This study examines the elements of matchmaking intention, highlighting a significant gap in matchmaking behaviors within Metaverse platforms. The study explores the socio-psychological and behavioral factors impacting matchmaking intention in this digital landscape. We developed a conceptual model integrating social presence theory and status quo bias with the technology acceptance model (TAM). Using survey data from 512 participants across various regions of India, we tested the proposed relationships through structural equation modeling. The results indicate that intimacy, interactivity, connectedness, and responsiveness contribute to increased agreeableness regarding matchmaking intention on Metaverse platforms. Furthermore, real, non-perceived usage significantly moderates the relationship between agreeableness and matchmaking intention. Our findings provide valuable insights for creating effective marketing strategies to enhance matchmaking user intentions and behaviors within the Metaverse. The study can be used to launch any new service through Metaverse.
In the digital landscape, online gaming has become an integral part of entertainment. This empirical research aims to examine the influence of AI-based emotional attachment-oriented anthropomorphic features and their impact on the online gaming experience. Under the paradigm of cognitive load theory (CLT) and Computers Are Social Actors (CASA) framework, a theoretical model was developed for an empirical investigation. To examine the model, the present study applied a partial least squares structural equation modeling process with 1802 respondents' data from India. The results show that AI-based emotional attachment anthropomorphic features enhance consumer's overall service experience. In addition, trust and engagement partially mediate the relationship between AI-based emotional attachment anthropomorphic features and consumer's overall service experience.