Biohacking: An exploratory study to understand the factors influencing the adoption of embedded technologies within the human body

Abstract

Wearable tech is leading way to embedded tech, i.e., implants inside the body designed to track and enhance human health and productivity among other things. Researchers have used Technology Acceptance Model (TAM) extensively to explain the factors influencing adoption of almost all technological innovations to date. Embedded tech, often referred to as biohacking, presents a unique set of factors that call for yet another revision of the model. Using diffusion of innovations, self-efficacy, and social exchange theory, a revision to the technology acceptance model is proposed with additional factors such as age and gender, embedded technology self-efficacy, perceived risk and privacy concerns to explain the adoption of embedded technologies within the human body. Data was collected through an online survey (N = 1063) using a Qualtrics panel and results suggest that age, gender, perceived usefulness, perceived ease of use, embedded technology self-efficacy, risk and privacy concerns all impact the adoption of embedded tech. Implications for the implant industry, policy makers, and researchers interested in such tech are drawn.

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