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Chapter 7
Measurement and Scaling
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Learning Objectives
• Understand the role of measurement in marketing research
• Explain the four basic levels of scales
• Describe scale development and its importance in gathering primary data
• Discuss comparative and noncomparative scales
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Measurement in Information Research
• Value of measurement in marketing
– Accurate measurement is essential to effective decision making
• Example – Predicting the success of a product based on current consumer preferences
• Overview of the measurement process
– Measurement: Integrative process of determining the intensity or amount of information about constructs, concepts, or objects
• Tasks – Construct selection and scale measurement
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Construct
• Hypothetical variable made up of a set of component responses or behaviors that are perceived to be related
– Construct development: Integrative process in which researchers determine what specific data should be collected for solving the defined research problem
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Exhibit 7.1 – Examples of Concrete Features and Abstract Constructs of Objects
Objects
Consumer Concrete properties: Age, sex, marital status, income, brand last
purchased, dollar amount of purchase, types of products purchased, and
color of eyes and hair
Abstract properties: Attitudes toward a product, brand loyalty, high-
involvement purchases, emotions (love, fear, anxiety), intelligence, and
personality
Organization Concrete properties: Name of company, number of employees, number of
locations, total assets, Fortune 500 rating, computer capacity, and types and
numbers of products and service offerings
Abstract properties: Competence of employees, quality control, channel
power, competitive advantages, company image, and consumer-oriented
practices
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Exhibit 7.1 – Examples of Concrete Features and Abstract Constructs of Objects (continued)
Marketing
Constructs
Brand loyalty Concrete properties: The number of times a particular brand is purchased,
the frequency of purchases of a particular brand, amount spent
Abstract properties: Like/dislike of a particular brand, the degree of
satisfaction with the brand, and overall attitude toward the brand
Customer
satisfaction
Concrete properties: Identifiable attributes that make up a product, service, or
experience
Abstract properties: Liking/disliking of the individual attributes making up the
product, positive feelings toward the product
Service quality Concrete properties: Identifiable attributes of a service encounter, for
example amount of interaction, personal communications, and service
provider’s knowledge
Abstract properties: Expectations held about each identifiable attribute and
evaluative judgment of performance
Advertising recall Concrete properties: Factual properties of the ad (for example, message,
symbols, movement, models, and text), aided and unaided recall of ad
properties
Abstract properties: Favorable/unfavorable judgments, attitude toward the ad
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Scale Measurement
• Process of assigning descriptors to represent the range of possible responses to a question about a particular object or construct
– Scale points: Designated degrees of intensity assigned to the responses in a given questioning or observation method
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Basic Scale Levels
Nominal Scale
• Questions require respondents to provide only some type of descriptor as the raw response
Ordinal Scale
• Allows a respondent to express relative magnitude between the answers to a question
Interval Scale
• Demonstrates absolute differences between each scale point
Ratio Scale
• Allows the researcher to identify the absolute differences between each scale point and make comparisons between the responses
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Exhibit 7.2 – Examples of Nominal Scales
Example 1:
Please indicate your marital status.
__ Married __ Single __ Separated __ Divorced __ Widowed
Example 2:
Do you like or dislike chocolate ice cream?
__ Like __ Dislike
Example 3:
Which of the following supermarkets have you shopped at in the last 30 days?
Please check all that apply.
__ Albertson’s __ Winn-Dixie __ Publix __ Safeway __ Walmart
Example 4:
Please indicate your gender:
__ Female __ Male __ Transgender
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Exhibit 7.3 – Examples of Ordinal Scales
Example 1:
We would like to know your preferences for actually using different banking methods. Among the
methods listed below, please indicate your top three preferences using a “1” to represent your first
choice, a “2” for your second preference, and a “3” for your third choice of methods. Please write the
numbers on the lines next to your selected methods. Do not assign the same number to two methods.
__ Inside the bank __ Bank by mail
__ Drive-in (Drive-up) windows __ Bank by telephone
__ ATM __ Internet banking
__ Debit card
Example 2:
Which one statement best describes your opinion of the quality of an Intel PC processor? (Please
check just one statement.)
__ Higher than AMD’s PC processor
__ About the same as AMD’s PC processor
__ Lower than AMD’s PC processor
Example 3:
For each pair of retail discount stores, circle the one store at which you would be more likely to shop.
__ Kmart or Target
__ Target or Walmart
__ Walmart or Kmart
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Exhibit 7.4 – Examples of Interval Scales
Example 1:
How likely are you to recommend
the Santa Fe Grill to a friend?
Definitely Will Not Recommend Definitely Will Recommend
1 2 3 4 5 6 7
Example 2:
Using a scale of 0-10, with “10” being Highly Satisfied and “0” being Not
Satisfied At All, how satisfied are you with the banking services you currently
receive from (read name of primary bank)? Answer:___
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Exhibit 7.4 – Examples of Interval Scales (continued)
Example 3:
Please indicate how frequently you use different banking methods. For each of
the banking methods listed below, circle the number that best describes the
frequency you typically use each method.
Banking Methods Never Use Use Very Often
Inside the bank 0 1 2 3 4 5 6 7 8 9 10
Drive-up window 0 1 2 3 4 5 6 7 8 9 10
24-hour ATM 0 1 2 3 4 5 6 7 8 9 10
Debit card 0 1 2 3 4 5 6 7 8 9 10
Bank by mail 0 1 2 3 4 5 6 7 8 9 10
Bank by phone 0 1 2 3 4 5 6 7 8 9 10
Bank by Internet 0 1 2 3 4 5 6 7 8 9 10
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Exhibit 7.5 – Examples of Ratio Scales
Example 1:
Please circle the number of children under 18 years of age currently living in
your household.
0 1 2 3 4 5 6 7 If more than 7, please specify: _____
Example 2:
In the past seven days, how many times did you go shopping at a retail
shopping mall?
_____ # of times
Example 3:
In years, what is your current age?
_____ # of years old
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Evaluating Measurement Scales
• Scale reliability – Extent to which a scale can reproduce the same or similar measurement results in repeated trials
• Scale reliability is assessed by:
– Test-retest technique
– Equivalent form technique
– Internal consistency technique
• Split-half test
• Coefficient alpha (Cronbach’s alpha)
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Evaluating Measurement Scales (continued)
• Scale validity – Assesses the accuracy of a measurement scale
– Face validity – Based on the researcher’s skills of intuitive evaluation
– Content validity – Measures the extent to which a construct represents all the relevant dimensions
– Convergent validity – Evaluated with multi-item scales
– Discriminant validity – Extent to which a single construct differs from other constructs
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Criteria for Scale Development
• Intellectual capacity of respondents
• Discriminatory power: Scale’s ability to discriminate between the categorical scale responses (points)
• Use of balanced or unbalanced scales
• Use of forced or nonforced choice scales
• Inclusion of negatively worded statements
• Desired measures of central tendency and dispersion
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Exhibit 7.7 – Relationships between Scale Levels and Measures of Central Tendency and Dispersion
Basic Levels of Scales
Measurements Nominal Ordinal Interval Ratio
Central Tendency
Mode Appropriate Appropriate Appropriate Appropriate
Median Inappropriate More Appropriate Appropriate Appropriate
Mean Inappropriate Inappropriate Most Appropriate Most Appropriate
Dispersion
Frequency Distribution Appropriate Appropriate Appropriate Appropriate
Range Inappropriate More Appropriate Appropriate Appropriate
Estimated Standard
Deviation
Inappropriate Inappropriate Most Appropriate Most Appropriate
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Scales to Measure Attitudes and Behaviors
• Likert scale
– Asks respondents to indicate the extent to which they agree or disagree with a series of mental belief or behavioral belief statements about a given object
• Semantic differential scale: Unique bipolar ordinal scale that captures attitudes or feelings about a given object
– Dimensions – Expertise, trustworthiness, and attractiveness
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Scales to Measure Attitudes and Behaviors (continued)
• Behavioral intention scale
– Captures the likelihood that people will demonstrate some type of predictable behavior intent toward purchasing an object or service in a future time frame
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Exhibit 7.8 – Construct or Scale Development Process
Steps Activities
1. Identify and define construct Determine construct dimensions/factors
2. Create initial pool of attribute
statements
Conduct qualitative research, collect secondary data,
and identify theory
3. Assess and select reduced set of
items/statements
Use qualitative judgment and item analysis
4. Design scales and pretest Collect data from pretest
5. Complete statistical analysis Evaluate reliability and validity
6. Refine and purify scales Eliminate poorly designed statements
7. Complete final scale evaluation Most often qualitative judgment, but may involve further
reliability and validity tests
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Other Rating Scales
• Noncomparative rating scales
– Require a judgment without reference to another object, person, or concept
• Comparative rating scales
– Require a judgment comparing one object, person, or concept against another on the scale
• Graphic rating scales
– Use a scale point format that presents a respondent with a graphic continuum as the set of possible raw responses to a given question
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Other Rating Scales (continued)
• Rank-order scales
– Allow respondents to compare their own responses by indicating their first, second, third, and fourth preferences, and so forth
• Constant-sum scales
– Require respondents to allocate a given number of points among each separate attribute or feature relative to all the other listed ones
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Scale Measurement Issues
• Single-item scale: Collects data about only one attribute of an object or construct
• Multiple-item scale: Simultaneously collects data on several attributes of an object or construct
• Clear wording prevents ambiguity
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Marketing Research in Action What Can You Learn from a Customer Loyalty Index?
• What level of scale design would be the most appropriate in creating the necessary scale measurements for collecting primary data on each construct?
• For each construct, design an example of the actual scale measurement that could be used to collect the data
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Marketing Research in Action What Can You Learn from a Customer Loyalty Index?
(continued 1)
• Identify the weaknesses associated with how Burke, Inc. measured its Secure Customer Index (SCI®)
– Identify each weakness and explain why it is one
• If you were the lead researcher, what types of scale measurement would you have used to collect the needed data for calculating SCI®?
– Why?
– Write some scale measurements you would use
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Marketing Research in Action What Can You Learn from a Customer Loyalty Index?
(continued 2)
• Do you agree or disagree with the Burke, Inc. interpretation of the value they provide their clients using the Customer Loyalty Index?
– Support your response