1 QUANTITATIVE DESIGN AND ANALYSIS QUANTITATIVE DESIGN AND ANALYSIS MARK 2048 MARK 2048 Instructor: Armand Gervais
Transcript
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1 QUANTITATIVE DESIGN AND ANALYSIS MARK 2048 Instructor: Armand
Gervais
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2 Chapter 12
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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
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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
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5 Exhibit 12.1 Design Likert, semantic differential and
behavior intention scales, and explain their strengths and
weaknesses
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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
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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
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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
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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
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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
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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
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12 Exhibit 12.2 Design Likert, semantic differential and
behavior intention scales, and explain their strengths and
weaknesses
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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
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14 Exhibit 12.3 Design Likert, semantic differential and
behavior intention scales, and explain their strengths and
weaknesses
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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
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16 Exhibit 12.4 Design Likert, semantic differential and
behavior intention scales, and explain their strengths and
weaknesses
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17 Exhibit 12.5 Design Likert, semantic differential and
behavior intention scales, and explain their strengths and
weaknesses
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18 Exhibit 12.6 Design Likert, semantic differential and
behavior intention scales, and explain their strengths and
weaknesses
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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
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20 Exhibit 12.7 Design Likert, semantic differential and
behavior intention scales, and explain their strengths and
weaknesses
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21 Exhibit 12.8 Design Likert, semantic differential and
behavior intention scales, and explain their strengths and
weaknesses
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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
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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
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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
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25 Exhibit 12.9 Different Forms of Non- comparative Rating
Scales
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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
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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
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28 Exhibit 12.10 Discuss the differences between noncomparative
and comparative scale designs
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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
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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
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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
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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
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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
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34 Chapter 13
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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
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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
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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
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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
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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
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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
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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
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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
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43 Exhibit 13.2 Explain why the type of information needed to
address a decision makers question and problems will influence he
structure and content of questionnaires
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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
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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
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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
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47 Exhibit 13.3 Explain why the type of information needed to
address a decision makers question and problems will influence he
structure and content of questionnaires
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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
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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
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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
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51 End here End here
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52 Exhibit 13.5 Explain why the type of information needed to
address a decision makers question and problems will influence he
structure and content of questionnaires
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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
Slide 54
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
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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
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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
Slide 57
57 Exhibit 13.7 Explain why the type of information needed to
address a decision makers question and problems will influence he
structure and content of questionnaires
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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
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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
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60 Exhibit 13.8 Explain why the type of information needed to
address a decision makers question and problems will influence he
structure and content of questionnaires
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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
Slide 62
62 Exhibit 13.9 Explain why the type of information needed to
address a decision makers question and problems will influence he
structure and content of questionnaires
Slide 63
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
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64 Exhibit 13.13 Discuss the importance of cover letters and
explain the guidelines to help eliminate common mistakes in cover
letters
Slide 65
65 Exhibit 13.14 Discuss the importance of cover letters and
explain the guidelines to help eliminate common mistakes in cover
letters
Slide 66
66 Exhibit 13.15 Discuss the importance of cover letters and
explain the guidelines to help eliminate common mistakes in cover
letters
Slide 67
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
Slide 68
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