Mobile Travel Apps and Generation Y in Malaysia

2020 ◽  
pp. 186-210
Author(s):  
Yulita Hanum P. Iskandar ◽  
Phoebe Yueng Hee Sia
Keyword(s):  
Generation Y ◽  
Tourism Industry ◽  
Intention To Use ◽  
Competitive Advantages ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Behavioral Intention To Use ◽  
Tourism Organization ◽  
To Receive ◽  
Practical Implications

Modern travelers prefer an easy and enjoyable experience upon travelling. According to several surveys, over 25% of respondents have installed mobile travel apps on their smartphone. Basically, the travel app is used to search and book flights or accommodation, while download and install the app is mainly to receive notification on the updated trip status and also for accessing app offline. Therefore, it's essential for tourism organization to emphasize on traveler preferences and new innovated technology could offer for competitive advantages in tourism industry. Generation Y grew up with technology and it constitutes 44% of population in Malaysia. Therefore, this research is focus on Generation Y in Malaysia, based on the UTAUT2 (Consumer Acceptance and Use of Information Technology) model to explore and predict the factors influencing the intention to use mobile travel apps. A total of 245 questionnaires were distributed to all states in Malaysia. Quantitative data were analyzed using IBM SPSS 22.0 and Smart PLS 3.0 software. The results findings show that performance expectancy has the highest significant relationship on behavioral to use mobile travel apps. It was followed by facilitating conditions and habit. Factors of effort expectancy, social influence, hedonic motivation and price value don't have much effect on individual's behavioral intention to use mobile travel apps. The theoretical, managerial and practical implications of these results are discussed.

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 E-Government Services Adoption: An Extension of the Unified Model of Electronic Government Adoption

SAGE Open ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 215824402093359
Author(s):  
Isaac Kofi Mensah ◽  
Guohua Zeng ◽  
Chuanyong Luo
Keyword(s):  
Structural Equation ◽  
Unified Model ◽  
Electronic Government ◽  
Equation Modeling ◽  
Intention To Use ◽  
Perceived Service Quality ◽  
Government Services ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Behavioral Intention To Use

This study proposed and validated an extension of the unified model of electronic government adoption (UMEGA). The data analysis was conducted with a structural equation modeling technique using Smart PLS 3.0. The results have demonstrated contrary to expectations that performance expectancy, effort expectancy, and social influence do not predict the attitude toward the use of e-government services. Facilitating conditions, however, were found to significantly determine both the behavioral intention to use and effort expectancy of e-government services. Also, perceived service quality and trust in government were found to positively predict, respectively, the intention to use and recommend the adoption of e-government services. The implications of these and other result findings of this study are thoroughly interrogated.

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 Healthcare providers’ acceptance of telemedicine and preference of modalities during COVID-19 pandemics in a low-resource setting: An extended UTAUT model

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250220
Author(s):  
Kirubel Biruk Shiferaw ◽  
Shegaw Anagaw Mengiste ◽  
Monika Knudsen Gullslett ◽  
Atinkut Alamirrew Zeleke ◽  
Binyam Tilahun ◽  
...  
Keyword(s):  
Low Income ◽  
Self Efficacy ◽  
Structural Model ◽  
Healthcare Providers ◽  
Intention To Use ◽  
Middle Income ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Behavioral Intention To Use

Background In almost all lower and lower middle-income countries, the healthcare system is structured in the customary model of in-person or face to face model of care. With the current global COVID-19 pandemics, the usual health care service has been significantly altered in many aspects. Given the fragile health system and high number of immunocompromised populations in lower and lower-middle income countries, the economic impacts of COVID-19 are anticipated to be worse. In such scenarios, technological solutions like, Telemedicine which is defined as the delivery of healthcare service remotely using telecommunication technologies for exchange of medical information, diagnosis, consultation and treatment is critical. The aim of this study was to assess healthcare providers’ acceptance and preferred modality of telemedicine and factors thereof among health professionals working in Ethiopia. Methods A multi-centric online survey was conducted via social media platforms such as telegram channels, Facebook groups/pages and email during Jul 1- Sep 21, 2020. The questionnaire was adopted from previously validated model in low income setting. Internal consistency of items was assessed using Cronbach alpha (α), composite reliability (CR) and average variance extracted (AVE) to evaluate both discriminant and convergent validity of constructs. The extent of relationship among variables were evaluated by Structural equation modeling (SEM) using SPSS Amos version 23. Results From the expected 423 responses, 319 (75.4%) participants responded to the survey questionnaire during the data collection period. The majority of participants were male (78.1%), age <30 (76.8%) and had less than five years of work experience (78.1%). The structural model result confirmed the hypothesis “self-efficacy has a significant positive effect on effort expectancy” with a standardized coefficient estimate (β) of 0.76 and p-value <0.001. The result also indicated that self-efficacy, effort expectancy, performance expectancy, facilitating conditions and social influence have a significant direct effect on user’s attitude toward using telemedicine. User’s behavioral intention to use telemedicine was also influenced by effort expectancy and attitude. The model also ruled out that performance expectancy, facilitating conditions and social influence does not directly influence user’s intention to use telemedicine. The squared multiple correlations (r2) value indicated that 57.1% of the variance in attitude toward using telemedicine and 63.6% of the variance in behavioral intention to use telemedicine is explained by the current structural model. Conclusion This study found that effort expectancy and attitude were significantly predictors of healthcare professionals’ acceptance of telemedicine. Attitude toward using telemedicine systems was also highly influenced by performance expectancy, self-efficacy and facilitating conditions. effort expectancy and attitude were also significant mediators in predicting users’ acceptance of telemedicine. In addition, mHealth approach was the most preferred modality of telemedicine and this opens an opportunity to integrate telemedicine systems in the health system during and post pandemic health services in low-income countries.

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.

What determines tourist adoption of smartphone apps?

2018 ◽  
Vol 9 (1) ◽  
pp. 50-64 ◽  
Author(s):  
Anil Gupta ◽  
Nikita Dogra ◽  
Babu George
Keyword(s):  
Perceived Risk ◽  
Smartphone Apps ◽  
Content Type ◽  
Factors Affecting ◽  
Perceived Trust ◽  
Use Of Technology ◽  
Effort Expectancy ◽  
Usage Behavior ◽  
Facilitating Conditions ◽  
Practical Implications

Purpose This study aims to identify factors affecting tourists’ intention of using travel apps installed in their smartphones. Design/methodology/approach A questionnaire was developed largely based on the available scales in the published literature. A total of 389 participants responded to the survey, out of which 343 valid responses were obtained for statistical analysis. Findings Significant predictors of smartphone app usage intention included performance expectancy, social influence, price saving, perceived risk, perceived trust and prior usage habits. Usage behavior was largely mediated by usage intention, except in the case of habits. Contrary to the expectation, factors such as hedonistic motivation, facilitating conditions or effort expectancy did not impact usage intention or behavior. Practical implications The study gives app developers vital cues on tourist expectations from the apps. Oftentimes, developers tend to focus entirely on the material utility of their apps, neglecting every other factor influencing use. One particular implication is that despite tourism being a hedonistic activity, travel app usage behavior is not a hedonistic activity. Originality/value This is one of the few studies to examine adoption of smartphone travel apps in an emerging economy context by using extended unified theory of acceptance and use of technology framework with additional constructs.

The Moderating Effect of Technology Awareness on the Relationship between UTAUT Constructs and Behavioural Intention to Use Technology: A Conceptual Paper

2013 ◽  
Vol 03 (02) ◽  
pp. 14-23
Author(s):  
Faruq Muhammad Abubakar ◽  
Hartini B. Ahmad
Keyword(s):  
Technology Adoption ◽  
Behavioural Intention ◽  
Intention To Use ◽  
Point Of Sale ◽  
Use Of Technology ◽  
Effort Expectancy ◽  
Unified View ◽  
Conceptual Paper ◽  
Facilitating Conditions ◽  
The Relationship

The volume and value of cash-based transactions in Nigeria is high and expected to rise. This is liked to non-adoption of new e-payment process introduced by the Central Bank. The adoption of Point of Sale (POS) terminal is reported to be very low. A number of researchers have used several technology adoption theories to answer a similar phenomenon, but their studies were fragmented. Thus the Unified Theory of acceptance and Use of Technology (UTAUT) combined eight among those numerous theories and models of technology adoption, toward a unified view. However, several studies that used UTAUT and investigate behavioural intention to use technology yielded conflicting findings. Therefore this paper, based on review of past literature, conceptualised that ‘technology awareness’ moderates the relationship between performance expectancy, effort expectancy, social influence, facilitating conditions and behavioural intention to use POS.

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.

Users Behavioral Intention Towards eGovernment in an African Developing Country

2018 ◽  
pp. 3654-3666
Author(s):  
Ayankunle A. Taiwo
Keyword(s):  
Technological Innovation ◽  
Developing Economies ◽  
Trust Model ◽  
Intention To Use ◽  
African Countries ◽  
Use Of Technology ◽  
Facilitating Conditions ◽  
Practical Implications ◽  
Study Performance ◽  
The Web

Ever since international emergence of the Internet, huge amounts of money have been invested on e-Government globally. Nevertheless, many African countries have recorded unsuccessful eGovernment initiatives. Optimal results are not exclusively dependent on technological innovation but combination of technologies and active participation of citizens. There is plethora of qualitative discussions on eGovernment with inadequate substantial quantitative study on the influence of trust on the adoption of eGovernment services in African developing economies. The unified theory of acceptance and use of technology (UTAUT) and the Web Trust model was integrated to investigate citizens' intention to use eGovernment services. Data relating to the constructs were collected from 310 respondents that participated in this study. Performance Expectancy, Effort Expectation, Facilitating Conditions and Trusting belief emerged as significant determinants of intention to use eGovernment services. Lastly, practical implications of the results are reported with discussion for further studies.

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