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Apps shoppers' behaviour and the moderating effect of product standardisation/brand recognition: a maximum likelihood estimation approach

Author

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  • Sajad Rezaei
  • Naser Valaei

Abstract

The purpose of this study is to examine the structural relationship between subjective norm, attitude, intention, and behaviour via Apps and the moderating effect of product standardisation/brand recognition. Confirmatory maximum likelihood estimation (MLE) approach, a covariance based-structural equation modelling (CB-SEM) technique, was performed for assessment of the reflective measurements, structural relationship between latent constructs and moderation effect. A total of 340 online questionnaires (N = 340) was collected and the results support the structural relationship between the latent constructs and specify a valid model fit (positive and direct effects). In addition, multigroup moderation SEM analysis (critical ratio values) reveal that the degree of standardisation/brand recognition (standard vs. non-standard) moderates the structural relationships. This study provides a basic set of guidelines for the application of confirmatory MLE in the evaluation of direct effects (one tail hypotheses) and multigroup SEM analyses for moderation effects. Theoretical and managerial implications of the study are further discussed.

Suggested Citation

  • Sajad Rezaei & Naser Valaei, 2018. "Apps shoppers' behaviour and the moderating effect of product standardisation/brand recognition: a maximum likelihood estimation approach," International Journal of Electronic Marketing and Retailing, Inderscience Enterprises Ltd, vol. 9(2), pages 184-206.
    • Handle: RePEc:ids:ijemre:v:9:y:2018:i:2:p:184-206
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