Effort Expectancy Research Articles

Extend UTAUT2 Model to Analyze User Behavior of China Construction Bank Mobile App

The outbreak of COVID-19 has been accelerating the digital transformation of financial institutions all over the world. Mobile banking APPs become an important channel to provide financial services in the Internet and Big Data era. Factors that restrict its development have attracted the close attention of scholars and practitioners around the world. Different from a general APP software, mobile banking APPs naturally have some financial attributes which set high requirements for personal privacy protection and other security issues. For this reason, this paper extends the original UTAUT2 model by incorporating a new constructor: perceived risks. The study carefully selects China Construction Bank’s mobile banking app (short as “the CCB APP”), as she is the biggest bank in China and has good novelty and representativeness in financial technology. This paper constructs an extended UTAUT2-based model using questionnaires and structural equation modeling the user behavior of CCB APP and tests the influencing factors of the proposed model through empirical analysis. Similar to other studies using the UTAUT2 model, the findings of this paper indicate that performance expectations, effort expectations, social influence, facilitators, and habits, all have a positive impact on CCB APP users’ intentions. Their intention to use was a mediating variable of user behavior, while facilitators directly influenced CCB users’ behavior. However, the study finds that perceived risk negatively affects the CCB users’ intention while hedonic motivation and price value do not significantly affect users’ decision-making process. Based on these findings, the misdirection should to be avoided in regard to financial APP development by financial institutions is discussed and the future research direction concerning mobile banking app adoption is illustrated.

Analysis of User Acceptance of the Mobile Application of National Health Insurance Using the UTAUT Model

Development technology in the field health own positive impact. On the field Health services are available developed mobile applications Forgive Health services to public by online. The Mobile JKN Application has objective For give service health to community and make it easier power health For give service optimally. On research This analyze about reception user The Mobile JKN application uses the Unified Theory of Acceptance and Use of Technology (UTAUT). Respondent data obtained during spread questionnaire that is as many as 110 respondents. Respondent data Then analyzed using Structural Equation Model (SEM) research results This show that Performance Expectancy (PE) and Social Influence (SI) have an influence significant to Behavioral Intention (BI). However, for Effort Expectancy (EE) it is not influential significant to Behavioral Intention (BI) with t-test values are 2.224, 2.224, and 1.198 respectively. Third variable the can explain influence to Behavioral Intention (BI) was 34.3%. Whereas for Facilitating Conditions (FC) and Behavioral Intention (BI) influence significant towards Use Behavior (UB) with t-test values are 4.013 and 5.636 respectively. As well as second variable the can explain influence on Use Behavior (UB) of 59.3%. So on research explain reception user to use Mobile JKN application with using UTAUT.

Analyzing User Experience and User Satisfaction: Evaluating User Acceptance of the Halo Hermina App

This research investigates the factors influencing user acceptance of the Halo Hermina mobile health application through an analysis of user experience and satisfaction. The study utilized a survey method to gather feedback from Halo Hermina users, assessing the questionnaire's validity and reliability. The results indicate strong validity across most items, with correlation values between 0.779 and 0.828 for performance expectancy and over 0.77 for effort expectancy. The reliability analysis shows high internal consistency, with Cronbach's Alpha values exceeding 0.976. User satisfaction scored the highest mean (4.027), indicating a consistent high level of satisfaction among users. The correlation analysis reveals significant relationships between performance expectancy, effort expectancy, facilitating condition, and behavioral intention, with the strongest correlation found between performance expectancy and effort expectancy (0.8796). Overall, the study emphasizes the crucial role of enhancing user experience and satisfaction to boost the adoption of mobile health applications like Halo Hermina, providing valuable insights for developers and stakeholders to enhance application features and service quality to meet user expectations effectively.

HARAPAN KINERJA DAN HARAPAN USAHA GURU DALAM MENGGUNAKAN TEKNOLOGI INFORMASI DAN KOMUNIKASI DENGAN PENDEKATAN UNIFIED THEORY OF ACCEPTANCE AND USE OF THECHNOLOGY DI SD NEGERI 28/IV KOTA JAMBI

This study aims to describe teachers' performance expectations and effort expectations in using Information and Communication Technology (ICT) through the Unified Theory of Acceptance and Use of Technology (UTAUT) approach. The research was conducted at Sekolah Dasar Negeri 28/IV Kota Jambi trough qualitative research with a case study design. Data were collected through observations and interviews with teachers at SDN 28/IV Kota Jambi. Data analysis was conducted through the Miles and Huberman model. The results indicate that two components of the UTAUT model, performance expectations and effort expectations, were achieved by the teachers in the learning process through ICT. The performance expectations aspect showed that ICT use in the learning process provided benefits, helped achieve learning objectives, made teachers more productive, innovative and creative, and enhanced collaboration among teachers. Meanwhile, the effort expectations aspect demonstrated that ICT use made it easier for teachers to conduct lessons, design learning tools, and made learning more effective, efficient, clearer, and easier to be understood.

Acceptance Analysis Of Web-Based Learning Media In Indramayu Regency Based On The UTAUT2 Model

<p>The current education system has adopted a 21st-century approach, emphasizing learning to know, learning to do, learning to be, and learning to live together. This shift has moved from a teacher-centered to a student-centered learning approach. 21st-century education demands the development of learning skills, innovation, information literacy, and digital literacy. The aim is to assess the extent to which variables such as Effort Expectancy (EE), Facilitating Conditions (FC), Hedonic Motivation (HM), ICT Usage Habits (IUH), Performance Expectancy (PE), Perceived Learning Opportunities (PLO), and Social Influences (SI) can influence Behavioral Intention (BI). Additionally, the study evaluates factors influencing the level of acceptance of web-based learning media usage among teachers in Indramayu Regency, using the UTAUT2 model.This research employs a qualitative descriptive method with a questionnaire as the instrument. The population comprises all teachers in Indonesia, with a sample of 100 elementary school teachers in Indramayu Regency. The findings indicate that variables EE, FC, HM, IUH, PE, PLO, and SI collectively have an 81.1% influence on Behavioral Intention (BI), while 18.9% is attributed to other unexplored factors. The hypothesis test results reveal that EE, FC, HM, IUH, PE, and SI do not significantly impact Behavioral Intention (BI). However, Perceived Learning Opportunities (PLO) has a significant influence on Behavioral Intention (BI).</p>

Continue Use Intention Analysis Using The Integration of The Unified Theory of Acceptance and Use of Technology (UTAUT) 2 and Delone & Mclean (D&M) Models Modified in The My TelU Mobile Student Account Application

My TelU Mobile is a learning support application released by Telkom University on May 25, 2021. This application can be downloaded on the Play Store and App Store and has become a super app that has quite a high number of downloads. However, its user traffic is not yet stable, as seen in the decreasing usage traffic during the lecture period. The purpose of this study was to determine the factors that influence the acceptance and use of the My TelU Mobile application using an integration of the UTAUT-2 and Delone & McLean models. This study uses a quantitative method with descriptive and causal research types. The sampling technique uses a non-probability sampling technique of the purposive sampling type with a sample size of 400 respondents. The data analysis technique uses descriptive analysis and PLS. The findings of this study are that effort expectancy, information quality, service quality, user satisfaction have a significant effect on continue use intention and system quality, information quality, service quality have a significant effect on user satisfaction. However, performance expectancy, social influence, facilitating condition, habit, hedonic motivation, and system quality do not have a significant effect on continue use intention of My TelU Mobile application.

Implementation of The Electronic Application for Marriage and Pregnancy (Elsimil) to Accelerate Stunting Reduction

Denpasar City is one of the areas that has succeeded in reducing the prevalence to 5.5%, one of which is by providing guidance to prospective brides to reduce the risk of stunting cases by implementing the ELSIMIL application. This study was conducted to obtain an overview of the factors that influence the behavior of using the ELSIMIL application in Denpasar City so that it can be an effort to accelerate stunting reduction. Data were collected from 14 informants, both users and policy holders. Data collection methods through interviews, observations, and document studies with validity testing through source triangulation and method triangulation. The results of the description of the ELSIMIL application implementation show that performance expectations, effort expectations, social influences, and facility conditions affect usage behavior along with behavioral intentions according to UTAUT theory. Performance expectations, which include perceived usefulness, motivation, relative advantage, and belief in the future potential of the application, are the main factors supporting usage behavior. Effort expectations include perceived ease and complexity of information can be a factor that supports behavioral intentions. Social support from family and friends and application conditions can also influence ELSIMIL usage behavior

Understanding Consumer Acceptance of AI in the Leisure Economy: A Structural Equation Modeling Approach

This research examines the determinants of consumer acceptance of artificial intelligence (AI) in the leisure economy, using a structural equation model to analyze responses from 560 participants. The study focuses on several psychological factors: Perceived Ease of Use (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Hedonic Motivation (HM), Perceived Value (PV), and Habit (HB), and their impact on Behavioral Intention (BI) to adopt AI technologies. Results indicate significant influence of six constructs (PE, FC, SI, PV, HM, HB) on BI, with the exception of one hypothesis. The research also assesses the role of Personal Innovativeness in enhancing the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model's predictive accuracy. This study contributes to understanding AI adoption in leisure, offering valuable insights for AI application development and marketing strategies in this sector.

Navigating Patients’ Intentions in Smart Health: Insights from Novel Factors

This research aims to evaluate the extent to which a specific set of factors affect patients’ intention to adopt and use smart health applications. These factors, derived from the unified theory of acceptance and use of technology (UTAUT), include technology anxiety (TA), perceived reliability (PR), inertia (Int) and privacy concern (PC). Data were collected from 259 participants via a cross-sectional survey. The researchers employed the partial least squares (PLS) method for data analysis using SmartPLS, a statistical tool based on structural equation modelling (SEM). The findings indicate that performance expectancy, facilitating conditions, Int and PR significantly influence patients’ intentions to adopt smart health services. However, no significant relationships were found between effort expectancy, social influence, PC, TA and the intention to adopt smart health services. This study contributes to the literature by integrating additional factors (TA, PR, Int and PC) into the UTAUT framework. Limitations of the study include the cross-sectional design, which may not capture changes over time, and the reliance on self-reported data, which may be subject to biases. Future research should consider longitudinal studies to examine the evolving nature of technology adoption and explore additional contextual factors that might influence patient intentions. This research provides practical insights for healthcare practitioners aiming to enhance the adoption of smart health applications.

Understanding metaverse adoption in education: The extended UTAUMT model

The metaverse, an immersive virtual environment enabling users to engage with digital experiences, has the potential to revolutionize education. However, research pertaining to this area is still in its early stages. This study investigates the variables that influence the acceptance of educational metaverses and the intention to use them. It also presents an expanded model called the Unified Theory of Acceptance and Use of Metaverse Technology (UTAUMT) to provide guidance to educators and decision-makers. The study involved 253 Vietnamese teachers and students who had experience with metaverse, selected through purposive sampling. The UTAUMT provides a comprehensive framework that encompasses various factors, including metaverse performance expectancy (MPE), metaverse effort expectancy (MEE), metaverse social influence (MSI), metaverse hedonic motivation (MHM), metaverse price value (MPC), metaverse self-efficacy (MSE), and metaverse facilitating conditions (MFC). These factors were assessed using a self-administered questionnaire. The findings indicate that MEE, MSI, MFC, MSE, and MBI have a considerable impact on the educational metaverse MUB. The extended UTAUMT model makes a theoretical contribution by including metaverse-specific elements into the technology acceptance framework. The managerial implications focus on the integration of the metaverse, training of users, and providing support to enhance the adoption rate. This study explores the elements that contribute to the adoption of metaverse technology in education and contributes to the existing literature on the acceptance of metaverse technology.

The role of readiness for change on behavioral intention viewed from performance and effort expectancy in the implementation of electronic medical records

Background: Technological developments have triggered a transformation in the implementation of electronic medical records (RME) in Indonesia, in line with regulations that require the implementation of RME in all health service facilities by the end of 2023. Although it has been proven to increase efficiency and reduce medical errors, the implementation of RME faces challenges such as infrastructure readiness and risk factors cultural. Purpose: To identify factors that influence the success of RME implementation, including performance expectations and the use of RME in health facilities in Indonesia. Method: The design of this research is quantitative, observational analytical type with a cross-sectional approach. The population of this study were employees of Community Health Centers in Kediri Regency. The probability sampling technique using a random sampling approach obtained a sample of 336 employees in 33 Community Health Centers and SmartPLS 2.9.8 was used to test the hypothesis. The variables used in this research are: performance expectancy (X1), effort expectancy (X2), Readiness for Change (Z), and Usage Intention (Y). Results: The results of the research show that there is a direct influence of performance expectancy, effort expectancy, and Readiness to Change on Usage Intention with P = 0.000. Individual Change Readiness Mediates performance expectancy and effort expectancy on Usage Intention, which has a significant effect with a P value of 0.001. Conclusion: This research concludes that new insights into the critical role of change readiness as a mediator between technology acceptance factors and behavioral intentions.

Influencing the Adoption of e-Government: A Systematic Literature Review

This Systematic Literature Review study discusses the factors that influence the adoption of e-government services with varsiability in the influence of these factors in various countries. The research confirms the importance of trust, performance expectancy, effort expectancy, social influence, and facilitating conditions in the acceptance and adoption of e-government services. Trust factors, especially related to information security and government transparency, were found to be key elements in driving e-government adoption. In addition, the expectation of benefits obtained, ease of use, and influence from the social environment also play an important role in people's decision to use the service. Suggested recommendations to increase e-government adoption involve improving technology infrastructure, supportive policies, technology training for government personnel, as well as an approach that considers local community conditions and factors. This study provides important insights for governments and agencies in improving e-government services and increasing the adoption of these technologies across various social and cultural environments.

Factors influencing Chinese pre-service teachers’ behavioral intention and use behavior to adopt VR training system: based on the UTAUT2 model

With the advent of the intelligence era, the empowerment of technology in education has triggered changes in the forms and concepts of teaching and learning. Virtual reality (VR), as a potential educational technology, has been widely used in teaching, providing students with almost real learning experiences. In particular, practice-centered pre-service teacher education is in greater need of VR. This case study applied and improved the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) as a theoretical foundation to explore pre-service teachers’ intention and behavior of adopting the VR training system. A sample of 278 Chinese pre-service teachers was collected by implementing the partial least squares structural equation modeling (PLS-SEM) via the Smart-PLS software. Study results reveal that pre-service teachers’ behavioral intention of adopting the VR training system is positively impacted by self-efficacy, effort expectancy, social influence, performance expectancy, facilitating conditions, and hedonic motivation, ranked from highest to lowest. Their use behavior with the training system is positively impacted by behavioral intention, facilitating conditions, and habit. Accordingly, this study presents suggestions for higher education institutions and VR education system developers on how to use and design VR training systems in pre-service teacher education through model construction, model validation, and conclusion analysis.

Understanding the dynamics of customer satisfaction and repurchase intentions in the era of platform service supply chain – a case study of Foodpanda in Pakistan

ABSTRACT This study investigates the evolving restaurant sector in Pakistan, highlighting the significant role of Platform Service Supply Chains (PSSC) facilitated by food ordering apps like Foodpanda. Understanding PSSC is essential for businesses to thrive in the digital age and effectively manage the dynamics of digital service delivery. Foodpanda exemplifies a complex multi-stakeholder ecosystem that involves intricate technology integration, logistics challenges, robust data management, and a continuous need for innovation in a competitive market. This research aims to identify the key factors driving customer satisfaction and repurchase intention in this dynamic environment, acknowledging the transformative impact on consumer behavior. It also examines how health consciousness and food safety concerns influence these relationships in Pakistan. The study employs an integrated model based on the Theory of Planned Behaviour (TPB) and the Unified Theory of Acceptance and Use of Technology (UTAUT), collecting data from a convenient sample of Foodpanda app users. Using structural equation modeling, the findings highlight critical determinants such as effort expectancy, perceived usefulness, information quality, perceived risk, social influence, and trust in shaping customer satisfaction. This satisfaction, in turn, positively affects repurchase intention. Importantly, the study reveals that health consciousness and food safety concerns negatively impact the positive relationship between customer satisfaction and repurchase intention. The paper contributes theoretically by exploring customer behavior intricacies within the PSSC framework and offers practical insights for researchers and professionals in the food app industry. However, it acknowledges limitations, such as the use of a convenient sample, and suggests avenues for further research in this growing field.

Intention to Use FinTech Payments: The Perspectives of Benefits, Risks, and Openness to Change

Objective - The COVID-19 pandemic has significantly transformed many aspects of daily life, including the way payments are made. While the usage of cashless payments has increased, cash remains the main mode of payment in Malaysia. Therefore, this study aims to explore the factors driving the intention to use FinTech payments based on the Unified Theory of Acceptance and Use of Technology (UTAUT) with the Value-based Adoption Model (VAM). Methodology/Technique – 546 usable responses were collected using a stratified sampling technique across 13 states in Malaysia. Then, structural equation modeling using the partial least squares approach was applied to test the hypotheses. Finding – The findings show that performance expectancy, effort expectancy, social benefit, privacy risk, and openness to change are the significant determinants of intention to use FinTech payments. Openness to change was found to be the most significant predictor of intention to use FinTech payments. However, the study failed to confirm the impact of social influence, economic benefit, security risk, and regulatory support on the intention to use FinTech payments. This study does not fully validate the significance of UTAUT and VAM constructs. Novelty – To the best of our knowledge, this is the first study that uses the UTAUT and VAM on intention to use FinTech payments together with openness to change and regulatory support. This is a framework that covers the decision-making determinants from the perspectives of benefits, risks, individual characteristics, and the external environment. Type of Paper: Empirical JEL Classification: G23, G28, G29 Keywords: FinTech Payment, Intention to Use, UTAUT, VAM, Benefits, Risks Reference to this paper should be referred to as follows: Chen, N.H; Habibullah, M.S; Sapar, R. (2024). Intention to Use FinTech Payments: The Perspectives of Benefits, Risks, and Openness to Change, GATR-Global J. Bus. Soc. Sci. Review, 12(3), 91–113. https://doi.org/10.35609/gjbssr.2024.12.3(1)

Adoption Drivers of Digital Platform for Coal Production Planning: an Extended UTAUT Model Using PLS-SEM Analysis

In 2022, the coal production industry encountered unprecedented challenges accompanied by a substantial global commodity price surge. The operational impact of this situation surpasses current technological capabilities of coal companies, particularly in optimizing coal blending scenarios. A pivotal aspect of digital transformation involves integration of new digital platform for production planning. This study employs the Unified Theory of Acceptance and Use of Technology in conjunction with decision theory to identify key factors influencing the platform adoption at a coal mining company. Structured questionnaires were utilized, followed by analysis using the SmartPLS 4.0.9.9 software. Findings reveal that both Performance Expectancy and Effort Expectancy positively influence users’ behavioral intention to adopt digital platform for production planning. Behavioral Intention, in turn, significantly impacts actual usage behavior. Unanticipated situational factors and others' attitudes were found to have negligible mediating effects, while variables such as age and experience showed no moderating influence on the pathways from behavioral intention to usage behavior. Companies are advised to improve digital platform performance through functionalities enhancements and pilot testing to reduce perceived effort and stimulate behavioral intention. Additionally, fostering a positive organizational mindset through routine motivational communications can further stimulate usage behavior.

Generative AI in student English learning in Thai higher education: More engagement, better outcomes?

Despite the growing body of research exploring artificial intelligence (AI) in educational contexts, there remains a critical gap in understanding the specific effects of generative AI (GAI) on English language learning, particularly within higher education in Thailand. This study addresses this gap by employing an explanatory sequential mixed-method design to explore both student and teacher perspectives. Quantitative data were analyzed using descriptive statistics, Mann-Whitney U tests, Spearman correlation analysis, and Kendall–Theil regression to examine students' acceptance, usage, and the relationship between GAI engagement and academic performance. Qualitative data, collected through structured written interviews, were analyzed using thematic analysis to uncover key themes from both student and teacher narratives. Quantitative findings reveal high student acceptance of GAI tools in terms of performance expectancy (M = 3.66, SD = .58), effort expectancy (M = 3.61, SD = .59), facilitating conditions (M = 3.51, SD = .59), and use behavior (M = 3.52, SD = .48), while social influence remained relatively lower (M = 3.31, SD = .54). Mann-Whitney U tests showed no statistically significant differences in GAI usage across high- and low-performing students (p > .05). Correlation analyses indicated strong associations between performance expectancy and other factors (ρ = .87, p < .001), yet no significant correlation with GPA (ρ = −.06, p = .76). Qualitative results from student reflections revealed improved efficiency, enhanced engagement, and increased linguistic confidence. Yet, concerns about overreliance on AI and the necessity for critical use were noted. Teacher narratives accentuated ethical concerns and the potential for GAI misuse, highlighting the need for balanced, responsible integration of AI into pedagogical practices. These findings underscore the potential of GAI to enhance learning experiences while emphasizing the importance of maintaining academic integrity and fostering critical thinking.

Chinese physicians’ perceptions and willingness to use telemedicine during the COVID-19 pandemic

The outbreak of the COVID-19 pandemic catalysed the rapid uptake of telemedicine as a vital tool for physicians to provide healthcare services to patients. However, despite the potential advantages of telemedicine, there remains a paucity of research examining physicians’ attitudes and utilisation patterns towards this mode of healthcare delivery. Therefore, this study investigated the factors impacting physicians’ telemedicine utilisation during the COVID-19 pandemic. Based on the unified theory of acceptance and use of technology and protection motivation theory, a cross-sectional survey was conducted between June 3rd and October 26th, 2022. A structural equation model was subsequently developed to validate the response-based research model. Of the 296 physicians surveyed, 134 reported an increase in the frequency of telemedicine use following the COVID-19 pandemic, and 88.9% of respondents supported the implementation of telemedicine services at their hospitals. The analysis revealed that perceived vulnerability, perceived severity, performance expectations, effort expectations, and facilitating conditions were significant factors influencing physicians’ willingness to adopt telemedicine. Importantly, the results suggest that strategies to enhance the usefulness and convenience of telemedicine systems are imperative for fostering adoption. Such efforts will be instrumental in expediting the promotion and implementation of internet-based healthcare services to enhance the accessibility of healthcare services in China.

Analyzing health service employees’ intention to use e-health systems in southwest Ethiopia: using UTAUT-2 model

BackgroundE-health systems have the potential to improve healthcare delivery and access to medical services in resource-constrained settings. Despite its impact, the system exhibits a low level of consumer acceptance and intention to use it. This research paper aims to analyze the intention of health service employees to use e-health systems in southwest Ethiopia using the UTAUT-2 model.MethodInstitutional-based cross-sectional studies were conducted at four referral hospitals (two private and two public) to examine the acceptance of e-health among consumers. Employees who had previous experience with diagnostic information systems and the health logistic information system were given structured questionnaires based on the UTAUT-2 model. The data were analyzed using the PLS-SEM method to identify the key factors that influence the intention to use e-health systems. The data were analyzed using SPSS version 20 and SmartPLS 3 software.ResultOut of the 400 surveyed employees, 225 (56.25%) valid questionnaires were collected. The findings indicate that three factors—effort expectancy (β = 0.276, t = 3.015, p = 0.001), habit (β = 0.309, t = 3.754, p = 0), and performance expectancy (β = 0.179, t = 1.905, p = 0.028)—had a significant positive impact on employees’ intention to use e-health systems. On the other hand, factors such as social influence, facilitating conditions, hedonic motivation, and price values did not appear as significant predictors of intention to use e-health. The study model was able to predict 63% of employees’ intentions to use e-health systems.ConclusionEffort expectancy, habit, and performance expectancy were significant predictors of employees’ intention to use e-health systems among health service employees in southwest Ethiopia. The study supports the ideas that ease of use, experience with information systems, and the role of the systems in improving job performance contribute to employees’ intention to use e-health. Policymakers and healthcare organizations in the region can use these findings to develop strategies for successful implementation and adoption of e-health systems, ultimately improving healthcare services and outcomes for the population.

Investigating older adults users' willingness to adopt wearable devices by integrating the technology acceptance model (UTAUT2) and the Technology Readiness Index theory.

With the continuous advancement of wearable technology, smart wearable devices are increasingly recognized for their value in health monitoring, assessment, and intervention for the older adults, thus promoting intelligent older adults care. This study, based on the theoretical framework of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and the Technology Readiness Index (TRI) model, aims to identify and explore the key factors influencing older adults consumers' willingness to adopt smart wearable devices and their impact mechanisms. A questionnaire survey was conducted to collect valid data from 389 older adults respondents. Empirical analysis validated the model's applicability and explored the key factors influencing acceptance. Factors influencing the use of smart wearable devices by the older adults include performance expectancy (β = 0.152, p < 0.001), effort expectancy (β = 0.154, p < 0.001), social influence (β = 0.135, p < 0.05), facilitating conditions (β = 0.126, p < 0.05), hedonic motivation (β = 0.166, p < 0.001), price value (β = 0.182, p < 0.001), and digital health literacy (β = 0.189, p < 0.001). Additionally, optimism (β = 0.208, p < 0.001), innovativeness (β = 0.218, p < 0.001), and discomfort (β = -0.245, p < 0.001) significantly positively influenced performance expectancy, while optimism (β = 0.282, p < 0.001), innovativeness (β = 0.144, p < 0.01), discomfort (β = -0.239, p < 0.001), and insecurity (β = -0.117, p < 0.05) significantly positively influenced effort expectancy. Insecurity did not significantly influence performance expectancy. Performance expectancy and effort expectancy partially mediated the relationship between personality traits (optimism, innovativeness, discomfort, and insecurity) and behavioral intention. Digital health literacy significantly negatively moderated the relationship between performance expectancy and behavioral intention, as well as between effort expectancy and behavioral intention. The study confirms that integrating the UTAUT2 model and TRI theory effectively explains the acceptance of smart wearable devices among older adults consumers, emphasizing the importance of enhancing digital health literacy in the design and promotion of smart health devices. The findings provide guidance for developers, increasing the acceptance and usage rate of these devices among the older adults.