1 QUANTITATIVE DESIGN AND ANALYSIS MARK 2048 Instructor: Armand Gervais

2 Chapter 12

3 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. Learning Objectives

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

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

6 Likert Scale 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 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 Scale format balanced between agreement and disagreement scale descriptors 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

7 Series of Hierarchical Steps for Developing a Likert Scale Series of Hierarchical Steps for Developing a Likert Scale 1. Step 1: Identify and understand the concept to be studied 2. 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

8 4. 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 5. 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

9 6. 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

10 Likert Scale Extensively Modified Likert Scale Extensively Modified 1. Initially, five scale descriptors were used Strongly agree, Agree, Neither agree nor disagree, Disagree, and Strongly disagree 2. Modified Likert scale expands this set to a six-point forced choice format or a seven-point free-choice format 3. 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

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

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

15 Different formats for the semantic differential scale format Different formats for the semantic differential scale format Why should you randomize the positive and negative pole descriptors? Why should you randomize the positive and negative pole descriptors? Halo effect bias Halo effect bias Another issue is the lack of extreme magnitude expressing in the pole descriptors Another issue is the lack of extreme magnitude expressing in the pole descriptors Dependable undependable attach a narratively expressed extreme 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 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 Matching standardized intensity descriptors to pole descriptors See exhibit 12.4 Scales to Measure Attitudes and Behaviors Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses

19 Behavior Intention Scale 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 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 Notice a time frame is given Scales to Measure Attitudes and Behaviors Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses

22 Strengths and Weaknesses of Attitude and Behavior Intention Scale Measurements Strengths and Weaknesses of Attitude and Behavior Intention Scale Measurements Knowledge of a individuals attitudes often is not a good predictor of behavior Knowledge of a individuals attitudes often is not a good predictor of behavior To Capture Peoples Attitudes and Behaviorsscale measurements are used but there is no one guaranteed best approach To Capture Peoples Attitudes and Behaviorsscale measurements are used but there is no one guaranteed best approach Data should be considered to be stable insights rather than as true facts Data should be considered to be stable insights rather than as true facts Behavior intentions are probably the most important area to examine 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 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 Design Likert, semantic differential and behavior intention scales, and explain their strengths and weaknesses

23 Other Types of Comparative and Non-comparative Scale Formats Other Types of Comparative and Non-comparative Scale Formats Noncomparative Rating Scalescale format that requires a judgment without reference to another object, person, or concept Noncomparative Rating Scalescale format that requires a judgment without reference to another object, person, or concept Comparative Ratingscale format that requires a judgment comparing one object, person, or concept against another on the scale Comparative Ratingscale 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

24 Methods Methods Graphic Rating Scales 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. (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 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. uses an evaluative scale point format that allows the respondents to express some type of postdecision or behavior evaluative judgment about an object. Scales to Measure Attitudes and Behaviors Discuss the differences between noncomparative and comparative scale designs

25 Exhibit 12.9 Different Forms of Non- comparative Rating Scales

26 Rank-Order Scales 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 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 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 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

27 Constant Sum Scales 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 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 Most appropriate in self-administered surveys Requires a lot of mental energy on the part of the respondent Requires a lot of mental energy on the part of the respondent Scales to Measure Attitudes and Behaviors Discuss the differences between noncomparative and comparative scale designs

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

29 When to Use Single-item or Multiple-item Scales When to Use Single-item or Multiple-item Scales Single-Item Scale Design Single-Item Scale Design when the data requirements focus on collection data about only one attribute of the object or construct being investigated when the data requirements focus on collection data about only one attribute of the object or construct being investigated Multiple-item Scale Design 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. to measure the object or construct of interest, will have to measure several items simultaneously rather than measuring just one item. Formative composite scale Formative composite scale Reflective 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

30 Decision to Use a Single-item versus Multiple- item Scale made in the construct development state Decision to Use a Single-item versus Multiple- item Scale made in the construct development state Two factors Two factors Must assess the dimensionality of the construct under investigation Must assess the dimensionality of the construct under investigation Must deal with the reliability and validity issues of the scales used to collect data Must deal with the reliability and validity issues of the scales used to collect data 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

31 Construct Development Issues Construct Development Issues Constructs should be clearly defined Constructs should be clearly defined Avoid double-barreled sub-dimensions Avoid double-barreled sub-dimensions Scale Measurement Issues Scale Measurement Issues All necessary instructions for both respondent and interviewer should be part of the scale measurement setup All necessary instructions for both respondent and interviewer should be part of the scale measurement setup Use clear wording and avoid ambiguity Use clear wording and avoid ambiguity Avoid leading phrases or words Avoid leading phrases or words Make sure the items are phrased unidimensionally Make sure the items are phrased unidimensionally Make sure the descriptors are relevant to the type of data being sought Make sure the descriptors are relevant to the type of data being sought 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

32 Screening Questions Screening Questions Use screens before questioning Use screens before questioning To identify qualified respondents To identify qualified respondents Skip Question Skip Question Avoid if possible Avoid if possible Instruction must be clearly communicated Instruction must be clearly communicated Ethical Responsibility of the Researcher Ethical Responsibility of the Researcher Develop and use the most appropriate scale Develop and use the most appropriate scale Avoid bias Avoid bias 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

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

34 Chapter 13

35 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 makers questions and problems will substantially influence the structure and content of questionnaires. Learning Objectives

36 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. Learning Objectives

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

38 Great Weaknesses of Questionnaire Design Great Weaknesses of Questionnaire Design Theory Theory many researchers do not understand the theory that underlies questionnaire development many researchers do not understand the theory that underlies questionnaire development Believed that designing questionnaires is an art rather than a science. 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 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 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 Discuss the theoretical principles of questionnaire design, and explain why a questionnaire is more than just asking a respondent some questions

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

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

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

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

44 Quality of the questiongood or bad Quality of the questiongood or bad Bad questions Bad questions Incomprehensible wording, the concept, or both cannot be understood 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 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 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 Double-barreled questions address more than one issue at a time Questionnaire format Questionnaire format the integrated layout of sets of question/scale measurements into a systematic instrument 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 makers question and problems will influence he structure and content of questionnaires

45 Hypotheses development Hypotheses development questionnaires are designed for collecting meaningful raw data to test a hypotheses rather than merely to gather facts 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 makers question and problems will influence he structure and content of questionnaires

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

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

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

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

51 End here End here

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

54 The Flowerpot Concept 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 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 the Information Objectives Determining Information Requirements Determining Information Requirements Flowerpot Approach to Questionnaire Development Discuss and employ the flowerpot approach in developing scientific questionnaires

55 Development of a Flowerpot-Designed Questionnaire Development of a Flowerpot-Designed Questionnaire Step 1Transform research objectives into information objectives Step 1Transform research objectives into information objectives Step 2Determine the appropriate data collection method Step 2Determine the appropriate data collection method Step 3determine information requirements for each objective Step 3determine 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

56 Step 4develop specific question/scale measurement formats Step 4develop specific question/scale measurement formats Key decisions Key decisions Type of data Type of data Question/scale format Question/scale format Question and specific point wording Question and specific point wording Step 5Evaluate question/scale measurements Step 5Evaluate question/scale measurements 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

58 Step 6Establish the Flowerpot format/layout Step 6Establish the Flowerpot format/layout This step becomes the core of the Flowerpot approach This step becomes the core of the Flowerpot approach Step 7Evaluate the questionnaire and layout Step 7Evaluate the questionnaire and layout Questionnaires layout should be reviewed and evaluated according to the objectives Questionnaires layout should be reviewed and evaluated according to the objectives Step 8Obtain the clients approval Step 8Obtain the clients approval May have new information or concernscreating need for some types of modifications May have new information or concernscreating 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

59 Step 9Pretest and revise the questionnaire Step 9Pretest and revise the questionnaire Should come from people who represent the respondent Should come from people who represent the respondent Step 10finalize the questionnaire format Step 10finalize the questionnaire format Placed in final format Placed in final format Step 11Implement the survey Step 11Implement the survey Begin the collection of the required raw data Begin the collection of the required raw data 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

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

63 Supervisor Instructions Supervisor Instructions Interviewer instructions Interviewer instructions Screening forms Screening forms Quote Sheets Quote Sheets Data sheets Data sheets Rating Cards Rating Cards Call record sheets Call record sheets 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

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

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

68 To Dos Compete SPSS assignment 1 Compete SPSS assignment 1 Complete assigned readings Complete assigned readings Complete Quiz 1 Complete Quiz 1 Read Research Document Read Research Document