31,396 research outputs found
Examining consumers’ adoption of wearable healthcare technology: The role of health attributes
With the advancement of information technology, wearable healthcare technology has emerged as one of the promising technologies to improve the wellbeing of individuals. However, the adoption of wearable healthcare technology has lagged when compared to other well-established durable technology products, such as smartphones and tablets, because of the inadequate knowledge of the antecedents of adoption intention. The aim of this paper is to address an identified gap in the literature by empirically testing a theoretical model for examining the impact of consumers’ health beliefs, health information accuracy, and the privacy protection of wearable healthcare technology on perceived usefulness. Importantly, this study also examines the influences of perceived usefulness, consumer innovativeness, and reference group influence on the adoption intention of wearable healthcare technology. The model seeks to enhance understanding of the influential factors in adopting wearable healthcare technology. Finally, suggestions for future research for the empirical investigation of the model are provided
Security risks and user perception towards adopting Wearable Internet of Medical Things
The Wearable Internet of Medical Things (WIoMT) is a collective term for all wearable medical devices connected to the internet to facilitate the collection and sharing of health data such as blood pressure, heart rate, oxygen level, and more. Standard wearable devices include smartwatches and fitness bands. This evolving phenomenon due to the IoT has become prevalent in managing health and poses severe security and privacy risks to personal information. For better
implementation, performance, adoption, and secured wearable medical devices, observing users’ perception is crucial. This study examined users’ perspectives of trust in the WIoMT while also exploring the associated security risks. Data analysed from 189 participants indicated a significant variance (R2 = 0.553) on intention to use WIoMT devices, which was determined by the significant
predictors (95% Confidence Interval; p < 0.05) perceived usefulness, perceived ease of use, and perceived security and privacy. These were found to have important consequences, with WIoMT users intending to use the devices based on the trust factors of usefulness, easy to use, and security and privacy features. Further outcomes of the study identified how users’ security matters while
adopting the WIoMT and provided implications for the healthcare industry to ensure regulated devices that secure confidential data
Empowering Homes with Intelligence: An Investigation of Smart Home Technology Adoption and Usage
The increasing interconnectedness of the world, coupled with the proliferation of connected devices, networks, and intricate systems, has paved the way for unparalleled opportunities in automation and sophisticated digital transformation. This has also led to a global rise in the adoption of smart and intelligent technologies within the smart home market. Norway, being a technologically advanced country with digitally skilled citizens, presents a potential market for the widespread adoption of smart home technologies. However, there is a lack of research on the adoption of smart home technology (SHT), specifically in Norway. Hence, this study aims at investigating the factors that influence Norwegian consumers' intentions to adopt smart home technologies, as well as the diffusion of smart home adoption in the Norwegian market. Employing a mixed-methods research design, this study gathered insights from both consumers and vendors through ten qualitative interviews and a survey with 100 participants over the period of seven months. The findings of this study provide empirical evidence supporting the significance of hedonic motivation, perceived price value, and social influence in relation to the use and adoption of SHT.publishedVersio
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Dissertation: Examining and investigating home modifications and smart home technologies to reduce fall injury among older adults.
Nearly one in six U.S. residents are over the age of 65. The proportion of older adults in the U.S. is anticipated to grow to 22.1% of the total population by 2050. The cost of treating age related conditions and injuries is expensive, government programs including Medicaid paid over $550 Billion in 2017, and makes up between 14-16% of the federal budget each year. With the high cost of treating age related conditions and injuries, and the proportion of older adults continuing to increase every year, it is imperative that researchers and government entities find and invest in preventative measures in order to reduce injury and related healthcare costs. Among the many age-related injuries older adults suffer, falls are arguably the most important to address. It is estimated that one in three older adults has a fall every year. In 2016, falls were the seventh leading cause of death among older adults. Approximately one third of all fallers require medical attention after experiencing a fall. Over 800,000 older adults are hospitalized each year due to fall related injuries. Injuries sustained as a result of a serious fall include various fractures, traumatic brain injuries, and other cuts and bruises.Home modifications, and more recently smart home technologies, can help increase the safety of older adults living in the community. With older adults wanting to “age in place”, installing these modifications and technologies before an accident happens may lower rates of injury. Today, dozens of companies sell various smart home devices for the consumer market. Bud despite the high demand for these technologies by the American consumer, the ability of these devices to keep older adults safe, and how older adults value these technologies, remains uncertain. These home technologies may be particularly beneficial to older adults living in rural areas due to the increased isolation and limited access to healthcare resources. Previous research indicates rural populations have a greater proportion of older adults compared to urban areas, yet lack the infrastructure to provide specialty care to this population. It is estimated that more than 60 million family members provide some sort of informal care to an older adult relative. Of all of these family members, nearly 40% report spending 20 or more hours a week providing this unpaid care. Previous research has failed to examine how these family members feel about home modifications and technologies for their older adult relative. Finding ways to ease the burden of caring for older family members will significantly better the situations of many family relatives.This dissertation aims to cover three areas. 1. Identify people at risk of suffering subsequent fall injuries. Find the average time between an initial fall injury and a subsequent fall injury, and find average time between an initial fall injury and death.2. Examine the preferences of older adults living in a rural area towards various smart home technologies and home modifications.3. Examine the preferences of family members of older adults regarding smart home technologies and home modifications
Understanding User Behavioral Intention to Adopt a Search Engine that Promotes Sustainable Water Management
An increase in users’ online searches, the social concern for an efficient management of resources such as water, and the appearance of more and more digital platforms for sustainable purposes to conduct online searches lead us to reflect more on the users’ behavioral intention with respect to search engines that support sustainable projects like water management projects. Another issue to consider is the factors that determine the adoption of such search engines. In the present study, we aim to identify the factors that determine the intention to adopt a search engine, such as Lilo, that favors sustainable water management. To this end, a model based on the Theory of Planned Behavior (TPB) is proposed. The methodology used is the Structural Equation Modeling (SEM) analysis with the Analysis of Moment Structures (AMOS). The results demonstrate that individuals who intend to use a search engine are influenced by hedonic motivations, which drive their feeling of contentment with the search. Similarly, the success of search engines is found to be closely related to the ability a search engine grants to its users to generate a social or environmental impact, rather than users’ trust in what they do or in their results. However, according to our results, habit is also an important factor that has both a direct and an indirect impact on users’ behavioral intention to adopt different search engines
The effect of trust, IT knowledge, and entrepreneur’s innovativeness to embrace or shun the internet of things
This study examines critical factors influencing Omani entrepreneurs’ adoption of the internet of things (IoT) by expanding the constructs at the unified theory of acceptance and use of technology (UTAUT2) with entrepreneurs’ innovativeness, IT knowledge (ITK), and trust. A cross-sectional survey questionnaire was used to collect data from 158 entrepreneurs in Oman. Data were analyzed through the structural equation modeling technique using SmartPLS. The results indicated that performance expectancy, habit, social influence, trust (TR), ITK, and entrepreneurs’ innovativeness (PI) significantly affect Omani entrepreneurs’ intention to adopt IoT. Nonetheless, the results show that there is no significant relationship between hedonic motivation, effort expectancy, price value, and facilitating conditions to adopt IoT. This study contributes to previous literature by incorporating entrepreneurs’ innovativeness, ITK, and trust into UTAUT2. Furthermore, this study was conducted in a Middle Eastern country with solid support from the government for entrepreneurs; also, there is a gap in such studies in this area. This study helps practitioners in the field better understand how to influence entrepreneurs, push them toward using IoT applications further, and encourage non-users to start using them
Understanding security risks and users perception towards adopting wearable Internet of Medical Things
This thesis examines users’ perception of trust within the context of security and privacy of Wearable Internet of Medical Things (WIoMT). WIoMT is a collective term for all medical devices connected to internet to facilitate collection and sharing of health-related data such as blood pressure, heart rate, oxygen level and more. Common wearable devices include smart watches and fitness bands. WIoMT, a phenomenon due to Internet of Things (IoT) has become prevalent in managing the day-to-day activities and health of individuals. This increased growth and adoption poses severe security and privacy concerns. Similar to IoT, there is a need to analyse WIoMT security risks as they are used by individuals and organisations on regular basis, risking personal and confidential information. Additionally, for better implementation, performance, adoption, and secured wearable medical devices, it is crucial to observe users’ perception. Users’ perspectives towards trust are critical for adopting WIoMT. This research aimed to understand users’ perception of trust in the adoption of WIoMT, while also exploring the security risks associated with adopting wearable IoMT. Employing a quantitative method approach, 189 participants from Western Sydney University completed an online survey. The results of the study and research model indicated more than half of the variance (R2 = 0.553) in the Intention to Use WIoMT devices, which was determined by the significant predictors (95% Confidence Interval; p < 0.05), Perceived Usefulness, Perceived Ease of Use and Perceived Security and Privacy. Among these two, the domain Perceived Security and Privacy was found to have significant outcomes. Hence, this study reinforced that a WIoMT user intends to use the device only if he/she trusts the device; trust here has been defined in terms of its usefulness, easy to use and security and privacy features. This finding will be a steppingstone for equipment vendors and manufacturers to have a good grasp on the health industry, since the proper utilisation of WIoMT devices results in the effective and efficient management of health and wellbeing of users. The expected outcome from this research also aims to identify how users’ security and perception matters while adopting WIoMT, which in future can benefit security professionals to examine trust factors when implementing new and advanced WIoMT devices. Moreover, the expected result will help consumers as well as different healthcare industry to create a device which can be easily adopted and used securely by consumers
Determinants of physicians' purchase intention for innovative services: Integrating professional characteristics with technology acceptance model and theory of planned behaviour
© 2015 Imperial College Press. This paper seeks to explore the factors that influence physicians' purchase intention for supplementary professional services that have been recently introduced to the market. For that reason, a model has been developed and empirically tested using data collected from 100 physicians regarding an innovative e-detailing service. Results show that physicians' purchase intention is significantly influenced by five factors. Three of them derive from the integration of Technology Acceptance Model (TAM) with the Theory of Planned Behaviour (TPB), i.e., perceived usefulness, perceived ease of use and professional image. The rest, namely work experience, working status and innovativeness, refer to physicians' professional characteristics. Work experience and innovativeness were found to have a significant effect on physicians' perceptions of the innovative service, whereas, physicians' current working status was not found to have significant influence on either their perceptions of the innovative service or their purchase intention
Research investigations on the use or non-use of hearing aids in the smart cities
This study aims to explore factors influencing behavioral intention to adopt hearing aids among old adults in smart cities. It argues that trust is a moderator to influence the relationship between attitude, subjective norm and individual's behavioral intention in smart cities. This study tests hypotheses using a sample of 103 respondents from six smart cities in China. The results reveal that attitude is main factor influencing individual's behavioral intention. Subjective norm and trust are both not statistically significant at the 95% confidence interval in the model of multiple-regression. Interestingly, it finds that trust moderates the relationship between subjective norm and individual's behavioral intention. It means that the audiologists' advice can positively affect person's behavioral intention in smart cities. The findings imply that the Theory of Reasoned Action can be partially used to explain the person's behavioral intention in Chinese context. This study contributes to encourage old people to use smart hospitals to consult audiologists about hearing loss and hearing aids rehabilitation. Hence, hearing aids can improve their quality of life (QoL), which can be reflected by the improved standard of living, better access to treatments and also the positive sentiment about their life, including comfort, friendship, happiness and a closer connection to the society
Fatores que afetam a adoção de análises de Big Data em empresas
With the total quantity of data doubling every two years, the low price of computing and data storage, make Big
Data analytics (BDA) adoption desirable for companies, as a tool to get competitive advantage. Given the availability
of free software, why have some companies failed to adopt these techniques? To answer this question,
we extend the unified theory of technology adoption and use of technology model (UTAUT) adapted for the BDA
context, adding two variables: resistance to use and perceived risk. We used the level of implementation of
these techniques to divide companies into users and non-users of BDA. The structural models were evaluated
by partial least squares (PLS). The results show the importance of good infrastructure exceeds the difficulties
companies face in implementing it. While companies planning to use Big Data expect strong results, current
users are more skeptical about its performance.Con la cantidad total de datos duplicándose cada dos años, el bajo precio de la informática y del almacenamiento
de datos, la adopción del análisis Big Data (BDA) es altamente deseable para las empresas, como un
instrumento para conseguir una ventaja competitiva. Dada la disponibilidad de software libre, ¿por qué algunas
empresas no han adoptado estas técnicas? Para responder a esta pregunta, ampliamos la teoría unificada
de la adopción y uso de tecnología (UTAUT) adaptado para el contexto BDA, agregando dos variables: resistencia
al uso y riesgo percibido. Utilizamos el grado de implantación de estas técnicas para dividir las empresas
entre: usuarias y no usuarias de BDA. Los modelos estructurales fueron evaluados con partial least squres (PLS).
Los resultados muestran que la importancia de una buena infraestructura excede las dificultades que enfrentan
las empresas para implementarla. Mientras que las compañías que planean usar BDA esperan muy buenos
resultados, las usuarias actuales son más escépticos sobre su rendimiento.Com a quantidade total de dados duplicando a cada dois anos, o baixo preço da computação e do armazenamento
de dados tornam a adoção de análises de Big Data (BDA) desejável para as empresas, como aquelas
que obterão uma vantagem competitiva. Dada a disponibilidade de software livre, por que algumas empresas
não adotaram essas técnicas? Para responder a essa pergunta, estendemos a teoria unificada de adoção e uso
de tecnologia (UTAUT) adaptado para o contexto do BDA, adicionando duas variáveis: resistência ao uso e risco
percebido. Usamos a nível da implementação da tecnologia para dividir as empresas em usuários e não usuários
de técnicas de BDA. Os modelos estruturais foram avaliados por partial least squares (PLS). Os resultados
mostram que a importância de uma boa infraestrutura excede as dificuldades que as empresas enfrentam para
implementá-la. Enquanto as empresas que planejam usar Big Data esperam resultados fortes, os usuários
atuais são mais céticos em relação ao seu desempenho
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