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Explicating Consumer Adoption of Wearable Technologies: A Case of Smartwatches From the ASEAN Perspective

Explicating Consumer Adoption of Wearable Technologies: A Case of Smartwatches From the ASEAN Perspective

Veerisa Chotiyaputta, Donghee Shin
Copyright: © 2022 |Volume: 18 |Issue: 1 |Pages: 21
ISSN: 1548-3908|EISSN: 1548-3916|EISBN13: 9781799893646|DOI: 10.4018/IJTHI.293195
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MLA

Chotiyaputta, Veerisa, and Donghee Shin. "Explicating Consumer Adoption of Wearable Technologies: A Case of Smartwatches From the ASEAN Perspective." IJTHI vol.18, no.1 2022: pp.1-21. http://doi.org/10.4018/IJTHI.293195

APA

Chotiyaputta, V. & Shin, D. (2022). Explicating Consumer Adoption of Wearable Technologies: A Case of Smartwatches From the ASEAN Perspective. International Journal of Technology and Human Interaction (IJTHI), 18(1), 1-21. http://doi.org/10.4018/IJTHI.293195

Chicago

Chotiyaputta, Veerisa, and Donghee Shin. "Explicating Consumer Adoption of Wearable Technologies: A Case of Smartwatches From the ASEAN Perspective," International Journal of Technology and Human Interaction (IJTHI) 18, no.1: 1-21. http://doi.org/10.4018/IJTHI.293195

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Abstract

This research aims to determine the key antecedent factors in consumers’ adoption of and their intention to recommend smartwatch wearable technology. The proposed research model combines the current technology acceptance and innovation diffusion theories with perceived aesthetic and perceived privacy risk to explain individuals’ smartwatch adoption and subsequent recommendation to other people. Based on a sample of 299 completed individual online surveys, the research employed partial least squares (a variance-based analysis method) for the model and hypotheses testing. The results showed some similarities as well as differences from the previous literature. The study found that performance expectancy, habit, and perceived aesthetic were the main predictors of smartwatch adoption. Compatibility was the antecedent factor of performance expectancy, and innovativeness directly influenced user adoption and effort expectancy. Consequently, user smartwatch adoption usually led to recommendation.