Customer Marketing Analytics Lecture 3
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Questions and Answers

What is one primary reason for using multi-item scales instead of single-item scales?

  • To reduce the need for scale evaluation.
  • To capture the complex nature of the construct. (correct)
  • To ensure every respondent answers the same way.
  • To make the measurement process faster.

    • Which type of scale primarily compares one item against another?

  • Reference scale
  • Comparative scale (correct)
  • Non-comparative scale
  • Ratio scale

    • What is evaluated to ensure that a scale is measuring what it is intended to measure?

  • Reliability
  • Usability
  • Applicability
  • Validity (correct)

    • In the multiple item measurement example for impulsive buying tendency, how is the score calculated?

    <p>By summing the item scores.</p> Signup and view all the answers

    Which characteristic makes single-item scales sufficient for certain constructs?

    <p>They assess objective and concrete constructs.</p> Signup and view all the answers

    What is the main focus of the lecture on Customer Marketing Analytics?

    <p>Measurement and Scaling in Marketing</p> Signup and view all the answers

    Which type of scale involves direct comparisons between options?

    <p>Comparative scales</p> Signup and view all the answers

    What are the two key aspects evaluated in scale evaluation?

    <p>Reliability and Validity</p> Signup and view all the answers

    Which of the following is NOT a construct that can be challenging to measure?

    <p>Age</p> Signup and view all the answers

    What is a potential consequence of not completing the prerequisite assignment for Customer Marketing Analytics?

    <p>Inability to pass the course</p> Signup and view all the answers

    Which of the following best describes 'dimensionality' in the context of scale analysis?

    <p>The number of distinct constructs measured</p> Signup and view all the answers

    What is the purpose of factor analysis in measurement?

    <p>To identify underlying relationships between variables</p> Signup and view all the answers

    Which of the following best represents a non-comparative scale?

    <p>Likert scale</p> Signup and view all the answers

    What is the initial step in defining a construct's domain?

    <p>Examine literature related to the construct</p> Signup and view all the answers

    Which type of validity assesses whether a scale performs as expected in relation to other variables?

    <p>Criterion validity</p> Signup and view all the answers

    What does convergent validity evaluate?

    <p>Whether a scale correlates positively with other measures of the same construct</p> Signup and view all the answers

    What is nomological validity concerned with?

    <p>The scale's behavior in accordance with the theoretical framework</p> Signup and view all the answers

    Which action is taken if an item in a scale has the lowest item to total correlation?

    <p>The item is deleted if its removal increases alpha</p> Signup and view all the answers

    What is the purpose of pretesting a questionnaire?

    <p>To ensure the understandability of all the items</p> Signup and view all the answers

    Which aspect is typically not addressed in discriminant validity?

    <p>Correlation with similar constructs</p> Signup and view all the answers

    What does a high alpha coefficient indicate about a scale?

    <p>The scale has high reliability</p> Signup and view all the answers

    What was the purpose of asking respondents about their awareness and purchase of rock record titles?

    <p>To evaluate their behavior related to music consumption</p> Signup and view all the answers

    What does a positive correlation between the Innovativeness variable and Rock Music Expertise indicate?

    <p>Higher innovativeness is associated with higher music expertise</p> Signup and view all the answers

    What action was taken regarding the item with the lowest item to total correlation during the scale refinement process?

    <p>It was deleted if that deletion increased alpha</p> Signup and view all the answers

    What was the alpha coefficient achieved after refining the scale?

    <p>.80</p> Signup and view all the answers

    What was one method used to ensure the understandability of the questionnaire items?

    <p>Pretesting with a sample of students</p> Signup and view all the answers

    What aspect of the scale did experts evaluate to improve its quality?

    <p>Aspects of innovativeness not represented in the scale</p> Signup and view all the answers

    What variable served as the primary measure of interest in this study?

    <p>Yes responses regarding awareness and purchase</p> Signup and view all the answers

    What type of correlation did the scale demonstrate with consumers’ overall trait innovativeness?

    <p>Positive correlation</p> Signup and view all the answers

    What does the 'elbow' in a scree plot indicate?

    <p>The optimal number of factors to retain</p> Signup and view all the answers

    How do you determine the number of factors to retain using the elbow rule?

    <p>By taking the number of factors before the elbow point</p> Signup and view all the answers

    What does a communality value less than 0.30 imply about a variable?

    <p>The variable is considered quite unique</p> Signup and view all the answers

    What is the main purpose of communalities in factor analysis?

    <p>To quantify the variance each variable explains</p> Signup and view all the answers

    Which item has the lowest communality from the provided values?

    <p>I show confidence in my staff</p> Signup and view all the answers

    Which method is used for the extraction of factors in this analysis?

    <p>Principal Component Analysis</p> Signup and view all the answers

    What is the implication of having all communalities reported as very high?

    <p>All variables are strongly related to the factors extracted</p> Signup and view all the answers

    What is the communality value for the statement 'I rarely overlook important factors when plans are made'?

    <p>0.650</p> Signup and view all the answers

    Study Notes

    Customer Marketing Analytics Lecture 3: Measurement and Scaling

    • Measurement in Marketing
      • How to measure concepts like price sensitivity, brand attitude, and customer loyalty?
      • Some concepts are easy to observe and measure (e.g., price, income) but others are more difficult (e.g., brand attitude, customer loyalty).
    • Types of Scales
      • Comparative scales: compare stimuli to each other (e.g., rank ordering brands).
      • Non-comparative scales: evaluate stimuli independently (e.g., rating a brand on a scale of 1 to 5).
    • Multiple Item Measurement Theory
      • Why use multi-item scales (e.g., questionnaires with several questions) instead of single-item scales?
      • To increase reliability by minimizing error.
      • To capture the complexity of constructs by improving validity.
      • Single-item scales are sometimes sufficient for concrete, objective constructs (e.g., age, income, purchase intention).
    • Construct Measurement
      • Latent variable: an unobservable concept like "impulsive buying tendency."
      • Indicators: observable items that represent the latent variable (e.g., multiple questions about impulsive buying).
      • By summing scores from multiple indicators, we can estimate the latent variable.
    • Scale Evaluation
      • Reliability: consistency of measurement.
      • Validity: whether the scale measures what it intends to measure.
    • Reliability
      • Internal consistency: how consistently different scale items are measuring the same construct.
      • Test-retest reliability: how consistent results are over multiple administrations of the same scale.
    • Validity
      • Criterion validity: how well the scale predicts related behavior or other variables.
      • Construct validity: aligns with theoretical understanding of the construct.
        • Convergent validity: high correlation with other measures of the same construct.
        • Discriminant validity: low correlation with measures of different constructs.
        • Nomological validity: confirms relationships between the scale and other constructs within a theoretical framework.
    • Factor Analysis and Dimensionality
      • Factor analysis: Statistical technique to identify underlying factors from correlated variables (scale items).
      • Dimensionality: Number of underlying dimensions or factors being measured by a scale.
      • Scree Plot: visual representation of eigenvalues (variance explained by each factor) to determine the optimal number of factors.
      • Eigenvalues: Measure of variance explained by each factor.
      • "Elbow rule": Look for the steep drop in eigenvalues to determine the optimal number of factors.
    • Communalities
      • How much variance of a single variable is explained by all extracted factors.
      • High communality implies the variable is closely related to the common factor structure.
      • Low communality (< .30) implies the variable is unique and may be a candidate for removal.
    • Example: Measuring Consumer Innovativeness
      • The text discusses a study measuring consumer innovativeness.
      • Different techniques were used to assess the scale's reliability and validity.
      • Reliability: Alpha coefficient of .80 demonstrates internal consistency.
      • Validity:
        • The scale demonstrates criterion validity by correlating positively with rock music expertise.
        • It also demonstrates construct validity by correlating with overall trait innovativeness, but not with need for uniqueness (discriminant validity).
      • Example of Testing Reliability and Validity:
        • Deleting items: Ensuring that removing items does not negatively impact internal consistency.
        • Pretesting with experts: Verifying that the scale measures the intended construct.
        • Correlating with other measures: Confirming expected relationships with other variables.

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    Description

    This quiz covers Measurement and Scaling in marketing analytics. It explores how to measure complex concepts like brand attitude and customer loyalty, the different types of scales, and the importance of multiple item measurement theory. Test your understanding of these essential marketing measurement techniques.

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