Structural model robustness checks in PLS-SEM

• Marko Sarstedt ^{[1] [6]} ; Christian M Ringle ^{[2] [7]} ; Jun-Hwa Cheah ^[3] ; Hiram Ting ^[4] ; Ovidiu I Moisescu ^[5] ; Lacramioara Radomir ^[5]
  1. [1] Otto-von-Guericke University Magdeburg

     Otto-von-Guericke University Magdeburg

     Landeshauptstadt Magdeburg, Alemania

     
  2. [2] Hamburg University of Technology

     Hamburg University of Technology

     Hamburg, Freie und Hansestadt, Alemania

     
  3. [3] Universiti Putra Malaysia

     Universiti Putra Malaysia

     Malasia

     
  4. [4] UCSI University

     UCSI University

     Malasia

     
  5. [5] Babeș-Bolyai University

     Babeș-Bolyai University

     Rumanía

     
  6. [6] Monash University Malaysia

     Monash University Malaysia

     Malasia

     
  7. [7] University of Waikato

     University of Waikato

     Nueva Zelanda

     

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• Localización: Tourism economics: the business and finance of tourism and recreation, ISSN 1354-8166, Vol. 26, Nº. 4, 2020, págs. 531-554
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Dialnet Métricas: 3 Citas
• Resumen

  • Partial least squares structural equation modeling (PLS-SEM) has become a standard tool for analyzing complex inter-relationships between observed and latent variables in tourism and numerous other fields of scientific inquiry. Along with the recent surge in the method’s use, research has contributed several complementary methods for assessing the robustness of PLSSEM results. Although these improvements are documented in extant literature, research on tourism has been slow to adopt the relevant complementary methods. This article illustrates the use of recent advances in PLS-SEM, designed to ensure structural model results’ robustness in terms of nonlinear effects, endogeneity, and unobserved heterogeneity in a PLS-SEM framework. Our overarching aim is to encourage the routine use of these complementary methods to increase methodological rigor in the field.