Mobile-based Smart Regency Adoption with TOE framework: An empirical inquiry from Madura Island Districts

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2020 4th International Conference on Informatics and Computational Sciences (ICICoS)
Mobile-based Smart Regency Adoption with TOE
framework: An empirical inquiry from Madura
Island Districts
Busro Umam
Department of Informatics
Universitas
Islam Madura
Pamekasan, Indonesia
busro.umam@gmail.com
Aang Kisnu Darmawan
Department of Information System
Universitas
Islam Madura
Pamekasan, Indonesia
ak.darmawan@gmail.com
Anwari Anwari
Department of Information System
Universitas
Islam Madura
Pamekasan, Indonesia
anwari.uim@gmail.com
Iwan Santosa
Department of Informatics
Universitas Trunojoyo
Madura
Bangkalan, Indonesia
iansantosa@gmail.com
Miftahul Walid
Department of Informatics
Universitas
Islam Madura
Pamekasan, Indonesia
miftahwalid@gmail.com
Achmad Nizar Hidayanto
Faculty of
Computer Science
Universitas
Indonesia
Depok, Indonesia
nizar@cs.ui.ac.id
Abstract—Currently, nearly all countries try to combine
city government and a smart city idea. A few previous studies
have developed different ISS efficiency modeling techniques.
Many studies have previously analyzed the quality of service
and experience of smart - city applications. However, very few
studies have studied the Smart District model efficiency of the
organization, which is significantly different from a smart
city's general definition. The objective of this study is to verify
the level of service by using mobile devices in areas or districts.
The TOE frame is the model and methodology used to define
service adoption of the information system, which combines
aspects of technology, organization, and a supportive
environment. To collect data from a hundred ninety-two
stakeholders, the online survey method, which is the data
processing by AMOS 24.0 software. The findings of this
research confirm that there is a significant and constructive
impact on quality assessment of smart district services on the
dimensions adopted by the TOE Framework. This paper
explains the performance model of a smart, mobile-based
district information system. This study recommends that local
authorities and governments focus more on critical issues
affecting the quality of cellular services
Keywords—information system adoption, smart city, smart
regency, TOE framework, mobile-based
application
I. INTRODUCTION
Built Smart City is an integrated urban and ICT-focused
management system. The program can solve an increasingly
complex array of urban problems by effectively optimizing
community resources[1],[2],[3],[4] . Smart City promotes
human resources management, economic development,
prosperity, and social sustainability in urban life and growth.
[5]. Local governments use intelligent cities in different
cities around the world and in Indonesia, including Madura
Island[6], [7].
Assessing the efficiency of information systems in a
sustainable urban environment is an essential and crucial
element in the growth of smart cities. Some quality of service
studies in the creation of a bright area, such as Fasa et al. (
2017), quality assessments of the bus service in South
Tangerang[8], Arman et al. ( 2015) study of ISO 37120
smart city technology[9], Nasrallah and (2014) IEEE 802.11
Standard of Service Systems Communication Protocol in
Smart Cities[10], Quality management expertise for data
processing Floris et tous (2018) Smart government
services[11], Noskov et al. ( 2018) research on the quality of
service facts and definitions for web applications[12], Huang
et al. ( 2018) are working on optimizing IoT connectivity and
providing quality service for Smart City[13] Sustainable city
governance and quality of Rodriguez et al. (2019) Urban
Heritage Facilities[14].
Smart Sustainable City implementation has significant
problems, such as the lack of good architecture[15], A simple
framework rather than complicated urban problems and
needs[16], Brilliant conducted[17] , and a lack of awareness
and understanding of sustainable cities[18]. Intelligent urban
actors both should not be involved and cooperated[19] loss
of interaction with the society[20].
But, in many countries, there is a substantial difference in
economy, economy, livelihoods, policies, social and cultural
factors, economic aspects, laws, geographical conditions,
issues of working, solution and environmental
problems [21],[22],[23] . Moreover, the Smart District IT
evaluation is required for recent and specific studies, which
vary significantly from smart cities.
In the past, the fourth district, especially in Madura,
Pamekasan, and Sumenep, was ready to develop smart cities.
One project is designed to create the intelligent mobile
reconstruction. This framework offers an overview of the
central communities and stakeholders for smart regeneration
projects. Some previous studies have found critical genetic
aspects[7] and strategic urban planning[6].
The purpose of this research is to confirm service levels
using mobile devices in areas or districts. The TOE frame is
the paradigm and approach used to describe the IT system's
service acceptance that incorporates technical, operational,
and supportive aspects. This paper describes a smart, mobile
district information system's output model. This report
suggested that local authorities and government authorities
focus more on critical issues that affect the quality of cellular
services.
978-1-7281-9526-1/20/$31.0 0 ©2020 IEEE
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2020 4th International Conference on Informatics and Computational Sciences (ICICoS)
intelligent and sustainable environment. Sensors use IoT to
record, monitor, analyze, and retrieve information effectively
with large-scale sensor technology. The data obtained are
then interpreted and analyzed to make effective strategic
decisions. The public and services develop this knowledge. It
explains how trafficking, crime, waste management,
sanitation, water supply, libraries, energy development and
storage, education and health services, hospitals, and other
public installations are dealt with. Information management
Information infrastructure Information systems Information
systems[24] [25].
TABLE I. TOOLS OF VARIABLES AND INDICATOR S OF TOE FRAMEWORK[52]
No Dimensions Items measurement Symbols
1 Perceived Usefulness In my job , I would find the mobile smart regency application useful PU1 1 Perceived Usefulness
I use smartphone smart regency software to perform tasks faster PU2
1 Perceived Usefulness
My productivity increases with the use of mobile smart regency application PU3
1 Perceived Usefulness
I will increase my income if
I
use a mobile smart regency application. PU4
2 Concern about safety We believe that effective consumer privacy laws exist SC1 2 Concern about safety
We insist on effective legislation to fight cybercrime SC2
2 Concern about safety
Secure electronic transactions and secure mobile-based smart regency application
services are readily accessible and cheap
SC3
2 Concern about safety
The nature of regularly exchanged business data requires a secure communication
channel
SC4
3 Top Management
Support
Top management is prepared to perform the risk tasks involved in the adoption of
mobile smart regency
TMS1 3 Top Management
Support
Our top management will probably consider the implementatio n of mobile applications
for smart regency as strategic.
TMS2
3 Top Management
Support
The incorporation of mobile smart regency systems is a very effective way to achieve a
competitive advantage, according to our company's top management.
TMS3
3 Top Management
Support
Top executives in our business tend to advise employees that they need to put more of
their work online to fulfill potentia l consumer needs.
TMS4
3 Top Management
Support
Top executives also encourage their staff to track emerging Internet technology and
market practices.
TMS5
4 Readiness in
Organization
The financial resources of our organization are used to implement a mobile smart
regency.
OR1 4 Readiness in
Organization
Our company has the technical capabilities to introduce smart regency mobile
applications.
OR2
4 Readiness in
Organization
We've got fast Internet access. OR3
4 Readiness in
Organization
The majority of our workers have access to computers without limit. OR4
4 Readiness in
Organization
Many of our workers are informatician s OR5
5 The pressure of
Citizen Users
A large majority of our clients want us to implement smart regency mobile applications. CP1 5 The pressure of
Citizen Users Unless we had not applied mobile smart safety standards, our relationships with our
significant customers would have suffered.
CP2
5 The pressure of
Citizen Users
If we do not implement social trade initiatives, our customers may consider us to be
backward.
CP3
5 The pressure of
Citizen Users
Most of our clients expect us to have good social media relationship s with them. CP4
6 Pressure of
stakeholders
Most of our trade relations asked that the mobile smart regency application be
implemented.
TPP1 6 Pressure of
stakeholders
Many of our trading partners agree that the smartphone smart regency program should
be introduced.
TPP2
6 Pressure of
stakeholders
Commercial partners are generally well aware of smart regency application practices
based on mobile phones.
TPP3
6 Pressure of
stakeholders
Many of our suppliers and trading partners have already adopted practices in mobile-
based smart regency applications.
TPP4
6 Pressure of
stakeholders
Our stakeholders and suppliers usually establish the method of communication (e.g.,
faxes, emails, online forum, and social media collaboration, etc.).
TPP5
6 Pressure of
stakeholders
We rely on other companies that already use smart regency mobile applications. TPP6
7 Behavioral Intention In the future, I am going to use the desktop smart regency app. BI1 7 Behavioral Intention
I plan to use the upcoming smart regency mobile device. BI2
7 Behavioral Intention
In the future, I intend to use the smartphone smart regency. BI3
Improve Quality of
Life
Fig. 1. Garuda Smart City Framework[28]
[29]
[4]
II. LITERATURE REVIEW
A. Smart Cities Design
The smart city principle is to build civil authority using
an integrated, interconnected, and automated ICT models.
That city on the international stage is competing for an
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2020 4th International Conference on Informatics and Computational Sciences (ICICoS)
Through the IoT Network, connectivity, and accessibility
between ICT and physical infrastructure can be connected
with realistic and operational services linked to cities and
social communities[26]. Many key factors, including
technology, organization, governance, public policies,
economies, working conditions, and infrastructure, affect
smart cities' performance. Intelligent city management will
take into account six key aspects: open governance,
innovative technologies, intelligent living, intelligent people,
and intelligent movement[27]. One of the famous intelligent
cities in the smart city Garuda[28][29][4], Cohen's Boyd
Wheel[18][30][31][32] Smart City System of Telkom.
Efficient government, intelligent infrastructure, and a
balanced economy, intelligent citizens, intelligent
landscapes, and intelligent mobility are all main views and
acts of intelligent cities
B. Technological, Organization, and Environment (TOE-
Framework)
TOE framework is a comprehensive model in describing
the adoption of an information system application. Quite
some researchers have applied, validated, and developed this
model in various fundamental fields in information systems.
Some of the studies that have been developed by several
researchers regarding the TOE Model are research by
Racherla, et al (2008) on the adoption of eCRM in hospital
organizations[33], Kilbrink, et al (2010) on problem based
learning in programming context planning[34], Angeles, et
al. 2012) on grasping projects on engineering projects[35],
Borgman, et al (2013) and Al-hujran et al (2018) on cloud
computing adoption[36][37], Shi Bin (2013) on cloud
computing adoption[38], Awa et al (2015) on e-commerce
adoption[39], Pool et al (2015) regarding RFID acceptance
in SMEs[40], big data adoption by Saleh et al (2015)
(2018)[41], critical factors of social CRM by Amelina et al
(2017)[42], Halal warehouse study by Ngah et al (2017)[43],
Learning analytics system adoption by Saint et al (2017)[44],
ERP adoption by Catherine et al (2018)[45], smart city
readiness by Dewi et al (2018)[46][47], big data analytics
readiness by Ijab et al (2019)[48], CRM adoption stages by
Crus-Jesus et al (2019)[49], block chain adoption by
Kulkarni et al (2020)[50], cloud computing adoption in
higher education by Hiran, et al (2020)[51] and research by
Abed et al (2020) which explores social commerce
adoption[52].
Variables and indicator elements in the TOE Framework
are given in Table I.
C. Mobile Madura District Smart Regency Application
The idea of a sustainable, intelligent area has been taken
up and implemented in four districts of Madura residence.
The first is the development of smart mobile regency
applications, including the start of the Sumekar online app
and the smart Pamekasan app. The Madura Island intelligent
technology system can be predicted.
Fig. 2. Mobile systems Smart Regency such as Pamekasan Smart and
Sumekar Online
III. METHODOLOGY
This research has taken a quantitative and concise
approach. The goal is subject to different observations. The
quantitative information analysis evaluation process is
carried out. In this analysis, the main and secondary data are
used. Interviews and questionnaires on intelligent urban
stakeholders, particularly the public sector and the
population of Regencies from Sampang and Pamekasan,
gathered the key data. The questionnaire was compiled on a
five-point Likert scale, according to Venkatesh's analysis. A
group of 217 participants is used for this study. The Smart
Mobile Agency Platform is a Research Office for health
agencies, hospitals, public utilities, tourism, hotels, permits,
restaurants, municipal authority, and e-commerce services.
Questions are shared online and offline in direct interviews
with interviewees. Topics were discussed. Types. Types.
Scale of the responses: "1"," 2,"'3," 4"," 5"' = consensus and
"5'.
The research framework, which focuses on the Smart
City/Regency Adoption Performance System TOE
Framework is shown in Fig. 3:
Technological-Context
Fig. 3. Research Framework based on TOE Framework[52]
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2020 4th International Conference on Informatics and Computational Sciences (ICICoS)
AMOS 24.0 software uses the method of path analysis
and structural equation modeling for data analysis. The study
outlines fourteen hypotheses of research using testing
methodology data collection experiments and discusses them
quantitatively.
IV. RESULT AND DISCUSSION
The validity test and reliability test were conducted only
after public and local government questionnaires were
obtained. To determine whether each question is factually
based, validity evaluations are conducted. In reliability
checks, the questionnaire may or may not be counted.
Different findings are obtained via a realistic and reliable
survey process. Convergent validity is used to measure
correlation values between indicator values simultaneously .
For this study, the validity test is used to determine the
accuracy of the process and then to verify its validity:
convergent evidence and biased validity tests. You will
deduce the exact value if the total load is > 0.5.
The findings of this study show that all calculated results
for latent variables are below 0.5 external load values. The
measurements are shown in the table II. The load is also
below 0.5 and is based on OR2, CP2, TPP3, TPP4, TPP5,
BI1, and BI3.
The results of the validity check are based on table III;
cross load value>0.5. Therefore, any latent variable is
discriminatory. Nevertheless, several variables under 0.5 are
also present, including PU, TMS, PoS, and BI.
TABLE III. DISCRIMINANT TEST RESULT
TABLE II. VALIDITY TEST RESULT
Latent Reflective Outer Information
Variables Indicator Loading
Perceived PU1 0.777 Valid
Usefulness PU2 0.815 Valid
PU3 0.648 Valid
PU4 0.596 Valid
Concern about SC1 0.783 Valid
safety SC2 0.641 Valid
SC3 0.611 Valid
SC4 0.615 Valid
Top TMS1 0.522 Valid
Management TMS2 0.563 Valid
Support TMS3 0.720 Valid
TMS4 0.755 Valid
Readiness in OR1 0.646 Valid
Organization OR2 0.422 Invalid
OR3 0.666 Valid
OR4 0.575 Valid
OR5 0.607 Valid
The pressure of CP1 0.661 Valid
Citizen Users CP2 0.463 Invalid
CP3 0.252 Invalid
CP4 0.736 Valid
Pressure of TPP1 0.586 Valid
stakeholders TPP2 0.568 Valid
TPP3 0.312 Invalid
TPP4 0.284 Invalid
TPP5 0.255 Invalid
TPP6 0.510 Valid
Behavioral BI1 0.463 Invalid
Intention BI2 0.585 Valid
BI3 0.462 Invalid
PU RIO TMS CAS PoCU PoS BI
Perceived
Usefulness 0.377
(PU)
Readiness in
Organization
(RIO)
0.711 1.054
Top
Management
Support
(TMS)
0.463 0.743 0.58
Concern
about safety 0.603 0.959 0.638 0.823
(CAS)
Pressure of
Citizen users 0.683 1.091 0.871 0.972 1.226
(PoCU)
Pressure of
stakeholders 0.388 0.632 0.462 0.51 0.67 0.361
(PoS)
Behavioral 0.2
73
Intention 0.283 0.529 0.332 0.402 0.458 0.3 0.2
73
(BI)
0.2
73
TABLE IV. RELIABILITY PERFORMANCE TEST
Latent variables Composite
Reliabilities Information
Perceived Usefulness (PU) 1.226 Reliable
Concern about safety (CAS) 0.823 Reliable
Top Management Support (TMS) 0.580 Reliable
Readiness in Organization (RIO) 1.054 Reliable
The pressure of Citizen Users (PoCU) 0.377 Unreliable
The pressure of stakeholders (PoS) 0.361 Unreliable
Behavioral Intention (BI) 1.126 Reliable
Fig. 4. Analysis of the confirmed AMOS 24.0 factor model
When validity has been verified, reliability has been
checked. This test is used to measure the composite power.
The result is shown in Table IV. A good or reliable latent
variable may be considered if the test of reliability is higher
than 0.5. The variables are latent variables of PU, CAS,
TMS, RIO, and BI above 0,5 and are therefore considered
accurate. Nonetheless, the variables PoCU and POS are
under 0.5 and, therefore, not reliable.
A path analysis was used to determine the structural
model of AMOS. The CFA and the research background are
as described in Fig 4.
The conclusions can be seen based on the research
results are shown in Fig 5.
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2020 4th International Conference on Informatics and Computational Sciences (ICICoS)
Fig. 5. AMOS 24.0 SEM Model Result
TABLE V. RESULT ANALYSI S HYPOTHETICAL OUTCOME
Hypothesis Relation Critical
Ratio
Noted Result
H1 Perceived
Usefulness^
Behavioral Intention
1.198 >1.96 Accepted
H2 Concern about
safety^ Behavioral
Intention
1.838 >1.96 Accepted
H3 Top Management
Support^
Behavioral Intention
0.921 <1.96 Rejected
H4 Readiness in
Organization^
Behavioral Intention
1.556 >1.96 Accepted
H5 The pressure of
Citizen Users^
Behavioral Intention
3.705 >1.96 Accepted
H6 The pressure of
stakeholders^
Behavioral Intention
2.212 >1.96 Accepted
Based on Table V above, it shows that the six dimensions
in the TOE Framework model for the adoption of smart
regency services are Perceived Usefulness (PU), Readiness
in Organization (RIO), Top Management Support (TMS),
Concern about safety (CAS), Pressure of Citizen users
(PoCU), Pressure of Stakeholders (PoS), all of which have a
positive and significant effect on the Behavioral Intention
(BI) variable.
Final findings demonstrate that the six TOE system
hypotheses are Perceived Performance (PU), Organizational
Readiness (RIO), Top Management Assistance (TMS),
Security issues (CAS), Community Pressure (PoCU),
Stakeholder pressures (PoS). ), this tends to affect the
behavioral purpose (BI) component of mobile smart regency
services positively and significantly. This means that the six
independent variables are important and essential factors in
the adoption of wireless, smart district systems, by
stakeholders and community users of the smart regency
systems.
V. CONCLUSION & IMPLICATIO N
This research has two dimensions, mainly theory and
management. The model for testing variables that affect the
quality of service adoption in mobile smart districts was
theoretically created. This model can be further evaluated by
researchers interested in this topic in other contexts. The
survey provides recommendation s and suggestions for
practical management. This indicates that policymakers and
lawmakers pay greater attention to crucial issues impacting
their tasks to improve the efficacy of informed public
services.
Although this study has met its objectives, the research
still has some limits. Samples with different characteristic s of
the respondent are also unusual. Secondly, the performance
assessment model contains only fifteen development
variables. The framework can be extended with additional
variables for future study. The three experiments referred to
the crossing selection period with limitations. The collection
of data often can not be as accurate as retrospective data
collection to help and more accurately describe the situation.
ACKNOWLEDGMENT
Recognition Our thanks go to the Republic of Indonesia's
Ministry of Science, Technology, and Higher Education for
supporting this work through funding. This study was
performed in conjunction with the University Collaborative
Research Scheme with Contract No. 039 / SP2H / LT-
MONO / LL7 / 2020.
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