IT Identity: Developing valid measures through CFA-based MTMM analysis

Michelle Carter

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

Informed by identity literature, this study develops a set of theory-based definitions and measures for investigating how individuals' self-identification with particular IT (termed IT identity) influences their ongoing IT use behaviors. In doing so, it contributes to both IS theory and research methods. For methods, determining whether a construct can be measured by at least two methods is an often overlooked aspect of establishing construct validity. Detailing the steps involved in CFA-based MTMM analysis may serve as a guide to IS researchers seeking to develop valid, or evaluate alternative, measures of perceptual phenomena. For IS theory, conceptualizing IT identity as a new form of material identity has the potential to open up new ways of thinking about individuals' long-term interactions with IT. In clearly articulating the construct's conceptual domain and operationalizing the construct, this study reinforces the point that there is a lot of theory involved in measurement.

Original languageEnglish (US)
Title of host publicationInternational Conference on Information Systems (ICIS 2013)
Subtitle of host publicationReshaping Society Through Information Systems Design
Pages2398-2415
Number of pages18
StatePublished - 2013
EventInternational Conference on Information Systems, ICIS 2013 - Milan, Italy
Duration: Dec 15 2013Dec 18 2013

Publication series

NameInternational Conference on Information Systems (ICIS 2013): Reshaping Society Through Information Systems Design
Volume3

Conference

ConferenceInternational Conference on Information Systems, ICIS 2013
Country/TerritoryItaly
CityMilan
Period12/15/1312/18/13

Keywords

  • Confirmatory factor analysis
  • Construct development
  • IT identity
  • Measurement
  • Multi-trait multi-method

ASJC Scopus subject areas

  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Library and Information Sciences

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