Measurement in Marketing
Measurement in Marketingis built to provide a state-of-the-art discussion of current topics in measurement and deepen readers' appreciation of the fundamental role of measurement in empirical research in marketing
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| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Bingley
Emerald Publishing Limited
2022
|
| Ausgabe: | 1st ed |
| Schriftenreihe: | Review of Marketing Research Series
v.19 |
| Schlagworte: | |
| Online-Zugang: | DE-2070s |
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Inhaltsangabe:
- Cover
- MEASUREMENT IN MARKETING
- REVIEW OF MARKETING RESEARCH
- EDITORIAL ADVISORY BOARD
- MEASUREMENT IN MARKETING
- Copyright
- CONTENTS
- ABOUT THE EDITOR-IN-CHIEF
- ABOUT THE CONTRIBUTORS
- INTRODUCTION
- Measurement in Marketing: Introduction by the Volume Editors
- References
- Philosophical Foundations of Concepts and Their Representation and Use in Explanatory Frameworks
- Abstract
- Simple Concepts
- Complex Concepts
- Simple Homogeneous and Heterogeneous Concepts
- Complex Concepts (Correlated Dimensions)
- Hierarchically Organized Multidimensional Concepts
- Brief Comment on Framework in Table 1
- Comment on Formative Versus Reflective Models
- Hylomorphism
- The Received View in Consumer Research
- Mind-Body Theories
- Role of Causality
- Hylomorphic Concepts and Hylomorphic Causality
- Conclusion
- Acknowledgments
- References
- Accounting for Uncertainty in the Measurement of Unobservable Marketing Phenomena
- Abstract
- The Common Factor Model Is Correct in the Population
- The Common Factor Is the Measurand
- Statistics Capture all of the Uncertainty Associated With Measurement
- Major Implications
- Example
- Conclusion
- References
- Measurement Error and Research Design: Some Practical Issues in Conducting Research
- Abstract
- Constructs and Measurement
- Constructs
- Constructs and Measurement Error
- Measure Development Process
- Elements of the Measure Development Process
- Items and Measures
- Measurement Approaches
- Indicators of Measurement Error
- Reliability and Validity
- Types of Validity
- Dimensionality
- Why Indicators of Measurement Error Matter
- Types of Measurement Error
- Types of Measures
- Stimulus- Versus Respondent-Centered Scales
- Formative Versus Reflective Indicators
- Measurement Issues in Day-to-Day Research
- Using Previously Validated Measures
- Using Partially Validated or Unvalidated Measures
- Using "Objective Versus Subjective" Measures
- Cross Cultural Measurement
- Measurement Error and Research Design
- Measurement Error and Experimental Design
- From Measurement Error to Research Design
- Conclusion
- Notes
- References
- The Advancement of Measurement Invariance Testing in Cross-Cultural Research in the Period 1999-2020. Executing Rather Than ...
- Abstract
- Introduction
- Part I Cross-Cultural and Cross-National Research in Marketing
- Bibliometric Analyses
- Highly Cited Articles in the Field and Their Impact in Practice
- Part II Testing Measurement Invariance in Marketing Research
- Background
- MI Assessment in Cross-Cultural Marketing
- Part III Articles Citing Measurement Invariance Testing and Beyond
- Conclusion and Discussion
- Limitations
- Future Research
- Acknowledgment
- Notes
- References
- How to Identify Careless Responders in Surveys
- Abstract
- The Phenomenon of Careless Responding in Surveys
- A Classification of Methods for Identifying Careless Responders
- Empirical Study
- Methods for Identifying Careless Responders
- Category 1 Methods: Self-Reported Effort
- Category 2 Methods: Response Times
- Category 3 Methods: Bogus Items and Instructional Manipulation Checks
- Category 4 Methods: Quality of Responses to Substantive Questions
- Relationships Between the Different Measures of Careless Responding
- Conclusion
- References
- An Application of M-MORE: A Multivariate Multiple Objective Random Effects Approach to Marketing Scale Dimensionality and I ...
- Abstract
- Identifying Scale Dimensionality and Selecting Items
- Traditional Paradigm
- The M-MORE Methodology
- Empirical Application
- Specify the Nature of the Focal Construct
- Generate a Pool of Scale Items for Each Dimension
- M-MORE Approach
- Traditional Factor Analysis Approach
- Criterion Validity Comparisons
- Discussion
- Limitations
- Conclusion
- Notes
- References
- On the Selection and Use of Implicit Measures in Marketing Research: A Utilitarian Taxonomy
- Abstract
- Introduction
- Four (Popular) Implicit Measures Suited for Marketing Research
- The Evaluative Priming Task
- The Affect Misattribution Procedure
- The Implicit Association Task
- The Propositional Evaluation Paradigm
- How Do Marketing Researchers Typically Justify the Use of (Specific) Implicit Measures?
- The Functional Mapping Approach
- Automaticity Features
- Unaware
- Unawareness of an Instigating Stimulus
- Unawareness of the Automatic Appraisals Triggered by a Stimulus
- Unawareness of the Influence of Automatic Appraisals on Subsequent Judgments, Feelings, and/or Behavior
- Unintentional and Uncontrolled
- Unintentional But Goal-Dependent
- Uncontrollable in the Counteracting Sense
- Efficient
- Fast
- Structure-Related Features
- Structural Makeup
- EPT
- AMP
- IAT
- PEP
- Versatility and Scope
- Reliability
- Ease of Completion
- Additional Evaluation Criteria
- Ease of Implementation
- Pencil-and-Paper Versus Digital Administration
- Completion Time
- Ease of Data Aggregation
- Relative Versus Nonrelative Measures
- Discussion
- References
- INDEX.