QUANTITATIVE DESIGN AND ANALYSIS MARK 2048 Instructor: Armand Gervais

Chapter 12

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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 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

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

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

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 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

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

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.

Different Forms of Non-comparative Rating Scales Exhibit 12.9

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

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

Discuss the differences between noncomparative and comparative scale designs Exhibit 12.10

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

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

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

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

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

Chapter 13

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.

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

End here

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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