Determinants of intention to use Islamic banking

2019 ◽  
Vol 13 (1) ◽  
pp. 147-163 ◽  
Author(s):  
Samia Ayyub ◽  
Wang Xuhui ◽  
Muhammad Asif ◽  
Rana Muhammad Ayyub
Keyword(s):  
Consumer Behavior ◽  
Technology Acceptance ◽  
Structural Equation ◽  
Perceived Usefulness ◽  
Practical Significance ◽  
Equation Modeling ◽  
Islamic Banking ◽  
Intention To Use ◽  
Content Type ◽  
Acceptance Model

Purpose This paper aims to explore the determinants of intention to use Islamic banking and compare the consumer behavior of users and non-users of Islamic banking. This study incorporates the theory of planned behavior in Islamic banking perspective with an additional construct from technology acceptance model. Design/methodology/approach The research is quantitative in nature, and survey questionnaire was used to get data from four cities of Pakistan. The study manages to get 300 questionnaires from which only 264 were usable for analysis. The structural equation modeling was used for testing the hypotheses. Findings The result shows that perceived behavior control and perceived usefulness are the most significant predictors of intention to use of Islamic banking among users and non-users. Attitude turns out to be a non-significant factor for non-users of Islamic banking. Subjective norm is also found to be non-significant with intention to use Islamic banking in both groups. Originality/value This study has theoretical as well as practical significance in the subject of consumer behavior in Islamic banking. Theoretically, it attempts to fill the gap caused by the scarcity of research in exploring the consumer behavior towards Islamic banking in Pakistan. This study provides insights into the consumer behavior of users and non-users of Islamic banking and thus presents a comparison. Practically, this study provides guidelines for Islamic banks in introduction, propagation and promotion of Islamic banking products and services to establish Islamic banking as a social norm.

Consumer acceptance of smart speakers: a mixed methods approach

2018 ◽  
Vol 12 (4) ◽  
pp. 418-431 ◽  
Author(s):  
Pascal Kowalczuk
Keyword(s):  
Technology Acceptance ◽  
Structural Equation ◽  
Online Survey ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
Smart Devices ◽  
Intention To Use ◽  
Content Type ◽  
Acceptance Model

PurposeVoice-activated smart speakers such as Amazon Echo and Google Home were recently developed and are gaining popularity. Understanding and theorizing the underlying mechanisms that encourage or impede consumers to use smart speakers is fundamental for enhancing acceptance and future development of these new devices. Therefore, building on technology acceptance research, this study aims to develop and test an acceptance model for investigating consumers’ intention to use smart speakers.Design/methodology/approachFirst, antecedents that may significantly affect the usage intention of smart speakers were identified through an explorative approach by a netnographic analysis of customer reviews (N= 2,186) and Twitter data (N= 899). Afterward, these results and contemporary literature were used to develop and validate an acceptance model for smart speakers. Structural equation modeling (SEM) was used to test the proposed hypotheses on data collected from 293 participants of an online survey.FindingsBesides perceived ease of use and perceived usefulness, the quality and diversity of a system, its enjoyment, consumer’s technology optimism and risk (surveillance anxiety and security/privacy risk) strongly affect the acceptance of smart speakers. Among these variables, enjoyment had the strongest effect on behavioral intention to use smart speakers.Originality/valueThis is the first study that incorporates netnography and SEM for investigating technology acceptance and applies it to the field of interactive smart devices.

A comprehensive acceptance model for smart home services

2022 ◽  
Vol 6 (1) ◽  
pp. 45-58 ◽  
Author(s):  
Amer Al-Husamiyah ◽  
Mahmood Al-Bashayreh
Keyword(s):  
Technology Acceptance ◽  
Smart Home ◽  
Structural Equation ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
Smart Devices ◽  
Intention To Use ◽  
Perceived Ease Of Use ◽  
Acceptance Model

Smart home services (SHSs) afford users an effective lifestyle management system, which provides human-oriented networking of smart devices and applications that enable users to control their homes from anywhere at any time. Despite the benefits of SHSs, however, their acceptance is very low. There remains a gap in the literature in terms of a comprehensive model that addresses users’ intention to use SHSs. To address this gap, the present study explored the factors that influence SHS acceptance among users based on well-established theoretical frameworks, such as the technology acceptance model, innovation diffusion theory, and the theory of planned behavior. To this end, the study integrated four additional factors, namely, perceived convenience, perceived connectedness, perceived cost, and perceived privacy risk, into the exploration and carried out structural equation modeling to quantitatively determine the effects of these factors. Questionnaires were administered to 750 users. The findings indicated that perceived compatibility, perceived convenience, perceived connectedness, perceived cost, perceived behavioral control with perceived usefulness, and perceived ease of use directly and indirectly exerted a significant influence on users’ intention to use SHSs.

scholarly journals Predicting students’ intention to adopt mobile learning

2018 ◽  
Vol 11 (2) ◽  
pp. 178-191 ◽  
Author(s):  
Charles Buabeng-Andoh
Keyword(s):  
University Students ◽  
Technology Acceptance ◽  
Mobile Learning ◽  
Structural Equation ◽  
Reasoned Action ◽  
Statistical Technique ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
Intention To Use ◽  
Content Type

Purpose The purpose of this paper is to explore the ability of the integration of technology acceptance model (TAM) and theory of reasoned action (TRA) to predict and explain university students’ intention to use m-learning in schools. Design/methodology/approach In total, 487 students participated in this study. A seven-likert scale survey questionnaire which comprised of 23 items was completed by the students. Structural equation modeling was used as the statistical technique to analyze the data. Findings The study found that the resulting model was fairly able to predict and explain behavioral intention (BI) among students in Ghana. In addition, this study found that attitudes toward use and subjective norm significantly influenced students’ BI to use mobile learning. The model explained 23.0 percent of the variance in BI, 33.8 percent in perceived usefulness and 47.6 percent in attitudes toward use. Of all the three endogenous variables, attitude had the greatest effect on BI. Originality/value Although, the above-mentioned models have been adopted in many studies, few or none have combined TRA and TAM as a research framework to predict and explain students’ intention to use m-learning since m-learning is fairly new in educational environments. Therefore, a model that combines all constructs from TRA and TAM was proposed in this study to explore university students’ intention to use m-learning in schools.

An acceptance model for smart watches

2015 ◽  
Vol 25 (4) ◽  
pp. 527-541 ◽  
Author(s):  
Ki Joon Kim ◽  
Dong-Hee Shin
Keyword(s):  
Technology Acceptance ◽  
Structural Equation ◽  
Online Survey ◽  
Perceived Usefulness ◽  
Relative Advantage ◽  
Equation Modeling ◽  
Content Type ◽  
Psychological Determinants ◽  
Smart Watch ◽  
Acceptance Model

Purpose – The purpose of this paper is to identify the key psychological determinants of smart watch adoption (i.e. affective quality (AQ), relative advantage (RA), mobility (MB), availability (AV), subcultural appeal) and develops an extended technology acceptance model (TAM) that integrates the findings into the original TAM constructs. Design/methodology/approach – An online survey assessed the proposed psychological determinants of smart watch adoption. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were conducted on collected data (n=363) using the AMOS 22 statistical software. The reliability and validity of the measurement assessing the proposed factor structure were examined via CFA, while the strength and direction of the hypothesized causal paths among the constructs were analyzed via SEM. Findings – The AQ and RA of smart watches were found to be associated with perceived usefulness, while the sense of MB and AV induced by smart watches led to a greater perceived ease of the technology’s use. The results also indicated that the devices’ subcultural appeal and cost were notable antecedents of user attitude (AT) and intention to use, respectively. Originality/value – Though smart watches are becoming increasingly popular, empirical studies on user perceptions of and ATs toward – them remain preliminary. This paper is one of the first scholarly attempts at a systematic prediction of smart watch usage, with implications for the adoption of future wearable technology.

scholarly journals Evaluating the customers' dining attitudes, e-satisfaction and continuance intention toward mobile food ordering apps (MFOAs): evidence from Bangladesh

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Md. Al Amin ◽  
Md. Shamsul Arefin ◽  
Nayeema Sultana ◽  
Md. Rakibul Islam ◽  
Israt Jahan ◽  
...  
Keyword(s):  
Technology Acceptance ◽  
Structural Equation ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
Continuance Intention ◽  
Safety Measures ◽  
Content Type ◽  
Online Sales ◽  
Convenience Sampling ◽  
Acceptance Model

PurposeThis study was designed to specifically explore confirmation and perceived usefulness associated with mobile food ordering apps (MFOAs) in consideration of their impacts upon attitudes, satisfaction and intention to continuously use.Design/methodology/approachThe research utilized the convenience sampling to gather data from 250 respondents having prior experience with MFOAs during COVID-19 pandemic period in Bangladesh. The Structural Equation Modeling technique was applied to analyze the data using SmartPLS 3 software.FindingsThis study's results showed that customers' perceived confirmation and usefulness were significant in determining their dinning attitudes. Besides, customers' dining attitudes were positively related to e-satisfaction. Finally, the customers’ continuance intention to use MFOAs was significantly influenced by their e-satisfaction.Research limitations/implicationsRestaurants managers should focus on online sales through MFOAs during the pandemic period since social distancing is a key strategy to manage COVID-19. Customers should be assured that the safety measures are undertaken while delivering the food.Originality/valueThis study incorporated the expectation-confirmation theory and technology acceptance model and tested it in the context of MFOAs.

scholarly journals Students’ intention to use high-immersion virtual reality systems for learning paragraph structure: a PLS-SEM exploratory study

2020 ◽  
pp. 291-297
Author(s):  
Ethan Douglas Quaid ◽  
Austin Pack ◽  
Alex James Barrett ◽  
Litong Zhou
Keyword(s):  
Virtual Reality ◽  
Technology Acceptance ◽  
Undergraduate Students ◽  
Structural Equation ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
Short Paper ◽  
Intention To Use ◽  
Antecedent Conditions ◽  
Acceptance Model

This short paper reports the findings of a study exploring English for Academic Purposes (EAP) students’ behavioral intention to use a high-immersion Virtual Reality (VR) system for learning paragraph structure. The study measured relationships between variables that may lead to learners’ intention to use the high-immersion VR Reality system through leveraging a hypothesized theoretical framework based upon a widely used technology acceptance model. Quantitative data were collected from 134 Sino-British English as a medium of instruction by university undergraduate students enrolled in EAP classes by means of a post-participation questionnaire. A Partial Least Squares - Structural Equation Modeling (PLS-SEM) exploratory analysis was executed. Results suggested that students’ intention to use the high-immersion VR learning environment was primarily determined by its usefulness for learning and not how easy it was to use. Furthermore, the degree to which the learners felt confident in their ability to operate the system had a large impact on how easy they perceived it was to use. And finally, the antecedent conditions of learners had little impact on the students’ perceived usefulness of the VR system.

scholarly journals Platform Adoption Factors in the Internet Industry

2018 ◽  
Vol 10 (9) ◽  
pp. 3185 ◽  
Author(s):  
Junic Kim
Keyword(s):  
Technology Acceptance ◽  
Structural Equation ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
Intention To Use ◽  
Perceived Ease Of Use ◽  
Positive Effects ◽  
Internet Industry ◽  
Acceptance Model

This study examines the factors influencing the choices of Internet platform services by applying the technology acceptance model. For this purpose, the analysis is conducted with 222 people who use different types of Internet platforms by utilizing structural equation modeling. The results show that perceived usefulness had positive effects on the intention to use, perceived ease of use, diversity, and security risks affected by the perceived usefulness, and the indirect influences on the intention to use. In addition, satisfaction (in relation to service quality) was found to affect both perceived ease of use and perceived usefulness. This research is significant because it will make it possible to predict users’ perceptions of Internet platforms, which is important for establishing relevant strategies.

Factors affecting sustainable adoption of e-health systems in Resource-Limited settings: an exploratory survey of Ethiopian hospitals from the perspective of healthcare professionals. (Preprint)

2019 ◽  
Author(s):  
Mulugeta Hayelom
Keyword(s):  
Technology Acceptance ◽  
Health Systems ◽  
Structural Equation ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
Intention To Use ◽  
Factors Affecting ◽  
Resource Limited ◽  
Referral Hospitals ◽  
Acceptance Model

BACKGROUND Electronic health (e-health) is becoming a prominent component of the health care system. The implementation and sustainable adoption of e-health systems is now taking as a big agenda in developing countries like Ethiopia, hence it all about saving a millions of lives. Even though there are some pilot e-health implementations, the success and sustainability of the systems are found less than the expected. So, this study aims to fill the gap in identifying the factors affecting sustainable adoption of e-health systems using the revised technology acceptance model at five referral hospitals of Amhara regional state of Ethiopia. OBJECTIVE To identify the factors affecting sustainable adoption of e-health systems using the revised technology acceptance model at five referral hospitals of Amhara regional state of Ethiopia. METHODS Institutional based cross-sectional study design was conducted among a total of 384 health care professionals. Self-administered questionnaire was used to collect the data. And the data were entered and the descriptive data were analyzed using Epi-info version 7 and SPSS version 20 respectively. Structural equation modeling, using AMOS 22, was also used to measure and clarify the degree of relationships between variables. RESULTS The findings of the structural equation modeling (SEM) indicates that perceived usefulness has significance influence on attitude (β =0.29, P<0.01) and intention to use e-health (β =0.38, P<0.01); technical infrastructure has significance influence on attitude (β =0.41, P<0.01) and intention to use e-health (β =0.34, P<0.01); staffs IT experience has significance influence on attitude (β =0.26, P<0.05); security concerns of a system has significance influence on attitude (β =0.34, P<0.05) and intention to use e-health (β =0.33, P<0.01); and attitude has also significance influence on intention to use e-health (β =0.52, P<0.01), respectively. CONCLUSIONS Electronic health system implementers and executives in resource limited settings are in urgent need of adoption models to design proper implementation strategies. The constructs; perceived usefulness, technical infrastructure, staffs IT experience, security concerns and attitude portrayed in the revised TAM model were found with a strong positive relationship with the dependent variable, intention to use e-health. Therefore, the implementers should give a priority in enhancing technical infrastructures of the organizations, staffs IT skill, and their attitude towards e-health by giving continuous support.

Impact of contextuality on mobile learning acceptance

2016 ◽  
Vol 13 (2) ◽  
pp. 107-122 ◽  
Author(s):  
Stephan Böhm ◽  
Georges Philip Constantine
Keyword(s):  
Language Learning ◽  
Technology Acceptance ◽  
Structural Equation ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
Learning Activity ◽  
Content Type ◽  
Location Aware ◽  
Mobile Learning Acceptance ◽  
Acceptance Model

Purpose This paper aims to focus on contextualized features for mobile language learning apps. The scope of this paper is to explore students’ perceptions of contextualized mobile language learning. Design/methodology/approach An extended Technology Acceptance Model was developed to analyze the effect of contextual app features on students’ usage intention. The suggested app concept applies context-triggered push notifications to initiate learning sessions based on a location-aware vocabulary. Partial least squares structural equation modeling (PLS-SEM) was used for an empirical validation of the proposed research model. Findings The results of the analysis revealed, that students perceived the proposed app as beneficial for their learning endeavors. The location-aware feature is essentially relevant to improve the perceived usefulness of the system, as it may increase the learning effectiveness of the app in their everyday life. Research limitations/implications The study was conducted in quite a homogenous population. The sample size of the survey was rather small (n = 45). Further research is necessary to confirm the promising results of the research. Originality/value The results give some first evidence that the integration of innovative contextual features in mobile language learning apps may increase the usage intention and motivation to engage in a learning activity.

The adoption of teaching assistant robots: a technology acceptance model approach

2016 ◽  
Vol 50 (4) ◽  
pp. 354-366 ◽  
Author(s):  
Eunil Park ◽  
Sang Jib Kwon
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Structural Equation ◽  
Rapid Development ◽  
Teaching Assistant ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
Content Type ◽  
User Attention ◽  
Acceptance Model

Purpose Based on rapid improvements in telecommunications and wireless networks with extensive educational contents, numerous studies have been conducted to improve our educational success/attainment/environment. With this trend, the purpose of this paper is to investigate users’ perceptions of teaching assistant (TA) robots and the possible motivations that impact the users’ intention to use (IU) the robots. Design/methodology/approach In light of the rapid development of and attempts at understanding interactions with social robots, including TA robots, this study uses structural equation modeling and confirmatory factor analysis. Findings The results indicated that perceived usefulness was the most crucial factor determining the users’ IU for TA robots. In addition, the relationships of the original technology acceptance model were confirmed. The study findings demonstrated the crucial importance of perceived enjoyment and service quality. Originality/value Although the role of TA robots has gained user attention, few investigations have been conducted to explain how IU is formed. The current study can thus act as the foundation for exploring the acceptance process in the context of TA robots.

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