Metaverse Banking Service: Are We Ready to Adopt? A Deep Learning-Based Dual-Stage SEM-ANN Analysis

Abstract

Metaverse banking service is the transformation from online banking to a metaverse environment that allows customers to access banking services and interact with representatives in a virtual environment. The metaverse refers to a virtual realm that integrates physical reality with digital environments, enabling users to interact, socialize, and participate in a wide range of activities through the use of avatars and immersive technologies. While there are advantages to adopt the metaverse, the metaverse adoption researches are scarce and primarily focus on the game, education, and sport, providing limited attention to banking services. Furthermore, most adoption research using standard information technology/information system models has focused primarily on organizational context and adopted compulsorily. Metaverse banking service is mainly adopted voluntarily by users and for personal purposes. Thus, this leads to the difficulty in drawing meaningful conclusions toward metaverse adoption. The study addresses these issues by proposing a new unified theory of acceptance and use of the metaverse technology model (UTAUMT), which consists of metaverse performance expectancy (MPE), metaverse facilitating conditions (MFC), metaverse effort expectancy (MEE), and metaverse social influence (MSI) to determine metaverse banking service adoption. Moreover, metaverse trust (MET) and metaverse financial resources (MEF) are also incorporated to investigate complexity in the metaverse environment. The integrated model has been developed and validated through a pretest (face validity and content validity) and pilot test before applying to 491 metaverses-experienced users in Vietnam through a questionnaire approach. Partial least squares structural equation modelling-artificial neural network (PLS-SEM-ANN) has provided a comprehensive result as it can capture both linear and nonlinear relationships. The results from the model showed that only one of the proposed hypotheses between metaverse financial resources (MEF) and behavioural intention to use metaverse banking services (BIM) was not supported in this study and thus needed further investigation. The study contributes to the academic literature by proposing new constructs to assess users’ likelihood of adopting metaverse banking services. The result also assists bank managers in understanding metaverse banking adoption and makes them realize the metaverse banking services’ growth opportunity to pursue. Given the limited scope of the study focusing solely on Vietnam, it would be advantageous for future research on the cultural variations among users of mobile social commerce to incorporate a comparative analysis across multiple countries, with a particular emphasis on Asian nations.