E-Government Utilization

Carter, Lemuria; Schaupp, Ludwig Christian; Hobbs, Jeffrey; Campbell, Ronald Ian

doi:10.4018/jegr.2012010105

Cited by 38 publications

(11 citation statements)

References 37 publications

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“…On most occasions when the word "reputation" (or the term "perceived reputation") is used, it is not defined and, therefore, it is not possible to state with confidence that the same issues of concern 55 are under consideration. There are some exceptions, for example Carter, Schaupp, Hobbs, and Campbell (2012), but even in this article reputation is only fleetingly discussed and is measured by just three variables (which are not identified). The lack of definitional 60 clarity may derive in part from the fact that reputation is a multidimensional concept and as a result can be difficult to bind precisely.…”

mentioning

confidence: 88%

“…Several scholars have either looked at this directly or considered the reputation of public sector bodies as part of a larger question (e.g. 425 Andreassen, 1994;Carmeli & Cohen, 2001;Carter et al, 2012;Luoma-Aho, 2008;Waeraas et al, 2015;Waeraas & Byrkjeflot, 2012). Andreassen (1994), for example, examines the attitude of the business community to local governments in Norway and shows that reputation is correlated with satisfaction and loyalty in the sense of the willingness of firms to remain in a local authority area.…”

Section: Reputationmentioning

confidence: 99%

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e-Government, Transparency & Reputation: An Empirical Study of Spanish Local Government

López-López

Antelo

Vázquez-Sanmartín

et al. 2018

Information Systems Management

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This paper examines the interrelationship between e-government, transparency, and reputation in Spanish local government. It postulates the existence of a three-way relationship, namely, that the degree of transparency in a local authority influences the reputation of that authority and that both transparency and reputation are influenced by the level of e-government service provided. The research is based on a study of 78 Spanish municipalities. The results are presented as a model. KEYWORDS e-Government; transparency; reputation; local government 65 have a reputation for integrity/lack of corruption while also being regarded as inefficient or bureaucratic. Notwithstanding this, some aspects of reputation have been extensively researched. Examples of these include trust (Connolly & Bannister, 2007; Jøsang,

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mentioning

confidence: 88%

Section: Reputationmentioning

confidence: 99%

e-Government, Transparency & Reputation: An Empirical Study of Spanish Local Government

López-López

Antelo

Vázquez-Sanmartín

et al. 2018

Information Systems Management

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“…EE has a negative impact on BI, indicating that respondents believe navigating My PhilHealth Portal is complicated. However, SI and FCs do not appear to be predictors of BI, implying those notions of prominent studies (Taylor and Todd,1995b;Chiu et al 2010;Lee and Lin 2008;Alraja, 2016;Carter et al, 2012), including the UTAUT model (Venkatesh et. al., 2003), appear to be different in the context of this study.…”

Section: Implications To Theorymentioning

confidence: 80%

Citizens’ Adoption of an E-Health System During the Pandemic

Mina,

Batara,

Hussien

et al. 2023

Internationally known as Journal of Government and Politics

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This study aimed to determine the factors influencing the behavioral intention of PhilHealth members to adopt My PhilHealth Portal using an extended unified theory of acceptance and use of technology (UTAUT). Variables from this theory were operationalized through indicators which were then translated into a self-reported online survey questionnaire distributed through email and Facebook. Purposive-homogeneous sampling was used to determine the sample size from the target population who are Cagayan de Oro City based PhilHealth formal economy members employed in either private or public sector. The data from the online survey was tested for reliability using IBM SPSS Statistics (version 20), and the Cronbach’s alpha (1951) coefficient was used to assess the validity of variables. To determine the causal relationship of variables on specific constructs, data were processed using licensed versions of IBM SPSS AMOS (version 26) to perform Structural Equation Modelling, which will further show the account for a specific impact of the constructs and moderating variables to behavioral intention. It is cross-sectional in nature and conducted within a short period of time. Citizens’ perceptions towards the adoption of My PhilHealth Portal can change over time as new knowledge and experiences will be accumulated. Therefore, future studies could employ a longitudinal design to obtain more accurate findings that are relevant to the general public’s adoption of government portals. Findings show that citizens’ behavioral intention to adopt My PhilHealth Portal is influenced by their trust on internet, trust on government, effort expectancy, and their perceived competence. However, the selected moderating variables appear to have no significant effect on TOI, TOG, EE, and PC to BI.

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“…It has also been found that SI constructs contain the explicit or implicit notion that people behave influenced by the way they believe others will perceive them as a result of using technology (Venkatesh et al, 2003). Previous e-government literature has investigated SI as a significant predictor of BI for use (Carter et al, 2012;Susanto & Aljoza, 2015). This study observes the effect of perceived usefulness, perceived ease of use, facilitating conditions, and social influence on the behavioral intention of the public of Semarang in utilizing SIKER.…”

Section: Introductionmentioning

confidence: 87%

“…In addition, the relationship between FC and BI in e-government adoption research has been explored in several studies. For example, Carter et al (2012) found that FC has a significant impact on an individual's intention to use the system. Social Influence (SI) is the degree to which an individual perceives that others who are important to them believe they should use the system (Venkatesh et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Factors Influencing Community Behavior towards SIKER: An Extension of the TAM model

Majid

Abidin

2023

J. Adv. Inf. Syst. Tech

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Sistem Kerja (SIKER) is a system that allows the public to make yellow cards/AK1, join job training, look for job vacancies and invite for interviews. In its application, not many public of Semarang city have adopted SIKER even though the city of Semarang is ranked 2nd in the excellent category in Central Java province in the e-government rankings. This study will observe the effect of perceived usefulness, perceived ease of use, facilitating conditions, and social influence on the behavioral intention of the public of Semarang city in utilizing SIKER, and the variables age and perceived trust will be used as intervening variables. This study uses a quantitative descriptive method with a data analysis approach using Partial Least Square Structural Equation Modeling (PLS-SEM) by utilizing SmartPLS version 3.2.9 tools. A number of 330 valid respondents participated in this current study. The results of this study show that the factors that influence the behavioral intention of the public of Semarang are perceived trust, perceived usefulness, facilitating conditions, and age with a negative direction. Perceived trust is proven to be the biggest factor influencing the behavioral intention to use SIKER services. Whereas the intervening effect of perceived trust is proven to intervene with perceived ease of use and perceived usefulness towards behavioral intention with the intervening effects of full mediation and partial mediation. However, for age, it is proven not to intervene with no intervening effect and unmediated effect.

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E-Government Utilization

Cited by 38 publications

References 37 publications

e-Government, Transparency & Reputation: An Empirical Study of Spanish Local Government

e-Government, Transparency & Reputation: An Empirical Study of Spanish Local Government

Citizens’ Adoption of an E-Health System During the Pandemic

Factors Influencing Community Behavior towards SIKER: An Extension of the TAM model

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