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

Sajad Rezaei, Naser Valaei

    Research output: Contribution to journalArticlepeer-review

    4 Citations (Scopus)
    6 Downloads (Pure)

    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.
    Original languageEnglish
    Pages (from-to)184-206
    Number of pages23
    JournalInternational Journal of Electronic Marketing and Retailing
    Volume9
    Issue number2
    Early online date3 Apr 2018
    DOIs
    Publication statusE-pub ahead of print - 3 Apr 2018

    Keywords

    • shopping intention via apps
    • shopping behaviour via apps
    • theory of reasoned action
    • TRA
    • subjective norm
    • attitude toward shopping via apps
    • product classification
    • maximum likelihood estimation approach

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