Proceedings of the 13th International Conference on Business, Accounting, Finance and Economics (BAFE 2025)

Factors affecting the intention to adopt wearable devices for health monitoring among white-collar workers in Malaysia

Authors
Seetha Munisamy1, Lai Ka Fei2, 3, Chang Ke Jun2, Lim En Gee2, Yip Ning2, Hemaniswarri Dewi Dewadas2, 3, 4, *
1Faculty of Medicine, Manipal University College Malaysia (MUCM), Jalan Padang Jambu, Bukit Baru, 75150, Melaka, Malaysia
2Teh Hong Piow Faculty of Business and Finance (THP FBF), Universiti Tunku Abdul Rahman, Kampar, 31900, Perak, Malaysia
3Centre for Business Management (CBM), Teh Hong Piow Faculty of Business and Finance, Universiti Tunku Abdul Rahman, Kampar, 31900, Perak, Malaysia
4Centre for Biomedical and Nutrition Research (CBNR), Faculty of Science, Universiti Tunku Abdul Rahman, Kampar, 31900, Perak, Malaysia
*Corresponding author. Email: hemaniswarri@utar.edu.my
Corresponding Author
Hemaniswarri Dewi Dewadas
Available Online 28 December 2025.
DOI
10.2991/978-94-6463-968-1_30How to use a DOI?
Keywords
Wearable Devices; Perceived Usefulness; Perceived Ease of Use; Facilitating Conditions; Social Influence; Technology Acceptance Model; Unified Theory of Acceptance and Use of Technology 2; White-collar Worker
Abstract

Wearable health technology gained significant attention for its potential to improve personal health management and reduce the burden on healthcare systems. Yet, despite its benefits, adoption among white-collar workers in Malaysia remains relatively low, highlighting the need to better understand the determinants of intention to adopt. This study examines the key factors influencing their intention to adopt wearable devices for health monitoring, focusing on perceived usefulness (PU), perceived ease of use (PEOU), facilitating conditions (FC), and social influence (SI). This study employed a quantitative approach, gathering responses from 408 white-collar workers across various industries and states in Malaysia. A structured questionnaire was distributed via Google Forms, and non-probability convenience sampling was used to select participants. The collected data were analyzed using SPSS, incorporating descriptive statistics, reliability testing, and inferential analysis. The results revealed that PU emerged as the strongest predictor of adoption intention (β = 0.405, p < 0.001), followed by SI (β = 0.229, p < 0.001). FC also showed a positive but weaker effect (β = 0.141, p = 0.033), while PEOU was not significant (β = 0.065, p = 0.323). Collectively, these variables explained 56.3% of the variance in adoption intention, confirming the robustness of the model. The study validates the applicability of the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) in the context of wearable health technology and provides practical insights for policymakers and businesses to develop strategies that promote the adoption of health monitoring wearable devices.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 13th International Conference on Business, Accounting, Finance and Economics (BAFE 2025)
Series
Advances in Economics, Business and Management Research
Publication Date
28 December 2025
ISBN
978-94-6463-968-1
ISSN
2352-5428
DOI
10.2991/978-94-6463-968-1_30How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Seetha Munisamy
AU  - Lai Ka Fei
AU  - Chang Ke Jun
AU  - Lim En Gee
AU  - Yip Ning
AU  - Hemaniswarri Dewi Dewadas
PY  - 2025
DA  - 2025/12/28
TI  - Factors affecting the intention to adopt wearable devices for health monitoring among white-collar workers in Malaysia
BT  - Proceedings of the 13th International Conference on Business, Accounting, Finance and Economics (BAFE 2025)
PB  - Atlantis Press
SP  - 440
EP  - 459
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-968-1_30
DO  - 10.2991/978-94-6463-968-1_30
ID  - Munisamy2025
ER  -