Determinants of Retention in Digital Banking: PLS-SEM Meets Necessary Condition Analysis

Abstract

The rapid digitalisation of the banking industry has transformed service delivery mechanisms and intensified competition among banks, making customer retention a critical strategic priority. This study examines the determinants and necessary conditions of customer retention intention in digital banking by integrating Partial Least Squares Structural Equation Modelling (PLS-SEM) with Necessary Condition Analysis (NCA). Data were collected from 435 bank customers in Goa using a structured questionnaire based on a five-point Likert scale. The measurement model was assessed for reliability and validity, followed by structural model estimation to test the hypothesised relationships among customer loyalty, digital commitment, employee performance, perceived information quality, perceived service orientation, post service recovery satisfaction, and switching cost. The results reveal that post service recovery satisfaction significantly enhances customer loyalty and customer retention intention, while employee performance, perceived information quality, and perceived service orientation strongly influence recovery satisfaction. In addition, the moderation effect of switching cost on the relationship between recovery satisfaction and retention intention is supported. The NCA findings further identify employee performance, perceived information quality, and recovery satisfaction as necessary conditions for achieving high levels of customer retention. By distinguishing between sufficient drivers and indispensable prerequisites, this study offers a novel theoretical contribution to digital banking and relationship marketing literature. The findings provide practical implications for banking managers seeking to strengthen service recovery systems and build long-term customer relationships in an increasingly digital environment.