scholarly journals The Determinants of Use and Acceptance of Mobile Assisted Language Learning: The Case of EFL Students in Morocco

2019 ◽  
Author(s):  
Nabil Morchid
Keyword(s):  
Language Learning ◽  
Technology Acceptance ◽  
Behavioral Intention ◽  
Teacher Feedback ◽  
Intention To Use ◽  
Performance Expectancy ◽  
Mobile Assisted Language Learning ◽  
Effort Expectancy ◽  
Behavioral Intention To Use ◽  
The Impact

The intent of this paper is to research the factors that determine students’ acceptance of mobile assisted language learning (MALL) in Morocco. This study emphasizes the inclusive character of the Unified Theory of Acceptance and Use of Technology (UTAUT). After careful assessment of the multiple relationships within UTAUT, a modified version of the theory was hypothesized then researched for the impact it has on the English as Foreign Language (EFL) context in Morocco. The technology acceptance model in this paper emphasized four directions connecting performance expectancy, effort expectancy, teacher feedback and compatibility to behavioral intention, also referred to as the determinants of behavioral intention to use MALL. For the purpose of this study, a technology enhanced environment was created. A total number of 156 EFL common core students were brought to interact on a WhatsApp-based platform by means of text-messaging. The WhatsApp treatment was optimized to synchronize with the institutionalized character of the teaching of English in Moroccan public schools. The questionnaire method was used for data collection. The data were screened for missingness, normality and outliers. Then, multiple reliability and validity tests were performed to substantiate the legitimacy of the dataset. Structural equation modelling (SEM) was used in the assessment of the measurement model and the structural model. The outputs of structural modelling corroborated the hypothesized directions connecting teacher feedback and compatibility to behavioral intention to use MALL while there was lack of support for the relationships linking performance expectancy and effort expectancy to behavioral intention to use MALL.

scholarly journals Investigating the Determinants of Students’ Intention to Use Business Simulation Games

2019 ◽  
Vol 58 (2) ◽  
pp. 433-458 ◽  
Author(s):  
Yu-Yin Wang ◽  
Yi-Shun Wang ◽  
Shi-En Jian
Keyword(s):  
Social Influence ◽  
Behavioral Intention ◽  
Partial Least Square ◽  
Intention To Use ◽  
Business Simulation ◽  
Simulation Games ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Behavioral Intention To Use

Business simulation games (BSGs) are educational tools that help students develop business management knowledge and skills. However, to date, relatively little research has investigated the factors that influence students’ BSG usage intention. Grounded on the extended unified theory of acceptance and use of technology, this study helped to fill this gap by exploring intention to use BSGs. Specifically, this study investigated the influence of performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and price value on behavioral intention to use BSGs. Data collected from 141 useful respondents were tested against the research model using partial least square approach. The results of this study indicated that behavioral intention to use BSGs was influenced by facilitating conditions, hedonic motivation, and price value. Unexpectedly, performance expectancy, effort expectancy, and social influence were not predictive of students’ behavioral intention to use BSGs. These findings enhanced our understanding of students’ BSG usage behavior and provided several important theoretical and practical implications for the application of BSG in the context of business and management education.

scholarly journals Predicting Patients’ Intention to Use a Personal Health Record Using an Adapted UTAUT Model: Secondary Data Analysis (Preprint)

2021 ◽  
Author(s):  
Consuela Cheriece Yousef ◽  
Teresa M. Salgado ◽  
Keisha Burnett ◽  
Laura E McClelland ◽  
Abin Thomas ◽  
...  
Keyword(s):  
Health Care ◽  
Behavioral Intention ◽  
Positive Attitude ◽  
Personal Health ◽  
Intention To Use ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Centered Care ◽  
Behavioral Intention To Use ◽  
Health Applications

BACKGROUND With the rise in the use of information and communication technologies in health care, there has been a push for patients to accept more responsibility for their health and well-being using eHealth tools such as personal health records (PHRs). PHRs support patient-centered care and patient engagement. To support the achievement of the Kingdom of Saudi Arabia’s Vision 2030 ambitions, the National Transformation program provides a framework to use PHRs in meeting the triple aim for health care – increased access, reduced cost, and improved quality of care – and to provide patient- and person-centered care. However, there has been limited research on PHR uptake within the country. OBJECTIVE The aim of this study was to identify predictors of patient intention to utilize the Ministry of National Guard-Health Affairs (MNG-HA) PHR (MNGHA Care) using an adapted model of the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical framework. METHODS This cross-sectional study utilized a survey developed based on the UTAUT to measure behavioral intention to use MNGHA Care among adults visiting MNG-HA facilities in Riyadh, Jeddah, Dammam, Madinah, Al Ahsa, and Qassim. The main theory constructs performance expectancy, effort expectancy, social influence, facilitating conditions, and positive attitude toward using the PHR were collected as independent variables. Age, gender, experience with health applications, and health status were tested as moderators between the main theory constructs and behavioral intention using hierarchical multiple regression. RESULTS Of the eligible population, a total of 261 adult patients were included in the analysis with a mean age of 35.07 years (± 9.61), male (n=132, 50.6%), university-educated (n=118, 45.2%), and at least one chronic medical condition (n=139, 53.3%). The model explained 48.9% of the variance in behavioral intention to use the PHR (P=.377). Performance expectancy, effort expectancy, and positive attitude were significantly associated with behavioral intention to use the PHR (P<.05). Prior experience with health applications moderated the relationship between social influence and behavioral intention to use the PHR (P=.043). CONCLUSIONS This research contributes to the existing literature on PHR adoption broadly as well as in the context of the Kingdom of Saudi Arabia. Understanding which factors are associated with patient adoption of PHRs can guide future development and support the country’s aim of transforming the health care system. Similar to other studies on PHR adoption, performance expectancy, effort expectancy, and positive attitude are important factors, and practical consideration should be given to how support these areas.

Smartphone Alcohol Use Disorder Recovery Apps: an Survey of Behavioral Intention to Use using UTAUT (Preprint)

2021 ◽  
Author(s):  
Rijuta Menon ◽  
Julien Meyer ◽  
Pria Nippak ◽  
Housne Begum
Keyword(s):  
Social Influence ◽  
Behavioral Intention ◽  
Alcohol Use Disorder ◽  
Survey Study ◽  
P Value ◽  
Intention To Use ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Behavioral Intention To Use

BACKGROUND Alcohol Use Disorder (AUD) carries a huge health and economic cost to society. Effective interventions exist but numerous challenges limit their adoption, especially in a pandemic context. AUD recovery apps (AUDRA) have emerged as a potential complement to in-person interventions. They are easy to access and show promising results in terms of efficacy. However, they rely on individual adoption decision and remain underused. OBJECTIVE The aim of this survey study is to explore the beliefs that determine the intention to use AUDRA. METHODS We conducted a cross-sectional survey study of people suffering from AUD. We used the Unified Theory of Acceptance and Use of Technology, which predicts use and behavioral intention to use based on performance expectancy, effort expectancy, social influence and facilitating conditions. Participants were recruited directly from two sources: first, respondents at addiction treatment facilities in Ontario, Canada were contacted in person and filled a paper form; second, members from AUD recovery support groups on social media were contacted and invited to fill an online sruvey. The survey was conducted between October 2019 and June 2020. RESULTS The final sample was comprised of 159 participants (124 online and 35 paper based) self-identifying somewhat or very much with AUD. Most participants (85.5%) were aware of AUDRA and those participants scored higher on performance expectancy, effort expectancy and social influence. Overall, the model explains 35.4% of the variance in behavioral intention to use AUDRA and 11.1% of the variance in use. Social influence (p-value 0.314), especially for women (p-value 0.227) and effort expectancy (p value 0.247) were key antecedents of behavioral intention. Facilitating conditions was not significant overall but was moderated by age (p value 0.231) suggesting that it matters for older participants. Performance expectancy did not predict behavioral intention, which is unlike many other technologies but confirms other findings with mhealth. Open-ended questions suggest that privacy concerns may play a significant role for AUDRA. CONCLUSIONS This study suggests that unlike many other technologies, the adoption of AUDRA is not mainly determined by utilitarian factors such as performance expectancy. Rather, effort expectancy and social influence play a key role in determining the intention to use AUDRA.

scholarly journals Analysis of Factors Affecting Behavioral Intention to Use E-Learning Uses the Unified Theory of Acceptance and Use of Technology Approach

2020 ◽  
Author(s):  
Ramllah . ◽  
Ahmad Nurkhin
Keyword(s):  
Social Influence ◽  
Behavioral Intention ◽  
Intention To Use ◽  
Performance Expectancy ◽  
Learning Intention ◽  
Effort Expectancy ◽  
E Learning ◽  
Facilitating Conditions ◽  
Behavioral Intention To Use ◽  
Descriptive Statistical Analysis

The purpose of this study isto analyze the influence of performance expectancy, effort expectancy, social influence, facilitating conditions, perceived creadibility, and anxiety on e-learning behavioral intention to use who are moderated by experience and voluntariness of use.The study population was 215 students who used e-learning in the Accounting Department of SMK N 1 Karanganyar. The sample selection using Slovin method with an error rate of 5% and sampling area technique obtained by respondents as many as 140 students. The technique of collecting data using a questionnaire. Data analysis techniques used descriptive statistical analysis and SEM-PLS. Data analysis tool using WarpPLS 5.0.The results of the descriptive statistical analysis show that the behavioral intention to use e-learning, performance expectancy, effort expectancy, social influence, facilitating conditions, perceived creativity, anxiety, experience and voluntariness of use are in the sufficient category. Hypothesis test results show the influence of performance expectancy on e-learning behavioral intention to use, effort expectancy does not affect the behavioral e-learning intention to use, social influence has an effect on behavioral e-learning intention to use, facilitating conditions have no effect on behavioral intention to Using e-learning, perceived creativity does not affect e-learning behavior, anxiety influences the behavioral intention to use e-learning, voluntary moderating negative social influences the behavioral e-learning intention to use, experience moderates the effect of effort expectancy on The behavior of e-learning intention to use, experience does not moderate the influence of social influence on the behavioral e-learning intention to use, experience does not moderate the effect of facilitating conditions on e-learning behavioral intention to use e-learning the conclusion of this study states that of the ten hypotheses proposed there are five types of hypotheses accepted. Keywords: E-learning, Behavioral Intention, UTAUT.

scholarly journals Investigating Effort Expectancy and Facilitating Conditions Affecting Behavioral Intention to Use Mobile Learning

2020 ◽  
Vol 55 (5) ◽  
Author(s):  
Nahla Aljojo ◽  
Bashair Alsuhaimi
Keyword(s):  
University Students ◽  
Mobile Learning ◽  
Behavioral Intention ◽  
Quantitative Research ◽  
Rapid Change ◽  
Intention To Use ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Behavioral Intention To Use ◽  
The Impact

The availability of internet access has created a rapid change in learning. This paper aims to investigate the impact of effort expectancy and facilitating conditions on behavioral intention to use mobile learning for Taibah University students in Saudi Arabia by using the unified theory of acceptance and use of technology model. Quantitative research methodology is used, so that the research-proposed formulated hypothesis will be tested. A sample of 110 Taibah University students was drawn. A survey questionnaire was designed for data collections to measure the impact of effort expectancy and facilitating conditions on behavioral intention to use mobile learning for Taibah University students. The independent variables of the research model are effort expectancy and facilitating conditions. The dependent variable is behavioral intention to use. The data was analyzed using statistical techniques, including reliability, validity, and regression analysis. The results indicate that effort expectancy and facilitating conditions were significant and directly influenced students' behavioral intention to use mobile learning.

Understanding users’ behavioral intention to use voice assistants on smartphones through the integrated model of user satisfaction and technology acceptance: a survey approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mine Bertan Yılmaz ◽  
Kerem Rızvanoğlu
Keyword(s):  
Regression Analysis ◽  
Technology Acceptance ◽  
Behavioral Intention ◽  
User Satisfaction ◽  
Integrated Model ◽  
Perceived Usefulness ◽  
Intention To Use ◽  
System Quality ◽  
Content Type ◽  
Behavioral Intention To Use

Purpose This study aims to determine system quality (SQ) and information quality (IQ) characteristics of voice assistants (VA) on smartphones that are affecting users’ satisfaction and technology acceptance, and how these affect behavioral intention (BI) to use. Design/methodology/approach This study uses the integrated model of user satisfaction and technology acceptance to evaluate users’ behavioral intention to use VAs on smartphones. The model represents a causal chain from the key characteristics of SQ and IQ to beliefs and attitudes that ultimately affect use. An online survey was conducted with 75 university students, and the data was analyzed using multivariate analysis: Simple linear regression analysis and multiple regression analysis. Findings While SQ and IQ of VAs had stronger effects on perceived ease of use (PEU), information satisfaction and PEU showed significant influences on perceived usefulness (PU). The results supported the influence of PEU, PU, and attitude on BI to use but with lesser effect than what PU and attitude together had on BI. Research limitations/implications The sample was drawn from a population of students at a single and small university. Although this study received 160 responses, only 75 were appropriate for analysis. Originality/value There is no research, which adopts technology acceptance and user satisfaction approaches to VAs. To measure the causal effects, this study determined system and information characteristics that could explain SQ and IQ of the current VAs on smartphones. This study tested the proposed framework within the scope of the integrated approach.

scholarly journals Analysis of E-Marketplace Use in East Java’s MSMEs Using the Technology Acceptance Model Approach

2021 ◽  
Author(s):  
Rurid Dwi Anggraeny ◽  
Imam Baihaqi
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Behavioral Intention ◽  
Technology Use ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Intention To Use ◽  
Perceived Ease Of Use ◽  
Acceptance Model ◽  
Behavioral Intention To Use

The e-commerce industry has the potential to be one of the drivers of the domestic economy. One of the impacts of the advancement of e-commerce is the emergence of many online-based marketplaces or so-called e-marketplaces. However, a lot of these online marketplaces sell 90% imported products. In addition, the outbreak of Covid-19 in Indonesia has prompted the government to establish several policies that have significantly reduced MSME performance by up to 70-100%. This study aimed to provide an empirical analysis of the influence of factors based on the Technology of Acceptance Model (TAM) approach, namely e-marketplace self-efficacy, complexity, perceived usefulness, perceived ease of use, attitude towards using, behavioral intention to use, and actual technology use in e-marketplaces. The sample consisted of MSMEs in East Java, especially those engaged in the food and beverage industry sector with ready-to-eat processed food products whose business activities use the Shopee e-marketplace application platform. This is an online shopping marketplace focused on mobile platforms. There were 150 respondents. The Structural Equation Model (SEM) was used. E-marketplace self-efficacy, complexity, perceived usefulness, perceived ease of use, attitude towards using, behavioral intention to use, and actual technology use in e-marketplaces all had positive effects on each other. This showed that a system that offers convenience will improve behavior, habits, and performance for MSMEs in using e-marketplace activities. The theoretical and methodological implications and opportunities for further research are discussed. Keywords: MSMEs, e-marketplace, technology acceptance model

User Behavioral Intention toward Using Mobile Healthcare System

2015 ◽  
pp. 128-143 ◽  
Author(s):  
Pantea Keikhosrokiani ◽  
Norlia Mustaffa ◽  
Nasriah Zakaria ◽  
Ahmad Suhaimi Baharudin
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Healthcare System ◽  
Behavioral Intention ◽  
Measurement Model ◽  
Healthcare Systems ◽  
Intention To Use ◽  
Mobile Healthcare ◽  
Effort Expectancy ◽  
Behavioral Intention To Use

This chapter introduces Mobile Healthcare Systems (MHS) and employs some theories to explore the behavioral intention of Smartphone users in Penang, Malaysia to use MHS. A survey was conducted in the form of questionnaire to Smartphone users in Penang, Malaysia for the duration of three weeks starting in September 2013. A total number of 123 valid surveys out of 150 were returned, which is equivalent to a response rate of 82%. The authors use Partial Least Squares (PLS) for analyzing the proposed measurement model. The factors that are tested are self-efficacy, anxiety, effort expectancy, performance expectancy, attitude, and behavioral intention to use. The results indicate which factors have a significant effect on Smartphone users' behavioral intention and which factors are not significant. The results assist in assessing whether MHS is highly demanded by users or not, and will assist in development of the system in the future.

scholarly journals Behavioural intention to use accounting application: perceived ease of use as mediating variable

2021 ◽  
Vol 7 (4) ◽  
pp. 211-218
Author(s):  
Desi Ilona ◽  
Zaitul
Keyword(s):  
Technology Acceptance ◽  
Structural Equation ◽  
Theoretical Implication ◽  
Equation Model ◽  
Ease Of Use ◽  
External Factors ◽  
Intention To Use ◽  
Perceived Ease Of Use ◽  
Performance Expectancy ◽  
Effort Expectancy

This study investigates the role of perceived ease of use as an intervening variable between two external factors from the technology acceptance model (TAM) and Accounting application (MYOB) usage intention. This paper broadened TAM by enhancing external factors: performance expectancy and effort expectancy. Seventy-nine accounting students responded in this study. Employing Structural Equation Model (SEM-PLS) concludes that perceived ease of use fully intercedes the connection between effort expectancy and MYOB usage intention. Besides, perceived ease of use also intervenes the association between performance expectancy and intention to use MYOB accounting application. However, the type of mediation is complimentary mediation. The practical and theoretical implication is discussing in this paper.

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