Development of System Continuance Models for Assessing among

Local E-Government in Indonesia

Dody Herdiana

, Dwi Yuniarto

, Esa Firmansyah

, Mulya Suryadi

, A’ang Subiyakto

, and Aedah

Binti Abd. Rahman

STMIK Sumedang, Jl. Angkrek Situ No.19, Sumedang, West Java, 45323, Indonesia

Syarif Hidayatullah State Islamic University Jakarta, Jl. Juanda, No. 95, Tangerang Selatan, Banten, 15412, Indonesia

Asia e University, Wisma Subang Jaya No. 106, Jalan SS15/4 47500 Subang Jaya, Selangor Darul Ehsan, Malaysia

Keywords: Model development, system continuance, acceptance and use, expectation-confirmation model, successful

model, local e-government.

Abstract: This study reports how to combine technology acceptance and use models based on expectations and

confirmations in the information system success model to objectively assess the continuance of local e-

government based on the organizational perspective and perspective of users in Indonesia. The developed

model is arranged in 11 variables and 48 indicators. Pathways of influence between variables are presented

by 16 links. However, this study does have some limitations. With regard to the level of use, there is no

fully mandatory use of the system, and not all UTAUT2 variables and the possibility of a moderator are

integrated with the model. Other studies used various assumptions, methods, and different understandings

can present different propositions. In addition, limitations can help to further study, especially the validity of

the proposed model. Future research can explore additional expansion variables and moderators, so that in

the new model between variables can be made more explicit relationships.

1 INTRODUCTION

The policy on the use of communication and

information technology (ITC) in government

processes (e-government) has encouraged in

improving the efficiency, effectiveness, transparency

and accountability of government administration

(Indonesia, 2003; Sá, Rocha and Cota, 2016; Waller

and Genius, 2015). E-government can increase the

delivery of government services effectively and

efficiently through ICT (Claver-Cortes, de Juana-

Espinosa and Valdés-Conca, 2018; Waller and

Genius, 2015; Yang and Rho, 2007), promote public

administration (United Nations, 2014), and allow

adjustments between the characteristics of public

services and specificities in local communities (Sá,

Rocha and Cota, 2016). Most developed countries

benefit from e-government services (Lee, Tan and

Trimi, 2005; Norris and Reddick, 2013; Roy, 2002),

but there is still plenty of room for global

improvement (United Nations, 2010; United

Nations, 2016). On the other hand, most researchers

are currently looking at the low level of

implementation of e-government services in

developing countries (Choi et al., 2016; Dada,

2006).

The study of the success of e-government

implementation leads to the success of IS

applications (Rana et al., 2015). However, studies

focus more on the supply side (organizational

perspective) and ignore the demand side (user

perspective). The local IS success indicator is a

continuation of the IS initiative (Baker-Eveleth and

Stone, 2015), even if in a customized form (Sá,

Rocha and Cota, 2016). In the context of this

research, the IS initiative is after the initial

implementation of e-government at the central and

regional governments (Altameem, Zairi and

Alshawi, 2006; Sá, Rocha and Pérez Cota, 2016).

The purpose of this study is to fill this gap by

proposing a conceptual model. This research

broadens knowledge and continues this tradition in

relation to the relationship of factors that influence

users to accept and use (Thomas, 2006; Venkatesh

and Davis, 2000; Venkatesh et al., 2003; Venkatesh,

Thong and Xu, 2012a) based on confirmation

(Bhattacherjee, 2001; Zolotov et al., 2018) and uses

3114

Herdiana, D., Yuniarto, D., Firmansyah, E., Suryadi, M., Subiyakto, A. and Binti Abd. Rahman, A.

Development of System Continuance Models for Assessing among Local E-Government in Indonesia.

DOI: 10.5220/0009948231143123

In Proceedings of the 1st International Conference on Recent Innovations (ICRI 2018), pages 3114-3123

ISBN: 978-989-758-458-9

(Baker-Eveleth and Stone, 2015) of IS success

(DeLone and McLean, 1992; Delone and McLean,

2003). The aim is to develop a more comprehensive

model for measuring the continuation of e-

government in Local Government, by adopting,

combining, and adapting (Subiyakto, 2017;

Subiyakto and Ahlan, 2014) acceptance and use of

technology (Venkatesh, Thong and Xu, 2012b),

expectation-confirmation (Bhattacherjee, 2001), and

success IS model (Delone and McLean, 2003).

Following the research program mentioned above,

two research questions were then proposed to guide

the implementation of this exploratory research.

RQ-1. How to understand the relationship

between the constructs of the

technology acceptance and use model,

the expectation-confirmation model, and

the IS success model?

RQ-2. How to combine technology acceptance

and use models and confirmation-

expectation models in IS success

models in the continuance of e-

government systems in Regional

Government?

This paper is presented in five parts. Each

section describes the research program from

research, literature review, research method, result

and discussion, and conclusions.

2 LITERATURE REVIEW

Local e-government services can be considered as an

extension of central e-government services, but have

a number of specificities that need to be emphasized

(Holgersson et al., 2017; Sá, Rocha and Cota, 2016).

In the context of research, a successful indicator of

local e-government is a continuance of e-

government initiatives, even if in an adapted form,

after the initial implementation of e-government at

the central and local governments. In this way,

researchers gather views on the determinants of

success that are not biased by one point of view

(Altameem, Zairi and Alshawi, 2006). The

successful implementation of e-government in the

long run (Baker-Eveleth and Stone, 2015) depends

on the willingness of citizens and the government to

adopt (Rana, Dwivedi and Williams, 2015; Wirtz

and Daiser, 2016). In addition, the successful

implementation of e-government is measured not

only in the perceived quality of information systems

but also in implicit comparisons with prior

expectations (Baker-Eveleth and Stone, 2015;

Bhattacherjee, 2001; Zolotov et al., 2018).

Although, the success model of DeLone and

McLean IS (DeLone and McLean, 1992; Delone and

McLean, 2003) is primarily used to assess the

success of IS as mentioned in many studies. (Briggs

et al., 2003; DeLone and McLean, 1992; Nguyen,

Nguyen and Cao, 2015; Rana et al., 2015; Subiyakto

et al., 2016a; Subiyakto et al., 2016b; Subiyakto et

al., 2016c; Subiyakto et al., 2015a; Subiyakto et al.,

2015b; Subiyakto et al., 2017). However, this model

cannot support the relationship between system

quality and perceived benefits (Nguyen, Nguyen and

Cao, 2015; S., Olfman and Ryan, 2005). This model

has not been able to evaluate factors related to e-

government that influence users to receive and use

(Thomas, 2006) e-government in the long run

(Baker-Eveleth and Stone, 2015). In addition, this

model has not been able to measure citizen

satisfaction based on confirmation and perceived

usefulness (Bhattacherjee, 2001).

The DeLone and McLean IS success model

(Delone and McLean, 2003) is very good for

assessing the success of the system based on

information quality (INQ), system quality (SYQ)

and IS quality of service (SVQ) that affect user

satisfaction (USF) and net benefits (NBF) from use

of IS (Yousef). Meanwhile, the Unified Theory of

Acceptance and Use of Technology (UTAUT) is a

theoretical framework that is widely used to

understand the adoption of users or the continuous

use of new technologies (Venkatesh et al., 2003).

This model was developed with four constructs from

the acceptance and use of technology to assess

society: performance expectations (PE), effort

expectations (EE), social influence (SI), and

facilitation conditions (FC). The UTAUT model is

then extended to Model Extended UTAUT

(UTAUT2) by adding three additional constructs:

hedonic motivation (HM), price value (PV), and

habit (HB) (Venkatesh, Thong and Xu, 2012a). The

UTAUT2 does not focus more on the organizational

context but emphasizes the context of consumer use,

this is different from the previous technology

acceptance model (Yuan et al., 2015).

The UTAUT2 model (Venkatesh, Thong and Xu,

2012a) is proposed to gain a better understanding of

technology acceptance. However, the UTAUT2

acceptance model (Venkatesh, Thong and Xu,

2012b) can only be used to evaluate user acceptance

of SI (Thomas, 2006). Whereas to analyze citizen

satisfaction as a result of confirmation (CF) of the

previous use (Yousef) of ICT and perceived

usefulness, it is proposed to use the Expectation-

Development of System Continuance Models for Assessing among Local E-Government in Indonesia

3115

Confirmation Model (ECM) (Bhattacherjee, 2001).

In our case, The ultimate goal of the ECM model is

to explain the continuance of the e-government

system (SYC) in the Regional Government.

On the other hand, e-government has become a

major topic of interest for academics and

practitioners (Almarabeh and AbuAli, 2010; Gil-

García and Pardo, 2005; Rana, Dwivedi and

Williams, 2015; Wirtz and Daiser, 2016). Although

local e-government services can be considered as an

extension of central e-government services, the first

has a number of specificities that need to be

emphasized (Holgersson et al., 2017; Sá, Rocha and

Cota, 2016). To date, it cannot identify of

continuance e-government evaluation models that

are specifically focused on local e-Government in

the Regional Government, and this justifies the

development of a new model whose purpose is to

create a model with this specificity (Sá, Rocha and

Cota, 2016; Sá, Rocha and Pérez Cota, 2016).

3 RESEARCH METHOD

Development of a more comprehensive model to

measure the success IS in the continuance of e-

government in this Regional Government (see Fig.

2), based on literature review (S1), then the

development of models (S2) with model

development steps (Subiyakto, 2017; Subiyakto and

Ahlan, 2014), namely developing a set of

assumptions (S2.1), adoption (S2.2), combining

(S2.3), and adapting (S2.4) from acceptance and use

of technology (Venkatesh, Thong and Xu, 2012b),

expectation-confirmation (Bhattacherjee, 2001), and

success IS model (Delone and McLean, 2003).

Picture. 1 shows the sequential stages of the

development model and its revision.

Table 1: List of the basic models and theories

List of the Basic Models and

Theories

References

The updated DeLone and

McLean IS success model

(Delone and

McLean,

2003)

The extended the UTAUT

model (UTAUT2)

(Venkatesh,

Thong and Xu,

2012a)

The expectation-confirmation

model (ECM)

(Bhattacherjee,

2001)

The IS project success model

(Subiyakto and

Ahlan, 2014)

Following the set of assumptions developed

(S2.1) in the study, this new model (see Figure 2),

based on (S2.2) previous works (Bhattacherjee,

2001; Delone and McLean, 2003; Venkatesh, Thong

and Xu, 2012a) is conceptualized (S2.3 and S2.4).

Table 1 represents the basic theory of model

development.

Furthermore, the operationalization phase (S3) is

carried out to be broken down into the level of

research data collection instruments (Subiyakto,

2018; Subiyakto et al., 2015c). Finally, the reporting

phase (S4) is conducted to propose the model

developed, in terms of conducting research.

Figure 1: The proposed research model.

4 RESULT AND DISCUSSION

The main objective of this research is to develop a

more comprehensive model to measure the

continuance of e-government in the regional

government. This new model developed refers to a

set of assumptions. First, the continuation of e-

government initiatives is an indicator of the success

of local e-government. Delone and McLean (2003

stated the continuous use system (SYC) became a

popular measure of success (Igbaria et al., 1997;

Larsen and Wetherbe, 1999; Taylor and Todd, 1995;

Teng and Calhoun, 1996). Second, the successful

implementation of e-government in the long run

(Baker-Eveleth and Stone, 2015) depends on the

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3116

willingness of citizens and the government to adopt

(Rana, Dwivedi and Williams, 2015; Wirtz and

Daiser, 2016); and (iii) the successful

implementation of e-government is measured not

only in the perceived quality of information systems,

but also in implicit comparisons with prior

expectations (Baker-Eveleth and Stone, 2015;

Bhattacherjee, 2001; Zolotov et al., 2018).

Figure 2: The proposed research model.

Referring to previous research (Altameem, Zairi

and Alshawi, 2006; Baker-Eveleth and Stone, 2015;

Bhattacherjee, 2001; Delone and McLean, 2003;

Rana, Dwivedi and Williams, 2015; Subiyakto,

2017; Thomas, 2006; Venkatesh, Thong and Xu,

2012a; Wirtz and Daiser, 2016; Zolotov et al.,

2018), the constructs of acceptance and use of

technology, expectation-confirmation, and IS

success was then adopted, combined and adapted by

researchers in the development of models to assess

factors that influence the user to receive and use

based on confirmation and success to the

continuance of e-government in the Regional

Government. Furthermore, the model development

dimensions which include SYQ, SVQ, INQ, PE, EE,

SI, FC, CF, USE, USF, and SYC are used to develop

16 hypotheses, as explained in the next paragraph.

Then each relationship will be tested in the

implementation of the research through a research

instrument developed (Table 4).

First, to meet the needs given the totality of

features and characteristics of a product or service

that bears its ability to become a reference for

quality (Thomas, 2006). Quality can also be

measured by a variety of perspectives (Guimaraes

and Igbaria, 1997). Delone and McLean (2003

assume that quality is divided into three dimensions:

information quality (INQ), system quality (SYQ),

and service quality (SVQ). When individuals feel

the quality produced by the system, this may affect

their perception of usability (Yousef) of the system.

Therefore, the higher the level of system quality, the

system will be more useful and easy to use (H1, H2,

H3, H4, and H5).

Table 2: List of the variables (Bhattacherjee, 2001; Delone

and McLean, 2003; Venkatesh, Thong and Xu, 2012a).

Variable Definition

SYQ

Level to describe the quality of the

content of the system.

SVQ

Level to assess how good the quality

of service is for users.

INQ

The degree to which the information

produced consistently meets user

requirements and expectations.

The extent to which users believe that

organizational and technical

infrastructure exists to support system

use.

The extent to which users feel that

other important people believe they

must use a new system.

The level of ease associated with the

use of the system.

The rate at which users believe that

using the system will help them

benefit in performance.

The level of user confirmation is

positive for system usage satisfaction.

USE

Level of system utilization by

individuals, groups, or organizations.

USF

The level of satisfaction with the

initial system usage is positively

related to the continuation of their

system.

SYC

The degree of the continuance of the

initiative of the system

Second, the four core constructs identified by

Venkatesh et al. (2003 in UTAUT2 (Venkatesh,

Thong and Xu, 2012b), remain the core construct

used in this research model. PE, EE, SI, and FC are

expected to positively and directly influence the

mandatory USE system (H6, H8, H10, and H11).

USE is expected to fully mediate the effect of the

model positively for USF (H14). Petter et al.,

(Petter, DeLone and McLean, 2008) treats "intention

to use" and "use" in avoiding the complexity of the

model as a single variable, namely "system use". In

addition, they argue that the intention to use is only

appropriate for the level of individual analysis, while

the use of the system can be measured both at the

individual and organizational level. In addition, the

researcher explored the moderator (age, gender,

experience) of UTAUT2 (Venkatesh, Thong and Xu,

2012a) in this model and found no statistically

significant moderating effects (Tamilmani, Rana and

Dwivedi, 2017; Yuan et al., 2015). Therefore, this

Development of System Continuance Models for Assessing among Local E-Government in Indonesia

3117

potential moderating variable is not included in our

model (see Figure 2).

Table 3: List of the indicators.

Indicator Definition

Ease of

Use

(SYQ1)

The degree of system freedom from

constraints, difficulties, and

problems during use.

Maintaina

bility

(SYQ2)

The degree associated with the ease

of SI in its study.

Response

Time

(SYQ3)

The degree associated with the

amount of time needed to respond

to commands from that user.

Functional

ity

(SYQ4)

The degree associated with the

system can be operated according to

the requirements that have been

planned.

Safety

(SYQ5)

The degree of the immune of the

system from unexpected attacks,

dangers, or damage.

Responsiv

eness

(SVQ1)

The degree of the system's reaction

to serve its users in a suitable way,

time and situation.

Flexibilty

(SVQ2)

The degree of the system adaptation

to serve its users in accordance with

the requested requirements.

Security

(SVQ3)

The degree of security of an

integrated system to serve users

safely from attacks, dangers, or

unexpected damage.

Functional

ity

(SVQ4)

The degree associated with system

service coverage corresponds to

functional requirements.

Extension

(SVQ5)

The degree associated with

additional system service coverage

that exceeds functional

requirements.

Accuracy

(INQ1)

The degree of feasibility of the

information produced.

Timelines

s (INQ2)

The degree of precision of the

system information processing

process at the planned time

duration.

Complete

ness

(INQ3)

The degree of information generated

by the system is complete or

without missing parts.

Consisten

cy (INQ4)

The tendency of the system to still

demonstrate the same information

in operations, services,

maintenance, or quality.

Relevance

(INQ5)

Linkage level of information

produced by the system with the

subject matter.

Perceived

usefulness

(PE1)

The extent to which a person

believes in using a particular system

will improve his work performance.

Table 3: List of the indicators (continued).

Indicator Definition

Extrinsic

motivation

(PE2)

The perception that users want to

do an activity is considered an

important role in achieving

valuable results that are different

from the activity itself.

Job-fit

(PE3)

How does the ability of a system

to improve individual work

performance.

Relative

advantage

(PE4)

The extent to which innovation is

considered better than its

predecessor.

Outcome

Expectations

(PE5)

The extent to which the quality of

community understanding and

ability must be achieved.

Perceived

Ease of Use

(EE1)

The extent to which the user's

perspective expects that using this

system is free from effort.

Complexity

(EE2)

The extent to which a system is

perceived is relatively difficult to

understand and use.

Subjective

norm (SI1)

A person's perception that most

people who are important to him

think he should or should not do

the intended behavior.

Social

factors (SI2)

Individual internalization of the

subjective culture of reference

groups and specific interpersonal

agreements that individuals have

done with others, in certain social

situations.

Image (SI3)

The extent to which the use of an

innovation enhances the image or

status of a person in one's social

system.

Perceiver

behavioral

control

(FC1)

Reflecting perceptions of

constraints on behavior and

including self-efficacy, resource

facilitation conditions, and

technological facilitation

conditions.

Facilitating

conditions

(FC2)

Objective factors in the

environment that the observer

enters into action are easy to do.

Services

provided

(CF3)

The degree of service provided by

the system is better than expected.

Experience

using (CF1)

The degree of experience using

the system is better than expected.

Innovation

perceived

(CF2)

The degree of innovation

perceived is better than expected.

Services

provided

(CF3)

The degree of service provided by

the system is better than expected.

Services

required

(CF4)

The degree of service required of

the system is better than expected.

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Overall,

using

confirmed

(CF5)

Overall, most use information

systems.

Table 3: List of the indicators (continued).

Indicator Definition

The

frequency of

use (USE1)

Levels related to the amount of

time used by the system.

The intensity

of use

(USE2)

Levels related to the amount of

time used by the system.

The extent of

use (USE3)

The level associated with the

scope of use of the system is

based on use or not using basic

and advanced system

capabilities.

Thoroughness

of use

(USE4)

The level associated with the

accuracy of use.

Appropriate

use (USE5)

The level associated with proper

use.

Efficiency

(USF1)

The level of user satisfaction

with the system is based on the

system to produce output with

the resources needed to achieve

output.

Effectivity

(USF2)

System user satisfaction level

based on the ability of the

system to meet user needs.

Flexibility

(USF3)

The system user level is related

to the adaptability of the system

according to the requested

requirements.

Adequately

(USF4)

The level of system user

satisfaction associated with

adequate system quality.

Overall

Satisfaction

(USF5)

The level of user satisfaction

with the system is related to the

adequacy of all aspects of the

system.

Continuity of

usability

(SYC1)

The degree of Continuance of

usability of the system.

Continuance

of services

provided

(SYC2)

The degree of continuance to

provide services.

Continuation

of usage

(SYC3)

The degree of continuance uses

the system.

System

continuation

(SYC4)

The degree of system

continuance.

Promote of

service

(SYC5)

The degree of promote of

service.

Third, the perception of ease of use (EE1) is

similar to business expectations (EE) (Chan et al.,

2010). Venkatesh et al. (2003 that for measurements

for attitudes already included in EE and PE, in

mandatory settings, attitudes should not be included

in the model. Chan et al., (Chan et al., 2010) state

that PE and EE are one of the important variables to

evaluate a system in a mandatory environment. Both

variables play a role to "encourage a positive attitude

towards and satisfaction of users with the use of the

system by increasing efficiency and minimizing

efforts in using technology (H7 and H9) (Petter,

DeLone and McLean, 2008)."

Finally, confirmation also has a significant effect

on perceived usefulness, can be seen by users who

can also be adjusted to the level of confirmation.

Confirmation (CF) is a new construction in research

on IS usage. Satisfaction (USF) with use (Yousef) IS

is predicted by confirmation (CF) of system use and

both by use (H12 and H13) (Bhattacherjee, 2001).

This construct conceptualization and validating its

effects on the continuation of the system (H15 and

H16) are two solutions to this study.

In short, it can be clearly seen that the

description of the development of the system

continuation model can explain the research

questions mentioned above and can prove the

possibility of developing new models by adopting,

combining, and adapting acceptance and use of the

technology (Venkatesh, Thong and Xu, 2012a),

expectation-confirmation (Bhattacherjee, 2001), and

success IS model (Delone and McLean, 2003).

Furthermore, the definition of each variable, the

indicators are broken down and the statements from

the questionnaire can be seen in Table 2, Table 3,

and Table 4 respectively.

This study contributes to the theoretical

development of the literature about the success of

existing information systems with the stages of

development from the acceptance and use of

technology, and the expectation in interpreting and

predicting the continuation of e-government systems

in the Regional Government. Second, this study

explores the continued use and satisfaction in the

continuance of information systems, thus

highlighting the important role of use and

satisfaction in the continuation of information

systems. In addition, the transparency of the model

development process and the credibility of the basic

model and the theory used can also be considered as

a model trust point.

This study does have some limitations. With

regard to usage rates, Lassila and Brancheau (Lassila

and Brancheau, 1999) identify various countries

Development of System Continuance Models for Assessing among Local E-Government in Indonesia

3119

using the system based on use or not using basic and

advanced system capabilities. Secondly, there is no

mandatory use of the system entirely. At certain

organizational levels, management has chosen to

implement the system and requires employees to use

it. Thus, while the use of a system can be mandatory

at one level, the adoption and use of the system itself

may be entirely voluntary, based on management

judgment, at a higher level. Management always has

the option to stop the system that does not provide

the desired results and benefits (Delone and

McLean, 2003).

Table 4: List of the questionnaire statements.

Statements of the questionnaires

SYQ1 - The system is easy to use.

SYQ2 - Easy maintenance system.

SYQ3 - The system is able to respond quickly

following the instructions given.

SYQ4 - The system is able to perform all the

functions required in its development.

SYQ5 - The system is safe in its use.

SVQ1 - System to provide services quickly.

SVQ2 - The system provides flexible services

according to user conditions.

SVQ3 - The system provides safe services.

SVQ4 - The system provides services that meet

the requirements in its development.

SVQ5 - The system provides services more than

the required functions.

INQ1 - The system produces information

accurately.

INQ2 - The system produces information in a

timely manner.

INQ3 - The system produces complete

information.

INQ4 - The system produces information

consistently throughout its operations.

INQ5 - The system produces information

according to the needs of its users.

PE1 - Using the system will improve my work

performance.

PE2 - Using the system in my work will increase

my productivity.

PE3 - The use of the system can increase the

effectiveness of the implementation of work

tasks.

PE4 - Using the system makes it easier to do my

work.

PE5 - Using the system can improve the quality

of community understanding and ability as a

result to be achieved.

EE1 - It will be easy for me to be skilled in using

the system.

EE2 - Working with a system is very

complicated, it is difficult to understand what is

happening.

SI1 - According to someone who is important to

me I have to use the system.

SI2 - In general, organizations have supported

the use of the system.

SI3 - People in my organization who use the

system have more prestige than those who don't.

FC1 - Users have the knowledge needed to use

the system.

FC2 - Someone (or group) provides assistance

for system difficulties.

FC3 - Using this system is compatible with all

aspects of the user's work.

Table 4: List of the questionnaire statements (continued).

Statements of the questionnaires

CF1 - My experience with using system was

better than what I expected.

CF2 - The system can meet gain performance in

excess of what required for the service.

CF3 - The service level provided by the system

was better than what I expected.

CF4 - The system can meet demands in excess of

what I required for the service.

CF5 - Overall, most of my expectations from

using system were confirmed.

USE1 - How often do users use this system.

USE2 - How much time does the user spend with

the system during normal days when the user

uses the computer.

USE3 - How much time does the user spend with

the system during normal days when the user

uses the computer to meet further needs.

USE4 - How accuracy of use of the system in

meet services needed.

USE5 - How appropriate of use of the system in

meet services needed.

USF1 - Users are satisfied with the level of

system efficiency.

USF2 - Users are satisfied with the level of

system effectiveness.

USF3 - Users are satisfied with the level of

system flexibility.

USF4 - Users are satisfied with the level of

system adequately.

USF5 - Users are satisfied with system

performance.

SYC1 - This system is always useful.

SYC2 - Users feel that they are not burdened

with the use of the system.

SYC3 - Users continue to use this system in the

future.

SYC4 - Users strongly advise others to keep

using the system.

SYC5 - Promote the system to the wider

community as a form of service.

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Finally, we do not integrate the variables of

hedonic motivation, price values, habits and possible

moderators into the original UTAUT2 (Venkatesh,

Thong and Xu, 2012a). Future research can explore

additional expansion variables and moderators, so

that the relationship between variables in the new

model can be made more explicit.

5 CONCLUSIONS

E-government has become a major topic of interest

for academics and practitioners. The study of the

success of e-government implementation is part of

the success study of the IS application. This research

continues this tradition and broadens knowledge

regarding the relationship of factors that influence

users to accept and use based on confirmation and

usefulness to IS success by adopting, combining,

and adopting acceptance and use of technology,

expectations, and IS success models, in the matter of

assessing the continuation of e-government in the

Regional Government. Factors that influence users

to receive and use e-government in the long run are

used by the author as an assumption of model

development. The model uses 11 variables, 48

indicators with 16 paths of influence between

variables. Researchers have also proposed 48

questions for the development of the next

questionnaire. In addition to this exploratory study

can contribute to the theoretical development of the

success of the existing information system literature

by adopting, combining, and adapting the

acceptance and use of technology, and expectations

in interpreting and predicting the continuity of the e-

government in the Regional Government, the

process the development of the proposed model and

its data collection instruments can be a practical

consideration for further studies. In addition, the

transparency of the model development process and

the credibility of the basic model and the theory used

can also be considered as a model trust point.

Despite the fact that this study does have some

limitations. With regard to the level of use, there is

no fully mandatory use of the system, and not all

UTAUT2 variables and the possibility of a

moderator are integrated into the model. Other

studies used various assumptions, methods and

different understandings can present different

propositions. In addition, limitations can help to

further study, especially the validity of the proposed

model. Future research can explore additional

expansion variables and moderators, so that the

relationship between variables in the new model can

be made more explicit.

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