1. QUANTITATIVE DESIGN AND ANALYSIS MARK 2048
Instructor: Armand Gervais

2. Chapter 12

3. Learning Objectives
1. Discuss what an attitude is and its three components.
2. Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses.
3. Discuss the differences between noncomparative and comparative scale designs as well as the appropriateness of rating and ranking scale measurements.
4. Identify and discuss the critical aspects of consumer attitudes and other marketplace phenomena that require measurement to allow us to make better decisions.
5. Discuss the overall rules of measurement and explain the differences between single versus multiple measures of a construct as well as direct versus indirect measures.

4. Nature of Attitudes and Marketplace Behaviors
Discuss what an attitude is and its three components. Identify and discuss the critical aspects of consumer attitudes
Nature of Attitudes and Marketplace Behaviors
Marketers Need to Better Understand Their Customers Attitude
learned predisposition to act in a consistent positive or negative way to a given object, idea, or set of information
Components of Attitudes
Cognitive
Beliefs, perceptions and knowledge about and object and its attributes
George Brown has small classes
Need more computer labs
Affective Component
Persons emotions or feelings toward a given object
I love George Brown, Coffee Time is dirty
Behavioral (Conitive) Component
A persons intended or actual behavior response to an object
I will not step inside a Coffee Time donut shop

5. Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Exhibit 12.1

6. Scales to Measure Attitudes and Behaviors
Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Scales to Measure Attitudes and Behaviors
Likert Scale
an ordinal scale format that 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
Scale format
balanced between agreement and disagreement scale descriptors

7. Scales to Measure Attitudes and Behaviors
Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Scales to Measure Attitudes and Behaviors
Series of Hierarchical Steps for Developing a Likert Scale
Step 1: Identify and understand the concept to be studied
Step 2: Assemble a large number of belief statements (e.g. 50 to 100)
3. Step 3: Subjectively classify each statement as having either a “favorable” or “unfavorable” relationship to the specific attitude under investigation. Then the entire list of statements is pretested (e.g. through a pilot test) using a sample of respondents

8. Scales to Measure Attitudes and Behaviors
Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Scales to Measure Attitudes and Behaviors
Step 4: Respondents decide the extent to which they either agree or disagree with each statement, using the intensity descriptors “strongly agree,” “agree,” “not sure,” “disagree,” “strongly disagree.” Each response is then given a numerical weight , such as 5, 4, 3, 2, 1. For assumed favorable statements, a weight of 5 would be given to a “strongly agree” response; for assumed unfavorable statements, a weight of 5 (book has a 5 but should be 1) would be given to a “strongly disagree” response
Step 5: A respondent’ overall-attitude score is calculated by the summation of the weighted values associated with the statements rated

9. Scales to Measure Attitudes and Behaviors
Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Scales to Measure Attitudes and Behaviors
Step 6: Only statements that appear to discriminate between the high and low total scores are retained in the analysis. One possible method is a simple comparison of the top (or highest) 25 percent of the total mean scores with the bottom (or lowest) 25 percent of total mean scores
7. Step 7: In determining the final set of statements (normally 20 to 25, statements that exhibit the greatest differences mean values between the top and bottom total scores are selected
8. Step 8: Using the final set of statements, steps 3 and 4 are repeated in a full study

10. Scales to Measure Attitudes and Behaviors
Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Scales to Measure Attitudes and Behaviors
Likert Scale Extensively Modified
Initially, five scale descriptors were used– Strongly agree, Agree, Neither agree nor disagree, Disagree, and Strongly disagree
Modified Likert scale expands this set to a six-point forced choice format or a seven-point free-choice format
Many researchers treat the Likert Scale Format as an Interval Scale

11. Scales to Measure Attitudes and Behaviors
Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Scales to Measure Attitudes and Behaviors
4. Characteristics of the Likert scale
It is the only summated rating scale that uses a set of agreement/disagreement scale descriptors
It measures only cognitive-based or specific behavioral beliefs
It does not measure intensity levels of affective or behavioral (conative) components
Best utilized for self-administered surveys, or personal interviews, or most online methods to collect the data
It can be used to identify and assess personal or psychographic (life style) traits of individuals

12. Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Exhibit 12.2

13. Scales to Measure Attitudes and Behaviors
Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Scales to Measure Attitudes and Behaviors
Semantic Differential Scale
unique bipolar ordinal scale format that captures a person’s attitudes and/or feelings about a given object
Most cases the scale employs and odd number of scale points thus including a neutral response
One of the few scales that captures both cognitive and affective data for any given factor

14. Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Exhibit 12.3

15. Scales to Measure Attitudes and Behaviors
Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Scales to Measure Attitudes and Behaviors
Different formats for the semantic differential scale format
Why should you randomize the positive and negative pole descriptors?
Halo effect bias
Another issue is the lack of extreme magnitude expressing in the pole descriptors
Dependable undependable attach a narratively expressed extreme
Must be careful not to use non-bi-polar descriptors to represent the poles. IE expert vs. not and expert
Matching standardized intensity descriptors to pole descriptors See exhibit 12.4

16. Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Exhibit 12.4

17. Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Exhibit 12.5

18. Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Exhibit 12.6

19. Scales to Measure Attitudes and Behaviors
Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Scales to Measure Attitudes and Behaviors
Behavior Intention Scale
a special type of rating scale designed to capture the likelihood that people will demonstrate some type of predictable behavior intent toward purchasing an object or service in a future time frame
Notice a time frame is given

20. Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Exhibit 12.7

21. Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Exhibit 12.8

22. Scales to Measure Attitudes and Behaviors
Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses
Scales to Measure Attitudes and Behaviors
Strengths and Weaknesses of Attitude and Behavior Intention Scale Measurements
Knowledge of a individual’s attitudes often is not a good predictor of behavior
To Capture People’s Attitudes and Behaviors–scale measurements are used but there is no one “guaranteed” best approach
Data should be considered to be stable insights rather than as true facts
Behavior intentions are probably the most important area to examine
Behavior can be explained, directly or indirectly, by measuring both the cognitive and affective elements of the consumers’ attitudes

23. Scales to Measure Attitudes and Behaviors
Discuss the differences between noncomparative and comparative scale designs
Scales to Measure Attitudes and Behaviors
Other Types of Comparative and Non-comparative Scale Formats
Noncomparative Rating Scale–scale format that requires a judgment without reference to another object, person, or concept
Comparative Rating–scale format that requires a judgment comparing one object, person, or concept against another on the scale

24. Scales to Measure Attitudes and Behaviors
Discuss the differences between noncomparative and comparative scale designs
Scales to Measure Attitudes and Behaviors
Methods
Graphic Rating Scales
(also referred to as continuous rating scales) use a scale point format that presents a respondent with some type of graphic continuum as the set of possible raw responses to a given question.
Performance Rating Scales
uses an evaluative scale point format that allows the respondents to express some type of postdecision or behavior evaluative judgment about an object.

25. Different Forms of Non-comparative Rating Scales
Exhibit 12.9

26. Scales to Measure Attitudes and Behaviors
Discuss the differences between noncomparative and comparative scale designs
Rank-Order Scales
allow respondents to compare their responses to each other by indicating their first preference and so forth until all the desired responses are placed in rank order
Paired-Comparison Scales
creates a pre-selected group of traits, product characteristics, or features that are paired against one another into two groups; respondents are asked to select which pair is more important to them

27. Scales to Measure Attitudes and Behaviors
Discuss the differences between noncomparative and comparative scale designs
Constant Sum Scales–
require the respondents to allocate a given number of points, usually 100, among several attributes or features based on their importance to the individual; this format requires a person to evaluate each separate attribute or feature relative to all the other listed ones
Most appropriate in self-administered surveys
Requires a lot of mental energy on the part of the respondent

28. Discuss the differences between noncomparative and comparative scale designs
Exhibit 12.10

29. Scales to Measure Attitudes and Behaviors
Discuss the overall rules of measurement and explain the differences between single versus multiple measures of construct and direct versus indirect measures
Scales to Measure Attitudes and Behaviors
When to Use Single-item or Multiple-item Scales
Single-Item Scale Design
when the data requirements focus on collection data about only one attribute of the object or construct being investigated
Multiple-item Scale Design
to measure the object or construct of interest, will have to measure several items simultaneously rather than measuring just one item.
Formative composite scale
Reflective composite scale

30. Scales to Measure Attitudes and Behaviors
Discuss the overall rules of measurement and explain the differences between single versus multiple measures of construct and direct versus indirect measures
Scales to Measure Attitudes and Behaviors
Decision to Use a Single-item versus Multiple-item Scale made in the construct development state
Two factors
Must assess the dimensionality of the construct under investigation
Must deal with the reliability and validity issues of the scales used to collect data

31. Recap of Key Measurement Design Issue
Discuss the overall rules of measurement and explain the differences between single versus multiple measures of construct and direct versus indirect measures
Recap of Key Measurement Design Issue
Construct Development Issues
Constructs should be clearly defined
Avoid double-barreled sub-dimensions
Scale Measurement Issues
All necessary instructions for both respondent and interviewer should be part of the scale measurement setup
Use clear wording and avoid ambiguity
Avoid “leading” phrases or words
Make sure the items are phrased unidimensionally
Make sure the descriptors are relevant to the type of data being sought

32. Scales to Measure Attitudes and Behaviors
Discuss the overall rules of measurement and explain the differences between single versus multiple measures of construct and direct versus indirect measures
Scales to Measure Attitudes and Behaviors
Screening Questions
Use screens before questioning
To identify qualified respondents
Skip Question
Avoid if possible
Instruction must be clearly communicated
Ethical Responsibility of the Researcher
Develop and use the most appropriate scale
Avoid bias

33. Summary Value of Attitude Measurement in Information Research
The Nature of Attitudes and Marketplace Behaviors
Scales to Measure Attitudes and Behaviors

34. Chapter 13

35. Learning Objectives
1. Identify and discuss the critical factors that can contribute to directly improving the accuracy of surveys, and explain why questionnaire development is not a simple process.
2. Discuss the theoretical principles of questionnaire design, and explain why a questionnaire is more than just asking a respondent some questions.
3. Identify and explain the communication roles of questionnaire in the data collection process.
4. Explain why the type of information needed to address a decision maker’s questions and problems will substantially influence the structure and content of questionnaires.

36. Learning Objectives
5. List and discuss the 11 steps in the questionnaire development process, and tell how to eliminate some common mistakes in questionnaire design.
6. Discuss and employ the “flowerpot” approach in developing scientific questionnaires.
7. Discuss the importance of cover letters, and explain the guidelines to help eliminate common mistakes in cover letter designs.

37. Value of Questionnaires in Information Research
Identify and discuss the critical factors that can contribute to directly improving the accuracy of surveys
Collecting Information for Decision Makers
Researcher’s Skill and Ability
Question/scale Measurement Format
Primary Data Need to Create New Information
Questionnaire
Questionnaire construction

38. Theoretical Principles of Questionnaire Design
Discuss the theoretical principles of questionnaire design, and explain why a questionnaire is more than just asking a respondent some questions
Great Weaknesses of Questionnaire Design
Theory
many researchers do not understand the theory that underlies questionnaire development
Believed that designing questionnaires is an “art” rather than a “science.”
Process itself should be a scientific one that integrates established rules of logic, objectivity, and systematic procedures
Words go into questions and that questions go into questionnaires, but not everyone understands that writing questions does not give you a questionnaire

39. Theoretical Principles of Questionnaire Design
Identify and Explain the Communication roles of questionnaire in the data collection process
Theoretical Components of a Questionnaire (or Data Collection Instruments)
Questionnaires
Words–
which to use in creating the questions and scales for collecting raw data from respondents
Wording Problems
Ambiguity
Can be interpreted in more than one way
Abstraction
Difficult to understand
Connotation
Significance of question

40. Theoretical Principles of Questionnaire Design
Explain why the type of information needed to address a decision maker’s question and problems will influence he structure and content of questionnaires
Question/setups
in a particular scale measurement to collect raw data from the respondent.
Type of question format
Unstructured questions –open-ended, the respondents reply in their own words Pros and Cons
Requires more thinking on the part of the respondent
Format of open-ended questions depend on the data collection method–personal interviews, traditional, and computer-assisted telephone interviews, or online and offline self-administered surveys

41. Explain why the type of information needed to address a decision maker’s question and problems will influence he structure and content of questionnaires
Exhibit 13.1

42. Theoretical Principles of Questionnaire Design
Explain why the type of information needed to address a decision maker’s question and problems will influence he structure and content of questionnaires
Structured questions –closed-ended formatted questions, where the respondent provides a response from a pre-determined set of possible responses.
Pros and Cons
Popular format in most self-administered types of questionnaires
Provides the researcher greater opportunities to control the thinking that respondents do in order to answer a question
Interviewer bias eliminated

43. Explain why the type of information needed to address a decision maker’s question and problems will influence he structure and content of questionnaires
Exhibit 13.2

44. Theoretical Principles of Questionnaire Design
Explain why the type of information needed to address a decision maker’s question and problems will influence he structure and content of questionnaires
Quality of the question–good or bad
Bad questions
Incomprehensible –wording, the concept, or both cannot be understood
Unanswerable –respondent does not have access the information needed or because none of the answer choices apply to the respondent
Leading or loaded –respondent is forced or directed into a response that would not ordinarily be given if all possible response categories or concepts were provided
Double-barreled questions –address more than one issue at a time
Questionnaire format
the integrated layout of sets of question/scale measurements into a systematic instrument

45. Theoretical Principles of Questionnaire Design
Explain why the type of information needed to address a decision maker’s question and problems will influence he structure and content of questionnaires
Hypotheses development
questionnaires are designed for collecting meaningful raw data to test a hypotheses rather than merely to gather facts

46. Theoretical Principles of Questionnaire Design
Explain why the type of information needed to address a decision maker’s question and problems will influence he structure and content of questionnaires
Hypotheses relate to
Nature of the respondent
Relationship between expressed attitudes and behavior of the respondent
Sociological structures and their influences on the respondent
Meaning of words and the respondent’s grasp of language and/or concepts
Relationships among a respondent’s knowledge, attitudes, and marketplace behaviors
Descriptive and predictive capabilities of attributes of the constructs

47. Explain why the type of information needed to address a decision maker’s question and problems will influence he structure and content of questionnaires
Exhibit 13.3

48. Theoretical Principles of Questionnaire Design
Explain why the type of information needed to address a decision maker’s question and problems will influence he structure and content of questionnaires
Description versus Prediction
Good questionnaire designs
Surveys
Descriptive design state of being or state of behavior Census
Predictive design state of mind state of intention
Accuracy versus Precision
Accuracy does data provide true state of affairs
Precision are questions and scales narrowly defined
The Value of a Good Survey Instrument
Main Function of a Questionnaire

49. Flowerpot Approach to Questionnaire Development
Discuss and employ the “flowerpot” approach in developing scientific questionnaires
Flowerpot Approach–
Specific framework—for integrating sets of question/scale measurements into a logical, smooth-flowing questionnaire
Identify—the critical rules-of-thumb, details, and decision factors regarding
Construct development
Attributes of objects
Various question/scale measurement formats
Wording of questions
Scale points

50. Flowerpot Approach to Questionnaire Development
Discuss and employ the “flowerpot” approach in developing scientific questionnaires
Reduce creating biased data–size and width of the data requirements must be determined for each objective–with the most general data requirements going into the biggest flowerpot and the next most general set of data going into a smaller pot
Questioning the layout–in good questionnaire design, the directional flow of data will be from general to more specific information

51. End here

52. Explain why the type of information needed to address a decision maker’s question and problems will influence he structure and content of questionnaires
Exhibit 13.5

53. Flowerpot Approach to Questionnaire Development
Discuss and employ the “flowerpot” approach in developing scientific questionnaires
According to the Flowerpot concept
Questionnaire begins with an introduction section
The researcher must decide how many research objectives are to be explored
Specific information would then be obtained within each of the objective categories
Good questionnaire designs end with demographic and socioeconomic questions

54. Flowerpot Approach to Questionnaire Development
Discuss and employ the “flowerpot” approach in developing scientific questionnaires
The Flowerpot Concept
primarily used to determine the appropriate sequential order of the question and scale measurements, it has a direct impact on several of the other developmental steps
Determining the Information Objectives
Determining Information Requirements

55. Flowerpot Approach to Questionnaire Development
List and discuss the 11 steps in the questionnaire development process, and tell how to eliminate come common mistakes in questionnaire design
Development of a Flowerpot-Designed Questionnaire
Step 1—Transform research objectives into information objectives
Step 2—Determine the appropriate data collection method
Step 3—determine information requirements for each objective

56. Flowerpot Approach to Questionnaire Development
List and discuss the 11 steps in the questionnaire development process, and tell how to eliminate come common mistakes in questionnaire design
Step 4—develop specific question/scale measurement formats
Key decisions
Type of data
Question/scale format
Question and specific point wording
Step 5—Evaluate question/scale measurements

57. Explain why the type of information needed to address a decision maker’s question and problems will influence he structure and content of questionnaires
Exhibit 13.7

58. Flowerpot Approach to Questionnaire Development
List and discuss the 11 steps in the questionnaire development process, and tell how to eliminate come common mistakes in questionnaire design
Step 6—Establish the Flowerpot format/layout
This step becomes the core of the Flowerpot approach
Step 7—Evaluate the questionnaire and layout
Questionnaire’s layout should be reviewed and evaluated according to the objectives
Step 8—Obtain the client’s approval
May have new information or concerns—creating need for some types of modifications

59. Flowerpot Approach to Questionnaire Development
List and discuss the 11 steps in the questionnaire development process, and tell how to eliminate come common mistakes in questionnaire design
Step 9—Pretest and revise the questionnaire
Should come from people who represent the respondent
Step 10—finalize the questionnaire format
Placed in final format
Step 11—Implement the survey
Begin the collection of the required raw data

60. Explain why the type of information needed to address a decision maker’s question and problems will influence he structure and content of questionnaires
Exhibit 13.8

61. Development of Cover Letter
Discuss the importance of cover letters and explain the guidelines to help eliminate common mistakes in cover letters
Cover Letter–
a separate written communication to a prospective respondent designed to enhance that person’s willingness to complete and return the survey in a timely manner
Cover letter is not the same as the introduction section in the questionnaire
Main role
Secondary role

62. Explain why the type of information needed to address a decision maker’s question and problems will influence he structure and content of questionnaires
Exhibit 13.9

63. Supplemental Documents Associated with Survey Instrument Designs
Discuss the importance of cover letters and explain the guidelines to help eliminate common mistakes in cover letters
Supervisor Instructions
Interviewer instructions
Screening forms
Quote Sheets
Data sheets
Rating Cards
Call record sheets

64. Discuss the importance of cover letters and explain the guidelines to help eliminate common mistakes in cover letters
Exhibit 13.13

65. Discuss the importance of cover letters and explain the guidelines to help eliminate common mistakes in cover letters
Exhibit 13.14

66. Discuss the importance of cover letters and explain the guidelines to help eliminate common mistakes in cover letters
Exhibit 13.15

67. Summary Value of Questionnaires in Information Research
Theoretical Principles of Questionnaire Design
The Flowerpot Approach to Questionnaire Designs
Development of Cover Letters
Supplemental Documents Associated with Survey Instrument Designs

68. To Do’s Compete SPSS assignment 1 Complete assigned readings
Complete Quiz 1
Read Research Document