SIoT robots and consumer experiences in retail: Unpacking repeat purchase intention drivers leveraging computers are social actors (CASA) paradigm

This study contributes to knowledge on the so far limited understanding of how to manage collaboration between Social Internet of Things (SIoT) service robots and consumers in the retail context. Embedded in Computers Are Social Actors (CASA) paradigm, we leverage a Partial Least Approach - Structural Equation Modelling (PLS-SEM) (n = 356) to show that word of mouth, consumer promotion experience, relationship quality, and inspiration significantly impact consumers' repeat purchase intention when SIoT robots are used. Noticeably, while relationship quality is significant, it has a negative coefficient indicating that consumers may have high pre-existing anxiety towards SIoT service robots.

Automated summary

This study contributes to the limited understanding of managing collaboration between SIoT service robots and consumers in retail by utilizing the CASA paradigm. Findings from the PLS-SEM analysis indicate that word of mouth, consumer promotion experience, relationship quality, and inspiration have significant impacts on consumers' repeat purchase intention, with the negative coefficient of relationship quality suggesting high pre-existing anxiety towards SIoT service robots.