Exploring User Acceptance Of Portable Intelligent Personal Assistants: A Hybrid Approach Using PLS-SEM And fsQCA

TL;DR

This study investigates the factors influencing user acceptance of a new portable AI assistant, combining PLS-SEM and fsQCA methods to identify key drivers and configurations for adoption and loyalty.

Contribution

It introduces an integrated hybrid approach using PLS-SEM and fsQCA to analyze user acceptance of PIPAs, extending TAM with AI-specific and design factors.

Findings

All hypothesized relationships are supported.

Three configurations lead to high user acceptance.

fsQCA confirms PLS-SEM results.

Abstract

This research explores the factors driving user acceptance of Rabbit R1, a newly developed portable intelligent personal assistant (PIPA) that aims to redefine user interaction and control. The study extends the technology acceptance model (TAM) by incorporating artificial intelligence-specific factors (conversational intelligence, task intelligence, and perceived naturalness), user interface design factors (simplicity in information design and visual aesthetics), and user acceptance and loyalty. Using a purposive sampling method, we gathered data from 824 users in the US and analyzed the sample through partial least squares structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA). The findings reveal that all hypothesized relationships, including both direct and indirect effects, are supported. Additionally, fsQCA supports the PLS-SEM findings and identifies three configurations leading to high and low user acceptance. This research enriches the literature and provides valuable insights for system designers and marketers of PIPAs, guiding strategic decisions to foster widespread adoption and long-term engagement.