U Unit 6 [MT355] Page 1 of 3 Unit 6 Assignment.docx

U
Unit 6 [MT355]
Page 1 of 3
Unit 6 Assignment: Design Appropriate Data Collection
Methods
In this Assignment, you will be assessed based on the following
outcome:
MT355-3: Design appropriate data collection methods.
Marketing researchers must become highly skilled at designing
appropriate methods of data collection,
especially when it comes to designing a data collection
methodology and developing survey questions
used in the construction of a data collection form.
In Part 1 of this Assignment, you will demonstrate your ability
to design a data collection methodology
using the knowledge obtained from Chapters 6 and 7 in your
textbook.
In Part 2 of this Assignment, you will demonstrate your ability
to develop a viable research study

questionnaire using the knowledge you obtain from Chapter 8 in
your textbook. Be sure to conduct
additional research to learn best practices used in marketing
research questionnaire development.
Directions for completing this Assignment
While completing this Assignment, it is essential that you
consider the ethics behind your data collection
methodology in Part 1, and in every question you develop in
Part 2. Always consider the validity of your
questions before making them ready for data collection.
Part 1: Situation Analysis – Research Problem Defined
It is essential for marketing researchers to develop an ability to
design appropriate data collection
methods. Follow the theoretical and conceptual methods you
learned about in Chapters 6 and 7 in the
“Essentials of Marketing Research” textbook.
Using the Random Scenario Generator (RSG), select a scenario
for your Assignment. (Reminder: The
RSG will prompt you to select 1 of 3 options for each of the
variables. Once you have selected from each
variable category, the resulting scenario is to be the basis for
your work on this Assignment. Each
student’s scenario will be documented.)

Part 1 will include:
-words (4-5 pages), in addition to the title, reference,
and appendix pages, informative
essay to define a research problem.
structure, double-spacing, 12-point Times
New Roman font, and it should follow all other APA 6th edition
formatting and citation guidelines.
of three academic resources) and
how this research will be useful in solving the research
problem.
ct the
research and explanation of how you will
choose your sample and collect your data.
https://kapextmediassl-
a.akamaihd.net/business/Media/MT355/MT355_1904C/RSG/stor
y.html
U
Unit 6 [MT355]

of 3
Part 2: Research Survey Design
Part 2 will include the following sections:
questionnaire design, and a 10-question market
research survey based on your scenario generated though the
RSG.
from Part 1)
o Create three open-ended questions
o Create three closed-ended questions
o Create four scaled response questions
this!)
you will do and why this is important.)
implementation and who will do it?)

For Unit 6 Assignment Submission:
Review this tutorial on Searching for Information in the
Library.
Directions for Submitting Your Assignment
Review the grading Rubric below before beginning this
Assignment. For additional help with writing an
informative essay and APA citation, please visit the W riting
Resources accessed through the Academic
Success Center within the Academic Tools area of the course.
Compose your Assignment as a Microsoft
W ord document and save it with your first name initial and last
name (Example: JDeem -MT355
Assignment- Unit6.docx). Submit your Assignment to the Unit 6
Assignment Dropbox by the end of the
unit.
MT355 Unit 6 Assignment: Develop a Survey Possible

Points
Earned
Points
Content, Focus, Use of Text/Outside Sources
Part 1: Situation Analysis – Research Problem Defined
Formulated a sampling plan to direct the primary data collection
process in a
marketing research study. W rite an informative essay with a
minimum of 1,000
words.
Explained the research problem. 5
Presented secondary data to substantiate the need for the
research study.
Collected a minimum of two primary and two secondary data
resources to
improve your understanding of the research problem and topic
area. Explained
why each research resource will be useful in solving the
research problem.
5
https://library.purdueglobal.edu/infolit_searchingexploration

U
Unit 6 [MT355]
Page 3 of 3
MT355 Unit 6 Assignment: Develop a Survey Possible
Points
Earned
Points
Designed a sampling plan, covering all steps in the design of a
sampling plan
as presented in Chapters 6 and 7 of the textbook.
Prepared a brief plan on how the sample was chosen, and
explained how the
data will be collected from the sample in the marketing research
study.
5
Explained how comparative or noncomparative scales are used
in the data
collection plan for your marketing research study.
5
Explained the validity of the survey developed. Used research
to support the

explanation. 5
Part 2: Research Survey Design
Applied all steps in the questionnaire design. 20
Developed three open-ended response questions. 5
Developed three closed-ended questions. 5
Developed four scaled response questions. 5
Clarity / Organization
You are expected to meet the following requirements with ease
in a 300 level
course. Penalties will be calculated as a percentage up to 50%
of the grade
and will apply if the following criteria are not met.
Applied informative essay style. W riting style, grammar, and
APA 6th edition
formatting.
Applied proper APA 6th edition formatting style; including in-
text citations, title
page, and reference page.
No spelling and grammatical mistakes.

Used appropriate language related to the strategy theories,
concepts, and
principles learned.
Professional use of abbreviations and acronyms.
Total Gross Assignment Score: 60
Late Penalty (-10% 1 week late, -20% for over one week. Prior
approval for
any projects later than 2 weeks.)
Total
Copyright © 2017 McGraw-Hill Education. All rights reserved.
No reproduction or distribution without the prior written
consent of McGraw-Hill Education.
Chapter 6
Sampling: Theory
and Methods

Learning Objectives
• Explain the role of sampling in the research
process
• Distinguish between probability and
nonprobability sampling
• Understand factors to consider when
determining sample size
• Understand the steps in developing a
sampling plan
Value of Sampling in Marketing
Research
• Sampling: Selection of a small number of
elements from a larger defined target group of
elements
– Assumes that the information gathered from the
small group helps make accurate judgments about
the larger group

Sampling as a Part of the Research
Process
• Sampling is used when it is impossible or
unreasonable to conduct a census
– Census: Research study that includes data about
every member of the defined target population
• Sampling plays an important role in designing
questionnaires
– Sampling decisions influence:
• Type of survey design
• Survey instrument
Basics of Sampling Theory
• Population: Identifiable group of elements of
interest to the researcher
– Pertinent to the information problem
• Defined target population: Complete set of

elements identified for investigation
– Sampling units: Target population elements
available for selection during the sampling process
• Sampling frame: List of all eligible sampling
units
Central Limit Theorem (CLT)
• Sampling distribution derived from a simple
random sample will be approximately
normally distributed
• Aids in understanding concepts of:
– Sampling error
– Statistical significance
– Sample sizes
Assessing Sampling Quality

• Challenges
– Census - Seldom conducted in survey research
– Sampling error - Determined only after a sample is
drawn and data collection is completed
Assessing Sample Quality
• Sampling error: Any bias attributable to
mistakes in either drawing a sample or
determining the sample size
• Nonsampling error: Bias that occurs in a
research study regardless of whether a sample
or census is used
Sampling Designs
• Probability sampling: Each sampling unit in
the defined target population has a known
probability of being selected for the sample
• Nonprobability sampling: Probability of

selection of each sampling unit is not known
– Selection is based on the judgment of the
researcher
• May or may not be representative of the target
population
Types of Probability and
Nonprobability Sampling Methods
Probability sampling
• Simple random sampling
• Systematic random
sampling
• Stratified random sampling
• Cluster sampling
Nonprobability sampling
• Convenience sampling
• Judgment sampling
• Quota sampling

• Snowball sampling
Probability Sampling Designs
• Simple random sampling: Every sampling unit
has a known and equal chance of being
selected
• Systematic random sampling: Defined target
population is ordered and selected
systematically
– Forms - Customer list, taxpayer roll, and
membership roster
Probability Sampling Designs (continued 1)
• Stratified random sampling: Separates the
target population into groups or strata and
selects samples from each stratum
– Proportionately stratified sampling: Each stratum
is dependent on its size relative to the population

– Disproportionately stratified sampling: Size of
each stratum is independent of its relative size in
the population
• Optimal allocation sampling: Sample size of a stratum
is determined based on its relative size and variability
Probability Sampling Designs (continued 2)
• Multisource sampling: Used when a single source
cannot generate a large or low incidence sample
• Cluster sampling: Sampling units are divided
into mutually exclusive and collectively
exhaustive subpopulations, called clusters
– Area sampling: Clusters are formed by geographic
designations
• Convenience sampling: Samples are drawn at
the convenience of the researcher

• Judgment sampling: Participants are selected
based on an experienced individual’s opinion
that they will meet the study's requirements
(continued)
• Quota sampling
– Participants are selected according to prespecified
quotas regarding demographics, attitudes,
behaviors, or some other criteria
• Snowball sampling: Set of chosen respondents
that helps a researcher identify additional
people to be included in a study
– Also called referral sampling
Exhibit 6.4 - Factors to Consider in
Selecting the Sampling Design
Selection Factors Questions

Research objectives Do the research objectives call for the use
of qualitative or quantitative research
designs?
Degree of accuracy Does the research call for making
predictions or inferences about the defined target
population, or only preliminary insights?
Resources Are there tight budget constraints with respect to
both dollars and human resources
that can be allocated to the research project?
Time frame How quickly does the research project have to be
completed?
Knowledge of the target population Are there complete lists of
the defined target population elements? How easy or
difficult is it to generate the required sampling frame of
prospective respondents?
Scope of the research Is the research going to be international,
national, regional, or local?
Statistical analysis needs To what extent are accurate statistical
projections and/or testing of hypothesized
differences in the data required?

Probability Sample Sizes
• Factors that determine sample sizes with
probability designs
– Population variance
– Level of confidence desired in the estimate
– Degree of precision desired in estimating the
population characteristic
• Precision: Acceptable amount of error in the sample
estimate
Probability Sampling and Sample
Sizes
• Formula used to calculate a sample size
2( )
n Z B,CL
σ

e
2
2
– ZB,CL - Standardized z-value associated with the
level of confidence
– σμ - Estimate of the population standard deviation
(σ) based on some type of prior information
– e - Acceptable tolerance level of error (stated in
percentage points)
Probability Sampling and Sample
Sizes (continued)
• Calculating sample size when the estimates of
a population proportion are of concern
2
B,CL 2
[ × ]

= ( )
P Q
n Z
e
– ZB,CL - Standardized z-value associated with the
level of confidence
– P - Estimate of expected population proportion
having a desired characteristic based on intuition
or prior information
– Q - – [1 – P]
– e - Acceptable tolerance level of error
Sampling from a Small Population
• Strategy used to prevent an unnecessarily
large sample size
– Calculated sample size is multiplied by the
following correction factor
N/(N + n − 1)
• N - Population size

• n - Calculated sample size determined by the original
formula
– Thus,
Sample size=(Specified degree of confidence × Variability
/Desired precision)2
× N/(N + n − 1)
Nonprobability Sample Sizes and Other
Sampling Methods
• For nonprobability samples:
– Sample size formulas cannot be used
– Determining the sample size is a subjective and
intuitive judgment
• Other sample size determination methods are
less formal
– Basing sample size on similar previous studies
– Determining sample size on the basis of the
number of questions in a questionnaire

Steps in Developing a Sampling
Plan
• Blueprint or framework needed to ensure that
the data collected are representative of the
defined target population
• Developing a sampling plan
– Define the target population
– Select the data collection method
– Identify the sampling frames needed
– Select the appropriate sampling method
Steps in Developing a Sampling
Plan (continued)
– Determine necessary sample sizes and overall
contact rates
– Create an operating plan for selecting sampling
units
– Execute the operational plan

Marketing Research in Action
Developing a Sampling Plan for a New Menu Initiative
Survey
• How many questions should the survey
contain to adequately address all possible new
menu items, including the notion of assessing
the desirability of new cuisines?
– How can it be determined that all necessary items
will be included on the survey without the risk of
ignoring menu items that may be desirable to
potential customers?
Developing a Sampling Plan for a New Menu Initiative
Survey (continued)
• How should the potential respondents be
selected for the survey?

– Should customers be interviewed while they are
dining?
– Should customers be asked to participate in the
survey upon exiting the restaurant?
– Should a mail or telephone approach be used to
collect information from customers or
noncustomers?
Chapter 8
Designing the
Questionnaire
Learning Objectives
• Describe the steps in questionnaire design
• Discuss the questionnaire development
process
• Summarize the characteristics of good

questionnaires
• Understand the role of cover letters
• Explain the importance of other documents
used with questionnaires
Value of Questionnaires
in Marketing Research
• Questionnaire: Formal framework consisting
of a set of questions and scales designed to
gather primary raw data
• Use questionnaires to collect data that can be turned
into knowledge about a person, object, or issue
Descriptive research designs
• Require researchers to collect a wide range of data
that can be used in predicting change in attitudes and
behaviors and in testing hypotheses
Predictive survey questionnaires

Steps in Questionnaire Design
Step 1 Confirm research objectives
Step 2 Select appropriate data collection
method
Step 3 Develop questions and scaling
Step 4 Determine layout and evaluate
questionnaire
Step 5 Obtain initial client approval
Step 6 Pretest, revise, and finalize
questionnaire
Step 7 Implement the survey
Step 1: Confirm Research Objectives
• Research objectives
– Collect data on selected demographic
characteristics
– Collect data on selected lifestyle dimensions
– Identify preferred banking services, as well as

attitudes and feelings toward those services
– Identify demographic and lifestyle characteristics
of market segments
Step 2: Select Appropriate Data
Collection Method
• Researcher must determine the:
– Data required to achieve the objectives
– Type of respondent demographic information
desired
• Researcher should follow a general-to-specific
order
Step 3: Develop Questions and Scaling
• Question format
– Unstructured questions: Open-ended questions
formatted to allow respondents to reply in their

own words
– Structured questions: Closed-ended questions
that require the respondent to choose from a
predetermined set of responses or scale points
(continued 1)
• Wording
– Avoid ambiguous and difficult words
– Sensitive questions should be structured carefully
• Sensitive questions: Include income, sexual beliefs or
behaviors, medical conditions, financial difficulties,
alcohol consumption, etc. that respondents are likely to
respond to incorrectly
(continued 2)
• Questions and scaling

– Bad questions: Any questions that prevent or
distort the fundamental communication between
the researcher and the respondents
• Questions are bad when they are unanswerable,
leading (loaded), and double-barreled
– Skip questions: Used if the next question or set of
questions should be responded to only by
respondents who meet a previous condition
Step 4: Determine Layout and Evaluate
Questionnaire
• Introductory section: Gives the respondent an
overview of the research
• Screening questions: Identify qualified
prospective respondents
– Prevent unqualified respondents from being
included in the study
• Research questions section: Second section of
the questionnaire that focuses on the research
questions

Questionnaire (continued 1)
• Demographic questions - Last section that
asks personal information
• Response order bias: Occurs when the order
of the questions or closed-end responses to a
particular question influences the answer
given
• Common methods variance (CMV): Biased
variance that results from the measurement
method used in a questionnaire
Questionnaire (continued 2)
• Online survey considerations
– Problems in:
• Determining response rate
• Recruiting participants

• Time taken to complete survey
– Online questionnaire design issues
• Effect of response box size on length of answer in open-
ended questions
• Radio button versus pull-down menu for responses
• Appropriate use of visuals
Step 5: Obtain Initial Client Approval
• Copies of the questionnaire should be given to
all parties involved in the project
– Gives an opportunity for the client to provide
suggestions of topics overlooked or to ask any
questions
• Researcher must obtain final approval of the
questionnaire prior to pretesting
Step 6: Pretest, Revise, and Finalize the

Questionnaire
• Pretest: Guide for conducting a larger main
study
– Provides a final evaluation of the questionnaire
– Helps a researcher determine:
• How much time respondents will need to complete the
survey
• Whether to add or revise instructions
• What to say in the cover letter
Step 6: Pretest, Revise, and Finalize the
Questionnaire (continued)
• Pilot study: Small-scale version of the
intended research study
– Includes all subcomponents that make up the
main study
– Commonly associated with quantitative
descriptive or predictive research studies

Step 7: Implement the Survey
• Focus is on the process followed to collect the
data using the agreed-upon questionnaire
– Process varies depending on whether the survey is
self-administered or interviewer-completed
Role of a Cover Letter
• Cover letter: Separate written communication
to a prospective respondent
• Designed to enhance respondent willingness to
complete and return a survey in a timely manner
– Primary role - Obtain the respondent’s
cooperation and willingness to participate in a
research project
• Good cover letter increases response rates

Exhibit 8.5 - Guidelines for Developing
Cover Letters
Factors Description
1. Personalization Cover letters should be addressed to the
prospective respondent. The research firm's
professional letterhead stationery should be used.
2. Identification of the organization Clear identification of the
name of the research firm conducting the survey or interview.
A disguised approach is most often used but an undisguised
approach that reveals the
actual client (or sponsor) of the study may be used.
3. Clear statement of the study's
purpose and importance
Describe the general topic of the research and emphasize its
importance to the
prospective respondent.
4. Anonymity and confidentiality Give assurances that the
prospective respondent's name will not be revealed. Explain
how the respondent was chosen, and stress that his or her input
is important to the
study's success.

5. General time frame of doing the study Communicate the
overall time frame of the survey or study.
6. Reinforce the importance of
respondent's participation
Communicate the importance of the prospective respondent's
participation.
7. Acknowledge reasons for
nonparticipation in survey or interview
Point out "lack of leisure time." "surveys classified as junk
mail," and "forgetting about
survey" reasons for not participating, and defuse them.
8. Time requirements and incentive Communicate the
approximate time required to complete the survey. Discuss
incentive,
if any.
9. Completion date and where and how
to return the survey
Communicate to the prospective respondent all instructions for
returning the completed
questionnaire.
10. Advance thank-you statement for

willingness to participate
Thank the prospective respondent for his or her cooperation.
Other Considerations in Collecting
Data
• Supervisor instructions
– Supervisor instruction form: Serves as a blueprint
for training people on how to execute an
interviewing process in a standardized fashion
• Outlines the process for conducting a study that uses
personal and telephone interviewers
• Interviewer instructions: Used to train
interviewers on how to:
– Select prospective respondents
Data (continued 1)

– Screen respondents for eligibility
– Conduct the actual interview
• Screening questions
– Ensure that respondents are representative of the
defined target population
• Quotas: Tracking system that collects data
from respondents
– Help ensure that subgroups are represented in the
sample as specified
Data (continued 2)
• Call or contact records: Recording document
that gathers basic summary information about
an interviewer’s performance efficiency

Designing a Questionnaire to Survey Santa Fe Grill
Customers
• Based on the research objectives, does the
current self-administered questionnaire
correctly illustrate sound questionnaire design
principles?
– Please explain why or why not
• Overall, is the current survey design able to
capture the required data needed to address
all the stated research objectives?
– Why or why not?
Designing a Questionnaire to Survey Santa Fe Grill
Customers (continued)
– If changes are needed, how would you change the
survey’s design?
• Evaluate the “screener” used to qualify the
respondents
– Are there any changes needed?

– Why or why not?
Chapter 7
Measurement and
Scaling
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

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
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
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
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

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
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
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
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

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:___
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
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
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)
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

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
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
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
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
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
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
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

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
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

(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
(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

U Unit 6 [MT355] Page 1 of 3 Unit 6 Assignment.docx

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U Unit 6 [MT355] Page 1 of 3 Unit 6 Assignment.docx