Research on elderly users' intentions to accept wearable devices based on the improved UTAUT model

Abstract

IntroductionAs the proportion of the world's elderly population continues to increase, wearable devices can provide ideas for solving a series of problems caused by population aging. Therefore, it is of great significance for the development of intelligent elderly care and the improvement of the quality of elderly care services to explore the factors that influence the intention of elderly users to accept wearable devices.MethodsAn improved unified theory of acceptance and use of technology (UTAUT) model is constructed from the perspective of elderly individuals, and new parameters are added, including four factors related to wearable devices, including performance expectancy, perceived cost, hedonic value and aesthetic appeal, and three factors related to elderly individuals, including personal physiological conditions, health anxiety and personal innovativeness in information technology. The data analysis was accomplished with the partial least square regression structural equation modeling.ResultsThe findings of this study revealed that performance expectancy, perceived cost, hedonic value and aesthetic appeal all have significant impact on elderly users' intention to use wearable devices. Furthermore, personal innovativeness in information technology, personal physiological condition, and intention to use all have significant impact on elderly users' actual usage behavior of wearable devices. However, there is no obvious relationship between health anxiety and actual usage behavior.DiscussionElderly adults' attention to wearable devices plays an important role in the development of the wearable device-related industry chain, which provides management suggestions for stakeholders.

Research on the Factors Affecting the Adoption of Smart Aged-Care Products by the Aged in China: Extension Based on UTAUT Model

“…Performance expectations have a positive effect on behavioral intentions, which result is consistent with previous findings [ 32 , 33 , 34 , 35 , 36 ]. The performance expectation factor has the largest effect other than behavioral intention, and Sun et al [ 74 ] showed that the higher the performance expectation, the stronger the willingness to use, which verifies the UTAUT model.…”

“…Perceived cost has a negative impact on behavioral intention, which result is consistent with previous findings [ 31 , 34 , 55 , 56 ]. It has been indicated that factors such as excessive monetary, learning and time costs significantly reduce the behavioral intention of the aged to use smart aged-care products.…”

“…Perceived cost theory has been widely applied in the field of smart aged-care [ 29 , 30 , 31 ]. The high initial costs associated with any new technology, product, or service are often seen as a major barrier to its acceptance [ 32 , 33 , 34 ]. As an emerging type of technology and product, the adoption of smart aged-care products by the aged will necessitate more time spent in learning, more money spent in purchasing, more effort expended in use, etc.…”

A Study on Immersion and Intention to Pay in AR Broadcasting: Validating and Expanding the Hedonic Motivation System Adoption Mode

“…Studies have examined the influence of aesthetic appeal on behavior within the context of website design. Research has explored the impact of customers' perceptions of the visual landscape of online shopping electronic services on the perceived value of electronic shopping and customer loyalty, emphasizing the potential influence of aesthetic appeal on consumer behavior [166,167]. Aesthetic appeal has been found to have a small but significant impact on participants' intention to revisit or recommend a website, indicating its potential influence on behavioral control [168].…”

Workout with a Smartwatch: A Cross-Sectional Study of the Effects of Smartwatch Attributes on Flow Experience and Exercise Intentions Depending on Exercise Involvement

“…However, little is known about the psychological mechanisms underlying the effects of smartwatch attributes on continued exercise intentions. Specifically, previous studies mainly focused on the effect of smartwatch attributes on smartwatch adoption by relying on the technology acceptance model (TAM) or its variations (e.g., extended technology acceptance model [ETAM]) [7][8][9][10][11][12][13][14]. Although these studies provide meaningful insight into how an individual initially adopts wearable-device technologies, it is also imperative to understand what smartwatch attributes help individuals engage in exercise and physical activities when considering such devices' main usage (i.e., healthcare) [15,16].…”