The Factors Influencing Taxpayers' Acceptance of E-Taxation System

2015 ◽  
pp. 105-121
Author(s):  
Adnan Gercek ◽  
Tolga Demirbas ◽  
Filiz Giray ◽  
Ayse Oguzlar ◽  
Mehmet Yuce
Keyword(s):  
Perceived Risk ◽  
Structural Equation ◽  
Model Performance ◽  
Equation Modeling ◽  
Intention To Use ◽  
Government Services ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Taxation System

E-taxation is one of the most popular e-government services. Most countries are focused on implementing an e-taxation system. The success of an e-taxation system depends on the taxpayers' acceptance of it. The taxpayers' intention to use an e-taxation system is determined by various factors. This chapter, based on empirical data collected from a survey of 505 respondents in Turkey, seeks to identify the factors that influence the taxpayers' acceptance of e-taxation system. It test various constructs of the UTAUT model – performance expectancy, trust perception, perceived risk, effort expectancy and facilitating conditions – on Turkish taxpayers' intention to use the e-taxation system. Structural equation modeling is used to analyze the effects of these variables on intention to use. The results indicate that performance expectancy and perceived risk have a significant impact on behavioral intention and that effort expectancy and facilitating conditions have a significant impact on intention to use.

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.

Effects of trust and perceived risk on user acceptance of a new technology service

2013 ◽  
Vol 41 (4) ◽  
pp. 587-597 ◽  
Author(s):  
Ji-Hwan Lee ◽  
Chi-Hoon Song
Keyword(s):  
Social Influence ◽  
Perceived Risk ◽  
Structural Equation ◽  
New Technology ◽  
Equation Modeling ◽  
Intention To Use ◽  
Performance Expectancy ◽  
Use Of Technology ◽  
Effort Expectancy ◽  
The Republic

We explored the precise impacts of trust and perceived risk on the core constructs of the unified theory of acceptance and use of technology (UTAUT). We applied the UTAUT model to the novel context of the Certified e-Document Authority (CeDA) service used in the Republic of Korea. Our results from structural equation modeling largely supported our hypotheses. Trust and perceived risk were shown to be direct antecedents of intention to use, and trust functioned as an indirect antecedent. Performance expectancy and social influence were shown to positively affect behavioral intention. Effort expectancy was also shown to influence performance expectancy. The combination of trust, perceived risk, performance expectancy, effort expectancy, and social influence accounted for 55.3% of the variance observed in users' intention to use CeDA services.

Modeling the Factors that Influence Ghanaian Entrepreneurs to Adopt e-Commerce

2021 ◽  
Vol 18 (06) ◽  
Author(s):  
Frederick Pobee
Keyword(s):  
Structural Equation ◽  
Partial Least Square ◽  
Least Square ◽  
Equation Modeling ◽  
Unified Theory ◽  
Cross Sectional ◽  
Performance Expectancy ◽  
Use Of Technology ◽  
Effort Expectancy ◽  
Facilitating Conditions

This study investigated the factors that influence Ghanaian entrepreneurs to adopt e-commerce. Cross-sectional data was gathered from 520 entrepreneurs in the most populous and industrious regions in Ghana. The unified theory of acceptance and use of technology (UTAUT) was employed to effectively understand the unexplored phenomenon of e-commerce adoption among Ghanaian entrepreneurs. Partial Least Square-Structural Equation Modeling (PLS-SEM) was used to test the hypothesized relationships. The findings indicate that performance expectancy, effort expectancy, and social influence (SI) positively and significantly influenced the behavioral intention (BI) to adopt e-commerce. Facilitating conditions (FC) and BI had a significant positive relationship with the adoption of e-commerce.

The Moderating Effects of Gender on E-Commerce Systems Adoption Factors

2018 ◽  
Vol 9 (4) ◽  
pp. 86-104
Author(s):  
Frederick Pobee ◽  
Daniel Opoku
Keyword(s):  
Behavioral Intention ◽  
Structural Equation ◽  
Equation Modeling ◽  
Moderating Effects ◽  
Performance Expectancy ◽  
Adoption Factors ◽  
Use Of Technology ◽  
Effort Expectancy ◽  
Actual Use ◽  
Facilitating Conditions

The purpose of this article was to investigate the moderating effects of gender on e-commerce systems adoption factors among university lecturers in Ghana. In order to achieve this purpose, the unified theory of acceptance and use of technology (UTAUT) was used as the theoretical lens for the study. Eight hypotheses were developed and tested. Data analysis was performed with a structural equation modeling (SEM) technique using SmartPLS Application. Using a survey of 223 respondents, the study showed that factors such as performance expectancy, effort expectancy, and facilitating conditions positively and significantly influenced Ghanaian lecturers' behavioral intention and ultimately the actual use of e-commerce systems. As for the moderating effects of gender, this study discovered that gender insignificantly moderated the effects of performance expectancy, effort expectancy and social influence on behavioral intention.

A two-stage structural equation modeling-neural network approach for understanding and predicting the determinants of m-government service adoption

2019 ◽  
Vol 21 (4) ◽  
pp. 419-438 ◽  
Author(s):  
Shamim Talukder ◽  
Raymond Chiong ◽  
Sandeep Dhakal ◽  
Golam Sorwar ◽  
Yukun Bao
Keyword(s):  
Neural Network ◽  
Structural Equation ◽  
Equation Modeling ◽  
Intention To Use ◽  
Government Service ◽  
Content Type ◽  
Service Adoption ◽  
Government Services ◽  
Performance Expectancy ◽  
And Performance

Purpose Despite the widespread use of mobile government (m-government) services in developed countries, the adoption and acceptance of m-government services among citizens in developing countries is relatively low. The purpose of this study is to explore the most critical determinants of acceptance and use of m-government services in a developing country context. Design/methodology/approach The unified theory of acceptance and use of technology (UTAUT) extended with perceived mobility and mobile communication services (MCS) was used as the theoretical framework. Data was collected from 216 m-government users across Bangladesh and analyzed in two stages. First, structural equation modeling (SEM) was used to identify significant determinants affecting users' acceptance of m-government services. In the second stage, a neural network model was used to validate SEM results and determine the relative importance of the determinants of acceptance of m-government services. Findings The results show that facilitating conditions and performance expectancy are the two important precedents of behavioral intention to use m-government services, and performance expectancy mediates the relationship between MCS, mobility and the intention to use m-government services. Research limitations/implications Academically, this study extended and validated the underlying concept of UTAUT to capture the adoption behavior of individuals in a different cultural context. In particular, MCS might be the most critical antecedent towards mobile application studies. From a practical perspective, this study may provide valuable guidelines to government policymakers and system developers towards the development and effective implementation of m-government systems. Originality/value This study has contributed to the existing, but limited, literature on m-government service adoption in the context of a developing country. The predictive modeling approach is an innovative approach in the field of technology adoption.

scholarly journals Toward an Understanding of University Students’ Continued Intention to Use MOOCs: When UTAUT Model Meets TTF Model

SAGE Open ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 215824402094185
Author(s):  
Liyong Wan ◽  
Shoumei Xie ◽  
Ai Shu
Keyword(s):  
University Students ◽  
User Satisfaction ◽  
Structural Equation ◽  
Equation Modeling ◽  
Utaut Model ◽  
Mediating Role ◽  
Performance Expectancy ◽  
Use Of Technology ◽  
Effort Expectancy ◽  
Facilitating Conditions

This study tries to propose a unified model integrating the unified theory of acceptance and use of technology (UTAUT) model, task–technology fit (TTF) model, and user satisfaction to investigate the determinants that affect university students’ continued intention of using massive open online courses (MOOCs). Based on the data of a survey on 464 respondents, structural equation modeling is adopted to assess the model. The results reveal that performance expectancy, effort expectancy, social influence, and user satisfaction are the crucial predictors of university students’ continued intention. TTF has an indirect influence on continued intention through user satisfaction. Performance expectancy is affected both by effort expectancy and TTF. Facilitating conditions do not directly influence continued intention; however, they present indirect influences in that they play a mediating role for user satisfaction. The findings help researchers and practitioners to attain a better understanding of university students’ continued usage intention of MOOCs. The implications and limitations of this study are also described.

scholarly journals Analisis Behavioral Intention Pada Layanan Aplikasi RCTI+

2020 ◽  
Vol 4 (5) ◽  
pp. 199
Author(s):  
Anggit Mardiana Permatasari ◽  
Hetty Karunia Tunjungsari
Keyword(s):  
Social Influence ◽  
Behavioral Intention ◽  
Structural Equation ◽  
Negative Influence ◽  
Equation Modeling ◽  
Moderator Variable ◽  
Performance Expectancy ◽  
Digital Era ◽  
Effort Expectancy ◽  
Facilitating Conditions

The current era is called the information age, where humans really need information. The existence of the internet on smartphones makes it easier for humans to get information and enjoy content wherever and whenever. One of the content services in Indonesia is the MNC Group's RCTI + application. Although RCTI + is a new company, RCTI + has an active number of users of 302,569 until November 2019. RCTI + has a fairly high market share because the digital era is growing rapidly. This study measures the interest of users of RCTI + applications in Indonesia by using a modified UTAUT2 research model, where researchers analyze the variables Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, Habit, and Content on Behavioral Intention. The data used in this study were 89 valid respondents obtained online using a questionnaire. Respondents are users of the RCTI + application. Researchers used Structural Equation Modeling (SEM) with SmartPLS software version 3.0 to test hypotheses. The results showed that Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Habit and Content had an influence on Behavioral Intention. However, Hedonic Motivations has a negative influence on Behavioral Intention. The Age variable as a moderator variable influences Content on Behavioral Intention, while Gender has no effect. This study resulted in an R2 of 0,900 and included in the moderate category. This research, has found that the variable that most influences Behavioral Intention is Habit.

Citizens' E-Government Services Adoption

2014 ◽  
Vol 1 (2) ◽  
pp. 80-96 ◽  
Author(s):  
Wadie Nasri
Keyword(s):  
Structural Equation ◽  
Policy Decision ◽  
Equation Modeling ◽  
Government Services ◽  
Performance Expectancy ◽  
Use Of Technology ◽  
Modeling Analysis ◽  
Proposed Model ◽  
Effort Expectancy ◽  
And Performance

This study investigates the factors that influencing citizens' intention to use e-government services and its causal relationships using the Unified Theory of Acceptance and Use of Technology model (UTAUT). Data relating to the constructs were collected from 150 respondents but only 85 responses were received and subjected to Structural Equation Modeling analysis (SEM). The proposed model fits the data well. The findings reveal that facilitating condition, social influence, attitude, effort expectancy and performance expectancy determine citizens' intention towards e-government services. Additionally, attitude is predicted jointly by effort expectancy and performance expectancy. This study would help government policy decision makers to increase the adoption of e-government services in Tunisia country.

The Moderating Effects of Gender on E-Commerce Systems Adoption Factors

2021 ◽  
pp. 319-340
Author(s):  
Frederick Pobee ◽  
Daniel Opoku
Keyword(s):  
Behavioral Intention ◽  
Structural Equation ◽  
Equation Modeling ◽  
Moderating Effects ◽  
Performance Expectancy ◽  
Adoption Factors ◽  
Use Of Technology ◽  
Effort Expectancy ◽  
Actual Use ◽  
Facilitating Conditions

The purpose of this article was to investigate the moderating effects of gender on e-commerce systems adoption factors among university lecturers in Ghana. In order to achieve this purpose, the unified theory of acceptance and use of technology (UTAUT) was used as the theoretical lens for the study. Eight hypotheses were developed and tested. Data analysis was performed with a structural equation modeling (SEM) technique using SmartPLS Application. Using a survey of 223 respondents, the study showed that factors such as performance expectancy, effort expectancy, and facilitating conditions positively and significantly influenced Ghanaian lecturers' behavioral intention and ultimately the actual use of e-commerce systems. As for the moderating effects of gender, this study discovered that gender insignificantly moderated the effects of performance expectancy, effort expectancy and social influence on behavioral intention.

scholarly journals Exploring the Determinants of Students' Satisfaction and Continuance Intention Using Online Learning in Jordan

2021 ◽  
pp. 28-41
Author(s):  
Hadeel Mahmoud Jebril
Keyword(s):  
Online Learning ◽  
Structural Equation ◽  
Equation Modeling ◽  
System Quality ◽  
Continuance Intention ◽  
School Students ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Students Satisfaction

This research investigates factors affecting online learning satisfaction and continuance intention by Jordan school students. To this end, an integrated model of Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and Information System Success (ISS) model has been used. A questionnaire was handed out to students from five Jordanian schools to collect data from 346 students, and the Structural Equation Modeling (SEM) technique was utilized to evaluate the proposed model. The findings indicated that the students' satisfaction is directly influenced by performance expectancy, effort expectancy, facilitating conditions, system quality. Besides, the empirical results showed that the continuance intention is directly influenced by students' satisfaction, performance expectancy, habit, effort expectancy, hedonic motivation, and facilitating conditions. The findings of this study will serve as a valuable resource for educational institutions, decision-makers, developers, and academics looking to enhance online learning systems by identifying the most important factors influencing students' satisfaction and continuance intention.

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