Modifying UTAUT2 for a cross-country comparison of telemedicine adoption

Schmitz, Anne; Díaz‐Martín, Ana M.; Guillén, Ma Jesús Yagüe

doi:10.1016/j.chb.2022.107183

Cited by 67 publications

(66 citation statements)

References 77 publications

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“…Gansser and Reich ( 2021 ) analyzes factors influencing the use of VAs in a daily life environment in three segments of mobility, home, and health, adding the variables wellbeing and health, convenience, comfort, sustainability, safety and security , and Personal Innovation . Schmitz et al ( 2022 ) investigated patients' intention in order to take advantage of virtual medical appointments by adding Perceived Security , and Perceived Product Advantage to the user intention model of variable analysis.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants

2022

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Virtual Assistants, also known as conversational artificial intelligence, are transforming the reality around us. These virtual assistants have challenged our daily lives by assisting us in the different dimensions of our lives, such as health, entertainment, home, and education, among others. The main purpose of this study is to develop and empirically test a model to predict factors that affect users' behavioral intentions when they use intelligent virtual assistants. As a theoretical basis for investigating behavioral intention of using virtual assistants from the consumers' perspective, researchers employed the extended Unified Theory of Acceptance and Use of Technology (UTAUT2). For this research paper, seven variables were analyzed: performance expectancy, effort expectancy, facilitating conditions, social influence, hedonic motivation, habit, and price/value. In order to improve consumer behavior prediction, three additional factors were included in the study: perceived privacy risk, trust, and personal innovativeness. Researchers carried out an online survey with 304 responses. The obtained sample was analyzed with Structural Equation Modeling (SEM) through IBM SPSS V. 27.0 and AMOS V 27.0. The main study results reveal that factors, such as habit, trust, and personal innovation, have a significant impact on the adoption of virtual assistants. However, on the other side, performance expectancy, effort expectancy, facilitating conditions, social influence, hedonic motivation, price/value, and perceived privacy risk were not significant factors in the users' intention to adopt this service. This research paper examines the effect of personal innovation, security, and trust variables in relation to the use of virtual assistants. It contributes to a more holistic understanding of the adoption of these intelligent devices and tries to fill the knowledge gap on this topic, as it is an emerging technology. This investigation also provides relevant information on how to successfully implement these technologies.

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Section: Theoretical Frameworkmentioning

confidence: 99%

Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants

2022

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“…In the meantime, Venkatesh et al (2003) proposed UTAUT, which has currently become one of the most popular theories in information systems and information technologies applications. Its prediction performance has been proven to be reasonably satisfactory (Andrews et al, 2021; Chao, 2019; Liu & Tao, 2022; Schmitz et al, 2022; Tan, 2013a, 2013b, 2019). UTAUT is a stable model, where the variance prediction of behavioral intention and use of technology reaches 56% and 40%, respectively.…”

Section: Introductionmentioning

confidence: 99%

Developing an Extended Theory of UTAUT 2 Model to Explore Factors Influencing Taiwanese Consumer Adoption of Intelligent Elevators

et al. 2022

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Followed by the fast developments in Internet of Things (IoT), artificial intelligence (AI) technologies, utilizing cloud architecture and big data, have been integrated into various aspects of our daily lives. Such an integration results in high levels of convenience, comfort, and energy savings. Deploying such new technologies benefits the elevator industry as well. Intelligent elevator with energy control schemes can improve the energy efficiency of eco-friendly applications. The purpose of this study is to examine the factors that affect the intelligent elevator adoption of Taiwanese people using the extended unified theory of acceptance and use of technology (UTAUT 2) model, which considers factors such as environmental consciousness, artificial intelligence optimism, attitude, and perceived quality. A well-structured face-to-face survey is performed to obtain data from the consumers living in central Taiwan. The data acquired are analyzed via structural equation modeling using the partial least squares method. The analysis results indicate that attitude, habit, performance expectancy, effort expectancy, and perceived quality are important factors that affect the behavioral intentions of consumers when adopting new technologies, such as an intelligent elevator. However, facilitating conditions adversely affect the behavioral intentions. In addition, environmental consciousness and artificial intelligence optimism are crucial factors that affect performance and effort expectancies, whereas the latter two contribute positively to attitude. The findings of this study supplement existing literature regarding the behavioral intentions for adopting intelligent elevators. Finally, the theoretical and practical significances of this research study are discussed.

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“…Several previous studies have shown that perceived ease of use influences perceived usefulness (Chandra & Hartono, 2018;Daragmeh et. al., 2021;Schmitz et al, 2022;Tsai et al, 2021;Wu & Chen, 2017). The easier a system is to use, the more people will think it is functional (Lai, 2017).…”

Section: Relationship Of Perceived Ease Of Use and Perceived Usefulnessmentioning

confidence: 99%

“…People will think that a system is functional when it is easy to use (Lai, 2017). Previous studies have shown that perceived ease of use influences perceived usefulness (Chandra & Hartono, 2018;Daragmeh et al, 2021;Schmitz et al, 2022;Tsai et al, 2021;Wu & Chen, 2017). Thus, this study formulates the following hypothesis.…”

Section: Relationship Of Perceived Ease Of Use and Behavioural Intent...mentioning

confidence: 99%

Determinants of intention to use e-wallet in Generation Z

Rahmadhani

Buchdadi²,

Fawaiq³

et al. 2023

Bisma (Bisnis Manaj.)

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Generation Z, as true digital natives or generations born and raised with the internet, is familiar with digital products. One digital product is an e-wallet used as an online payment method. This study aims to discover the factors that influence behavioural intention to use e-wallets in generation Z that use an e-wallet and live in Greater Jakarta. The theoretical basis of this study is the Technology Acceptance Model (TAM), where the variables involved are behavioural intention to use, perceived ease of use, and perceived usefulness, and two other factors, i.e., perceived security and social influence. A total of 245 respondents were collected by online survey and analysed with Structural Equation Modelling (SEM). This study finds that social influence affects perceived ease of use positively and significantly. Perceived ease of use influences perceived usefulness positively and significantly. Perceived ease of use and perceived usefulness positively influence behavioural intention to use. However, social influence does not influence perceived usefulness, and perceived security does not influence behavioural intention to use. This study's originality resides in its examination of reported ease of use and perceived usefulness as mediating variables of social influence on Generation Z's propensity to use e-wallets.

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Modifying UTAUT2 for a cross-country comparison of telemedicine adoption

Cited by 67 publications

References 77 publications

Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants

Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants

Developing an Extended Theory of UTAUT 2 Model to Explore Factors Influencing Taiwanese Consumer Adoption of Intelligent Elevators

Determinants of intention to use e-wallet in Generation Z

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