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Models with Latent Concepts and Multiple Relationships: Structural Equation Modeling

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Quantitative Data Analysis

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Abstract

One of the best-known models in Information Systems research is the Technology Acceptance Model (TAM), which postulates that users will intend to use a system if they find it useful and easy to use, and that they will find a system useful if they find it is easy to use. This model has been studied over and over again, typically by surveying users (or even non-users) of some system with questions about the degree to which they find the system useful and/or easy to use and whether they intend to use it in the future.

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Notes

  1. 1.

    Causal logic should not be equated with causality. SEMs do not prove causality per se. At best, causality can be approached using SEM if and when the design of the study is appropriate. We discuss the issue of examining causality in data in more detail in Chap. 7.

  2. 2.

    Information on the intricacies of construct development is available in [4–7].

  3. 3.

    For more information on the various fit indices, see [14].

  4. 4.

    http://afhayes.com/spss-sas-and-mplus-macros-and-code.html

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Authors and Affiliations

  1. QUT Business School, Queensland University of Technology, Brisbane, Queensland, Australia

    Willem Mertens & Jan Recker

  2. Dept. of Economics and Management, University of Padova, Padova, Italy

    Amedeo Pugliese

  3. School of Accountancy, Queensland University of Technology, Brisbane, Queensland, Australia

    Amedeo Pugliese

Authors
  1. Willem Mertens
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  2. Amedeo Pugliese
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  3. Jan Recker
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Mertens, W., Pugliese, A., Recker, J. (2017). Models with Latent Concepts and Multiple Relationships: Structural Equation Modeling. In: Quantitative Data Analysis. Springer, Cham. https://doi.org/10.1007/978-3-319-42700-3_4

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