Performance Expectancy Research Articles

Predicting EFL University Students' Acceptance of Mobile Assisted Language Learning through the UTAUT2 Model

This study used the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model to examine the factors influencing the acceptance of MALL by the Moroccan EFL students of Sidi Mohamed Ben Abdellah University. For this purpose, 150 undergraduate EFL students participated in the research. The survey questionnaire adapted from (UTAUT2) model showed the influence of the following factors on students' behavioral intention to use MALL: performance expectancy, effort expectancy, social impact, facilitating conditions, hedonic motivation, and habit. The findings highlighted the importance of perceived usefulness and ease of use, the need for institutional support, engaging learning experiences, and promoting MALL use as a habit. This study provides valuable insights for educators and policymakers seeking to optimize MALL adoption and improve language learning outcomes.

National Health Education Standards: Model Guidance for Curriculum and Instruction (Third Edition).

Since the 1990s, national standards have been developed in K-12 subject areas. National standards in health education were first released in 1995 with a second set released in 2007. A third edition, the National Health Education Standards: Model Guidance for Curriculum and Instruction was developed in 2022 under the auspices of the National Consensus for School Health Education. The purpose of this article is to present an overview of the third edition including descriptions of the development process;the 8 standards and aligned performance expectations; considerations related to the translation, dissemination, and implementation of the standards; and projections for potential impact regarding teaching and student outcomes. To develop new standards, the National Consensus formed 3 groups: the Management, Development, and Expert Review Groups. These groups employed an iterative process that included the development of 3 drafts of the standards before finalization. This process included a review of each draft by the 3 groups. The second draft included additional qualitative feedback from over 500 school health education leaders, practitioners, and stakeholders. The third edition includes 8 standards with aligned performance expectations. A description and rationale are provided for each standard along with standard-specific teaching guidance. The third edition of the National Standards for School Health Education provides guidance to state departments of education and local schools in the development and implementation of health instruction that promotes meaningful learning to guide students in the promotion of their own health and the health of others.

Recognizing human activities using light-weight and effective machine learning methodologies

Background Human activity recognition (HAR) is increasingly important in enhancing healthcare systems by enabling accurate monitoring of individuals' movements through sensor data. This paper is motivated by the need to improve the accuracy of HAR, particularly for applications in e-health systems, where reliable activity detection can lead to better health outcomes. The study explores six prominent machine learning techniques—decision tree, random forest, linear regression, Naïve Bayes, k-nearest neighbor, and neural networks—to determine which methods can most effectively predict activities like walking, sitting, standing, laying, walking upstairs, and walking downstairs. Methods We employed these six machine learning algorithms to analyze a comprehensive dataset derived from various sensors. Each model was rigorously trained and evaluated to compare its effectiveness in recognizing human activities. The experiments aimed to identify strengths and weaknesses in each approach, with particular emphasis on advanced techniques such as random forest, convolutional neural networks (CNNs), and gated recurrent networks (GRNs). Results The experimental evaluation revealed that the random forest classifier, CNN, GRN, and neural networks delivered promising results, achieving high accuracy levels. Notably, the neural network model excelled, attaining an impressive accuracy of 98%. In contrast, the Naïve Bayes model did not meet the performance expectations set by the other algorithms. Conclusions This research effectively classifies activities such as sitting, standing, laying, walking, walking downstairs, and walking upstairs, underscoring the potential of machine learning in HAR. The findings highlight the superior performance of neural networks in enhancing activity recognition, which could lead to advanced applications in e-health systems and improve overall healthcare monitoring strategies.

Determinants of Generative AI System Adoption and Usage Behavior in Korean Companies: Applying the UTAUT Model

This study addresses the academic gap in the adoption of generative AI systems by investigating the factors influencing technology acceptance and usage behavior in Korean firms. Although recent advancements in AI are accelerating digital transformation and innovation, empirical research on the adoption of these systems remains scarce. To fill this gap, this study applies the Unified Theory of Acceptance and Use of Technology (UTAUT) model, surveying 300 employees from both large and small enterprises in South Korea. The findings reveal that effort expectancy and social influence significantly influence employees’ behavioral intention to use generative AI systems. Specifically, effort expectancy plays a critical role in the early stages of adoption, while social influence, including support from supervisors and peers, strongly drives the adoption process. In contrast, performance expectancy and facilitating conditions show no significant impact. The study also highlights the differential effects of age and work experience on behavioral intention and usage behavior. For older employees, social support is a key factor in technology acceptance, whereas employees with more experience exhibit a more positive attitude toward adopting new technologies. Conversely, facilitating conditions are more critical for younger employees. This study contributes to the understanding of the interaction between various factors in AI technology adoption and offers strategic insights for the successful implementation of AI systems in Korean companies.

Satisfaction With the Use of a Mobile Application: Adopsi Teknologi pada Aplikasi Mobile PLN

The development of information technology has an impact on business growth in Indonesia. One example is PT PLN developing the PLN mobile application to facilitate customers in accessing the services provided. The purpose of this study is to determine the influence of Barriers (Resistance to change and Technological Complexity) and Facilitators (Technical Support, Compatibility, Performance Expectancy, and Easy of use) on Satisfaction with the use of a mobile application in the Mobile PLN app. The research method used in this study is a quantitative method by distributing questionnaires to users of the PLN mobile app. The results of the study indicate that resistance to change positively affects user satisfaction with the mobile PLN application, as users feel more satisfied when the application does not disrupt their routines. Conversely, technological complexity negatively affects user satisfaction; the higher the complexity, the lower the satisfaction. A stable and easy-to-use application increases satisfaction. Effective and responsive technical support also enhances user satisfaction. The application's compatibility with users' lifestyles has a significant impact; an application integrated with users' routines increases satisfaction. Fulfilled performance expectations, such as tangible benefits, efficiency, and productivity, also positively affect user satisfaction. Easy of use has a significant influence; an intuitive and user-friendly application increases overall user satisfaction.

Making a Splash: A Closer Look at Early Specialization in Competitive Diving.

This review article explores the multifaceted aspects of early specialization in diving, focusing on its implications for injury prevalence, performance, and mental health. It highlights the increasing trend of early specialization driven by ambitions for collegiate and Olympic success, despite recommendations advocating for diversification. Divers are at risk for acute and overuse injuries, particularly during high-velocity water entries; however, data on injury patterns, especially among elite divers and early specializers, remains scarce. Recent data suggest a correlation between early specialization and reduced rates of certain injuries among youth divers, but distinguishing between acute and overuse injuries is crucial. Additionally, early specialization may pose mental health risks, with divers facing pressures related to performance, body image, and parental expectations. This article underscores the need for tailored guidelines to mitigate injury risks and promote holistic well-being among youth divers, recognizing the complex interplay between physical and psychological factors in sports specialization.

“Always be relevant”: a phenomenological study of the actor’s workday

ABSTRACT Background Actors face a demanding entertainment industry characterised by understaffing, precarious working conditions, temporary contracts, intense work pressure, and rigorous performance expectations. These challenges create barriers in their workday and influence their health and well-being. Methods This qualitative study involved in-depth interviews with 14 actors from across Norway with diverse backgrounds and acting experiences. Results Through a reflective lifeworld research analysis, the essential phrase “to always be relevant” was identified. This essence consists of four components: understanding informal professional structures, being available for the industry, maintaining a good reputation, and always being in motion. Conclusions The mantra “always be relevant” serves actors as both a necessary guide to sustaining themselves in an insecure and unpredictable industry and as a source of detriment due to its potential to blur the boundaries between work and leisure. This blurriness is also a core to chronic stress that might promote ill health.

Analyzing the interplay between social media analytics and nudges in pandemic control

This study employs a data-driven approach to examine the government's use of data insights and nudges to promote social distancing during the pandemic. Drawing from well-established technology adoption theories, a nationwide online survey was conducted among professionals and postgraduate students adapting to remote work and learning. The study unveils that access to suitable information and communication technology (ICT) significantly influences people's willingness to adhere to social distancing and work from home (WFH). Moreover, respondents' expectations of WFH's impact on job performance emerged as a critical driver for sustained social distancing, with individuals' habits playing a pivotal role in enhancing WFH performance expectancy. Notably, the study pioneers in exploring the psychological effects of government nudges during a pandemic, shedding light on an uncharted aspect of pandemic control strategies.

Impacting Elements of Metaverse Platforms’ Intentional Use in Cultural Education: Empirical Data Drawn from UTAUT, TTF, and Flow Theory

This study aims to address the need for design guidelines in developing a cultural-heritage-based metaverse educational system. Using the UTAUT, the TTF model, and Flow Theory, a theoretical framework is constructed. Through qualitative research based on the GT, three user perception factors—presence, interactivity, and narrativity—are introduced as external variables to explore the relationship between these factors and users’ willingness to adopt the cultural heritage metaverse system. The study examines this relationship from the dual perspectives of user perception and technology acceptance. A scale was designed to test the theoretical model empirically, and 298 valid responses were collected through a structured process involving GT coding, pre-testing, and formal surveys. The findings indicate that interactivity, narrativity, and presence significantly enhance the flow experience, while factors such as performance expectancy, effort expectancy, social influence, facilitating conditions, technology–task fit, and flow positively influence users’ intention to adopt the system. Among these, technology–task fit emerged as the most influential factor. This integrated approach reduces subjectivity and bias in criteria determination, enhancing the objectivity and precision of cultural heritage metaverse system assessments and making the system more responsive to user needs.

Development of financial literacy and fintech adoption on women SMEs business performance in Indonesia

Women-owned small businesses are crucial to the Indonesian economy. Despite this contribution, women entrepreneurs face many challenges when building their businesses, especially getting business loans. Women entrepreneurs adopt less technology and have less financial expertise than men. This study aims to determine financial literacy factors affecting women SMEs' business success and the extent of financial technology (FinTech) use as an alternative funding source to formal financial institutions. The study examines FinTech adoption using the Unified Theory of Acceptance and Use of Technology (UTAUT Theory). This study also examines how FinTech adoption mediates the indirect effect of financial literacy on SME business performance. The study uses a quantitative research approach using a judgmental sample of 270 women entrepreneurs who have previously used FinTech. The data is analyzed with SEM-PLS. According to the study, effort expectancy, performance expectancy, and social influence all have a beneficial impact on FinTech adoption among women-owned small businesses. The survey found that FinTech adoption was a key factor influencing women SMEs' business performance. The findings also indicate that financial literacy has a beneficial effect on business success. The study reveals FinTech adoption as a mediating factor in the association between financial literacy and SMEs business success. As a result, our findings contribute to a better understanding of how digital technology adoption affects SMEs' performance and long-term sustainability. The findings offer insights for entrepreneurs, policymakers, and company owners looking to enhance the survival rate of SMEs by improving operations and harnessing digital technology to promote capital accessibility, FinTech adoption, and financial literacy.

Graduate Education in China Meets AI: Key Factors for Adopting AI-Generated Content Tools

Abstract Factors influencing Chinese graduate students’ adoption of AI-generated content (AIGC) tools are examined through partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The developed AIGCT-SI model incorporates key elements such as information accuracy, trust, and privacy concerns. PLS-SEM results indicate that performance expectancy, effort expectancy, facilitating conditions, and habit significantly impact students’ intentions, with trust acting as a key mediator, particularly for privacy concerns and social influence. FsQCA reveals seven configurations, demonstrating how combinations of performance expectancy, effort expectancy, and facilitating conditions drive adoption. A bidirectional relationship between privacy concerns and trust is observed, with trust mitigating privacy risks in several configurations. This integrative approach highlights the complex dynamics of AIGC tool adoption and provides strategic insights for their effective use in Chinese graduate education. As the findings are based on the Chinese context, further exploration in other educational settings is encouraged to validate their broader applicability.

Application of the Extended Unified Theory of Acceptance and Use of Technology to a Robotic Golf Caddy: Health Consciousness as a Moderator

The COVID-19 pandemic not only accelerated the spread of contactless robot services but also revitalized the golf industry. These changes have expedited the adoption of robot caddies, making it necessary to conduct research on golfers’ acceptance of robot caddies. This study, thus, intended to investigate the importance of the extended unified theory of acceptance and use of technology (UTAUT) in the framework of robotic golf caddies and examined health consciousness as a moderator. An online survey was conducted with South Korean golfers, and a total of 391 responses were analyzed. The data analysis results indicated that all five dimensions of the extended UTAUT have a positive impact on attitude. Also, attitude is a significant predictor of both intentions to use and word-of-mouth intentions. Lastly, this study discovered that the moderating effect of health consciousness on the correlation between performance expectancy and attitude was significant.

The eMoney revolution: how culture and technology drive adoption and use?

Purpose The use of electronic money (eMoney) as a noncash payment method is gaining popularity globally. However, the usages of eMoney are culturally influenced and can vary within a country. These cultural disparities can result in divergent patterns of eMoney adoption and use. This study aims to investigate the factors influencing the adoption and use of eMoney in Indonesia. This study integrated the unified theory of acceptance and use of technology model with Hofstede’s cultural dimensions to develop a framework examining both technological and cultural perspectives. Design/methodology/approach Data was collected through an online survey of 484 Indonesians and analyzed using partial least squares structural equation modeling. Findings The results showed that the constructs of the unified theory of acceptance and use of technology model, namely, performance expectancy, effort expectancy, social influence and facilitating conditions, all had a significant impact on behavioral intention to adopt eMoney as well as actual usage. However, not all of Hofstede’s cultural dimensions moderated these relationships as hypothesized. Surprisingly, masculinity/femininity and power distance emerged as important moderators of eMoney usage. Practical implications This integrated model provides valuable insights into how to consider cultural influences when designing strategies to promote new payment technologies in Indonesia. The findings point to both technological and cultural factors shaping patterns of adoption and use of eMoney in the country. Originality/value Although many research has looked at how culture affects the acceptability of technology in banking, few studies have looked at how culture affects the use of mobile money. This study offers a valuable contribution by investigating how Indonesian culture moderates the relationship between behavioral intentions and actual use of eMoney. The findings provide guidance for practitioners seeking to facilitate eMoney services in developing markets by elucidating the cultural factors that most influence customer adoption. As such, this research fills an important gap regarding the understudied domain of mobile money and its intersection with national culture.

Acceptance of Digital Discharge Management Interventions Among Patients After Bariatric Surgery: A Cross-Sectional Study

Bariatric surgery is an effective long-term treatment for severe obesity, but relapse rates remain high. Digital interventions can enhance patient care, yet research on the intention to use digital discharge management interventions is lacking. This study aims to assess the behavioral intention to use digital discharge management interventions after bariatric surgery and to identify differences in sociodemographic and medical characteristics, as well as potential key drivers and barriers. A cross-sectional study with N = 514 patients was conducted using the Unified Theory of Acceptance and Use of Technology (UTAUT). Mean scores for behavioral intention and predictors were calculated. Group differences were analyzed with independent t-tests and analyses of variance with post hoc tests. Drivers and barriers were assessed through multiple hierarchical regression analysis. The behavioral intention to use digital discharge management interventions was high. Significant predictors included age (β = −0.17, p < 0.001), eHealth literacy (β = 0.10, p = 0.037), internet anxiety (β = −0.15, p = 0.003), and time since bariatric operation (β = −0.13, p = 0.005). The predictors performance expectancy (β = 0.23, p < 0.001), effort expectancy (β = 0.36, p < 0.001), and social influence (β = 0.26, p < 0.001) were significantly positive key factors. These results confirm the need for implementing digital discharge interventions after bariatric surgery, with various drivers and barriers identified for application usage.

Adoption of Cashless Payment Among Undergraduate Students: A Case Study

The increasing acceptance of cashless payment systems has led to a significant transformation in the global financial transaction landscape in recent years. As technology evolves and consumer preferences shift, digital payment methods are gradually taking the place of traditional cash transactions. This change not only facilitates financial transactions for individuals and businesses but also has significant implications for convenience, security, and financial inclusion. This paper investigates the key factors driving the transition to cashless transactions during this period, along with the benefits and drawbacks associated with society's growing embrace of this innovative approach to managing finances. The primary focus of research in this area revolves around the adoption and use of digital or cashless payment methods. A quantitative methodology was employed, and a questionnaire was administered to 113 participants. The data were analyzed using the Statistical Package for Social Science (SPSS) Version 27. The findings indicated that Performance Expectancy (PE) and Perceived Technology Security (PT) played significant roles in the adoption of cashless payments among undergraduate students while Facilitating Condition (FC) and Social Influence (SI) did not significantly affect their adoption of such payment methods. This study provides valuable insights into assessing individuals' willingness, intentions, or actual behaviors regarding various electronic transaction forms, including mobile wallets, credit/debit cards, online payments, and contactless methods. Additionally, researchers can utilize these variables to explore the factors that influence users' acceptance or rejection of cashless payment systems.

Factors predicting innovation-decisions: The effects of performance expectancy, social influence, and facilitating conditions on U.S. Extension’s promotion of precision agriculture technologies

Factors predicting innovation-decisions: The effects of performance expectancy, social influence, and facilitating conditions on U.S. Extension’s promotion of precision agriculture technologies

Determinants of Online Dating Application Among Millennials

Online dating has become increasingly popular in recent years, these platforms provide a convenient and accessible way to meet new people. Studies on the use of dating applications among men and women highlight how these technologies shape communication practices and social relationships. For this study, the Unified Theory of Acceptance and Use of Technology (UTAUT) was applied to discover the determinants of online dating apps’ adoption intention. Possible determinants that might affect the intention to adopt online dating apps are sought and critically reviewed. The variables proposed in this research include performance expectancy, effort expectancy, social influence, facilitating conditions, and an additional variable – trust. Five hypotheses were constructed, questionnaires were distributed and responses were collected to determine the adoption intention of young millennials in Malaysia. The test results indicated that trust, performance expectancy and social influence influenced the adoption intention of online dating applications. Based on the results, for performance expectancy, it was revealed that users expressed concerns about the utility of dating applications in facilitating beneficial functions, such as broadening social networks, enhancing dating opportunities, and meeting dating needs. For social influence, it revealed that individuals, especially peers, who hold significance in their lives, influence their decision to engage with online dating apps. These influential individuals impact the users' intentions by communicating the benefits of online dating apps and recommending their use. As trust improves, millennials are less reluctant to adopt online dating apps, contributing to an increase in the user base for such applications

A Conceptual Framework of Navigating Digital Banking: How Gender Impacts Adoption Intentions in Klang Valley

Malaysian banking users have encountered negative experiences while adopting traditional bank services. Several customers and businesses face limited access to traditional banking products and services due to factors such as low or irregular income, bad credit, or a lack of conveniently located banks. The acceptability of digital banking products and services in Malaysia is currently unknown and inadequate due to the general lack of familiarity among Malaysians with the notion of digital banking. Conventional methods of analyzing consumer behavior, which primarily consider historical data and current resources, will not result in the achievement of branchless banking in the future. This paper presents a framework that examines how various factors such as performance expectancy, effort expectancy, social influence, facilitating condition, hedonic motivation, price value, and habit may influence behavioral intention. Additionally, the framework considers gender as a moderator variable. The results of this study are anticipated to expand the existing body of knowledge on behavioral intention and bring advantages to marketers and digital banking providers.

Factors Impacting the Use of Donation-Based Crowdfunding Platforms in Saudi Arabia: The Case of Ehsan Platform

This research investigates the factors influencing people's intentions to use donation-based crowdfunding platforms in Saudi Arabia, focusing on the Ehsan platform supervised by the Saudi Data and Artificial Intelligence Authority (SDAIA). Ehsan aims to ensure proper monetary distribution to genuinely needy individuals, thereby reducing financial fraud and corruption. For the platform's success, it is essential that citizens effectively utilize it. Employing the Unified Theory of Acceptance and Use of Technology, the study analyzes the determinants that influence intentions to use Ehsan and actual use behaviors. An empirical study was conducted with 224 Saudi citizens from various age groups, and the research model was validated using the Partial Least Squares (PLS) approach. Findings reveal that performance expectancy and facilitating conditions significantly impact intentions to use Ehsan, while effort expectancy and social influence do not. The results indicate a positive association between participants' intentions to use Ehsan and their actual usage. This study enhances the understanding of factors affecting donation-based crowdfunding platforms in Saudi Arabia and offers practical insights for platform developers and decision-makers to consider in their design and modifications.

Evaluating the Impact of AI Dependency on Cognitive Ability among Generation Z in Higher Educational Institutions: A Conceptual Framework

This research aims to examine the factors of AI dependency (AID) and to investigate the relationship between AI dependency on cognitive ability (CA) among Generation Z (Gen Z) in higher educational institutions. The factors involved are academic self-efficacy (ASE), academic stress (AS), and performance expectation (PE). In this research, the proposed research design is a quantitative method. A self?administered questionnaire will be distributed to respondents, a group of students who were born between 1997 to 2012, and the AI user. The questionnaire will be utilizing the Google Form platform for easier data collection. A snowball sampling method will be applied. Then, the data collected will be analyzed through the partial least square (PLS-SEM) technique. The research findings are expected to highlight the significant emphasis on the contributing factors of AI dependency among Gen Z students. Then, the findings will also provide a model to understand better the impact of AI dependency on cognitive ability. Additionally, it is foreseen that the findings will help various parties, including the government, to create better models for helping Gen Z students apply AI in decent ways to help them increase their cognitive ability. It is also considered a long-term strategy to become a nation with numbers of high cognitive ability citizens. Further, a practical framework based on AI dependency on cognitive ability will be developed as a guideline to support the effort of the government or industry practitioners to increase awareness among Gen Z students on how crucial to possess high cognitive ability.