Skip to main content

Managing generative artificial intelligence in the daily lives of people with disabilities

Research Abstract
Purpose

This research examines whether people with disabilities (PwDs) are willing to adopt generative artificial intelligence (GenAI) and identifies the factors influencing their use behavior in their daily lives.

Design/methodology/approach

The theoretical framework presented in this study integrates the unified theory of technology acceptance and use (UTAUT) and its extension, the UTAUT2, with the stimulus-organism-response (S-O-R) model. Empirical data were quantitatively analyzed using SmartPLS 4.

Findings

Effort expectancy, facilitating conditions and hedonic motivation (stimuli) positively affect perceived value (organism). Anxiety (stimulus) exerts a negative effect on perceived value. Perceived value generates a response by significantly affecting behavior intention, which drives GenAI use behavior in PwDs’ daily lives. If these stimuli are not properly managed, they lead to non-use by PwDs, resulting in avoidance behavior.

Research limitations/implications

This study enriches the technological innovation management literature by presenting a theoretical framework of the stimuli that affect GenAI use behavior by PwDs.

Practical implications

By underlining the interplay between PwDs and new technologies, this study offers practical implications and recommendations for tech and non-tech companies, policymakers and regulators to implement advanced technologies inclusively. It guides these practitioner groups to enhance user-centered innovation by adhering to the principles of inclusive technology design.

Originality/value

This study offers an inclusive analysis of GenAI use behavior by PwDs. Its originality lies in focusing on PwDs’ perceptions rather than predefined corporate-driven factors.

Research Authors
Attia Abd alkader Attia Ali
Research Date
Research Journal
Management Decision
Research Publisher
Emerald Publishing Limited
Research Rank
Q1
Research Website
https://doi.org/10.1108/MD-10-2024-2471
Research Year
2025