Attitude Measurement What is an Attitude

Attitude Measurement

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

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)

Multi-Attribute Attitude Models n Ab = b i e i i=1 Ab = attitude toward brand bi = belief about the relationship between brand attribute i ei = attribute importance weight i n = number of salient attributes

Multi-Attribute Attitude Models Example Attribute Value (ei) Store X Store Y Store Z Wide Selection 0. 3 +2 +3 +3 Low Price 0. 2 +3 -2 -1 High Quality 0. 3 -1 +3 +1 Convenient location 0. 2 +2 +2 +3 biei for Store X: (0. 3)(+2) + (+3)(0. 2) + (-1)(0. 3) + (+2)(0. 2) = 1. 3 biei for Store Y: (+3)(0. 3) + (-2)(0. 2) + (+3)(0. 3) + (+2)(0. 2) = 1. 8 biei for Store Z: (+3)(0. 3) + (-1)(0. 2) + (+1)(0. 3) + (+3)(0. 2) = 1. 6

Attitude Research Attitude Action/ Behavior

Three Components of Attitude Cognitive Component Affective Component Action Component

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

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”?

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

Ideas, Concepts, Constructs and Variables • 1. . E. g. How much do you like Winthrop University? • Hate it----Dislike it----neither like nor dislike ---Like it----Love it – Variable: • 2. E. g. “Did you buy the product when you last went to the store? ” Y/N • Variable:

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.

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

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

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

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

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

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

What are the problems with this scale

Single item scales • Comparative Scales – forces respondent to evaluate the object w. r. t. another, on the same attribute • Example: • Compared to Burger King, how would you rate Mc. Donald’s Hamburgers on taste – – – Very superior Superior Neither superior or inferior Inferior Very inferior

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

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

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

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

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: Hard drive size: RAM size: Price: TOTAL 30 20 10 40 100 Possible problems with this scale?

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

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

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

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

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 responses from disinterested respondents

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

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

Likert scale example – Satisfaction survey of Bank Strongly Disagree Neutral Disagree Agree Strongly Agree Courteous service 1 2 3 4 5 Convenient locations 1 2 3 4 5 Convenient hours 1 2 3 4 5 Low interest loans 1 2 3 4 5

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

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

Stapel Scale Heavy +3 Consistent Quality +3 Tangy +3 +2 +2 +2 +1 +1 +1 -1 -2 -2 -2 -3 -3 -3

Exercise – Identify the scale

Exercise – Identify the scale

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

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

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

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?

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

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

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