AI healthcare adoption: a privacy calculus model incorporating emotions and techno-social factors.

Presenter Information

Katia Guerra, Boise State University College of Business and EconomicsFollow
Vess L. Johnson, University of North TexasFollow

Paper Type

ERF

Description

This research investigates technical characteristics and technological, social, and affective factors that influence the evaluation of perceived privacy risks and benefits toward adopting AI-based smart healthcare services in the USA. The study develops a research model that integrates Privacy Calculus Theory (PCT) with new constructs, i.e., AI technical characteristics (personalization and anthropomorphism), technological factors (perceived ease of use and perceived usefulness), social factors (social influence and privacy regulation) and two opposite emotional states (enjoyment and exhaustion). A survey will be developed and distributed using crowdsourcing through Prolific. The findings of our research will shed light on the different role of technical characteristics and technological, social, and affective factors on the calculus between perceived risks and benefits in relation to the adoption of AI-based smart healthcare services.

Paper Number

1576

Comments

SIG ADIT

Recommended Citation

Guerra, Katia and Johnson, Vess L., "AI healthcare adoption: a privacy calculus model incorporating emotions and techno-social factors." (2023). AMCIS 2023 Proceedings. 21.
https://aisel.aisnet.org/amcis2023/sig_adit/sig_adit/21