Analyzing the Elderly Users’ Adoption of Smart-Home Services

Pal, Debajyoti; Funilkul, Suree; Vanijja, Vajirasak; Papasratorn, Borworn

doi:10.1109/access.2018.2869599

Cited by 89 publications

(79 citation statements)

References 93 publications

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“…Usefulness perception is the degree to which a user believes that a product or technology is helpful to the performance or daily life after using it. Usability perception is the degree to which a product or technology is easy for users to learn and use [52,53]. The two constructs of usefulness perception C5 and usability perception C6 come from the technology acceptance model.…”

Section: Steps To Calculate Importance Based On Neighborhood Rough Setmentioning

confidence: 99%

Using Neighborhood Rough Set Theory to Address the Smart Elderly Care in Multi-Level Attributes

Zhou

Tan

et al. 2020

Symmetry

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The neighborhood rough set theory was adopted for attributes reduction and the weight distribution of condition attributes based on the concept of importance level. Smart elderly care coverage rate is low in China. A decisive role in the adoption of smart elderly care is still a problem that needs to be addressed. This study contributes to the adoption of smart elderly care was selected as the decision attribute. The remaining attributes are used as conditional attributes and the multi-level symmetric attribute set for assessing acceptance of smart elderly care. Prior studies are not included smart elderly care adoption attributes in multi-levels; hence, this problem needs to be addressed. The results of this study indicate that the condition attribute of gender has the greatest influence on the decision attribute. The condition attribute of living expenses for smart elderly care has the second largest impact on decision attribute. Children’s support for the elderly decency of the novel elderly care system and the acceptance of non-traditional elderly care methods belong to the primary condition attribute of traditional concept. The result indicates traditional concepts have a certain impact on the adoption of smart elderly care and a condition attribute of residence also has a slight influence on the symmetric decision attribute. The sensitivity analysis shows the insights for uncertainties and provides as a basis for the analysis of the attributes in the smart elderly care service adoption.

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Section: Steps To Calculate Importance Based On Neighborhood Rough Setmentioning

confidence: 99%

Using Neighborhood Rough Set Theory to Address the Smart Elderly Care in Multi-Level Attributes

Zhou

Tan

et al. 2020

Symmetry

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“…The attitude of older adults in adopting smart technologies is also discussed as an important factor for them to enjoy well-being while leading independent lives (Courtney et al, 2008;Pal et al, 2018). Various studies are attempting to understand the characteristics of older adults and apply them to design.…”

Section: Evaluation Frameworkmentioning

confidence: 99%

A Critical Review of Smart Residential Environments for Older Adults With a Focus on Pleasurable Experience

Lee

Kim

2020

Front. Psychol.

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Various smart services and technologies have been developed to support older adults' well-ness, make their daily tasks easier, and enhance their overall quality of life. When people grow older, older adults inevitably experience a significant decrease in their physical, cognitive, and sensory capabilities, which makes them develop negative attitudes toward technology. In this regard, this study highlights that older adults require not only usable and practical spaces but also smart residential environments that can fulfill them emotionally. Research on smart environments for this population should consider the hedonic and experiential factors of interacting with technology, such as fun, fulfillment, play, and user engagement. This study aims to provide a comprehensive review of smart residential environments to support positive aging and pleasurable user experience in the architecture domain. For this critical review emphasizing the pleasurable smart environment, an evaluation framework was developed, consisting of four categories: well-ness, independence, acceptance, and design. Through an extensive analysis of selected papers in the architecture domain, it was found that studies on the smart home tend to focus on utilitarian factors, such as usability, monitoring physical experiences, and simulating energy efficiency, and rarely mention psychological well-ness. Smart environments should be designed to not only emphasize efficiency, effectiveness, and satisfaction but also to engage older adults and provide them positive experiences. As various smart technologies continue to evolve and integrate into smart living spaces, it is important to understand older adults' cognitive and emotional aspects and make the smart environment a more comfortable place for them.

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“…Through the analysis of a large number of documents, the theoretical basis of the study lies in the theory of reasoned action, the theory of planned behavior, and the technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT) evolved on this basis. The theoretical models are based on the adopted theories to increase constructs or combine with other theories, including the elderly smart home technology acceptance model [17]; the conceptual extension model based on UTAUT model [18,19]. Pal et al [20] presented the effectiveness of three theoretical models of TAM, rational behavior theory, and planned behavior theory on the adoption of smart homes by the elderly.…”

Section: Proposed Modelmentioning

confidence: 99%

“…Ergonomics refers to the three elements of human, machine, and environment as the main body of a human-machine system, making the design of the machine and the living environment suitable for the physiological and psychological characteristics of the human, so that people can work and live in comfortable and convenient conditions [16]. Prior studies based on the models to explain the systematic attributes that influence the acceptance behavior of elderly users [17]. In lieu of those studies, the empirical study results provide rich data for Meta quantitative analysis.…”

Section: Proposed Modelmentioning

confidence: 99%

“…Pal et al [17] indicated the Elderly Smart Home Technology Acceptance Model, analyzed the behavioral data of 254 elderly people using smart homes technology, and found a significant relationship between affordability and behavioral intention. Knowledge and experience include the user's education level, and Prior experience in using gerontechnology products or services.…”

Section: User Individual Characteristicsmentioning

confidence: 99%

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Exploring the Systematic Attributes Influencing Gerontechnology Adoption for Elderly Users Using a Meta-Analysis

et al. 2020

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This study aims to explore the key systematic attributes influencing the acceptance of gerontechnology by seniors in response to global aging and rapid technological progress. A meta-analysis was carried out to quantitatively synthesize the results of 25 empirical studies published from 2010 to 2020. After standardized coding and descriptive statistics, as well as tests and analysis of main effects and heterogeneity, publication bias. The following results were obtained: Perceived usefulness and perceived ease of use have a significant positive impact on the user’s attitude and behavioral intention; performance expectancy, effort expectancy, trust, technical performance and subjective norm have a significant positive correlation with the user’s behavioral intention; social influence, facilitating conditions have a positive correlation with the user’s behavioral intention; anxiety has a significant negative correlation to the user’s behavioral intention. The key systematic influencing attributes are classified into three categories: (1) User individual characteristics; (2) product and technical characteristics; and (3) environmental characteristics. This study provides researchers and practitioners with a systematic evidence-based basis to reduce the gap in decision-making for gerontechnology practices.

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Analyzing the Elderly Users’ Adoption of Smart-Home Services

Cited by 89 publications

References 93 publications

Using Neighborhood Rough Set Theory to Address the Smart Elderly Care in Multi-Level Attributes

Using Neighborhood Rough Set Theory to Address the Smart Elderly Care in Multi-Level Attributes

A Critical Review of Smart Residential Environments for Older Adults With a Focus on Pleasurable Experience

Exploring the Systematic Attributes Influencing Gerontechnology Adoption for Elderly Users Using a Meta-Analysis

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