Digital Trust and Personalization Strategy As Drivers Of Customer Retention In E-Commerce: A Structural Equation Modeling Approach

Abstract

This study examines the relationships between digital trust, personalization strategy, and customer retention in e-commerce. A quantitative explanatory survey design and purposive sampling were used to collect responses from e-commerce users who had completed online purchases and experienced platform features such as product recommendations or promotional offers. The questionnaire measured digital trust, personalization strategy, and customer retention using a five-point Likert scale. Data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS), including assessment of indicator loadings, convergent validity, internal consistency reliability, path coefficients, bootstrapped significance, and explained variance (R²). The manuscript supplied for revision does not report the final sample size, respondent profile, indicator statistics, path coefficients, p-values, or R² values; these results must be inserted from the original dataset before the abstract can make a defensible statement about effect strength or statistical significance. Conceptually, the study considers digital trust and personalization as related dimensions of e-commerce customer relationship management. The study’s contribution is to examine both constructs in one model while recognizing that claims about their relationships with retention must be supported by the empirical estimates.