The Relationship of Performance Expectancy, Effort Expectancy, and Social Influence on Behavioural Intention to Online Registration System of Health Institutional Service in Surabaya

2017 ◽  
Author(s):  
Eka Wilda Faida
Keyword(s):  
Social Influence ◽  
Behavioural Intention ◽  
Registration System ◽  
Performance Expectancy ◽  
Institutional Service ◽  
Effort Expectancy ◽  
Online Registration ◽  
Relationship Of ◽  
The Relationship

ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PERILAKU PENGGUNAAN SISTEM E-LEARNING UNDIKSHA DENGAN MODEL UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY (UTAUT)

2021 ◽  
Vol 1 (2) ◽  
pp. 1
Author(s):  
I Gede Arya Sukarya ◽  
I Made Ardwi Pradnyana ◽  
Nyoman Sugihartini
Keyword(s):  
Social Influence ◽  
Learning System ◽  
Moderator Variable ◽  
Performance Expectancy ◽  
Use Of Technology ◽  
Effort Expectancy ◽  
E Learning ◽  
Use Behavior ◽  
Relationship Of ◽  
The Relationship

Sistem E-learning dikembangkan oleh Undiksha untuk meningkatkan efektivitas dan kualitas pembelajaran. Namun pada kenyataannya E-learning Undiksha belum dimanfaatkan secara maksimal oleh dosen di lingkungan Undiksha. Pengguna dapat menerima dan menggunakan sistem adalah hal yang penting untuk dapat mengetahui tingkat keberhasilan dari implementasi sistem tersebut. Oleh karena itu penelitian ini bertujuan untuk menganalisis faktor-faktor yang mempengaruhi perilaku penggunaan sistem E-learning Undiksha dengan model Unified Theory of Acceptance and Use of Technology (UTAUT). UTAUT merupakan salah satu model penerimaan teknologi yang menggabungkan delapan teori penerimaan teknologi sebelumnya. UTAUT memiliki empat konstruk utama yaitu ekspektasi kinerja, ekspektasi usaha,  pengaruh sosial dan kondisi yang memfasilitasi.Data diperoleh dengan cara menyebarkan kuesioner tertutup dengan sampel 64 Dosen Undiksha. Dianalisis menggunakan software SPSS. Hasil penelitian ini menunjukkan bahwa (1) Ekspektasi kinerja, ekpektasi usaha, pengaruh sosial dan kondisi yang memfasiitasi berpengaruh positif terhadap perilaku penggunaan sistem E-learning Undiksha (2) Variabel moderator jenis kelamin memperkuat hubungan ekspektasi kinerja dan ekspektasi usaha terhadap perilaku penggunaan sistem E-learning Undiksha sedangkan untuk variabel moderator jenis kelamin memperlemah hubungan variabel pengaruh sosial terhadap perilaku penggunaan sistem E-learning Undiksha (3) Variabel moderator umur memperkuat hubungan variabel ekspektasi kinerja, ekspektasi usaha, pengaruh sosial dan kondisi yang memfasilitasi terhadap perilaku penggunaan sistem E-learning Undiksha (4) Variabel moderator pengalaman memperkuat hubungan ekspektasi usaha, pengaruh sosial dan kondisi yang memfasilitasi terhadap perilaku penggunaan sistem E-learning Undiksha.AbstractE-learning was developed by ganesha university of education to improve learning effectiveness and quality. Yet, this system had not used maximally by lecturers in the institution.  Users which could accept and use the system was an important thing to know degree of its implementation successfulness. Hence, this study aimed at analyzing factors affecting use behavior of UNDIKSHA’s E-learning system with Unified Theory of Acceptance and Use of Technology (UTAUT) model. UTAUT is one of technology acceptance model combining 8 previous technology acceptance theories. It has 4 main constructs, namely performance expectancy, effort expectancy, social influence, and facilitating condition.The data were collected through giving closed questionnaire to lecturers. It involved 64 lecturers in UNDIKSHA as the sample of this study. The obtained data were analysed by means of SPSS. The results show that (1) Performance expectancy, effort expectancy, social influence, and facilitating condition have positive impact on the use behavior of the E-learning system, (2) Gender moderator variable strengthens the relationship of performance expectancy and effort expectancy towards the use behavior of the E-learning system, but weakens the relationship between social influence variable and the use behavior, (3) Age moderator variable strengthens the relationship of performance expectancy, effort expectancy, social influence, and facilitating condition towards the use behavior of the E-learning system, and (4) Experience moderator variable strengthens the relationship of performance expectancy, effort expectancy, social influence, and facilitating condition towards the use behavior of the E-learning system.

scholarly journals Elucidating social networking apps decisions

2018 ◽  
Vol 9 (2) ◽  
pp. 118-142 ◽  
Author(s):  
Pei Ying Chua ◽  
Sajad Rezaei ◽  
Man-Li Gu ◽  
YokeMoi Oh ◽  
Manimekalai Jambulingam
Keyword(s):  
Social Influence ◽  
Social Networking ◽  
Behavioural Intention ◽  
Young Generation ◽  
Market Segment ◽  
Content Type ◽  
Latent Constructs ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
The Relationship

PurposeThe purpose of this paper is to investigate the determinants of behavioural intention and use behaviour towards social networking apps. Exogenous latent constructs, namely, performance expectancy, effort expectancy and social influence are the key antecedents proposed based on the unified theory of acceptance and use of technology to predict the usage intention and behaviour of social networking apps (i.e. endogenous latent constructs). Experience as a moderator is the extended construct to explain social networking apps user’s behavioural intention.Design/methodology/approachTo target young generation (Millennial), a cross-sectional data collection approach was conducted to collect data from the social networking apps users (i.e. Facebook, WhatsApp, WeChat, Twitter, Instagram, YouTube, Snapchat and others) whereby a total of 384 valid questionnaires were obtained from six universities in Malaysia. Statistical analysis using partial least squares path modelling approach and a variance-based structural equation modelling (VB-SEM) techniques is performed to analyse the measurement and structural relationship.FindingsThe findings indicate that performance expectancy, effort expectancy and social influence determine behavioural intention, and behavioural intention impacts social networking apps use behaviour. Moreover, the moderation analysis reveals that the relationship between effort expectancy and behavioural intention is moderated by experience, whereas the relationship between social influence and behavioural intention is not moderated by experience.Originality/valueWhile the surge of social networking apps has gained tremendous popularity among Millennial as an attractive market segment, previous studies mainly have focussed on intention and behaviour of online users in general. Despite apps and related technologies which have opened a new era of effective communications in marketing, social networking apps usage intention and behaviour focussing on Millennial is not well understood in the current literature. This study contributes and sheds lights on the current issue of social networking apps usage intention and behaviour and looks into a key rising market segment, the Millennial users.

scholarly journals Modeling Factors Affecting Student’s Usage Behaviour of E-Learning Systems in Lebanon

2016 ◽  
Vol 11 (2) ◽  
pp. 299 ◽  
Author(s):  
Ra'ed (Moh'd Taisir) Masa'deh ◽  
Ali Tarhini ◽  
Ashraf Bany Mohammed ◽  
Mahmoud Maqableh
Keyword(s):  
Social Influence ◽  
Learning Systems ◽  
Behavioural Intention ◽  
Equation Modeling ◽  
Positive Effects ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
E Learning ◽  
Facilitating Conditions ◽  
The Impact

<p>This study seeks to explore the factors that influence students’ usage behaviour of e-learning systems. Based on the strong theoretical foundation of the TAM, UTAM and using structural equation modeling (SEM) via AMOS 20.0, this research paper examines the impact of performance expectancy, effort expectancy, hedonic motivation, habit, social influence, and trust on student’s behavioural intention, which is later examined along with facilitating conditions on student’s usage behaviour of e-learning systems. Data was collected from students at two universities in Beirut (capital of Lebanon) using a cross-sectional questionnaire survey between January and March 2015. The results revealed direct positive effect of performance expectancy, hedonic motivation, habit, and trust on student’s behavioural intention to use e-learning explaining around 71% of overall behavioural intention. Meanwhile, behavioural intention and facilitating conditions accounted for 40% with strong positive effects on student’s usage behviour of e-learning systems. However, both effort expectancy and social influence did not impact student’s behavioural intention.</p>

scholarly journals Factors Determine the Behavioural Intention in Adopting the Blockchain Technology by Malaysian Public Sector Officers

2020 ◽  
Vol 20 (1) ◽  
pp. 34-43
Author(s):  
Mohd Izzat Latifa ◽  
Zukarnain Zakaria
Keyword(s):  
Public Sector ◽  
Social Influence ◽  
New Technology ◽  
Behavioural Intention ◽  
The Public ◽  
Performance Expectancy ◽  
Blockchain Technology ◽  
Effort Expectancy ◽  
The Government ◽  
Facilitating Conditions

Recently, Blockchain technology has attracted great attention in both private organisations and the public sector around the world. However, not many are aware and understand this new technology. Thus, lack of understanding of the Blockchain technology could influence the intention in adopting the technology. Therefore, the objective of this paper is to identify the behaviour intention towards adopting Blockchain Technology in the Malaysian Public Sector. Data were gathered using a questionnaire to analyse the relationship between factors such as Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions and Trust with Behavioural Intention to adopt Blockchain Technology. The data were gathered from 100 officers in various government department. The survey revealed that majority of the government officers are aware about the Blockchain technology. However, most of them have inadequate exposure and knowledge about the technology. Findings from the regression analysis found that Trust, Performance Expectancy and Social Influence positively and significantly influence the behaviour intention of government officers in adopting Blockchain technology. Meanwhile, Effort Expectancy and Facilitating Conditions were found not significant. The findings from this study suggest that it is essential to develop strategies to implement a suitable Blockchain application in the public sector. Prior to such implementation, it is imperative for government officers to be equipped with knowledge, skills and resources related to the Blockchain technology.

scholarly journals The acceptance of radiographers to use Non-fluoroscopy Guided Positioning and the influence of leadership: a survey research

2019 ◽  
Vol 54 (4) ◽  
pp. 295-301
Author(s):  
S. Germonpré ◽  
G. Vermaut ◽  
J. Trybou
Keyword(s):  
Social Influence ◽  
Survey Research ◽  
Predictive Value ◽  
Behavioural Intention ◽  
Intention To Use ◽  
Helpful Tool ◽  
Moderation Analysis ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Using Data

Although using fluoroscopy to position the patient for radiographic examinations cannot be justified, it is commonly used by several radiology departments. In an attempt to understand the determinants of non-fluoroscopy-guided positioning, this study investigates the predictive value of performance expectancy, effort expectancy and social influence. Subsequently, the moderation of individualised consideration by the head radiographer, as a leadership trait, is tested. The study is performed by using data of a self-administered paper and pencil questionnaire distributed among 17 Belgian hospitals. All 301 radiographers working in radiology departments were invited to cooperate. We found that effort expectancy is the strongest predictor, closely followed by performance expectancy. The effect of social influence is also found to be significant. The outcome of the moderation analysis shows that only the effect of social influence on the behavioural intention to use non-fluoroscopy-guided positioning is significantly moderated by individualised consideration. In conclusion we can state that the findings of this research can be a helpful tool for radiologists and head radiographers to stimulate the staff to improve imaging practices.

Moderating effects of online shopping experience on customer satisfaction and repurchase intentions

2014 ◽  
Vol 42 (3) ◽  
pp. 187-204 ◽  
Author(s):  
Ilias O. Pappas ◽  
Adamantia G. Pateli ◽  
Michail N. Giannakos ◽  
Vassilios Chrissikopoulos
Keyword(s):  
Online Shopping ◽  
Group Analysis ◽  
Moderating Effects ◽  
Content Type ◽  
Performance Expectancy ◽  
Shopping Behaviour ◽  
Effort Expectancy ◽  
Shopping Experience ◽  
Relationship Of ◽  
The Relationship

Purpose – Satisfaction and experience are essential ingredients for successful customer retention. This study aims to verify the moderating effect of experience on two types of relationships: the relationship of certain antecedents with satisfaction, and the relationship of satisfaction with intention to repurchase. Design/methodology/approach – This paper applies structural equation modelling (SEM) and multi-group analysis to examine the moderating role of experience in a conceptual model estimating the intention to repurchase. Responses from 393 people were used to examine the differences between high- and low-experienced users of online shopping. Findings – The research shows that experience has moderating effects on the relationships between performance expectancy and satisfaction and satisfaction and intention to repurchase. This study empirically demonstrates that prior customer experience strengthens the relationship between performance expectancy and satisfaction, while it weakens the relationship of satisfaction with intention to repurchase. Practical implications – Practitioners should differentiate the way they treat their customers based on their level of experience. Specifically, the empirical research demonstrates that the expected performance of the online shopping experience (performance expectancy) affects satisfaction only on high-experienced customers. Instead, the effort needed to use online shopping (effort expectancy) and the user's belief in own abilities to use online shopping (self-efficacy) influence satisfaction only on low-experienced customers. The effect of trust and satisfaction is significant on online shopping behaviour on both high- and low-experienced customers. Originality/value – This paper investigates how different levels of experience affect customers' satisfaction and online shopping behaviour. It is proved that experience moderates the effect of performance expectancy on satisfaction and the effect of satisfaction on intention to repurchase. It also demonstrates that certain effects (effort expectancy and performance expectancy) are valid for only one of the two examined groups, while only one effect (trust) is valid for both (high- and low-experienced).

(Preprint)

2018 ◽  
Author(s):  
Alaa Ali Abd-Alrazaq ◽  
Bridgette Bewick ◽  
Tracey Farragher ◽  
Peter Gardner
Keyword(s):  
Structural Equation ◽  
Behavioural Intention ◽  
Successful Implementation ◽  
Privacy And Security ◽  
Convenience Sample ◽  
Factors Associated ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
The Relationship

BACKGROUND Electronic Personal Health Records (ePHRs) are secure web-based tools that enable individuals to access, manage, and share their medical records. England recently introduced a nationwide ePHR called Patient Online. As with ePHRs in other countries, adoption rates of Patient Online remain low. Understanding factors affecting patients’ use of ePHRs is important to increase adoption rates and improve the implementation success of ePHRs. OBJECTIVE This study aims to examine factors associated with patients’ use of ePHRs in England. METHODS The Unified Theory of Acceptance and Use of Technology (UTAUT) was adapted to the use of ePHRs. To empirically examine the adapted model, a cross-sectional survey of a convenience sample was carried out in four general practices in West Yorkshire, England. Factors associated with use of ePHRs were explored using Structural Equation Modelling (SEM). RESULTS Of 800 eligible patients invited to take part in the survey, 624 (78%) participants returned a valid questionnaire. Behavioural intention was significantly influenced by performance expectancy (β=0.57, P<0.001), effort expectancy (β=0.16, P<0.001), and perceived privacy and security (β=0.24, P<0.001). The path from social influence to behavioural intention was not significant (β=0.03, P=0.183). Facilitating conditions and behavioural intention significantly influenced use behaviour (β=0.25, P<0.001; β=0.53, P<0.001, respectively). Performance expectancy significantly mediated the effect of effort expectancy and perceived privacy and security on behavioural intention (β=0.19, P<0.001; β=0.28, P=0.001, respectively). Age significantly moderated three paths; PEBI, EEBI, and FCUB. Sex significantly moderated only the relationship between performance expectancy and behavioural intention. Two paths were significantly moderated by education and internet access: EEBI and FCUB. Income moderated the relationship between facilitating conditions and use behaviour. The adapted model accounted for 51% of the variance in performance expectancy, 76% of the variance in behavioural intention, and 48% of the variance in use behaviour. CONCLUSIONS This study identified the main factors that affect patients’ use of ePHRs in England, which should be taken into account for the successful implementation of these systems. For example, developers of ePHRs should involve patients in the process of designing the system to consider functions and features that fit patients’ preferences and skills, thereby, create a useful and easy to use system. The proposed model accounted for 48% of the variance in use behaviour, indicating the existence of other, as yet unidentified, factors that influence adoption of ePHRs. Future studies should confirm the effect of the factors included in the current model and to identify additional factors.

scholarly journals The Role of Trust and Risk in Citizens’ E-Government Services Adoption: A Perspective of the Extended UTAUT Model

2021 ◽  
Vol 13 (14) ◽  
pp. 7671
Author(s):  
Wenjuan Li
Keyword(s):  
Social Influence ◽  
Perceived Risk ◽  
The Internet ◽  
Government Services ◽  
Utaut Model ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
The Government ◽  
The Relationship

This research particularly aims to investigate how trust and perceived risk influence citizens’ e-government adoption. The findings of the study reveal that citizens’ trust of the government (TOG) and trust of the internet (TOI) positively affect citizens’ e-government adoption (EGA); perceived risk (PR) is negatively associated with citizens’ EGA. Interestingly, this study also demonstrates the negative moderating effect of PR on the relationship between TOG and EGA, TOI and EGA. The results also indicate that performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitation conditions (FC) influence citizens’ EGA positively. Lastly, implications for practice and research are discussed.

Modeling Millennials’ Adoption Intentions of E-banking: Extending UTAUT with Perceived Risk and Trust

2021 ◽  
pp. 231971452110526
Author(s):  
Akansha Mer ◽  
Amarpreet Singh Virdi
Keyword(s):  
Social Influence ◽  
Perceived Risk ◽  
Structural Equation ◽  
Sampling Technique ◽  
Positive Association ◽  
Behavioural Intention ◽  
Primary Data ◽  
Equation Modeling ◽  
Performance Expectancy ◽  
Effort Expectancy

The rationale of this research is to analyse and observe the factors that persuade millennials’ acceptance, adoption and usage of e-banking services in the banking industry in India. This research used primary data gathered from millennials in India. The sampling technique used is judgment sampling. Statistical analysis is conducted using structural equation modeling. The study’s findings indicate that effort expectancy, trust, social influence, performance expectancy and perceived risk are the factors that impinge on millennials’ behavioural intention of e-banking. The study suggests that effort expectancy, trust, social influence and performance expectancy posit a positive association with the e-banking behavioural intention of millennials in India. On the contrary, perceived risk is in a negative association with the e-banking behavioural intention of the millennials. The study makes a novel contribution to the literature with reference to India, being a pioneer attempt to investigate the factors that affect e-banking acceptance by millennials in Indian banks by extending UTAUT with perceived risk and trust. The present study contributes to the literature on e-banking adoption in India by highlighting that trust plays a crucial role in Indian millennials’ intention to adopt e-banking technology in high-power distance country like India.

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