Measurement Models for Marketing Constructs

Hans Baumgartner () and Bert Weijters
Additional contact information
Hans Baumgartner: Smeal College of Business, Penn State University

Chapter Chapter 9 in Handbook of Marketing Decision Models, 2017, pp 259-295 from Springer

Abstract: Abstract Researchers who seek to understand marketing phenomena frequently need to measure the phenomena studied. Yet, constructing reliable and valid measures of the conceptual entities of interest is a nontrivial task, and before substantive issues can be addressed, the adequacy of the available measures has to be ascertained. In this chapter, we discuss a wide variety of measurement modelsMeasurement model that researchers can use to evaluate the quality of their measures. It is assumed that, generally, multiple measures are necessary to capture a construct adequately. We first present the congeneric measurement modelCongeneric measurement model , in which continuous observed indicators are seen as reflections of an underlying latent variableReflections of an underlying latent variable , each observed variable loads on a single latent variable, and no correlations among the unique factors (measurement errors) are allowed. We contrast the congeneric measurement model with the formative measurement modelFormative measurement model , in which the observed measures cause the composite variable of interest, and we also consider measurement models that incorporate a mean structure (in addition to a covariance structureCovariance structure ) and extend the single-group modelSingle-group model to multiple groupsMultiple group model . Finally, we address three limitations of the congeneric measurement model (zero loadings of observed measures on non-target constructs, no correlations among the non-substantive components of observed measures, and the assumption of continuous, normally distributed indicators) and present models that relax these limiting assumptions.

Keywords: Congeneric Measurement; Exploratory Structural Equation Modeling (ESEM); Standardized Root Mean Square Residual (SRMR); ESEM Model; Customer Citizenship Behavior (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (4)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-319-56941-3_9

Ordering information: This item can be ordered from
http://www.springer.com/9783319569413

DOI: 10.1007/978-3-319-56941-3_9

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().