Predicting the antecedents of consumers' intention toward purchase of mutual funds: A hybrid PLS‐SEM‐neural network approach

Abstract

AbstractThe current study intends to identify the behavioural antecedents of investors' attitude and investment intention toward mutual funds using a robust SEM‐ANN approach. It focuses on novel factors in the purview of the COVID‐19 pandemic, increasing digitalization and social media usage. The research outcome indicates that attitude (ATB), awareness (AW) and investment decision involvement (IDI) have a significant positive relation with investment intention (BI). In contrast, perceived barrier (PBR) negatively relates to investment intention. Herd behaviour (HB) and social media influence (SMI) do not influence investment intention toward mutual funds. Moreover, all the tested predictors share direct relation with the attitude toward mutual fund investment, barring perceived risk (PR), which has an inverse relationship. As per the outcome of ANN sensitivity analysis, attitude is the most crucial determinant of investment intention. It is followed by awareness (AW), perceived barriers (PBR) and investment decision involvement (IDI). Among the significant determinants of attitude, self‐efficacy (SE) is the most important determinant, followed by perceived usefulness (PU), perceived emergency (PEMER), subjective norms (SN) and perceived risk (PR).