characteristic they possess

14. Classification of attitude scales Attitude Scales Single-Item Scales Continuous Scales Itemized Category Scales Comparative Scales Paired Comparison Scales Rank-Order Scales Constant Sum Scales Pictorial Scales Multi-Item Scales Stapel Scales Likert Scales Semantic Differential Scales

15. Continuous Scales How would you rate Sears as a department store? Version 1: Probably the worst -------------------------------------------- Probably the best Version 2: Probably the worst -------------------------------------------- Probably the best Problems: Unreliable in interpretation hence not widely used

16. Typical Attitude Rating Scales Single item scales – Only one item to measure the construct Comparative Rank order Pictorial Constant sum Multi-item rating scales – More than one item to measure the construct Likert Semantic Differential Stapel

17. Single Item rating scales Advantages –Relatively quick, uncomplicated measurement –Relatively simple to analyze Problems –Can one item measure all the dimensions of the construct?

18. Single item scales Itemized-category scales –Labels each category on the scale Example: What is your overall satisfaction with McDonald’s Hamburgers –Very satisfied –Quite satisfied –Somewhat satisfied –Not at all satisfied

19. What are the problems with this scale

20. Single item scales Comparative Scales – forces respondent to evaluate the object w.r.t. another, on the same attribute Example: Compared to other fast food restaurants, how would you rate McDonald’s Hamburgers on taste –Very superior –Superior –Neither superior or inferior –Inferior –Very inferior

21. What are the problems with this scale How will you overcome this problem?

22. Single item scales Rank-order scales – –requires respondents to arrange a set of objects with regard to a common criterion e.g. interest in an ad, brand preferences, etc. Closely corresponds with the choice process since buyers make direct comparisons amongst competing alternatives

23. Rank Order Scales Brand A _____ Brand B _____ Brand C _____ Brand D _____ Brand E _____ Brand F _____ Brand G _____ Brand H _____ Brand I _____ Please rank the following in order of your preference where 1 = your most preferred and 9 = your least preferred.

24. What are the problems with this scale How will you improve this scale?

25. Single item scales Constant sum scaling –Allocate a fixed number of rating points amongst several objects / attributes to reflect relative preference for the objects / importance of the attributes –Multi-attribute model importance weights

26. Constant Sum Scale Divide 100 points among the following attributes of a PC in terms of how important they are to you in making a purchase decision. Clock Speed:30 Hard drive size:20 RAM size:10 Price:40 TOTAL100 Possible problems with this scale?

27. Single item scales Pictorial Scales –Various levels of the scale are depicted pictorially –Generally used when surveying children / illiterate samples

28. Pictorial Scales Interviewer says: Eating Honey Munch Cereal makes me feel:

29. Designing Scales Number of Scale Categories 2 to infinity (Problems?) 5 – 7 preferred Strength of the Anchors colorful vs. very colorful vs. extremely colorful Strong anchors are less likely to be used Balance of a Scale balanced vs. unbalanced (problems with unbalanced scales?) Equal number of categories on both sides

30. Designing Scales Types of poles used in the scale Sweet and not-sweet vs. sweet and bitter Problems? Labeling of the Categories no labels vs. some labels vs. all labels Labeling reduces ambiguity Labeling also causes cracks

31. Designing scales Number of response alternatives –Five to seven is a good number –Two to three generally stifle responses and frustrate respondents –More than nine is superfluous –An odd number is preferred since a neutral position can be legitimately adopted “Don’t Know” option –Use it when there is a distinct possibility –Overuse may attract fence-sitters’ responses

32. Multiple Item Scales Attitudes to complex objects like cars, insurance, credit cards, etc. may have many facets Unrealistic to expect just one item to capture all these facets Here we use multi-item scales Example: Attitudes to Winthrop University

33. Likert Scale Require respondents to indicate their degree of agreement / disagreement with a variety of statements related to the attribute or object Also called summated scales because scores on individual items are summed to obtain scores for respondents

34. Likert scale example – Satisfaction survey of Bank Strongly Disagree DisagreeNeutralAgreeStrongly Agree Courteous service 123 4 5 Convenient locations 12 3 45 Convenient hours 1 2345 Low interest loans 1234 5

35. Semantic Differential Scale Used to describe a set of beliefs that comprise a person’s image of an object Each scale item is bounded at each end by a polar adjective or phrase / bipolar adjectives or phrases Can be spatially represented on profile maps to a clearer understanding

36. Semantic Differential Scale Low Price Bitter Smooth Tangy Consistent Quality Spotty Quality High Price Not Bitter 1 1

37. Stapel Scale HeavyTangyConsistent Quality -3 -2 +1 +2 +3 -3 -2 +1 +2 -3 -2 +1 +2 +3

38. Exercise – Identify the scale

40. Accuracy of Attitude Measurements Reliability –Does the scale perform consistently over time and over different sets of respondents? –Test-Retest reliability: administering the same scale at two different points in time to the same / different sample –Absence of reliability induces random error in the measurement –Reliability of 0.7 and above is generally good

41. Reliability of Attitude to Brand scale from Marketing Literature On a scale of 1 to 5, please rate your feelings about Pantene : Bad12345Good Dislike very 12345Like very muchmuch Unpleasant12345Pleasant Poor quality12345High quality Reliability: 0.88 Source: Mitchell Andrew A. & J. C. Olsen (1981), “Are Product Attribute Beliefs the only Mediator of Advertising Effects on Brand Attitudes?” Journal of Marketing Research, 18 (3), (August) 318-32

42. Accuracy of Attitude Measurements Validity –Does the scale measure what it is intended to measure? –Absence of validity induces systematic error in the measurement i.e. the scale is measuring something else over and above the construct in question (e.g. attitudes) –A valid measure is one that reflects the true score

43. Accuracy of attitude measurements Observed score = true score + systematic error + random error Hence a valid measure has both zero systematic and random errors If random error is zero (i.e. the scale is perfectly reliable) it may still not be valid –The scale may be consistently measuring something else Hence reliability is a necessary but not sufficient pre-condition of validity

44. Types of validity Face validity – a knowledgeable conclusion about the scale validity Convergent validity –Criterion validity – does the variable predict another variable satisfactorily Does attitude to brand predict purchase intentions, both measured at the same time? –Predictive validity – if the DV is measured in the future Does college GPA predict the amount of salary you earn in the future? Does attitude to brand predict future buying behavior?

45. Types of validity Discriminant validity –Is your construct different from another construct –Are attitude to brand and purchase intentions two different constructs, or the same construct with two different labels? –Effect of attitude to brand and purchase intentions on purchase behavior Construct validity –Conclusion about the measure after testing reliability, convergent and discriminant validity

46. Accuracy of Attitude Measurements Sensitivity –Ability of the scale to capture meaningful differences in attitudes –Can be achieved by increasing the levels but the greater the levels the lower the reliability –Generally 5 to 7 levels are good Generalizability –Ease of scale administration and interpretation in different research settings Relevance –Validity x Reliability (between 0 to 1) –Meaningfulness to measure a construct

47. Accuracy of Attitude Measurements Dimensionality –Does the construct consist of only one dimension or more than one dimensions –E.g. Attitudes – 1,2 or 3 dimensions? –Measured through a factor analysis