The smart wearable device is a new breed of mobile device that offers diversified utilities for health, sport, and finance for consumers worldwide. The current study aims to investigate the provocation of the intention to use smart wearable payment devices among Malaysian consumers. The unified theory of technology acceptance and use of technology (UTAUT) was employed with the cross-sectional survey-based data to explain the adoption of the smart wearable payment device. Furthermore, the UTAUT model was extended with trust and lifestyle compatibility factors to investigate smart wearable payment device adoption. The survey-based data were collected through the online survey and analyzed through the symmetrical modeling approach of partial least squares structural education modeling (PLS-SEM) to evaluate theoretical associations between the study constructs. The fuzzy set qualitative comparative analysis (fsQCA) was employed as an asymmetrical approach. As a result, it was found that the ease of use, lifestyle compatibility, and trust significantly impacted the intention to adopt smart wearable payment devices. However, social influence and facilitating conditions did not support the intention of adopting smart wearable payment devices. Adopting these devices requires policy and infrastructure development to harness the adoption of smart wearable payment devices. This paper is concluded with study limitations and future research suggestions.
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http://dx.doi.org/10.3389/fpsyg.2022.863544 | DOI Listing |
Adv Mater
January 2025
Hubei key laboratory of energy storage and power battery, School of Mathematics, Physics and Optoelectronic Engineering, Hubei University of Automotive Technology, Shiyan, 442002, P. R. China.
The inherent trade-off between permeability and selectivity has constrained further improvement of passive linear force-electric conversion performance in nanofluidic pressure sensors. To overcome this limitation, a 3D nanofluidic membrane with high mechanical strength utilizing aramid nanofibers/carbon nanofiber (ANF/CNF) dual crosslinking is developed. Due to the abundant surface functional groups of CNF and the high mechanical strength of ANF, this large-scale integrated 3D nanofluidic membrane exhibits advantages of high flux, high porosity, and short ion transport path, demonstrating superior force-electric response compared to conventional 1D and 2D configurations.
View Article and Find Full Text PDFAdv Mater
January 2025
Hangzhou Institute of Technology, Xidian University, Hangzhou, 311231, P. R. China.
Environmentally induced sensor temperature fluctuations can distort the outputs of a sensor, reducing their stability during long-term health monitoring. Here, a passive isothermal flexible sensor is proposed by using hierarchical cellulose aerogel (HCA) as the top tribonegative layer, which allows the sensor to adapt dynamic thermal environments through both radiative cooling and heat insulation. The radiative cooling effect can cool down the temperatures of a sensor in summer, while the hollow microfibers in HCA provide ultralow thermal conductivity to reduce internal heat loss in winter.
View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
School of Materials and Energy, University of Electronic Science and Technology of China, Chengdu 611731, China.
Flexible thermoelectric generators (FTEGs) can continuously harvest energy from the environment or the human body to supply wearable electronic devices, which should be a clean energy solution and provide an opportunity to satisfy the increasing power consumption of multimodal sensing and data transmission in wearable electronic devices. Here, the 64-pair FTEG was fabricated by introducing the plated through-hole and heterotypic electrode structures to optimize the thermal transport, showing the largely improved output power of 4.1 mW and record-high power density of 312 μW cm at a given ambient temperature of 15 °C inside a measurement equipment.
View Article and Find Full Text PDFSci Rep
January 2025
Dr. D. Y. Patil Vidyapeeth, Pune, Dr. D. Y. Patil School of Science & Technology, Tathawade, Pune, India.
JMIR AI
January 2025
Human-Computer Interaction and Human-Centered AI Systems Lab, AI for Healthcare Lab, Charles V. Schaefer, Jr. School of Engineering and Science, Stevens Institute of Technology, Hoboken, NJ, United States.
Background: Acute marijuana intoxication can impair motor skills and cognitive functions such as attention and information processing. However, traditional tests, like blood, urine, and saliva, fail to accurately detect acute marijuana intoxication in real time.
Objective: This study aims to explore whether integrating smartphone-based sensors with readily accessible wearable activity trackers, like Fitbit, can enhance the detection of acute marijuana intoxication in naturalistic settings.
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