User Acceptance of AR Assistance System in Maintenance: Toward a Human-Centered Industry

Igor Lima Dourado; Lorena Caires Moreira; Marcos Kauffman; Ben Horan

doi:10.1080/10447318.2026.2651339

User Acceptance of AR Assistance System in Maintenance: Toward a Human-Centered Industry

Igor Lima Dourado
, Lorena Caires Moreira
, Marcos Kauffman
, Ben Horan

Centre for Manufacturing and Materials

Deakin University

Research output: Contribution to journal › Article › peer-review

4 Downloads (Pure)

Abstract

Augmented reality (AR) technologies are key enablers of Industry 5.0, empowering the workforce and offering significant benefits in maintenance operations. However, challenges with user adoption and acceptance hinder industrial implementation. Therefore, this work proposes an improved framework based on the technology acceptance model (TAM), extended with technology, task, and user-related factors, to better understand and predict the acceptance of AR assistance systems (ARAS) in industrial maintenance settings. A user study was conducted to test the model empirically. With N = 57 participants, TAM’s main paths were confirmed. Among external factors, perceived risk negatively influences the intention to use, while augmentation quality positively impacts ease of use and usefulness (indirect). The results demonstrate the model’s explained variance (R ² = 43.2%) and high predictive capabilities. Contributions and implications are also presented for academics and practitioners aiming to enhance user adoption and implementation strategies of maintenance-based ARAS, thereby promoting a human-centered manufacturing.

Original language	English
Pages (from-to)	(In-Press)
Number of pages	26
Journal	International Journal of Human-Computer Interaction
Volume	(In-Press)
Early online date	25 May 2026
DOIs	https://doi.org/10.1080/10447318.2026.2651339
Publication status	E-pub ahead of print - 25 May 2026

Bibliographical note

2026 The Author(s). Published with license by Taylor & Francis Group, LLC.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), whichpermits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has beenpublished allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

Keywords

Industry 5.0
augmented reality
maintenance
technology acceptance
user study

ASJC Scopus subject areas

Human Factors and Ergonomics
Human-Computer Interaction
Computer Science Applications

Access to Document

10.1080/10447318.2026.2651339Licence: CC BY

Dourado2026VoRFinal published version, 1.69 MBLicence: CC BY

Cite this

@article{8a17f46739c64c7e82714582ac84711e,

title = "User Acceptance of AR Assistance System in Maintenance: Toward a Human-Centered Industry",

abstract = "Augmented reality (AR) technologies are key enablers of Industry 5.0, empowering the workforce and offering significant benefits in maintenance operations. However, challenges with user adoption and acceptance hinder industrial implementation. Therefore, this work proposes an improved framework based on the technology acceptance model (TAM), extended with technology, task, and user-related factors, to better understand and predict the acceptance of AR assistance systems (ARAS) in industrial maintenance settings. A user study was conducted to test the model empirically. With N = 57 participants, TAM{\textquoteright}s main paths were confirmed. Among external factors, perceived risk negatively influences the intention to use, while augmentation quality positively impacts ease of use and usefulness (indirect). The results demonstrate the model{\textquoteright}s explained variance (R 2 = 43.2\%) and high predictive capabilities. Contributions and implications are also presented for academics and practitioners aiming to enhance user adoption and implementation strategies of maintenance-based ARAS, thereby promoting a human-centered manufacturing.",

keywords = "Industry 5.0, augmented reality, maintenance, technology acceptance, user study",

author = "\{Lima Dourado\}, Igor and \{Caires Moreira\}, Lorena and Marcos Kauffman and Ben Horan",

note = " 2026 The Author(s). Published with license by Taylor \& Francis Group, LLC.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), whichpermits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has beenpublished allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.",

year = "2026",

month = may,

day = "25",

doi = "10.1080/10447318.2026.2651339",

language = "English",

volume = "(In-Press)",

pages = "(In--Press)",

journal = "International Journal of Human-Computer Interaction",

issn = "1044-7318",

publisher = "Taylor and Francis",

}

TY - JOUR

T1 - User Acceptance of AR Assistance System in Maintenance: Toward a Human-Centered Industry

AU - Lima Dourado, Igor

AU - Caires Moreira, Lorena

AU - Kauffman, Marcos

AU - Horan, Ben

N1 - 2026 The Author(s). Published with license by Taylor & Francis Group, LLC.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), whichpermits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has beenpublished allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

PY - 2026/5/25

Y1 - 2026/5/25

N2 - Augmented reality (AR) technologies are key enablers of Industry 5.0, empowering the workforce and offering significant benefits in maintenance operations. However, challenges with user adoption and acceptance hinder industrial implementation. Therefore, this work proposes an improved framework based on the technology acceptance model (TAM), extended with technology, task, and user-related factors, to better understand and predict the acceptance of AR assistance systems (ARAS) in industrial maintenance settings. A user study was conducted to test the model empirically. With N = 57 participants, TAM’s main paths were confirmed. Among external factors, perceived risk negatively influences the intention to use, while augmentation quality positively impacts ease of use and usefulness (indirect). The results demonstrate the model’s explained variance (R 2 = 43.2%) and high predictive capabilities. Contributions and implications are also presented for academics and practitioners aiming to enhance user adoption and implementation strategies of maintenance-based ARAS, thereby promoting a human-centered manufacturing.

AB - Augmented reality (AR) technologies are key enablers of Industry 5.0, empowering the workforce and offering significant benefits in maintenance operations. However, challenges with user adoption and acceptance hinder industrial implementation. Therefore, this work proposes an improved framework based on the technology acceptance model (TAM), extended with technology, task, and user-related factors, to better understand and predict the acceptance of AR assistance systems (ARAS) in industrial maintenance settings. A user study was conducted to test the model empirically. With N = 57 participants, TAM’s main paths were confirmed. Among external factors, perceived risk negatively influences the intention to use, while augmentation quality positively impacts ease of use and usefulness (indirect). The results demonstrate the model’s explained variance (R 2 = 43.2%) and high predictive capabilities. Contributions and implications are also presented for academics and practitioners aiming to enhance user adoption and implementation strategies of maintenance-based ARAS, thereby promoting a human-centered manufacturing.

KW - Industry 5.0

KW - augmented reality

KW - maintenance

KW - technology acceptance

KW - user study

UR - https://www.scopus.com/pages/publications/105040030841

U2 - 10.1080/10447318.2026.2651339

DO - 10.1080/10447318.2026.2651339

M3 - Article

SN - 1044-7318

VL - (In-Press)

SP - (In-Press)

JO - International Journal of Human-Computer Interaction

JF - International Journal of Human-Computer Interaction

ER -

User Acceptance of AR Assistance System in Maintenance: Toward a Human-Centered Industry

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this