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Understanding and Acceptance of Smart City Policies: Practitioners’ Perspectives on the Malaysian Smart City Framework

Abstract

Whilst a plethora of research exists on the smart cities and project performance evaluations, only few studies have focused on the smart city policy evaluation from the perspective of its acceptance by practitioners. This paper aims to generate insights by evaluating the smart city policy through a developing country case study—i.e., Malaysia. This study employed a questionnaire survey method for data collection and analyzed the data by using Fuzzy Delphi analysis. A group of 40 practitioners was gathered in a focus group discussion through purposive sampling. The main objectives of this survey were to identify the understanding and acceptance levels of the seven smart city domains and respective strategies that are outlined in the Malaysian Smart City Framework. The results disclosed that the practitioners possessed divergent levels of understanding and acceptance in terms of smart city domains. The study participant practitioners accepted all understanding and acceptance objectives of smart economy, living, people, and governance domains (expert agreement 75–92% and threshold d value 0.123–0.188), but rejected all objectives for both smart environment and digital infrastructure domains (expert agreement 55–74% and threshold d value 0.150–0.212). Along with this, acceptance of smart mobility was also rejected (expert agreement 56% and threshold d value 0.245). The findings reveal that considering all opinions expressing dissensus is essential when building more inclusive smart city strategies. This study contributes to the smart city discourse as being one of the first in capturing professional practitioners’ understanding and acceptance on a national level smart city policy by applying the Delphi method in the smart city context. Most importantly, the study informs urban policymakers on how to capture the voices and perspectives of the general public on national and local smart city strategy and initiatives.
sustainability
Case Report
Understanding and Acceptance of Smart City Policies:
Practitioners’ Perspectives on the Malaysian Smart
City Framework
Seng Boon Lim 1, Jalaluddin Abdul Malek 1, Md Farabi Yussoff Md Yussoff 2and Tan Yigitcanlar 3,4,*


Citation: Lim, S.B.; Malek, J.A.;
Yussoff, M.F.Y.M.; Yigitcanlar, T.
Understanding and Acceptance of
Smart City Policies: Practitioners’
Perspectives on the Malaysian Smart
City Framework. Sustainability 2021,
13, 9559. https://doi.org/
10.3390/su13179559
Received: 5 August 2021
Accepted: 23 August 2021
Published: 25 August 2021
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1Center for Research in Development, Social and Environment (SEEDS),
Faculty of Social Sciences and Humanities, University Kebangsaan Malaysia, Bangi 43600, Malaysia;
lims@ukm.edu.my (S.B.L.); jbam@ukm.edu.my (J.A.M.)
2Federal Government Administrative Centre, Federal Department of Town and Country Planning,
Ministry of Housing and Local Government, Putrajaya 62675, Malaysia; farabi@planmalaysia.gov.my
3School of Architecture and Built Environment, Queensland University of Technology,
Brisbane, QLD 4000, Australia
4School of Technology, Federal University of Santa Catarina, Campus Universitario,
Florianópolis 88040-900, SC, Brazil
*Correspondence: tan.yigitcanlar@qut.edu.au or tan.yigitcanlar@ufsc.br; Tel.: +61-7-3138-2418
Abstract:
Whilst a plethora of research exists on the smart cities and project performance evalua-
tions, only few studies have focused on the smart city policy evaluation from the perspective of
its acceptance by practitioners. This paper aims to generate insights by evaluating the smart city
policy through a developing country case study—i.e., Malaysia. This study employed a questionnaire
survey method for data collection and analyzed the data by using Fuzzy Delphi analysis. A group of
40 practitioners was gathered in a focus group discussion through purposive sampling. The main
objectives of this survey were to identify the understanding and acceptance levels of the seven smart
city domains and respective strategies that are outlined in the Malaysian Smart City Framework. The
results disclosed that the practitioners possessed divergent levels of understanding and acceptance
in terms of smart city domains. The study participant practitioners accepted all understanding and
acceptance objectives of smart economy, living, people, and governance domains (expert agreement
75–92% and threshold dvalue 0.123–0.188), but rejected all objectives for both smart environment
and digital infrastructure domains (expert agreement 55–74% and threshold dvalue 0.150–0.212).
Along with this, acceptance of smart mobility was also rejected (expert agreement 56% and threshold
dvalue 0.245). The findings reveal that considering all opinions expressing dissensus is essential
when building more inclusive smart city strategies. This study contributes to the smart city discourse
as being one of the first in capturing professional practitioners’ understanding and acceptance on
a national level smart city policy by applying the Delphi method in the smart city context. Most
importantly, the study informs urban policymakers on how to capture the voices and perspectives of
the general public on national and local smart city strategy and initiatives.
Keywords:
Europe; Fuzzy Delphi method; Hong Kong; India; Malaysia; smart cities; smart city
policy; smart urbanization; urban policy; policy evaluation
1. Introduction
Since the early 2000s, smart city development has been gaining global momentum.
Thus, many models or concepts have been formed, adopted, and evaluated [
1
]. For
example, the seminal smart city concept by [
2
] laid the basis for the formation of six smart
city domains (i.e., smart economy, people, governance, mobility, environment, and living)
and emphasized activities that would cultivate independent citizens. Since then, many
models have been adopted and adapted from the concept of [
2
], such as the smart cities
wheel by [
3
], the initiative framework of the smart city by [
4
], the alternative framework for
Sustainability 2021,13, 9559. https://doi.org/10.3390/su13179559 https://www.mdpi.com/journal/sustainability
Sustainability 2021,13, 9559 2 of 31
smart city governance by [5], the conceptual framework for defining the smart city by [6],
and the Unified Smart City Model by [
7
]. On the other hand, top-down smart policies that
have been adopted and adapted from the work of [
2
] include the Hong Kong Smart City
Blueprint [8] and the Malaysian Smart City Framework (MSCF) [9].
Furthermore, many studies have evaluated smart city performance. For instance,
Ref. [
2
] developed the European medium-sized (smart) city indicators and ranking; Ref. [
10
]
used the analytic network process (ANP) to investigate the relations between smart city
domains, actors (i.e., government, industry, university, and civil society), and strategies;
Ref. [
11
] examined the Malaysian smart city domains through the AHP; Ref. [
12
] devel-
oped a smart city descriptor scoring table to qualitatively compare smart city domains
performance in Singapore, Korea, and Malaysia; Ref. [
13
] developed a smart city sharable
framework to evaluate 17 smart cities in China; Ref. [
14
] developed a fuzzy synthetic eval-
uation of the challenges facing smart city development in developing countries; Ref. [
15
]
developed a typology of smart city assessment tools and evaluated 122 cities; Ref. [
16
]
developed the smart city index and ranking; and ref. [
17
] recently developed a smart city
measurement framework for inclusive growth.
Nevertheless, far less research has been conducted on evaluating the smart city policy,
with the exception of scholars such as [
18
], who made a general evaluation of the smart
city policy and the challenges facing five UK cities. It is crucial to evaluate each planned
top-down policy, especially from the public perspective. With just internal assessments by
the authorities and departments, actual situations and shortfalls may be overlooked. This
might result in overall failure and wasted investment and resources. Taking the case of the
MSCF, launched in 2019, to date there have been no evaluation reports on the strategies
being planned. Furthermore, the period from 2021 to 2022 has been scheduled as the
time to implement smart initiatives nationwide [
9
]. Many local authorities lack suitable
references and benchmarking on the details of the smart city domains and strategies to be
adopted [
19
]. Without reference to evaluation, authorities or officers on the ground tend to
believe that a blueprint is perfect and will follow it to the letter. Thus, in this research, and
given the practical knowledge gaps, the authors intend to answer the following questions:
What level of understanding do practitioners have of the smart city domains stated
in MSCF?
What level of acceptance do practitioners have of the smart city domains stated
in MSCF?
Based on these research questions, this study aims to evaluate the understanding and
acceptance of practitioners from various sectors who are involved in smart city develop-
ment in developing countries (using Malaysia as a case study). Knowing the levels of
public understanding and acceptance was intended to be the output of this study, which
would thus provide guidance to governments and policymakers to improve the smart city
strategies and policies so that more smart and inclusive living is available to their citizens.
2. Literature Background
Understanding the basic smart city domains is mainly influenced by the six domains
outlined by [
2
], namely the smart economy, living, environment, people, governance,
and mobility.
According to [
2
], the smart economy component is characterized by competitiveness.
Among the sub-components of the smart economy (in the case of medium-sized European
city rankings) are an innovative spirit, entrepreneurship, an economic image and trademark,
productivity, labor market flexibility, and international embeddedness. As the economy
is a broad concept and its strategies are context-based, many scholars and agencies have
suggested measuring specific components, including nineteen economic attributes in the
case of India, as stated by [
20
]. These include promoting balanced and sustainable economic
growth, making strategic investments on strategic assets, and knowing that all forms of
economics function at the local level. In another case, the smart economy domain of the
Sustainability 2021,13, 9559 3 of 31
Hong Kong Smart City Blueprint [
8
] promotes sharing economy, fintech, smart tourism,
and re-industrialization.
In the case of Malaysia, the components stated in MSCF are to intensify the application
of technology and digitalization in core business functions, enhance the usage of e-payment,
attract investment in high value-added industries, create a workforce to match the jobs in
these industries, provide technology labs and collaborative platforms, establish incubators
and accelerators, and leverage existing government assistance and funding. Supporting
literature can be found in Table 1.
Table 1. Smart economy domain.
Smart Economy Strategy Reference
Intensify technology application and digitalization in core business functions [2,2022]
Enhance the usage of e-payment [2325]
Attract investment in high value-added industries [26,27]
Create workforce to match jobs in high value-added industries [4,28,29]
Provide technology labs and collaborative platforms [22,30,31]
Establish incubators and accelerators [32,33]
Leverage on existing government assistance and funding [20,30]
High value-added activities refer to the major contribution of a private industry or
government sector to overall gross domestic product (GDP) [
34
]. Contributions to GDP
include higher wages and compensation for employees, taxes on production, lower import
subsidies, and a gross operating surplus [
34
]. The Hong Kong labor market is an example of
a concentration of high value-added service industries, with 25.9% of employees working
in public administration or in the social and personal services industry in 2014 [
35
]. How-
ever, it is challenging to transition from low to high value-added industries in developing
countries. This is the case in Indonesia, where low value-added industries such as textiles
are desperately fighting rising wages and seeking protection from international competi-
tion. High value-added sectors largely utilize technology in various activities, including
designing products, delivering products, processing customer orders, and improving prod-
uct quality [
27
]. Nevertheless, according to MSCF, technology disruptors in Malaysia,
such as robotics and analytics, are shifting traditional services towards value-adding and
non-traditional service areas. However, the authors observed that MSCF did not refer to
the issues of wages and imbalanced urban-rural development. Correspondingly, the smart
city policy has offered opportunities within the Fourth Industrial Revolution (Industry 4.0)
mostly in developed states and urban areas, while less-developed states and rural areas,
such as Sabah, are mentioned far less.
The second domain of smart living is characterized by the quality of life. Among the
sub-components found in the smart living concept outlined by [
2
] are cultural facilities,
health conditions, individual safety, housing quality, educational facilities, touristic attrac-
tivity, and social cohesion. In the Indian case, [
20
] scoped smart living into 14 attributes,
including promoting shared values in society, celebrating local history and culture, and
opening highly accessible public spaces. In the case of Hong Kong, their strategies are in
building a Wi-Fi-connected city, developing faster digital payment systems, providing free
electronic identity (eID) citizenship for government and commercial online transactions,
and launching a $1 billion funding scheme to support the procurement of technological
products by elderly and rehabilitation service units [8].
In Malaysia, the MSCF strategies are to enhance safety and security, promote the
provision of quality housing, optimize emergency responses, enhance the quality of health-
care services through digital technology and encourage urban farming for better living.
Supporting literature can be found in Table 2.
Sustainability 2021,13, 9559 4 of 31
Table 2. Smart living domain.
Smart Living Strategy Reference
Enhance safety and security [20,36,37]
Promote quality housing [2,38]
Optimize emergency response [20,39]
Enhance quality of healthcare services through digital technology [4043]
Encourage urban farming for better living [23,44]
Concerning the element of enhancing safety and security, one key initiative in Malaysia
is the focus on crime reduction [
36
,
45
]. For example, under the safe city initiative through
the Ministry of Housing and Local Government, a safer city can be created using several
strategies, such as crime prevention through environmental design (CPTED) and crime pre-
vention through social design (CSPD) [
46
]. With CPTED, information and communication
technology (ICT), and mechanical surveillance design initiatives are popular, including
the installation of closed-circuit television (CCTV) in public spaces, IoT (internet-of-things)
lighting, safety (panic button) alarms, and establishing GIS (geographic information sys-
tem) mapping for crime detection [
36
]. In the case of the capital city, Kuala Lumpur, crime
is always an important issue for the citizens and the city authorities. Research has shown
that the challenges to making Kuala Lumpur a safe city can be mitigated by enhancing
the role of guardians (i.e., the authorities); promoting CPTED and CSPD activities; and
assisting victims and offenders with psychological, financial, and family assistance [47].
The idea behind the third domain, smart environment, centers on preserving natural
resources. The smart environment sub-components outlined by [
2
] are the attractivity of
natural conditions, pollution, environmental protection efforts, and sustainable resource
management. Another source of reference from India, Vinod Kumar [
20
], presented 22
attributes to describe the smart environment, which included protecting nature; managing
water resources, water supply systems, floods, and inundations effectively; encouraging
neighborliness and a spirit of community; upgrading urban resilience to the impacts of
climate change; and creating a low-carbon environment based on energy efficiency, renew-
able energy, and the like. In the Hong Kong case, the strategies are focused on reducing the
carbon intensity; promoting energy efficiency and conservation in the community, with a
particular focus on green and intelligent buildings; reducing waste; and monitoring the air
pollution and cleanliness of public spaces [8].
In Malaysia, MSCF smart environment strategies include the need to preserve green
areas and enhance the management of trees in public parks; strengthen the integrated and
sustainable solid waste management; strengthen the solid waste laws and policies; improve
the air quality and its monitoring system; improve the water quality and its monitoring
system; increase energy efficiency and promote renewable energy sources in the community;
enhance disaster risk management by adopting advanced technology applications; enhance
the non-revenue water management; and encourage the development of a low-carbon city
concept that can be adopted at the local level. Supporting literature can be found in Table 3.
Table 3. Smart environment domain.
Smart Environment Strategy Reference
Preserve green area and enhance the management of trees in public parks [2,48]
Strengthen the integrated and sustainable solid waste management [2,48]
Strengthen the solid waste laws and policies [49,50]
Improve the air quality and its monitoring system [50,51]
Improve the water quality and its monitoring system [2,50]
Increase energy efficiency and promote renewable energy sources in community [2,20,37]
Enhance the disaster risk management by adopting advanced technology application [52,53]
Enhance the non-revenue water management [2,54]
Encourage the development of low carbon city concept to be adopted at local level [48,55]
Sustainability 2021,13, 9559 5 of 31
In terms of park and green area management, the reduction in size of reserved forest
and the preservation of green space in development plans are continual issues in Malaysia.
Although forest land may have been gazetted, new development plans have always
resulted in excuses to degazette forest reserves in favor of mixed-use development. For
example, the Selangor State Government has recently granted a mixed development project
on 931 hectares of the Kuala Langat North Forest Reserve, which is largely a move to
rescind the protected status of the remnants of a once-sprawling peat forest that has been
home to four indigenous Temuan settlements. The project also threatens wildlife [
56
].
This is one case that demonstrates the image of the Malaysian government, which can
easily override gazetted land protection with the introduction of new plans under political
influence and with profitable intentions, despite concerns for the public good of civil society,
climate change, and the overall environment.
In terms of community attitudes to environmental protection, much change is re-
quired in Malaysia, especially within the authority-dependence mindset. The study on
the Iskandar territory, Johor, Malaysia, Ref. [
57
] showed that residents are conscious of the
need for environmental cleanliness; however, their mindsets were hindered by the belief
that the cleanliness of public space is mainly the responsibility of the authorities. Thus,
Ref. [
57
] reaffirmed that the involvement and accountability of all parties are much needed
in caring for the natural environment.
The fourth domain of smart people is characterized by social and human capital [
2
].
The indicators for the case of Europe include the level of qualification, affinity with life-
long learning, social and ethnic plurality, flexibility, creativity, cosmopolitanism, open-
mindedness, and participation in public life. In the case of India, ‘smart people’ are
proposed as being the fundamental building block of a smart city system because, without
people’s active participation, a smart city system would not function effectively
(Figure 1)
.
Thus, Ref. [
20
] proposed eleven attributes of smart people by including the need to be
actively involved in the city’s sustainable development; excel in creativity and finding
unique solutions to challenging issues; opt for lifelong learning and use e-learning models;
and be cosmopolitan and open-minded and hold a multicultural perspective. In the case
of Hong Kong, this focuses on nurturing young talent, innovation, and entrepreneurial
culture [8].
Sustainability 2021, 13, x FOR PEER REVIEW 5 of 32
Table 3. Smart environment domain.
Smart Environment Strategy Reference
Preserve green area and enhance the management of trees in public parks [2,48]
Strengthen the integrated and sustainable solid waste management [2,48]
Strengthen the solid waste laws and policies [49,50]
Improve the air quality and its monitoring system [50,51]
Improve the water quality and its monitoring system [2,50]
Increase energy efficiency and promote renewable energy sources in community [2,20,37]
Enhance the disaster risk management by adopting advanced technology application
[52,53]
Enhance the non-revenue water management [2,54]
Encourage the development of low carbon city concept to be adopted at local level [48,55]
In terms of park and green area management, the reduction in size of reserved forest
and the preservation of green space in development plans are continual issues in Malay-
sia. Although forest land may have been gazetted, new development plans have always
resulted in excuses to degazette forest reserves in favor of mixed-use development. For
example, the Selangor State Government has recently granted a mixed development pro-
ject on 931 hectares of the Kuala Langat North Forest Reserve, which is largely a move to
rescind the protected status of the remnants of a once-sprawling peat forest that has been
home to four indigenous Temuan settlements. The project also threatens wildlife [56]. This
is one case that demonstrates the image of the Malaysian government, which can easily
override gazetted land protection with the introduction of new plans under political in-
fluence and with profitable intentions, despite concerns for the public good of civil society,
climate change, and the overall environment.
In terms of community attitudes to environmental protection, much change is re-
quired in Malaysia, especially within the authority-dependence mindset. The study on the
Iskandar territory, Johor, Malaysia, [57] showed that residents are conscious of the need
for environmental cleanliness; however, their mindsets were hindered by the belief that
the cleanliness of public space is mainly the responsibility of the authorities. Thus, [57]
reaffirmed that the involvement and accountability of all parties are much needed in car-
ing for the natural environment.
The fourth domain of smart people is characterized by social and human capital [2].
The indicators for the case of Europe include the level of qualification, affinity with life-
long learning, social and ethnic plurality, flexibility, creativity, cosmopolitanism, open-
mindedness, and participation in public life. In the case of India, ‘smart people’ are pro-
posed as being the fundamental building block of a smart city system because, without
people’s active participation, a smart city system would not function effectively (Figure
1). Thus, [20] proposed eleven attributes of smart people by including the need to be ac-
tively involved in the city’s sustainable development; excel in creativity and finding
unique solutions to challenging issues; opt for lifelong learning and use e-learning mod-
els; and be cosmopolitan and open-minded and hold a multicultural perspective. In the
case of Hong Kong, this focuses on nurturing young talent, innovation, and entrepreneur-
ial culture [8].
Figure 1. Smart city system building blocks, adapted from [20].
Figure 1. Smart city system building blocks, adapted from [20].
In the case of Malaysia, the strategies are to improve moral education in schools;
enhance public awareness in practicing good moral and civic duties; increase skilled
and talented human capital at every level; enhance public participation and community
empowerment initiatives; improve gender sensitization and the inclusivity of vulnerable
groups; and increase public willingness to adapt to emerging technologies. Supporting
literature can be found in Table 4.
Sustainability 2021,13, 9559 6 of 31
Table 4. Smart people domain.
Smart People Strategy Reference
Improve moral education in schools [58,59]
Enhance public awareness in practicing good moral and civic [59,60]
Increase skilled and talented human capital at every level [8,20]
Enhance public participation and community empowerment initiatives [20,6163]
Improve gender sensitization and inclusivity of vulnerable groups [52,64]
Increase the public willingness to adapt with emerging technologies [8,20,65]
The element of cultivating skilled and talented human capital is particularly crucial,
as Malaysia is determined to adopt the National Fourth Industrial Revolution Policy
(Malaysian Industry 4.0 Policy), which was launched recently on 1 July 2021 [
66
]. This
Industry 4.0 policy was launched with the purpose of transforming Malaysia into a high-
income state through technology and digitalization. Five fundamental technologies of the
Industry 4.0 policy include artificial intelligence, the internet of things, blockchain, cloud
computing and big data analytics, and advanced materials and technologies [
67
]. For the
young generation to master these Industry 4.0 skills, it is crucial to plan every level of
education properly. The Industry 4.0 policy is aligned with the Shared Prosperity Vision
2030, launched in 2019. The aim is to drive Malaysia towards developed nation status
by 2030.
The moral and spiritual education element is considered appropriate for the majority
Muslim society in Malaysia. The moral element of cultivating smart people is comparatively
silent in most western European smart societies (refer to [
2
,
68
]). Since the early 1980s,
Royal Professor Ungku Abdul Aziz bin Ungku Abdul Hamid, a well-known academician
in Malaysia, has creatively interpreted a religious and moral form of development, which
represents a balance between the spiritual and material world and is geared towards the
needs of the local Muslim community [
59
]. The emphasis on the moral and spiritual
element adopted in the MSCF will further strengthen the quality of Malaysian citizenship
by developing a more peaceful and caring society.
Citizen participation and community empowerment are often identified as important
elements in realizing a citizen-centric smart city [
20
,
62
]. However, this attention should
never be blinded by political actions that assume that tokenism and non-participation (refer
to [
61
]) satisfy this type of participation. On the contrary, it is vital to involve citizens in
decision making and agenda setting in the smart city initiatives [69].
The core value of the fifth domain of smart governance is political participation. From
the European perspective, Ref. [
2
] described smart governance using the components of
participation in decision making, public and social services, and transparent governance.
The systematic literature review by [
70
] summarized six attributes for building a smart
governance system. It should be based on ICT, external collaboration and participation,
internal coordination, decision-making processes, e-administration, and outcomes. Prior
research also suggests that the main outcome of smart city governance is the production of
a wide range of public values through innovative collaborations [70].
From the Indian perspective, Ref. [
71
] suggested 12 steps to convert existing e-
governance to smart governance, including an increase in city expenditure on ICT; the
ease of access to e-services such as lodge complaints, claims and rights to information; and
the promotion of e-democracy through e-decision making and e-voting. From the Hong
Kong perspective, smart governance is promoted through using open data for smart city
innovations; building smarter city infrastructure, such as the fifth generation (5G) mobile
network; building a new big data analytics platform; data sharing among government
departments; and adopting building information modelling (BIM) for major government
capital work projects [8].
From the MSCF perspective, the components include increasing the scope of e-
government services, increasing the quality of e-government services, elevating the use of
data sharing platforms across government agencies, and promoting information disclosure
Sustainability 2021,13, 9559 7 of 31
and open data from the Government. Table 5shows the smart governance strategies in
MSCF and the related citations.
Table 5. Smart governance domain.
Smart Governance Strategy Reference
Increase the scope of e-government services [64,71,72]
Increase the quality of e-government services [2,40,71,73]
Elevate the use of data sharing platform across government agencies [26,70,74,75]
Promote information disclosure and open data from government [8,7679]
It is crucial to be aware of the component of elevating the use of data sharing plat-
forms across government agencies, as the isolated performance of government agencies
was identified by the former prime minister as hindering the performance and services
of government agencies [
80
]. In fact, this lack of efficiency, which is due to excessive
bureaucracy, the reluctance of public servants to share data, and other factors, is not a new
issue in the delivery of the Malaysian government system [81,82].
Concerning the sixth domain, smart mobility, the main concerns outlined by [
2
] were
transport and ICT. The sub-components of [
2
] include local accessibility; (inter)national
accessibility; the availability of an ICT infrastructure; and sustainable, innovative, and safe
transport systems. In the case of India, Ref. [
20
] described smart mobility in terms of ten
attributes, such as a focus on the mobility of people but not vehicles; advocating walkability
and cycling; balanced transportation options such as a mass rapid transit system; and
seamless mobility for differently abled people. In the Hong Kong case, the strategies
are to focus on intelligent transport systems and traffic management; public transport
interchanges/ bus stops and parking; environmental friendliness in transport; and smart
airports with facial biometric technology. These features should offer a hassle-free travel
experience [8].
In the Malaysian case, the smart mobility strategies address the need to establish
intelligent transport management; enhance data sharing and digital mobility platforms;
establish demand-based ridesharing services; utilize AI and the sensor-based predictive
maintenance of a public transport fleet and infrastructure; enhance the dynamic smart
parking infrastructure; establish an electric vehicle revolution; enhance collaboration with
academia on research and development (R&D) into, and the commercialization of, EVs
and next-generation automobiles; and promote the usage of public transport applications.
Table 6shows the smart mobility strategies in MSCF and the related citations.
Table 6. Smart mobility domain.
Smart Mobility Strategy Reference
Establish intelligent transport management [2,8,20]
Enhance data sharing and digital mobility platform [83,84]
Establish demand-based ride sharing services [8,20,85]
Utilize AI and sensor-based predictive maintenance of public transport fleet and infrastructure [2,22,43,85,86]
Enhance dynamic smart parking infrastructure [8,43,83]
Establish electric vehicle revolution [85,87]
Enhance collaboration with academia on R&D and commercialization on EVs and next-generation
automobile [83,85]
Promote the usage of public transport application [8,8385]
In general, all the components and strategies in various countries discussed above
indicate that smart mobility is universal, regardless of whether it is introduced in the
global north or south. The common item is the promotion of people-centric (rather than
vehicle-centric) [
83
] and environmentally friendly (rather than utility convenient) trans-
portation means [
84
]. The measures involved include opting to cycle and walk and to take
public transport in the city rather than using a personal vehicle that produces greenhouse
gas, carbon emissions, and pollution. This is predominantly important in many Asian
cities; for example, Kuala Lumpur is characterized by heavy car dependence, leading to
Sustainability 2021,13, 9559 8 of 31
traffic congestion and delays [
85
]. Planning for future mobility must focus less on building
more highways and being car-dependent but rather on alternative ways of thinking about
environmentally friendly mobility means and adoption. Considering the need for environ-
mental protection and the preference for connecting two destination points via electronic
platforms/communication, the actual physical cost of travelling could be reduced.
In addition to the above six basic domains, the authors would like to discuss another
emerging domain, that of smart digital infrastructure. This domain did not appear as an
individual domain in [
2
,
8
,
20
]. Giffinger et al. [
2
] explicitly merged this element into the
smart mobility domain. Meanwhile, in the case of Hong Kong, this digital infrastructure is
explained/inserted in the smart government domain. As digital infrastructure is a frequent
practice in Western and developed countries in Europe and North America, it is quite
ready and more embedded into other domains. Under the New York Smart and Equitable
City Plan 2015, digital infrastructure was embedded in the domains of smart buildings
and infrastructure; smart transport and mobility; smart energy and environment; smart
public health and safety; and smart government and community [
88
]. All the sectors and
strategies within the smart cities concept center on ICT infrastructure, a point on which the
authors and the majority of smart city scholars agree (Figure 2).
Sustainability 2021, 13, x FOR PEER REVIEW 8 of 32
Enhance collaboration with academia on R&D and commercialization on
EVs and next-generation automobile [83,85]
Promote the usage of public transport application [8,83–85]
In general, all the components and strategies in various countries discussed above
indicate that smart mobility is universal, regardless of whether it is introduced in the
global north or south. The common item is the promotion of people-centric (rather than
vehicle-centric) [83] and environmentally friendly (rather than utility convenient) trans-
portation means [84]. The measures involved include opting to cycle and walk and to take
public transport in the city rather than using a personal vehicle that produces greenhouse
gas, carbon emissions, and pollution. This is predominantly important in many Asian cit-
ies; for example, Kuala Lumpur is characterized by heavy car dependence, leading to traf-
fic congestion and delays [85]. Planning for future mobility must focus less on building
more highways and being car-dependent but rather on alternative ways of thinking about
environmentally friendly mobility means and adoption. Considering the need for envi-
ronmental protection and the preference for connecting two destination points via elec-
tronic platforms/communication, the actual physical cost of travelling could be reduced.
In addition to the above six basic domains, the authors would like to discuss another
emerging domain, that of smart digital infrastructure. This domain did not appear as an
individual domain in [2,8,20]. Giffinger et al. [2] explicitly merged this element into the
smart mobility domain. Meanwhile, in the case of Hong Kong, this digital infrastructure
is explained/inserted in the smart government domain. As digital infrastructure is a fre-
quent practice in Western and developed countries in Europe and North America, it is
quite ready and more embedded into other domains. Under the New York Smart and
Equitable City Plan 2015, digital infrastructure was embedded in the domains of smart
buildings and infrastructure; smart transport and mobility; smart energy and environ-
ment; smart public health and safety; and smart government and community [88]. All the
sectors and strategies within the smart cities concept center on ICT infrastructure, a point
on which the authors and the majority of smart city scholars agree (Figure 2).
Figure 2. Digital infrastructure is the heart of smart city development [89].
However, in most private sectors conceptions, due to the propagation and sale of
their latest technologies, this digital infrastructure element is explicitly highlighted. In the
case of Frost and Sullivan, it is even divided into two different domains: smart technology
and smart infrastructure (Figure 3).
Figure 2. Digital infrastructure is the heart of smart city development [89].
However, in most private sectors conceptions, due to the propagation and sale of their
latest technologies, this digital infrastructure element is explicitly highlighted. In the case
of Frost and Sullivan, it is even divided into two different domains: smart technology and
smart infrastructure (Figure 3).
Sustainability 2021, 13, x FOR PEER REVIEW 9 of 32
Figure 3. Smart city domains [90].
In MSCF, smart digital infrastructure has been designated as a separate seventh do-
main. The smart digital infrastructure strategies include the need to enhance the roles of
service providers in developing digital infrastructure; enhance internet speed and connec-
tivity; enhance the government’s role in facilitating the development of communication
infrastructure; enhance indoor and outdoor network coverage; strengthen policies related
to personal data protection; and strengthen policies related to cybersecurity. Table 7 illus-
trates the strategies of the smart digital infrastructure domain and its related citations.
Table 7. Smart digital infrastructure domain.
Smart Digital Infrastructure Strategy Reference
Enhance service provider’s role in developing digital infrastructure [8,37,90,91]
Enhance internet speed and connectivity [90,92]
Enhance government’s role in facilitating the development of communication
infrastructure [8,70,93]
Enhance indoor and outdoor network coverage [2,94,95]
Strengthen policies related to personal data protection [96–98]
Strengthen policies related to cybersecurity [8,37,89,99,100]
One form of digital infrastructure to attract attention in smart city development is the
IoT. Using the internet, the IoT is a network that interconnects ordinary physical objects,
such as smartphones, with identifiable addresses to provide intelligent services [101]. In
2021, 35 billion IoT devices were expected to be installed and there were 46 billion con-
nected devices around the world [102]. These numbers, in total, represent more than ten
times the size of the world population. Therefore, it could be imagined that it is crucial to
tackle the cybersecurity issues that relate to using IoT machines and to address the need
for personal data protection as part of living in smart cities. In Malaysia, cybersecurity
cases rose by 82.5% between 18 March and 7 April 2020 (838 cases), compared to the same
timeframe in 2019 (459 cases) [103]. These cases include some form of cyberbullying; fraud
or intruding into an unauthorized system such as phishing and email scams; data
breaches and distributed denial of service (DDoS) attacks on local businesses; and hacking
into private video conferencing chats and harassing the participants during the COVID-
19 movement control period.
To tackle these cybersecurity problems in combination with promoting IoT adoption,
in 2015, the National IoT Strategic Roadmap was launched by the Ministry of Science,
Technology, and Innovation, with the national applied R&D center MIMOS Bhd. as the
implementation secretariat and with the support of agencies such as Cybersecurity Ma-
laysia [104]. This roadmap targeted the contribution of RM 9.3 billion (about USD 2.2 bil-
lion) to the gross national income and the creation of more than 14,000 highly skilled em-
ployment opportunities by 2020. In addition, other policies have been initiated, such as
Figure 3. Smart city domains [90].
Sustainability 2021,13, 9559 9 of 31
In MSCF, smart digital infrastructure has been designated as a separate seventh do-
main. The smart digital infrastructure strategies include the need to enhance the roles of
service providers in developing digital infrastructure; enhance internet speed and connec-
tivity; enhance the government’s role in facilitating the development of communication
infrastructure; enhance indoor and outdoor network coverage; strengthen policies re-
lated to personal data protection; and strengthen policies related to cybersecurity. Table 7
illustrates the strategies of the smart digital infrastructure domain and its related citations.
Table 7. Smart digital infrastructure domain.
Smart Digital Infrastructure Strategy Reference
Enhance service provider’s role in developing digital infrastructure [8,37,90,91]
Enhance internet speed and connectivity [90,92]
Enhance government’s role in facilitating the development of
communication infrastructure [8,70,93]
Enhance indoor and outdoor network coverage [2,94,95]
Strengthen policies related to personal data protection [9698]
Strengthen policies related to cybersecurity [8,37,89,99,100]
One form of digital infrastructure to attract attention in smart city development is the
IoT. Using the internet, the IoT is a network that interconnects ordinary physical objects,
such as smartphones, with identifiable addresses to provide intelligent services [
101
].
In 2021, 35 billion IoT devices were expected to be installed and there were 46 billion
connected devices around the world [
102
]. These numbers, in total, represent more than
ten times the size of the world population. Therefore, it could be imagined that it is crucial
to tackle the cybersecurity issues that relate to using IoT machines and to address the need
for personal data protection as part of living in smart cities. In Malaysia, cybersecurity
cases rose by 82.5% between 18 March and 7 April 2020 (838 cases), compared to the same
timeframe in 2019 (459 cases) [
103
]. These cases include some form of cyberbullying; fraud
or intruding into an unauthorized system such as phishing and email scams; data breaches
and distributed denial of service (DDoS) attacks on local businesses; and hacking into
private video conferencing chats and harassing the participants during the COVID-19
movement control period.
To tackle these cybersecurity problems in combination with promoting IoT adoption,
in 2015, the National IoT Strategic Roadmap was launched by the Ministry of Science,
Technology, and Innovation, with the national applied R&D center MIMOS Bhd. as
the implementation secretariat and with the support of agencies such as Cybersecurity
Malaysia [
104
]. This roadmap targeted the contribution of RM 9.3 billion (about USD 2.2
billion) to the gross national income and the creation of more than 14,000 highly skilled
employment opportunities by 2020. In addition, other policies have been initiated, such
as the National Industry 4.0 policy, the National Cyber Security Policy, and the Malaysia
Personal Data Protection Act 2010. MSCF mentioned the need to review and enforce
stronger laws, as well as upgrade security systems and procedures in the public and private
sectors. In this context, cybersecurity has been identified as a policy to be strengthened in
the smart city context.
3. Methodology
After outlining the smart city domains and examples of smart city policies worldwide,
this methodology section explains the MSCF case study, the samples of respondents, the
data collection, the questionnaire design, and the data analysis method.
3.1. The Case of Malaysian Smart City Framework
MSCF is the first top-down document to formulate the direction of smart city devel-
opment in Malaysia. The document was launched in September 2019 and drafted by the
Ministry of Housing and Local Government. In MSCF, smart cities are defined as “cities
Sustainability 2021,13, 9559 10 of 31
that use ICT and technological advancement to address urban issues, including to improve
quality of life, promote economic growth, develop a sustainable and safe environment and
encourage efficient urban management practices” [
9
]. This definition, in practice, aims to
achieve the vision of “quality and smart living” [9].
In terms of planning, the implementation of smart cities nationwide is divided into
three phases from 2019 to 2025. These are phase 1 (the foundation stage), from 2019 to 2020
(two years); phase 2 (the development stage), from 2021 to 2022 (two years); and phase
3 (the advanced development and monitoring stage), from 2023 to 2025 (three years). To
ensure its effective implementation, understanding, and acceptance among the people
must also be investigated, especially for urban residents. Hence, this study focuses on
the understanding and acceptance among professionals of MSCF. The study has been
developed to identify the appropriateness of the outlined strategies.
As discussed previously, various components/strategies can be found in academic
and grey literature under the grouping of each smart city domain, all of which depends
on managing problems and challenges in local contexts. The case is the same in Malaysia,
where the government had customized the domains, components, and strategies according
to the local challenges. Based on the planned domains, 90 questionnaire items were
designed (see Appendix A) and face validated by two smart city experts.
3.2. Sampling and Data Collection
This study employed a quantitative survey via the Fuzzy Delphi method. In obtaining
expert opinions using the Fuzzy Delphi method, the ideal sample size is between 10 and 50
respondents [
105
,
106
]. Therefore, the authors decided to sample 40 smart city practitioners
from the Kuala Lumpur Greater Valley area, including the city of Kuala Lumpur, Putrajaya,
and Cyberjaya (Table 8).
Table 8. Informant sampling.
Characteristic Quantity (N = 40) Percentage (%)
Gender
Male 19 47.5
Female 21 52.5
Age
23–30 years old 1 2.5
31–40 24 60.0
41–50 13 32.5
51 years old and above 2 5.0
Race
Malay 36 90.0
Chinese 2 5.0
Bumiputera Sabah and Sarawak 2 5.0
Academic qualification
Bachelor’s degree 26 65.0
Master’s degree 8 20.0
PhD 6 15.0
Employment sector
Government 32 80.0
Private 4 10.0
Self-employed 4 10.0
Work experience
5 to 8 years 4 10.0
9 to 10 years 8 20.0
11 to 15 years 13 32.5
16 to 20 years 8 20.0
21 years and above 7 17.5
Job Position
Director/CEO 12 25.5
Assistant director/Senior officer 10 21.3
Executive officer 8 17.0
Engineer/Planner/Architect 14 29.8
Technician 3 6.4
Sustainability 2021,13, 9559 11 of 31
As Table 8shows, this group of practitioners consisted of those in the government, pri-
vate, and self-employed sectors. They represented the middle class and various professional
job roles, such as director/CEO, assistant director/senior officer, executive officer, engi-
neer/planner/architect, and technician. Since the 1970s, the middle class has emerged as a
significant group contributing to the urbanization process in major cities in Malaysia [
107
].
Thus, the selection of professionals as respondents was significant given the composition
of this group, the majority of whom lived in urban areas. The professionals were selected
based on various criteria: they had to have a minimum of five-year work experience;
possess at least a bachelor’s degree; and be primarily involved in the planning, design,
delivery, and management of cities and their development.
The success of the Fuzzy Delphi method depends on the insights and information
supplied by experts. Thus, a panel of experts/respondents was identified through a
purposive sampling and nomination process, rather than random selection. Later, a focus
group discussion was organized, and data were collected.
3.3. Questionnaire Design
Through a structured questionnaire, a survey strategy of enquiry was conducted.
Three sections were used in the questionnaire to obtain information from the respondents.
Section one was designed to determine the respondent’s background. Section two focused
on their understanding, while section three focused on their acceptance of the MSCF’s
domains. The questionnaire adopted a closed-ended design. The respondents were asked
to rate the 90 variables based on their level of significance using a five-point Likert scale,
with five being Strongly Agree and one being Strongly Disagree. For the details of the
survey items, see Appendix A. Aghimien et al. [
14
] adopted a similar approach in their
study that evaluated the challenges facing smart cities.
3.4. Data Analysis
In addition, the Fuzzy Delphi method was chosen as the analysis technique to obtain
the agreement of experts, namely the professionals, based on the study objectives. The
Fuzzy Delphi method is a Delphi method performed to obtain information regarding
consensus on measurement variables or factors from a group of experts [
108
,
109
]. The
Delphi Method has been shown to be effective in publishing the best ideas/views through
collective responses from expert informants [
110
]. With the principle of “more minds are
better than a single mind”, the Fuzzy Delphi method is designed as a forecasting tool to
gather the ideas of structured groups, which are said to be more accurate than unstructured
predictions [
111
]. This technique allows experts to coordinate their actions systematically
in addressing a particular problem or difficulty and reach a consensus.
In this study, expert consensus was evaluated based on the seven MSCF domains,
namely the smart economy, smart living, smart environment, smart people, smart govern-
ment, smart mobility, and smart digital infrastructure. Each of these domains has its own
strategic initiatives to enable cities in Malaysia to achieve smart city status. Respondents’
understanding and acceptance were analyzed to achieve the objectives of the study.
Questionnaire data obtained from the focus group feedback of professionals were
analyzed using a formulated Microsoft Excel worksheet by [
106
]. The experts’ score inputs
were evaluated in stages. Mathematical scores—the Likert scale and the triangular fuzzy
scale scores for each item—were obtained (Table 9) and converted into mean values. Later,
the threshold value
(d)
, the percentage of expert agreement and the “defuzzification”
process of the fuzzy score with
α
-cut value were calculated. Finally, based on the above
three criteria, the ranking positions of the consensus items accepted/rejected by the expert
panel were analyzed.
Sustainability 2021,13, 9559 12 of 31
Table 9. Triangular fuzzy number scale [106].
Strongly Disagree Disagree Moderately Agree Agree Strongly Agree
Likert scale 1 2 3 4 5
Triangular fuzzy
Delphi scale 0.0 0.0 0.2 0.0 0.2 0.4 0.2 0.4 0.6 0.4 0.6 0.8 0.6 0.8 1.0
In detail, let us say the item “I am ready to use e-payment in my daily affairs” was
scored 5 (strongly agree) by an expert. The score is converted into the minimum, most
plausible, and maximum values of 0.6, 0.8, and 1.0 fuzzy scores. It indicated the expert is
agreeable to the item is 60%, 80%, and 100%, respectively. Then, the fuzzy scale of (0.6, 0.8,
1.0) is converted into mean value (m)among the 40 responds.
Next, according to [
112
], the calculation of the threshold (
d
) value performed was
as follows:
d(m,n)=r1
3[(m1n1)2+(m2n2)2+(m3n3)2](1)
where,
d= the threshold value,
m1= the smallest mean value of a fuzzy number,
m2= the most plausible mean value of a fuzzy number,
m3= the maximum mean value of a fuzzy number,
n1= the smallest value of a fuzzy number,
n2= the most plausible value of a fuzzy number, and
n3= the maximum value of a fuzzy number.
The value of ‘d’ (the threshold value) for all items of the questionnaire indicates expert
consensus agreement for each item. According to [
112
], the value of ‘d’ must be greater
than or equal to 0.2 to indicate consensus agreement for each item.
For the expert agreement/consensus percentage, if the expert consensus exceeded
75%, it was considered accepted [
113
,
114
]. Then, through the process of defuzzification or
the process of determining the scores, the ranking positions of each item were determined.
The formula used to determine the ranking/score for an item was as follows:
Amax =1
3(m1+m2+m3)(2)
After an assessment was made, if the fuzzy
(Amax )
score or
α
-cut value was equal to
or exceeded 0.5, this indicated expert consensus to accept the item [115].
The Delphi method is a widely accepted, efficient, and effective way of bringing
together experts to discuss, debate, and organize a body of information in order to develop
a validated instrument, reach agreement on an issue, uncover common factors, or forecast
trends [
116
,
117
]. This method is deemed particularly highly reliable when more than
ten experts in the given field were employed [
105
,
106
]. Additionally, to minimize the
bias, it is important to involve experts in a study that possess extensive experience, high
qualifications, and knowledge in the field or the subject matter [
118
]. Evidently, this study
meets these requirements as it has involved 40 experts with a minimum of five-year work
experience, possessed at least a bachelor’s degree, and involved intensively in the planning
and management of smart cities in the context of Malaysia (Table 8). Hence, we did not
employ an additional validation mechanism for the generated results of the Delphi study.
4. Results
In general, the understanding and acceptance of the targeted group of experts in this
study were contested. This shows that the community has different perceptions of the smart
city domains stated in the MSCF. This divergent phenomenon can be described in two
ways. Firstly, from the domain perspective, the majority of domains (i.e., smart economy,
Sustainability 2021,13, 9559 13 of 31
living, people, and governance) were accepted, two domains (i.e., smart environment
and digital infrastructure) were rejected, while the smart mobility domain was partially
accepted. Secondly, from the objective perspective, more than half of the domains were
accepted (Table 10).
Table 10. Results of Fuzzy Delphi analysis by smart city domains.
Domain Threshold (d) Value Expert Agreement (%) Average of Fuzzy Score
(Amax)Result Ranking by the
Fuzzy Score
(U) (A) (U) (A) (U) (A) (U) (A) (U) (A)
Smart Economy 0.142 0.139 76% 89% 0.725 0.731 Accepted Accepted 2 2
Smart Living 0.132 0.171 75% 91% 0.719 0.700 Accepted Accepted 4 4
Smart Environment 0.189 0.212 57% 55% 0.654 0.639 Rejected Rejected 7 7
Smart People 0.123 0.128 80% 83% 0.745 0.743 Accepted Accepted 1 1
Smart Government 0.188 0.184 92% 91% 0.704 0.698 Accepted Accepted 5 5
Smart Mobility 0.164 0.245 83% 56% 0.724 0.654 Accepted Rejected 3 6
Smart Digital
Infrastructure 0.204 0.150 72% 74% 0.670 0.725 Rejected Rejected 6 3
Note: U stands for Understanding, A stands for Acceptance. Three conditions to accept an item: threshold value (d)
0.2, percentage of
experts’ consensus 75%, and average fuzzy score (Amax )αcut value = 0.5.
To accept the criteria of the Fuzzy Delphi analysis, the results must meet three condi-
tions: (a) threshold value, d
0.2, (b) expert agreement percentage
75%, and (c) average
fuzzy score
(Amax )α
cut value = 0.5. Overall, all the domains fulfilled the third
criteria, with fuzzy scores equal to or exceeding 0.5. Meanwhile, the threshold value and
expert agreement showed mixed results.
To provide more detail on the item results, as shown in Table 11, the smart economy
and living had a 100% acceptance rate for the objective of Acceptance, hinting that these
two domains can be implemented directly at ground level with little modification. On
the other hand, the smart environment scored the lowest acceptance rates, 22.22% for the
Understanding objective and 33.33% for the Acceptance objective. This result indicates
that the smart environment domain has experienced great public dissensus and more
refinement is needed before its implementation to avoid later failures.
Table 11. Results of Fuzzy Delphi analysis by objectives.
Objective Domain Item Accepted Item % of Acceptance Rejected Item % of Rejection Fuzzy Score Interval
Understanding Economy 7 5 71.43 2 28.57 0.775 0.655 = 0.120
Living 5 4 75.00 1 25.00 0.775 0.620 = 0.155
Environment 9 2 22.22 7 77.78 0.745 0.572 = 0.173
People 6 4 66.67 2 33.33 0.765 0.715 = 0.050
Government 4 3 75.00 1 25.00 0.725 0.693 = 0.032
Mobility 8 6 75.00 2 25.00 0.755 0.685 = 0.070
Digital
Infrastructure 6 3 50.00 3 50.00 0.735 0.523 = 0.212
Acceptance Economy 7 7 100.00 0 0.00 0.770 0.710 = 0.060
Living 5 5 100.00 0 0.00 0.725 0.670 = 0.055
Environment 9 3 33.33 6 66.67 0.720 0.557 = 0.163
People 6 4 66.67 2 33.33 0.770 0.720 = 0.050
Government 4 3 75.00 1 25.00 0.715 0.680 = 0.035
Mobility 8 3 37.50 5 62.50 0.700 0.563 = 0.137
Digital
Infrastructure 6 4 66.67 2 33.33 0.760 0.655 = 0.105
Total 90 54 61.36 34 38.64
Note: Refer Appendix Bfor detailed calculations.
In general, the results of the analysis on the smart economy, living, people, and
governance domains met all three conditions of the Fuzzy Delphi method in terms of
Understanding and Acceptance. However, some item details must be addressed (refer to
Appendix B).
First, for the Understanding objective of the smart economy, the two rejected items
were items 3 (high value-added industry investment, with threshold value d= 0.21, and
expert agreement at only 33%) and 7 (assistance to business operations, with 73% expert
agreement). For the Acceptance objective of the smart economy, all the items were ac-
Sustainability 2021,13, 9559 14 of 31
cepted. For the high value-added industry investment, the respondents did not arrive at a
consensus. Some thought that the authorities should focus on the manufacturing sector,
especially in suburban and rural areas, instead of prioritizing high value-added industry,
which would accelerate the existing urbanization issues in metropolitan Malaysia, such as
in Kuala Lumpur and the Klang Valley area.
Second, under smart living, the only problematic Understanding item was item 1
(crime reduction). Respondents were less able to comprehend why Malaysia was stated
as having a high, instead of moderate, crime rate, since most of them lived in peaceful
environments. Meanwhile, they were inclined to accept that the MSCF would be able to
reduce the crime rate effectively through ICT applications, such as the installation of CCTV
in public areas.
Third, for the understanding and acceptance of smart people, all four rejected items
were due to the 70% to 73% expert agreement. For item 3, the acceptance of the education
policy for human capital development, respondents were not fully confident that the
restructuring of education at the tertiary level would produce innovative graduates. One
respondent commented that the current graduate market indicated that graduates were able
to perform at routine levels while lacking innovative thinking and solution-
creation skills.
Fourth, for the understanding and acceptance of smart governance, item 3—inter-
governmental data sharing—was the only item rejected as the threshold value d= 0.224
and 0.202. Respondent feedback suggested that they did not understand how inter-
governmental data could be shared in practice, as some were still experiencing issues
such as the separate performance of departments, the redundancy of providing data to
particular departments, and the inability to receive valid and complete data through
a single department enquiry. For example, the Department of Statistics does not pro-
vide open demographic data by city or district level so one needs to go to the particular
local authorities.
The major focus of this study should be the smart environment and digital infrastruc-
ture domains because both were rejected in terms of the understanding and acceptance
objectives. In general, for the environment, its threshold (d) construct for Acceptance (0.212)
was more than 0.2 while both values of expert agreement (57% for Understanding and 55%
for Acceptance) were less than 75%. For digital infrastructure, its threshold (d) construct
for Understanding (0.204) was also more than 0.2 while both values of expert agreement
(72% for Understanding and 74% for Acceptance) were also less than 75%. These negative
results show that the public remain less likely to understand and accept the components
planned in these two domains, smart environment, and digital infrastructure.
In detail, for the smart environment, the three lowest-ranked Understanding items
related to items 1 (park and green area management), 8 (non-revenue water management
and reporting), and 9 (low-carbon city and carbon emissions). Meanwhile, the three
lowest-ranked Acceptance items related to items 7 (readiness towards disaster-resilient
cities), 4 (air quality monitoring) and 2 (waste segregation and recycling). From the overall
perspective, the environment-related issues worrying the public are broad in scope and a
cause for grave alarm. The smart environment domain facings major public understanding
and acceptance issues and the authorities should prioritize improvements in this domain.
For the smart digital infrastructure, two items of interest in terms of Understanding
are items 6 (cybersecurity) and 5 (personal data protection); for Acceptance, they are items
1 (roles of service providers) and 2 (internet speed). It seems that respondents lacked
confidence in the authority’s online system security and personal data protection, and felt
they were vulnerable to cyber-attacks and personal data leaks. Attention should also be
given to the respondents who did not fully accept that private service providers were solely
responsible and thought that the government was too. Another important issue involved
rural areas with low internet speeds of 4G and below.
For the smart mobility, the result was accepted for Understanding but rejected for
Acceptance. The acceptance of respondents was rejected since the threshold (d) conduct
Sustainability 2021,13, 9559 15 of 31
was 0.245, which is over the 0.2 required; furthermore, the expert agreement of 56% was
much less than the 75% required.
Clearly, the rejection phenomenon identified for the Acceptance objective needs at-
tention. A low level of expert agreement was observed for items 6 (electric vehicle), 1
(smart traffic management), 8 (public transport application), and 5 (smart parking in-
frastructure). These results showed that the respondents were worried about the traffic
planning presented in the MSCF and were unconvinced by the solutions related to the
issues stated above.
5. Discussion
5.1. Voicing Dissensus Opinions for Building a More Inclusive Smart City Blueprint
The findings indicate divergent expert perceptions. The different job roles and em-
ployment sectors of the respondents could be expected to produce diverse results. Figure 4
summarizes the occurrence of three conditions.
Sustainability 2021, 13, x FOR PEER REVIEW 16 of 32
Figure 4. Dissensus opinions on the understanding and acceptance of smart city domains.
The dissensus in the results is a finding that leaders and policymakers should be
aware of. They should accept this reality and include those opinions that do not always
favor the majority. For example, people were dissatisfied with the smart environment do-
mains; for example, they did not comprehend the ineffectiveness of the authorities’ park
and green area management and preservation, nor did they accept that the authorities had
done enough pertaining to this matter. Evidence from [2,20] showed that the smart envi-
ronment covers a wide range of natural resources preservation and the resilience of hu-
man actions to the impact of climate change; thus, it is crucial to contemplate the divergent
opinions from the respondents.
For smart digital infrastructure, respondents did not recognize that their personal
data are protected by the Malaysia Personal Data Protect Act 2010; they felt unsafe from
cyber-attacks and were also unconvinced that the authorities would reduce cyber threats
and have a positive impact by protecting online users.
For smart mobility, although most understood that this domain is important, they
showed disagreement in accepting the implemented initiatives. For example, they did not
express confidence in the promotion of autonomous, and electric or green vehicles, smart
traffic light functioning, and public transport applications. This finding is interesting from
a global perspective as these measures are working elsewhere in other countries, meaning
they were understood by the respondents. However, it is clear that the authorities should
improve these matters to bring about greater local acceptance and avoid wasted invest-
ment. The following subsections provide various ideas for reconsidering the implementa-
tion of smart city domains in MSCF.
In the broader topic of smart city’s understanding and acceptance, the above result
reflected a developing country’s context and dynamic in practice [1,14]. The administra-
tors should be responsive and improve the smart city domains and strategies from time
to time. As for the specific scientific field, the smart environment needs more attention as
climate change is real [2,20,87] and applying smart digital infrastructure with higher se-
curity [21,22,37] to counter this global issue is urgently needed to be addressed.
5.2. Rethinking the Viability of Smart City Domains and Strategies
A smart economy tends to possess high value-added industries, so it is proposed that
high value-added industrial investment promotion initiatives be reconsidered geograph-
ically as the distribution of secondary industry is unbalanced and currently heavily favors
the Peninsula and urban areas [119]. Sabah and Sarawak are still heavily dependent on
primary products (i.e., timber, oil, and LNG). Targeting the relocation of manufacturing
sectors to less-developed areas, which would create new urban growth centers or smart
cities, needs far more attention, rather than targeting high-value investment in the already
mature urban and metropolitan areas. Furthermore, wages in less-developed areas need
Figure 4. Dissensus opinions on the understanding and acceptance of smart city domains.
The dissensus in the results is a finding that leaders and policymakers should be aware
of. They should accept this reality and include those opinions that do not always favor the
majority. For example, people were dissatisfied with the smart environment domains; for
example, they did not comprehend the ineffectiveness of the authorities’ park and green
area management and preservation, nor did they accept that the authorities had done
enough pertaining to this matter. Evidence from [
2
,
20
] showed that the smart environment
covers a wide range of natural resources preservation and the resilience of human actions
to the impact of climate change; thus, it is crucial to contemplate the divergent opinions
from the respondents.
For smart digital infrastructure, respondents did not recognize that their personal
data are protected by the Malaysia Personal Data Protect Act 2010; they felt unsafe from
cyber-attacks and were also unconvinced that the authorities would reduce cyber threats
and have a positive impact by protecting online users.
For smart mobility, although most understood that this domain is important, they
showed disagreement in accepting the implemented initiatives. For example, they did not
express confidence in the promotion of autonomous, and electric or green vehicles, smart
traffic light functioning, and public transport applications. This finding is interesting from
a global perspective as these measures are working elsewhere in other countries, meaning
they were understood by the respondents. However, it is clear that the authorities should
improve these matters to bring about greater local acceptance and avoid wasted investment.
The following subsections provide various ideas for reconsidering the implementation of
smart city domains in MSCF.
In the broader topic of smart city’s understanding and acceptance, the above result
reflected a developing country’s context and dynamic in practice [
1
,
14
]. The administrators
should be responsive and improve the smart city domains and strategies from time to
Sustainability 2021,13, 9559 16 of 31
time. As for the specific scientific field, the smart environment needs more attention
as climate change is real [
2
,
20
,
87
] and applying smart digital infrastructure with higher
security [21,22,37] to counter this global issue is urgently needed to be addressed.
5.2. Rethinking the Viability of Smart City Domains and Strategies
A smart economy tends to possess high value-added industries, so it is proposed that
high value-added industrial investment promotion initiatives be reconsidered geographi-
cally as the distribution of secondary industry is unbalanced and currently heavily favors
the Peninsula and urban areas [
119
]. Sabah and Sarawak are still heavily dependent on
primary products (i.e., timber, oil, and LNG). Targeting the relocation of manufacturing
sectors to less-developed areas, which would create new urban growth centers or smart
cities, needs far more attention, rather than targeting high-value investment in the already
mature urban and metropolitan areas. Furthermore, wages in less-developed areas need to
be improved since continuing to invest in high-value industries in urban areas will further
exacerbate the urbanization issues. Malaysia could learn from India in promoting balanced
and sustainable economic growth and ensuring all economic activities work well at the lo-
cal level (refer to [
20
]). Furthermore, Malaysia could also learn from Hong Kong in placing
greater focus on sharing economic activities among regions and in the re-industrialization
of the necessary supporting primary and secondary sectors (refer to [8]).
Another point to consider is the potential of e-commerce. Online transaction expansion
initiatives that are gaining a place in the hearts of consumers can be created in line with
the increasingly busy lifestyle of urban citizens. A study of online purchasing practices in
Malaysia by [
120
] found that buying online was chosen because it is a convenient and easy
way to shop for necessities while avoiding long queues at the counter. Online shopping
is a trend in modern society since internet usage has increased in the last decade. It has
accelerated under the stay-at-home new normality caused by the COVID-19 pandemic
threat. Thus, considering online shopping initiatives as part of the smart economy initiative
should enable improvements in the economic status of urban residents, either as traders or
customers, which would facilitate the lives of both parties [25].
For smart living, the experts rejected the understanding that the crime rate in Malaysia
remains high compared to other countries. The respondents thought that the crime rate was
under control level. This opinion matches the findings of [
121
], whose local studies in Kuala
Lumpur showed that city residents are comfortable with the crime situation. Additionally,
Ref. [
121
] found that the perception that the crime rate was high in Malaysia actually did
exist in the foreign discourse. Thus, the authorities could consider all such perspectives,
turning their focus to the means of adaptation to the fear of crime, the omnipresence of
police in public spaces, and assistance to prevent criminal acts in community areas [
47
,
121
].
Furthermore, in terms of smart living, voluntary and more active community in-
volvement initiatives related to the safety, educational, and health aspects of the local
community can be added to reduce the extent of the dependence on government resources.
According to [
122
], community involvement ensures that the needs and aspirations of the
community are not neglected; the result is that community members will be educated and
subsequently empowered. This shows that the role of the community can resolve local
issues more effectively.
In terms of smart people, referring to skilled and talented human capital, the gov-
ernment must rethink tertiary education and determine how to actively produce digitally
talented innovative graduates to suit the value-added industry in the Industry 4.0 era.
More structured and holistic learning opportunities within the areas of IoT devices devel-
opment, telecommunications, middleware, big data analytics, and artificial intelligence
are needed. This is because engineering students currently focus mainly on hardware
and connectivity aspects while computer science students learn middleware and big data
analytics separately [
104
]. To adopt Industry 4.0 technologies in Malaysian smart city
society, a radical paradigm shift in educating graduates so they transform into talented
human capital should be the priority, a notion that was reaffirmed by the Prime Minis-
Sustainability 2021,13, 9559 17 of 31
ter [
67
]. Thus, the 2013 national education policy is somewhat outdated, so rethinking
how to enhance it through the Industry 4.0 perspective is crucial. Questions such as how
to nurture young people so they master the fundamental Industry 4.0 technologies in
stages, from primary, secondary, and tertiary education up to life-long learning for the
elderly community members, should become the central aim in formulating a new national
education policy.
Next, moral and ethical development, as mentioned in the MSCF, is considered a good
move for developing countries like Malaysia, as many Western developed countries have
resolved this moral element (refer to [
2
]). As mentioned in the literature, Ungku Aziz’s
1980s ideas are still considered fundamental and remain relevant enough to be adopted in
the current smart city development in Malaysia. Although the values of education related
to moral development were stated in the National Education Blueprint 2013, the latest
education plan could be enhanced based on the five principles of Maqasid Al-Syariah,
namely caring for religion, caring for life, caring for intellect, caring for one’s offspring,
and caring for property. Maqasid Al-Syariah refers to the noble purpose of Islamic law,
which is based on the principle of Maslahat and which mankind could universally obtain
through the text or authority of Islamic law [
123
]. This universal concept is seen by all
as practicable.
Another aspect to enhance in terms of smart people in Malaysia is the level of civic par-
ticipation in local authority decision-making and programs [
73
]. Participation in decision-
making differs from community empowerment: the former involves the level of citizen
power and can influence agenda setting, while the latter refers to the tokenism level of ser-
vice delivery stages [
61
]. Furthermore, in the former, people are active in decision-making
and co-creating with the authorities, whereas, in the latter, people tend to be in a weaker,
beneficiary, or reactive position when they are deemed ‘empowered’ by the authorities.
Contemplating the lower level of participation in decision-making in Malaysia, the au-
thors argue that the implementation of the MSCF could enhance the extent of this form
of participation. Although it may face dissensus of opinion, in the long term, this move
will help in building more democratic spaces and independent citizenship for Malaysian
nation-building [124].
On the governance issue, excessive bureaucracy, delays in approving applications and
licenses, as well as a lack of information on new policies and regulations are among the
main problems plaguing the government’s delivery system [
81
,
82
]. Inter-governmental
data sharing is another challenge due to the separate departmental practices in Malaysia.
To address this, Hong Kong’s initiatives can be adopted, such as building a new big data
analytics platform; adopting public cloud services, which would enable real-time data
transmission and sharing among government departments; and enhancing security features
so that government departments can deliver efficient and agile e-services [
8
]. Future smart
city governance should make effective use of their data assets to secure outcomes that
are appropriate to citizens’ needs. Investment by agencies in system-wide data capture,
integration, and analytics capabilities [75] is a crucial aspect to develop.
Apart from data sharing, smart governance ultimately aims to produce public values
for citizens, such as from the perspective of asset management and financial and economic
sustainability [
93
]. To realize such public values, e-democracy must be upheld through
active e-voting and e-decision making [
71
], which is a major topic for Malaysian smart
development advocates to deliberate. According to the Democracy Index 2020, out of
167 countries, Malaysia (ranked 39) and India (ranked 53) fell into the category of flawed
democracies. Meanwhile, Hong Kong ranked 87 due to its hybrid regime of flawed
democracy and authoritarian control [
125
]. In terms of the purpose of building independent
citizens [
2
] within the conception that smart cities are democratic ecologies [
126
], Malaysia
and similar places must actually strive further to achieve higher transparency and open
governance. As suggested by [
127
], ‘good enough governance’ for smart city societies in
Malaysia should consider the cultural context of the Muslim majority, prioritize governance
Sustainability 2021,13, 9559 18 of 31
content that allows more scope for political participation and free speech, and cultivate the
imagination and unselfishness of children.
Furthermore, it was found that the understanding and acceptance of initiatives in the
smart environment is the most critical among all the domains. In this regard, announce-
ments on smart environment initiatives must be intensified and expanded to ensure the
sustainability of the existing environment. Most importantly, the authors’ view is that
environmental accountability initiatives must be added to this component to enable each
party to understand the concept and play their respective roles in caring for the environ-
ment. In the case of maintaining a clean environment, Ref. [
57
] found that all stakeholders
should take responsibility, not solely the authorities. Efforts to maintain and preserve
the environmental space relate to the question of community awareness and attitude,
which, if sufficiently high, would ensure that the environment is always clean, healthy,
and sustainable.
In terms of preserving parks and green spaces in urban areas, Malaysia’s develop-
ment control guidelines set a minimum of 10% green and open space reservation, which
is considered relatively low. In comparison, the city of Wuhan, China, has launched its
Wuhan Low-Carbon Urban Development Plan 2013, which reserves 28% for green ar-
eas in the city [
48
]. Therefore, a rethink is suggested that would impose a greater green
space allocation in new development plans and, together with agencies such as PLAN-
Malaysia, the MSCF could incorporate this higher green space allocation as one of its smart
environment initiatives.
In terms of smart mobility and, in particular, electrical vehicles (EVs) in Malaysia,
Putrajaya city bought 150 electric buses (each costing RM 1.5 million). They operate
in Putrajaya and the vicinity, the aim being to cut carbon emissions, noise pollution,
and traffic congestion while improving public transport and parking systems [
128
]. The
operation of the electric buses is calibrated by battery capacity and charging facilities
and has been found to outperform conventional bus operations [
129
]. However, cases
of the inefficiency of public transport management were identified, whereby the electric
buses were found abandoned at the Depoh Putrajaya. Bus breakdowns are frequent due
to lack of maintenance, unreliable and delayed bus arrival times, and reductions in bus
routes [
130
]. Thus, although electric cars are efficient in costs and energy saving with
long-term usage [
84
], the adoption of an EV ecosystem is required, involving features such
as efficient management and the availability of efficient power charging stations.
As for privately-owned electric cars, it has been found that the understanding and
acceptance of the community is still low. The respondents in this study felt the costs
involved in owning and maintaining a private electric vehicle were higher than those of a
typical vehicle. It is true that research has shown that the cost of electric vehicle ownership
in Malaysia is not yet as competitive as typical internal combustion vehicles [
131
]. This
shows the market and society acceptance of electric cars remains still low. Those involved
in the MSCF should rethink the issues of EVs, along with the latest National Automotive
Policy 2020, in promoting affordable new technologies. For example, incentives and
funding are available under the National Automotive Policy 2020 to develop the technology
and engineering required for NxGV (next-generation vehicles), autonomous vehicles, MaaS
(mobility-as-a-service), and Industry 4.0 [
132
]. Thus, MSCF initiatives such as promoting
collaboration with the private sector in developing affordable EVs could be implemented.
Last but not least, for the smart digital infrastructure, in terms of the cybersecurity
and personal data protection issues, it seems that the MSCF did not provide clear direction
on how to strengthen the necessary cybersecurity and personal data protection. The
ranking of Malaysia as eighth out of 194 countries in the Global Cybersecurity Index
2021 [
133
] seems to contradict the results of this study’s finding. Recently reported cyber
intrusion cases [
103
] were over the targeted 9000 to 10,000 per year [
9
], and the assessment
of the National IoT Strategic Roadmap was also ambiguous [
104
]. All the supporting
agencies, such as Cybersecurity Malaysia, the Department of Personal Data Protection, and
the Malaysia Administrative Modernization and Management Planning Unit must work
Sustainability 2021,13, 9559 19 of 31
more closely together and actively provide improvements or amendments to the policies,
especially more strict enforcement of the Malaysian Personal Data Protection Act 2010.
As for the issues of low internet speed and digital infrastructure coverage in less-
developed states and rural areas, more MSCF initiatives could be planned in conjunction
with the latest National Digital Infrastructure Plan (JENDELA), the Malaysian Industry 4.0
Policy, and the Malaysia Digital Economy Blueprint (MyDigital). For instance, the current
wireless broadband coverage in Malaysia is 96.7% for 2G, 95.3% for 3G, and 91.8% for
4G coverage in populated areas, with 25 Mbps speed [
134
]. Therefore, MSCF initiatives
could plan to achieve 100% 4G coverage in populated areas and a speed of 100 Mbps by
adopting 5G.
6. Conclusions
First, Malaysia’s experience in smart city development dates back to 1996 Multimedia
Super Corridor Malaysia initiative and the later efforts in developing research universities
and integrating them with the city they are located [
135
,
136
]—through knowledge-based
urban development principles to make space and place for smart urban communities [
137
].
Today, with its new smart city framework, Malaysia aims to transform its cities and
societies into smarter ones. This paper aims to generate insights into how this framework
is perceived with professional practitioners. In order to do so, this study conducted an
empirical investigation concerning the seven smart city domains planned as part of a
top-down national policy of the Malaysian Smart City Framework (MSCF). The findings
disclosed that smart environment and digital infrastructure require the most attention,
followed by smart mobility, governance, living, economy, and people.
Second, this study has contributed to the smart city discourse and literature particu-
larly by examining the levels of understanding and acceptance from the multi-perspectives
of practitioners from various sectors. The study is unique as it is one of the first in capturing
professional practitioners’ voices and perspectives on a national level smart city policy that
impacts a large portion of the population. This finding is an important insight added to
the literature investigating, in detail, smart city domains in practice. The divergent and
dissensus opinions from the ground are valuable references for leaders and policymakers
to consider in building a more inclusive and smarter city blueprint. Furthermore, applying
the Fuzzy Delphi method in smart city studies is rather new. It has great potential to
be explored and expanded into urban studies and planning disciplines as this method is
popular in education, business, and management studies [138].
Last, the limitations of this study are the selection of purposive sampling for the Fuzzy
Delphi analysis and the formulation of questionnaire items from the broader scopes of
the smart city domains. Thus, based on the smart city domains and after designing two
objectives of understanding and acceptance, future studies could explore other qualitative
or quantitative methods to justify the results in this study. Other studies that evaluate the
implementation of the smart city domain objectives could be conducted, such as using
structural equation modelling to assess the implementation of smart city strategies in
Greece [
139
] and acceptance of smart meters in Malaysia [
37
]. Moreover, future studies
could be expanded to capture the voices and perspectives of the general public on national
and local smart city strategy and initiatives. This will be the focus of our prospective study.
Author Contributions:
Conceptualization and methodology, writing—original draft preparation,
software, formal analysis, investigation, and data curation, S.B.L.; supervision, validation, resources,
funding acquisition, project administration, review and editing, J.A.M., M.F.Y.M.Y. and T.Y. All
authors have read and agreed to the published version of the manuscript.
Funding:
The study received funding support from the Malaysian Ministry of Higher Education
(grant number FRGS/1/2019/SS06/UKM/02/2). The funder was not involved in the planning,
execution, write-up, or other contents of this article.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement:
Informed consent was obtained from all participants involved in
the study.
Sustainability 2021,13, 9559 20 of 31
Data Availability Statement: Data are contained within the article and appendixes.
Acknowledgments:
The authors wish to thank study participants, managing editor and three
anonymous reviewers for their invaluable comments and constructive critiques.
Conflicts of Interest:
The authors declare no conflict of interest and have no financial or proprietary
interests in any material presented/discussed in this article.
Appendix A. Survey Items
Table A1. Domain 1: Smart Economy.
Item Understanding Acceptance
Intensify technology application and
digitalization in core business functions
I am aware that the use of technology in the
services sector needs to be expanded and
intensified in order to be able to compete with
the use of technology in the manufacturing
sector.
I am sure the application of technology and
digitization in core business functions can be
implemented quickly.
Enhance the usage of e-payment I understand that the widespread use of debit
and credit cards catalyzes e-payment.
I am ready to use e-payment in my daily
affairs.
Attract investment in high value-added
industries
I understand that investment promotion
activities have been restructured to target high
value-added industry investors.
I am confident that the attractiveness of high
value-added investments can be increased
from time to time.
Create a workforce to match jobs in high
value-added industries
I am aware that computer science skills and
critical thinking need to be widely
disseminated as the high value-added industry
sector requires creative and innovative
employees.
I am sure the matching of high-income work
with high value-added industries can be more
efficient.
Provide technology labs and collaborative
platforms
I understand that the strengthening and
establishment of technology laboratories can
help entrepreneurs to become more efficient in
penetrating a wider market.
I am confident that the establishment of
technology laboratories and collaborative
platforms can enhance knowledge exchange in
various fields.
Establish incubators and accelerators I understand that incubators and drivers need
to work more closely to meet market needs.
I am sure the creation of incubators and
drivers can help realize new ideas to produce
more competitive businesses that impact the
local community and society.
Leverage existing government assistance and
funding
I understand that the assistance provided by
various government agencies should be used
optimally to improve business operations.
I am confident that the optimal use of facilities
provided by the Government can help
improve business operations.
Table A2. Domain 2: Smart Living.
Item Understanding Acceptance
Enhance safety and security through
perspectives of crime
I understand the crime rate in Malaysia is
still high compared to other countries.
I am sure the installation of analytical
proactive surveillance, such as CCTV, can
reduce the crime rate in Malaysia.
Promote quality housing I understand the promotion of the smart
home can improve the quality of life.
I believe that the adoption of smart home
applications, such as facial recognition
systems and IoT lighting, could provide
better quality housing.
Optimize emergency response
I understand that an emergency call
center can help in cases of emergency,
such as fire.
I believe that the adoption of an
emergency call center with a real-time
mobile rescue application is crucial when
an emergency occurs.
Enhance the quality of healthcare services
I believe good healthcare can improve the
quality of life.
I believe that the Smart City Framework
is able to facilitate public health services.
Encourage urban farming for better living
I believe that urban farming activities can
enhance the relationship between
neighbors and their sense of belonging.
I am confident that through urban
farming, a community can work together
more closely and appreciate each other.
Sustainability 2021,13, 9559 21 of 31
Table A3. Domain 3: Smart Environment.
Item Understanding Acceptance
Preserve green areas and enhance the
management of trees in public parks
I understand that local authorities have
improved the management efficiency of
public parks, such as adapting the use of
smart management systems to preserve
green areas (i.e., the use of RFID
technology to inventory existing trees).
I gain positive effects from the use of
well-managed public parks and green
areas by local authorities, such as
increased social interaction, peace of
mind, and stress reduction.
Strengthen integrated and sustainable
solid waste management
I am aware that waste segregation at
source and the recycling of waste are the
best solid waste management methods to
maintain environmental sustainability.
I always practice waste segregation at
source and the recycling of waste items at
home and work.
Strengthen the solid waste laws and
policies
I am of the view that the government has
provided adequate laws and policies to
improve solid waste management in the
country.
I am confident that the laws and policies
formulated by the government can
improve the sustainability of the
country’s solid waste management.
Improve the air quality and its
monitoring system
I am aware of the importance of using
public transport as an initiative to reduce
carbon emissions that can affect the
environmental air quality.
I strive to increase my use of modes of
public transportation in day-to-day
affairs to help reduce carbon emissions.
Improve the water quality and its
monitoring system
I understand that the government has,
over time, improved the efficiency of the
water monitoring system technology.
I am confident that the improvement of
water monitoring system technology in
urban areas by the government will
provide a high-quality, clean water source
for residents.
Increase energy efficiency and promote
renewable energy sources
I find that efforts are being made by the
government and the private sector to
increase the use of renewable energy in
the community.
I have applied the use of energy-efficient
appliances, such as LED lighting, at home
and at work to reduce the use of
electricity generated from fossil fuels.
Enhance disaster risk management by
adopting advanced technology
applications
I understand that the government has
implemented disaster risk management
through the use of the latest technology,
such as warning delivery systems, to
facilitate the delivery of information to
the public.
I participate in disaster management
awareness programs organized at the
community level so that I can be better
prepared in the event of a disaster.
Enhance Non- Revenue Water
Management
I am of the view that public
understanding of the importance of
non-revenue water management in water
resources management has increased.
I immediately make an online report to
the agency or responsible party when
faced with incidents such as a burst pipe.
Encourage the development of the
low-carbon city concept to be adopted at
the local level
I understand that the implementation of
initiatives to reduce carbon emissions
from buildings and vehicles has been
implemented in tandem with the
urbanization process.
I believe the development of low-carbon
cities by private developers is a positive
step towards reducing the carbon
footprint of urban areas.
Table A4. Domain 4: Smart People.
Item Understanding Acceptance
Improve moral education in schools
I agree that the element of moral
education among the younger generation
is important as it is an initial step in the
formation of an ethical society.
I welcome the government’s intention to
improve moral education and prioritize it
in the early stages of schooling.
Enhance public awareness in practicing
good morals and civics
I understand and realize that the concept
of a moral and ethical society is an
important element in building a smart
city culture.
I agree that the building of a smart city
community culture can be achieved
through civic awareness programs on
public facilities, the environment, and the
importance of community living.
Sustainability 2021,13, 9559 22 of 31
Table A4. Cont.
Item Understanding Acceptance
Increase the volume of skilled and
talented human capital at every level
I think that the formation of an educated
and highly skilled generation is an
important aspect of building a
knowledgeable society as part of the
construction of smart cities.
I am confident that the restructuring of
the education policy at every level in the
fields of research, science and technology
will produce a generation of
highly-educated, skilled and innovative
people.
Enhance public participation and
community empowerment initiatives
I realize that community participation,
community engagement, and community
empowerment are highly important in
every policy formation of a country and
lead to the well-being of the people.
I agree the community needs to be
directly involved in the making of every
government policy and initiative through
a simple and fast digital platform.
Improve gender sensitization and the
inclusivity of vulnerable groups
I am aware that the interests and needs of
women and people with disabilities
(OKU) must be taken into account in
every aspect of urban development
planning.
I support the idea that facilities are
provided in every urban development,
which through a digital medium, take
into account the needs and safety of all
groups, especially women and people
with disabilities (OKU).
Increase public willingness to adapt to
emerging technologies
I understand that the concept of the
smart city formation will be formed from
a skilled and efficient society and with
the use of IT.
I agree that it is time for digital skills to
be learned earlier in childhood and
subsequently introduced into continuous
learning in the community through
digital billboards placed in public spaces.
Table A5. Domain 5: Smart Government.
Item Understanding Acceptance
Increase the scope of e-government
services
I understand that through the Smart City
Framework, the government can widen
the scope of government services to the
community.
I believe that through the Smart City
Framework, a wider range of
government services will be available to
the community.
Increase the quality of e-government
services
I understand that the use of the Smart
City Framework can improve the quality
of e-government services.
I believe the Smart City Framework can
improve e-government services to the
community.
Elevate the use of data sharing platforms
across government agencies
I am confident that if inter-governmental
data sharing works well, there will be
fewer community complaints and
better-quality government/private
services.
Through inter-governmental data
sharing, I have received valid and
accurate data/information from
government/private organizations.
Promote the use of information
disclosure and open data on behalf of the
government
I understand that the dissemination of
open data and authentic information can
expedite the transparency of
governmental services.
I agree that the accessibility of open data
and information dissemination would
benefit all.
Table A6. Domain 6: Smart Mobility.
Item Understanding Acceptance
Establish intelligent transport
management
I understand the importance of smart
transportation management, such as the
use of smart traffic lights, the use of
sensors for traffic management, and
pollution tracking.
I am satisfied with the way smart
transportation management functions,
such as with the use of smart traffic lights,
the use of sensors for traffic management,
and pollution tracking.
Sustainability 2021,13, 9559 23 of 31
Table A6. Cont.
Item Understanding Acceptance
Enhance the use of data sharing and
digital mobility platforms
I understand the importance of data
sharing and digital mobility platforms.
I am willing to use data sharing and
digital mobility platforms.
Establish demand-based ridesharing
services
I know about on-demand ridesharing
service applications for vans or shuttle
buses, trains, Grab, or SOCAR.
I use on-demand ridesharing service
applications for vans or shuttle buses,
trains, Grab, or SOCAR services.
Utilize AI and sensor-based predictive
maintenance for the public transport fleet
and infrastructure
I understand the use of AI (Artificial
Intelligence) and sensor-based
maintenance forecasting for the public
transportation infrastructure and traffic.
I agree that AI and sensor-based forecast
maintenance for the public transport
infrastructure is required so that forecast
maintenance can take place before
damage and disruption occurs.
Enhance the dynamic smart parking
infrastructure
I know about dynamic smart parking
infrastructures, like smart parking meters
and apps that provide real-time parking
vacancy information.
I use smart parking infrastructure, such
as smart parking meters and apps that
provide real-time parking vacancy
information.
Establish an electric vehicle revolution
I understand the importance and
necessity of the electric vehicle
revolution.
I have used electric cars/green
vehicles/energy-efficient
vehicles/electric buses.
Enhance collaboration with academia on
R&D into, and the commercialization of,
EVs and next-generation automobile
I understand the importance of
collaborating with academics and the
private sector in R&D into, and the
commercialization of, next-generation
electric vehicles and cars.
I am willing to work with academics and
the private sector on the framework,
testing, and regulation of autonomous
vehicles/long-term transit planning.
Promote the usage of public transport
applications
I know about applications regarding
travel on public transport services such
as buses, trains, or taxis.
I use applications regarding travel on
public transport services such as buses,
trains or taxis.
Table A7. Domain 7: Smart Digital Infrastructure.
Item Understanding Acceptance
Enhance the roles of service providers in
developing digital infrastructure
I am confident that the infrastructure
sharing policy among service providers
will provide better high-speed internet
services.
I understand that the role of completing
the communication infrastructure of a
new development project is the
responsibility of the developer.
Enhance internet speed and connectivity
I know that the government will enforce
minimum internet speed standards in
stages.
I am aware that most major cities in
Malaysia are equipped with 4G
high-speed internet facilities.
Enhance the government’s role in
facilitating the development of
communication infrastructure
I understand that the government always
assists service providers in facilitating the
development of communication
infrastructure.
I believe that the Malaysian Commission
of Communications and Multimedia
(MCMC) should enforce the appropriate
standards for network services.
Enhance indoor and outdoor network
coverage
I agree that development companies need
to equip new development projects with
fiber optic lines to support the Smart City
policy.
I agree that new buildings are equipped
with in-building fiber optic network
access facilities.
Strengthen policies related to personal
data protection
I am confident that the personal
information of internet users is protected
by the Personal Protection Act 2010.
I am sure that the reduction of cyber
threats will have a positive impact on the
government, companies and individuals.
Strengthen policies related to
cybersecurity
I understand that online systems and
information are safe from cyber-attacks.
I feel that policies and laws related to
cybersecurity and personal data need to
be updated periodically to protect
consumers.
Sustainability 2021,13, 9559 24 of 31
Appendix B. Fuzzy Delphi Analysis Results
Table A8. Domain 1: Smart Economy (Understanding).
No.
Triangular Fuzzy Number Defuzzification Process
Result
Ranking
according to the
Fuzzy Score
Threshold
(d) Value
Expert
Agreement (%) m1m2m3Average of
Fuzzy Score
1 0.067 88% 0.575 0.775 0.975 0.775 Accepted 1
2 0.107 78% 0.555 0.755 0.955 0.755 Accepted 2
3 0.210 33% 0.455 0.655 0.855 0.655 Rejected 7
4 0.130 78% 0.545 0.745 0.945 0.745 Accepted 3
5 0.193 88% 0.490 0.690 0.890 0.690 Accepted 6
6 0.156 98% 0.515 0.715 0.915 0.715 Accepted 5
7 0.133 73% 0.540 0.740 0.940 0.740 Rejected 4
Table A9. Domain 1: Smart Economy (Acceptance).
No.
Triangular Fuzzy Number Defuzzification Process
Result
Ranking
according to the
Fuzzy Score
Threshold
(d) Value
Expert
Agreement (%) m1m2m3Average of
Fuzzy Score
1 0.080 88% 0.570 0.770 0.970 0.770 Accepted 1
2 0.130 78% 0.545 0.745 0.945 0.745 Accepted 3
3 0.179 90% 0.510 0.710 0.910 0.710 Accepted 7
4 0.156 98% 0.515 0.715 0.915 0.715 Accepted 4
5 0.158 98% 0.510 0.710 0.910 0.710 Accepted 6
6 0.156 98% 0.515 0.715 0.915 0.715 Accepted 4
7 0.115 75% 0.550 0.750 0.950 0.750 Accepted 2
Table A10. Domain 2: Smart Living (Understanding).
No.
Triangular Fuzzy Number Defuzzification Process
Result
Ranking
according to the
Fuzzy Score
Threshold
(d) Value
Expert
Agreement (%) m1m2m3Average of
Fuzzy Score
1 0.206 35% 0.420 0.620 0.820 0.620 Rejected 5
2 0.101 83% 0.560 0.760 0.960 0.760 Accepted 2
3 0.171 81% 0.41 0.78 0.87 0.687 Accepted 4
4 0.113 83% 0.555 0.755 0.955 0.755 Accepted 3
5 0.069 90% 0.575 0.775 0.975 0.775 Accepted 1
Table A11. Domain 2: Smart Living (Acceptance).
No.
Triangular Fuzzy Number Defuzzification Process
Result
Ranking
according to the
Fuzzy Score
Threshold
(d) Value
Expert
Agreement (%) m1m2m3Average of
Fuzzy Score
1 0.179 90% 0.470 0.670 0.870 0.670 Accepted 5
2 0.183 90% 0.500 0.700 0.900 0.700 Accepted 3
3 0.165 85% 0.492 0.824 0.741 0.686 Accepted 4
4 0.155 95% 0.525 0.725 0.925 0.725 Accepted 1
5 0.172 93% 0.510 0.710 0.910 0.710 Accepted 2
Table A12. Domain 3: Smart Environment (Understanding).
No.
Triangular Fuzzy Number Defuzzification Process
Result
Ranking
according to the
Fuzzy Score
Threshold
(d) Value
Expert
Agreement (%) m1m2m3Average of
Fuzzy Score
1 0.242 35% 0.375 0.570 0.770 0.572 Rejected 9
2 0.128 70% 0.540 0.740 0.940 0.740 Rejected 2
3 0.214 35% 0.425 0.625 0.825 0.625 Rejected 5
4 0.122 73% 0.545 0.745 0.945 0.745 Rejected 1
5 0.155 93% 0.530 0.730 0.930 0.730 Accepted 3
6 0.193 90% 0.490 0.690 0.890 0.690 Accepted 4
7 0.244 23% 0.400 0.600 0.800 0.600 Rejected 6
8 0.201 48% 0.390 0.585 0.785 0.587 Rejected 8
9 0.204 45% 0.400 0.590 0.790 0.593 Rejected 7
Sustainability 2021,13, 9559 25 of 31
Table A13. Domain 3: Smart Environment (Acceptance).
No.
Triangular Fuzzy Number Defuzzification Process
Result
Ranking
according to the
Fuzzy Score
Threshold
(d) Value
Expert
Agreement (%) m1m2m3Average of
Fuzzy Score
1 0.174 50% 0.425 0.625 0.825 0.625 Rejected 6
2 0.233 33% 0.395 0.590 0.790 0.592 Rejected 7
3 0.219 35% 0.445 0.640 0.840 0.642 Rejected 4
4 0.260 38% 0.380 0.570 0.770 0.573 Rejected 8
5 0.189 88% 0.505 0.705 0.905 0.705 Accepted 2
6 0.181 90% 0.505 0.705 0.905 0.705 Accepted 2
7 0.256 38% 0.360 0.555 0.755 0.557 Rejected 9
8 0.246 30% 0.435 0.630 0.830 0.632 Rejected 5
9 0.153 98% 0.520 0.720 0.920 0.720 Accepted 1
Table A14. Domain 4: Smart People (Understanding).
No.
Triangular Fuzzy Number Defuzzification Process
Result
Ranking
according to the
Fuzzy Score
Threshold
(d) Value
Expert
Agreement (%) m1m2m3Average of
Fuzzy Score
1 0.088 83% 0.565 0.765 0.965 0.765 Accepted 1
2 0.107 78% 0.555 0.755 0.955 0.755 Accepted 2
3 0.133 73% 0.540 0.740 0.940 0.740 Rejected 5
4 0.122 73% 0.545 0.745 0.945 0.745 Rejected 4
5 0.122 80% 0.550 0.750 0.950 0.750 Accepted 3
6 0.169 93% 0.515 0.715 0.915 0.715 Accepted 6
Table A15. Domain 4: Smart People (Acceptance).
No.
Triangular Fuzzy Number Defuzzification Process
Result
Ranking
according to the
Fuzzy Score
Threshold
(d) Value
Expert
Agreement (%) m1m2m3Average of
Fuzzy Score
1 0.110 80% 0.555 0.755 0.955 0.755 Accepted 2
2 0.080 88% 0.570 0.770 0.970 0.770 Accepted 1
3 0.128 70% 0.540 0.740 0.940 0.740 Rejected 3
4 0.133 73% 0.540 0.740 0.940 0.740 Rejected 3
5 0.150 95% 0.530 0.730 0.930 0.730 Accepted 5
6 0.165 93% 0.520 0.720 0.920 0.720 Accepted 6
Table A16. Domain 5: Smart Government (Understanding).
No.
Triangular Fuzzy Number Defuzzification Process
Result
Ranking
according to the
Fuzzy Score
Threshold
(d) Value
Expert
Agreement (%) m1m2m3Average of
Fuzzy Score
1 0.182 95% 0.505 0.700 0.900 0.702 Accepted 2
2 0.192 90% 0.495 0.695 0.895 0.695 Accepted 3
3 0.224 88% 0.500 0.690 0.890 0.693 Rejected 4
4 0.155 95% 0.525 0.725 0.925 0.725 Accepted 1
Table A17. Domain 5: Smart Government (Acceptance).
No.
Triangular Fuzzy Number Defuzzification Process
Result
Ranking
according to the
Fuzzy Score
Threshold
(d) Value
Expert
Agreement (%) m1m2m3Average of
Fuzzy Score
1 0.176 95% 0.495 0.695 0.895 0.695 Accepted 3
2 0.169 93% 0.515 0.715 0.915 0.715 Accepted 1
3 0.202 85% 0.480 0.680 0.880 0.680 Rejected 4
4 0.191 90% 0.500 0.700 0.900 0.700 Accepted 2
Sustainability 2021,13, 9559 26 of 31
Table A18. Domain 6: Smart Mobility (Understanding).
No.
Triangular Fuzzy Number Defuzzification Process
Result
Ranking
according to the
Fuzzy Score
Threshold
(d) Value
Expert
Agreement (%) m1m2m3Average of
Fuzzy Score
1 0.137 75% 0.540 0.740 0.940 0.740 Accepted 3
2 0.130 78% 0.545 0.745 0.945 0.745 Accepted 2
3 0.113 83% 0.555 0.755 0.955 0.755 Accepted 1
4 0.209 85% 0.495 0.695 0.895 0.695 Rejected 7
5 0.147 80% 0.540 0.740 0.940 0.740 Accepted 3
6 0.220 85% 0.485 0.685 0.885 0.685 Rejected 8
7 0.175 90% 0.515 0.715 0.915 0.715 Accepted 6
8 0.177 90% 0.520 0.720 0.920 0.720 Accepted 5
Table A19. Domain 6: Smart Mobility (Acceptance).
No.
Triangular Fuzzy Number Defuzzification Process
Result
Ranking
according to the
Fuzzy Score
Threshold
(d) Value
Expert
Agreement (%) m1m2m3Average of
Fuzzy Score
1 0.311 20% 0.390 0.590 0.790 0.590 Rejected 7
2 0.184 90% 0.485 0.685 0.885 0.685 Accepted 4
3 0.227 80% 0.490 0.690 0.890 0.690 Rejected 3
4 0.176 93% 0.500 0.700 0.900 0.700 Accepted 1
5 0.245 25% 0.465 0.660 0.860 0.662 Rejected 5
6 0.346 25% 0.380 0.555 0.755 0.563 Rejected 8
7 0.200 93% 0.495 0.690 0.890 0.692 Accepted 2
8 0.273 20% 0.460 0.650 0.850 0.653 Rejected 6
Table A20. Domain 7: Smart Digital Infrastructure (Understanding).
No.
Triangular Fuzzy Number Defuzzification Process
Result
Ranking
according to the
Fuzzy Score
Threshold
(d) Value
Expert
Agreement (%) m1m2m3Average of
Fuzzy Score
1 0.165 95% 0.530 0.725 0.925 0.727 Accepted 2
2 0.217 85% 0.495 0.690 0.890 0.692 Accepted 3
3 0.191 93% 0.485 0.680 0.880 0.682 Accepted 4
4 0.144 73% 0.535 0.735 0.935 0.735 Rejected 1
5 0.214 30% 0.460 0.660 0.860 0.660 Rejected 5
6 0.291 58% 0.330 0.520 0.720 0.523 Rejected 6
Table A21. Domain 7: Smart Digital Infrastructure (Acceptance).
No.
Triangular Fuzzy Number Defuzzification Process
Result
Ranking
according to the
Fuzzy Score
Threshold
(d) Value
Expert
Agreement (%) m1m2m3Average of
Fuzzy Score
1 0.221 33% 0.455 0.655 0.855 0.655 Rejected 6
2 0.202 90% 0.490 0.690 0.890 0.690 Rejected 5
3 0.110 80% 0.555 0.755 0.955 0.755 Accepted 2
4 0.101 83% 0.560 0.760 0.960 0.760 Accepted 1
5 0.134 80% 0.545 0.745 0.945 0.745 Accepted 3
6 0.134 80% 0.545 0.745 0.945 0.745 Accepted 3
Note: Three conditions to accept an item: threshold value (d)
0.2, percentage of experts’ consensus
75%, and average fuzzy score
(Amax )αcut value = 0.5.
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