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Using PLS Path Modeling for Assessing Hierarchical Construct Models: Guidelines and Empirical Illustration1

MIS Quarterly · 2009 · Vol. 33(1) · pp. 177–195
Martin WetzelsOdekerken-Schrödervan Oppen

Abstract

In this paper, the authors show that PLS path modeling can be used to assess a hierarchical construct model. They provide guidelines outlining four key steps to construct a hierarchical construct model using PLS path modeling. This approach is illustrated empirically using a reflective, fourth-order latent variable model of online experiential value in the context of online book and CD retailing. Moreover, the guidelines for the use of PLS path modeling to estimate parameters in a hierarchical construct model are extended beyond the scope of the empirical illustration. The findings of the empirical illustration are used to discuss the use of covariance-based SEM versus PLS path modeling. The authors conclude with the limitations of their study and suggestions for future research.

Customer Service Quality and LoyaltyTechnology Adoption and User BehaviourConsumer Retail Behavior StudiesConstruct (python library)Computer scienceEmpirical researchPath (computing)Knowledge managementData scienceManagement scienceEngineeringMathematicsStatistics
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