DISDA: Digital Service Design Architecture for Smart City Ecosystems

Mouzhi Ge

1 a

and Barbora Buhnova

2 b

Deggendorf Institute of Technology, Deggendorf, Germany

Faculty of Informatics, Masaryk University, Brno, Czech Republic

Keywords:

Digital Service, Service in Society, Service Design Architecture, Social Connectivity.

Abstract:

Due to the interoperability difﬁculty and development bottleneck of various services in a city, the effective

design of services has become a critical concern in smart city ecosystems. Based on the interconnection

concept of Management by Competencies, this paper proposes an DISDA architecture to facilitate the digital

service design in a smart city ecosystem. The DISDA architecture not only can guide the users to design the

services with the deﬁned processes but also can measure the maturity of the existing services and determine

possible service improvements. Based on the proposed service design architecture, we conduct a case study

to validate the usability and applicability of the proposed service design architecture.

1 INTRODUCTION

With the rapid growth of emerging smart technologies

and services, smart city ecosystems have been exten-

sively studied over the last decade (Gasc

o-Hernandez,

2018; Albino et al., 2015). From previous studies, it

can be seen that digital services have been considered

as one of the important components in a smart city

ecosystem, since the digital service is capable of con-

necting service providers, users, infrastructures, and

communities in a common ecosystem to support the

value co-creation (Kashef et al., 2021; Salim et al.,

2021).

On the other hand, digital service creation and de-

livery have become one of the strategic objectives in

smart city ecosystems and can directly echo the stake-

holders’ concerns in a smart city (Oliveira and Cam-

polargo, 2015; Buhnova et al., 2022). The impor-

tance of digital service has demonstrated that the ca-

pacity of smart city ecosystems to create and share

value for stakeholders is directly related to new infor-

mation technology, processes, services and associated

business and information architectures (Silva et al.,

2020). In this paper, we consider smart city as a typ-

ical ecosystem, and in turn the services are scoped as

the digital services in a city.

While service-oriented initiatives have been de-

veloped in a variety of domains such as urban plan-

https://orcid.org/0000-0002-4107-5303

https://orcid.org/0000-0003-4205-101X

ning, mobility, transportation, smart living and com-

munity, smart environment, emergency, e-health, and

government (Kashef et al., 2021; Ge et al., 2018),

we found that the services in one domain are usually

developed for some speciﬁc purpose or for this do-

main only. Therefore, the current services in the smart

city ecosystem often encounter interoperability and

development bottleneck issues (Koo and Kim, 2021).

This results in that even similar services among dif-

ferent domains are isolated with each other. For ex-

ample, the transportation IoT service in the mobil-

ity and transportation domain cannot be re-used for

the urban road construction or emergency route plan-

ning (Bangui et al., 2020). Thus, urban planning and

emergency domain have to develop their own services

respectively to obtain the transportation information

(Bangui et al., 2021).

As a result, it can increase the service creation

cost, increase service incompatibility and possibly re-

duce the citizen’s satisfaction. Furthermore, a large

amount of the developed services are not aligned with

the uniﬁed goal in smart city ecosystems and the ser-

vice provider does not know how to improve an ex-

isting service, for example, (Kakarontzas et al., 2014)

found that 44% of the services do not have a clear

goal that can respond to the demands in a smart city

ecosystem. One of the reasons is that there is a lack

of systematic service design architecture in the smart

city ecosystem. Service design, especially digital ser-

vice design, is critical for building a smart city ecosys-

tem.

Ge, M. and Buhnova, B.

DISDA: Digital Service Design Architecture for Smart City Ecosystems.

DOI: 10.5220/0011056100003200

In Proceedings of the 12th International Conference on Cloud Computing and Services Science (CLOSER 2022), pages 207-214

ISBN: 978-989-758-570-8; ISSN: 2184-5042

207

This paper, therefore, aims to develop a system-

atic service design architecture for the digital service

developments in the smart city ecosystem. We have

adapted the framework from Management by Com-

petencies (Plam

ınek and Fi

ser, 2005) due to its in-

terconnection nature and incorporated this framework

with digital service design processes. Instead of de-

veloping a reference architecture like (Clement et al.,

2017) to proﬁle services in a smart city ecosystem, the

proposed architecture focuses on facilitating the pro-

cesses of digital service design in smart city ecosys-

tems.

The contributions of the paper are accordingly

two-fold: (1) a systematic service design architec-

ture DISDA that can guide the users with a deﬁned

speciﬁcation to design the digital services, (2) a ma-

turity pyramid of the service design that can be used

to deﬁne the goals of new service design, measure the

service maturity and improve the existing services in

smart city ecosystems.

The remainder of the paper is organized as fol-

lows. Section 2 revisits the related work on service

development and service engineering for service de-

sign. Based on the review, Section 3 proposes a digi-

tal service design architecture, which is adapted from

the framework of Management by Competence. Sec-

tion 4 further describes the speciﬁcations of the archi-

tecture from four perspectives: usefulness, efﬁciency,

stability and dynamics. In order to validate the archi-

tecture, section 5 conducts a case study in the context

of smart transportation. Finally, section 6 concludes

the paper and outlines future research for digital ser-

vice design in smart city ecosystems.

2 SERVICE DEVELOPMENT AND

SERVICE ENGINEERING

Service development research is directly related to

service design. The early research works regarding

service development can be traced back to the 1970s,

and at that time, new service research streams have

appeared (Moradi et al., 2020), such as New Service

Development, Service Design, Service Engineering

(Dragoicea et al., 2020). Over the last decade, inte-

grating physical products and various services has be-

come a crucial strategy for many companies (Pirola

et al., 2020). However, designing and developing

a Product-Service System (PSS) is a complex task

due to a long-term relationship among different ac-

tors in the system (Song et al., 2021). In order to cope

with the complexity in service design and develop-

ment, researchers proposed a large number of mod-

els and methods to design a PSS. However, most of

these models and methods lack evaluations in practice

(Pirola et al., 2020). Therefore, the design of services

is still on the theoretical level as seen in (Jan

acek

and Fabricius, 2021), and service development is less

efﬁcient than the development of physical products

(Froehle et al., 2016). This motivates us to further

conduct research on the service design and carry out

the design in practice such as Smart City context. In

this paper, we deﬁne the digital service design pro-

cess by adopting the concept of New Service Devel-

opment, which is deﬁned as a process of developing

a new service from initiating an idea for a service to

the service market launch (Lin and Hsieh, 2011). As

such, the process of digital service design starts from

service idea initiation and ends with realizing the ser-

vice in the smart ecosystem.

Another research stream dealing with design and

development of services is the service engineering.

It approaches the service design challenge in a sys-

tematic and methodological way using engineering

know-how. It is, therefore, a rational and heuris-

tic approach based on the discussion of alternatives,

goals, constraints, and procedures, through the adop-

tion of modeling and prototyping methods, aiming

to increase the value of service offering by improv-

ing the service conception, service delivery and ser-

vice consumption (Shimomura and Tomiyama, 2005;

Chohan and Hu, 2020; Holmlid and Evenson, 2008).

Most renowned service engineering process models

are based on the following three classical models.

(1) Waterfall model, a linear, sequential design pro-

cess following phases of requirements analysis, de-

sign, implementation, testing, integration, and main-

tenance. It is a simple model, not recommended for

complex development. (2) V-model, a linear product-

development process in shape of a letter V. The left

side of the V describes a decomposition of require-

ments and a creation of system speciﬁcation, while

the right side stands for integration of decomposed

parts and their veriﬁcation. (3) Spiral model, a model

with a cyclic approach for improving the precision of

deﬁnition and implementation of the system in several

increments (cycles) for a decrease of a risk degree.

In (Pezzotta et al., 2014), the authors conducted a

detailed analysis of the literature on service engineer-

ing process models and derived four main common

phases, (1) customer analysis, (2) requirements anal-

ysis, (3) PSS design, (4) PSS test and implementa-

tion. They argue, as well as some others (Bertot et al.,

2016), that a customer is an important element of a

service design since they co-design the service, but

there is another important factor, which is the com-

pany itself. It needs to standardize and optimize its

processes for it to remain competitive. Based on this

CLOSER 2022 - 12th International Conference on Cloud Computing and Services Science

208

idea, they propose Service Engineering Methodology

that is aligned with other service engineering process

models in terms of the four phases. In this paper,

we consider service engineering models as a develop-

ment base for designing the digital services in smart

ecosystems (Walletzk

y et al., 2019).

3 DISDA: DIGITAL SERVICE

DESIGN ARCHITECTURE

DISDA is a digital service design architecture in-

spired by the Management by Competencies (MbC)

that was developed as a holistic guideline for the com-

panies and intended to solve problems from root cause

instead of patching from where the service pitfalls

take place. MbC is a systematic method for com-

pany management. It is based on a harmonic devel-

opment of competitive and soft aspects of business

environment. The main rationale behind MbC is to

interconnect the discrete company segments, perfor-

mance requirements and company competences. It

is based on several well-known theories such as The-

ory of constraints (Goldratt, 1990), Theory of vitality

(Plam

ınek, 2006), Person-centered approach (Rogers,

1979), Learning organization (Senge., 1994), Sci-

entiﬁc management (Taylor, 1911), Re-engineering

(Hammer and Champy, 2001), as well as Balanced

scorecard (Kaplan and Norton, 1996).

The goal of MbC is to help the company achieve

vitality, which is a status of the company can be con-

tinuously successful, not restricting the possibility of

being successful in a shot time. In other words, not

exhausting its own resources just for one-time suc-

cess. MbC deﬁnes competence as an ability to use

human resources of a personnel (such as knowledge,

skills, qualities) on a speciﬁc task in order to fulﬁll

the task’s requirements, whereby, the competencies

and tasks help interconnect the performance require-

ments of a company with possibilities it has. MbC

helps to reach vitality by developing the relationships

among its requirements and possibilities using em-

ployee’s competencies.

The strategy of developing requirements is de-

scribed by one of the MbC tools, the pyramid of vital-

ity, see Figure 1. It states that every service design can

start from thinking about usefulness. That is, which

product or service from the company can be delivered

and useful to the stakeholders. The process goes from

identifying stakeholders, their needs and deﬁning a

service that satisﬁes the needs of stakeholders. In the

next step, it comes to level of the efﬁciency, where the

speciﬁed service is decomposed to processes and ac-

tivities with necessary resources that are gathered into

Figure 1: Pyramid of Vitality adopted from MbC.

appropriate structures to ensure proper distribution of

resources for the processes and activities.

Nevertheless, creating a service and receiving a

temporary proﬁt in return can be not stable. For exam-

ple, the company can be negatively affected by busi-

ness or requirement change, which is a critical part of

the business environment. The company needs to be

able to react quickly to those changes. Thus, the third

level is the continuous improvement in the company

such as process optimization and conforming market

trends e.g. based on the customer research. Hence,

the stability level is about company’s improvement

based on customer feedback and people who is will-

ing to react to changes in the company and quickly

allow the changes.

Finally, the strategic step to vitality is called dy-

namics. It should not only be just reactive for the

company, it should be also proactive, such as predict-

ing the future and being prepared for market trends,

or even inﬂuencing the future. For this objective, the

people who are involved in a company should ac-

tively search for new opportunities and ideas. MbC

approaches the development of a company in a mean-

ingful and logical way from the fundamental step of

ﬁnding stakeholders, for whom the company aims to

provide useful products or services, through the ef-

ﬁciency of a company processes, till predicting and

creating new areas for business. We found that the

rationale of MbC is in line with our perception of dig-

ital service development in smart ecosystems such as

smart cities. Therefore, we adopt the four maturity

levels from MbC to develop the following digital ser-

vice architecture.

DISDA: Digital Service Design Architecture for Smart City Ecosystems

209

Figure 2: DISDA: Digital Service Design Architecture.

4 ARCHITECTURE

SPECIFICATIONS

In this section, we specify our DISDA digital service

design architecture as Figure 2, which is inspired by

MbC, speciﬁcally the pyramid of vitality based on the

Theory of Vitality. The pyramidal shape illustrates the

strategy of digital service development and consists of

four levels as the pyramid of vitality and maturity. We

describe each level from bottom to top as follows.

4.1 Usefulness

The goal of the ﬁrst level of the DISDA architecture

is to ﬁnd out which services a city ecosystem needs

to be created, for example, the city can choose and

deﬁne city service that will fulﬁll the speciﬁc needs

of the stakeholders. In this stage, the city needs to

follow a deﬁnition scheme, which has reversed order.

It means that the city should at ﬁrst focus on deter-

mining the stakeholders (e.g., commuting citizens),

then identify stakeholders’ needs (e.g., to travel efﬁ-

ciently throughout the city) and ﬁnally propose a ser-

vice that fulﬁlls identiﬁed needs (e.g., intelligent traf-

ﬁc control service). The service of intelligent trafﬁc

control should be described as precisely as possible at

this stage to deﬁne measures of the service success.

Thus, usefulness level speciﬁes a relevant city service

by choosing the stakeholders to whom a city will of-

fer values in term of appropriating city services that

can address their needs.

Table 1: Usefulness properties.

Property Deﬁnition

Goal choose and deﬁne relevant digi-

tal services

Input information about stakeholders

and their needs

Process stakeholders need city service

Output service speciﬁcation

Usefulness: Efﬁciency Relation. The service spec-

iﬁcation in the usefulness level is then transferred to

the efﬁciency level for further optimization.

CLOSER 2022 - 12th International Conference on Cloud Computing and Services Science

210

4.2 Efﬁciency

In this phase, the efﬁciency level is to deﬁne the ser-

vice development and creation. It starts with an elab-

oration of the service (e.g., intelligent trafﬁc lights in

our case) into a process map describing a service cre-

ation process (e.g. simulate different trafﬁc lights dis-

tributions, changing trafﬁc lights for intelligent ones),

followed by resources identiﬁcation and assignment

(e.g. storage, computers, trafﬁc lights, engineers, la-

borers). And arranging this complex into appropriate

structures (e.g., simulation can run in parallel with

ﬁnding more information about possible providers

and precede the change of current trafﬁc lights) to

supply the resources for respective processes. Efﬁ-

ciency level ensures an efﬁcient creation of the city

services by deﬁning the processes and their resources

organized into structures in order to provide a proper

amount of quality resources to the right object and on

time.

Table 2: Efﬁciency properties.

Property Deﬁnition

Goal improve or optimize service

process

Input service speciﬁcation from the

usefulness level

Process city service speciﬁcation →

processes → resources → struc-

tures

Output process deﬁnitions with re-

quired resources, organization

structure deﬁnition, role speciﬁ-

cation

Output service speciﬁcation

Efﬁciency: Stability Relation. The relation between

these two levels is recurrent, while the stability level

acquires feedback from the efﬁciency level and trans-

lates them into change actions for efﬁciency level.

4.3 Stability

In order to adapt and enhance the service (functional-

ity, efﬁciency, reducing costs, etc.), the city needs to

get the feedback by using the service. Feedback can

be automatically acquired in the form of sensed and

evaluated data (e.g., service response time, service

malfunction reports) as well as in the way of users’

opinions (e.g., what they like, what they are miss-

ing). Stakeholders’ involvement is needed to evolve

the service, e.g., service users need to be willing to

share feedback, the city needs to manage the service,

and the service provider should upgrade the service

efﬁciently based on the feedback. The stability level

helps a company to quickly react and adapt itself us-

ing feedback and stakeholders’ cooperation.

Table 3: Stability properties.

Property Deﬁnition

Goal obtain and evaluate relevant

data and information about ser-

vice and service context to con-

ﬁrm current approach or to pro-

pose a service change

Input service data & stakeholders’ in-

formation

Process get data → evaluate by goals →

conﬁrm current approach | pro-

pose service changes

Output service conﬁrmation | service

change proposal

Stability: Dynamics Relation. Dynamics gathers

relevant data from the stability level to predict the

trends and proposes possible changes back to the sta-

bility level. The relation is also rotative, but the dura-

tion of one execution cycle is usually longer than the

efﬁciency – stability relation.

4.4 Dynamics

The dynamics level proactively prepares possible

changes and predicts the future state in parallel with

the service adaptation. Forecasting as well as inﬂu-

encing the future is a challenging task that needs the

active participation of stakeholders. Therefore, even

more demanding personnel management is necessary

for enabling stakeholders’ pro-activity. The dynam-

ics level proposes service changes based on forecasts

and estimations of the future allowed by stakehold-

ers activity achieved by personnel management. With

the recent development of machine learning and big

data technologies (Mac

ak et al., 2020), the predica-

tion function can be more integrated to services. It

also reﬂects the ”smartness” of service, which is in

the city ecosystems called as smart services.

5 CASE STUDY

In order to validate the DISDA architecture, we have

conducted a case study in the context of smart trans-

portation for a metropolitan city in Czech Republic.

The case study is targeting on the trafﬁc control ser-

vice that is designed for more than 700 000 inhabi-

tants in this city. The city aims to design a smart

DISDA: Digital Service Design Architecture for Smart City Ecosystems

211

Table 4: Dynamics properties.

Property Deﬁnition

Goal forecast future trends and possi-

bilities in a larger context and be

prepared for them

Input data and information from the

context

Process get data → ﬁnd trends → pro-

pose service changes

Output service change proposal

transportation service for its citizens. We will use

the DISDA architecture to design smart transportation

service in the city.

As shown in Figure 2, the DISDA architecture is

developed to guide the practitioners to design services

in a smart city ecosystem. In our context, we focus on

the transportation service design. In the initial use-

fulness level, a smart transportation service ﬁrstly has

to be useful and meet the user’s requirements. There-

fore, this service needs to provide a safe and reliable

service for the citizens to travel around the city. This

can meet the basic requirement of citizens.

Afterwards, the service design enters to the second

level that focuses on the efﬁciency. In this level, the

processes and structures of services can be improved

to more efﬁcient. For example, with limited resources

how to cover the most inhabited locations by the pub-

lic transportation network, also how to make the trav-

els from A to B more smooth by reducing the transi-

tion time. The DISDA architecture can effectively in-

dicate the service design objectives when the service

can meet the basic needs of the citizens.

In the stability level, the service design begins to

involve the feedback from the citizens. This is fea-

tured by a feedback and changes loop. This loop is

expected to make the magnitude of changes in a con-

vergent way, in turn it can reach the stability status

of a service. In order to consider one concrete trans-

portation service in our case study, we have scoped

down the trafﬁc control service as a sequence of the

trafﬁc lights in the roads. For example, the light itera-

tion can be optimized to allow trafﬁcs to wait for less

red lights.

Furthermore, the smart transportation service pro-

vides a channel to collect feedback from the citizens

as well as adapt the service to address the new or

changed requirements. For example, if citizens pro-

vide the feedback that at the rush hours some traf-

ﬁc lights in the main roads can be optimized. This

can on one hand reduce the possibility of trafﬁc jam

and on the other hand increase the citizen’s service

satisfaction. The feedback channel in this phase is

important as the service stakeholders are usually do

not know how to quickly send feedback to a public

service. Assuming the well-known and easy-to-use

feedback channel, the feedback is expected to be con-

verged to a stabilized limited amount.

Therefore, the stability phase is expected to bal-

ance the adaptation of the service, acceptance and

satisfaction of citizens. Also in this phase, the ser-

vice can handle the interoperability across different

services. For example, trafﬁc control service can also

cooperate with the school service, some trafﬁc light

near school can be adjusted based on the school-off

time.

Finally, the service is expected to have the abil-

ity of predicting and preparing to react to possible or

unexpected situations. For example, if there is some

special event or celebration in the city, trafﬁc control

service can predict other possible routes based on the

constraint of expected blocking roads, and meanwhile

make clear detour for the citizens.

Consider that when different services in a city are

designed with the DISDA architecture, we are able to

interlink and connect the services in the same level.

This is especially important when different service

have reached the stability level. The changes in the

level should also include the interoperability improve-

ments across different stable services. For example,

a stable transportation service can be interconnected

to the healthcare services in the city. By using the

DISDA architecture, when designing the smart ser-

vices, we can easily identify the level of a smart ser-

vice, and the goal of reaching to the next level. Thus,

the usability and applicability have been veriﬁed dur-

ing this case study.

6 CONCLUSIONS

This paper proposes an architecture, named DISDA,

to help the users to design new digital services and

improve existing digital services in smart city ecosys-

tems. The DISDA architecture is adapted from the

essence of Management by Competencies, which

contains four maturity levels: usefulness, efﬁciency,

stability, and dynamics. In each level, the service de-

sign processes are speciﬁed to illustrate how to design

the service in order to achieve the maturity level of the

service. Among the levels, the relations are described

to guide the service designers to walk from one level

to another. More importantly, different smart services

can be inter-connected with each other for each level.

In order to validate the proposed architecture, we

have conducted a case study on smart transportation

service in a metropolitan city. The results of the case

study have indicated the usability and applicability of

CLOSER 2022 - 12th International Conference on Cloud Computing and Services Science

212

the DISDA architecture. Furthermore, it can be seen

that DISDA architecture can facilitate the service de-

sign, service improvement as well as handling the in-

teroperability across different services so that to for-

mulate a smart city ecosystem.

As future works, we plan to reﬁne further the ser-

vice design processes and conduct more case studies

in different application domains to verify the validity

and reliability of the proposed digital service design

architecture. We will also deepen the architecture into

a technical design and further show the how different

services can be connected in each DISDA service ma-

turity level.

ACKNOWLEDGEMENTS

The work was supported from ERDF/ESF “Cy-

berSecurity, CyberCrime and Critical Informa-

tion Infrastructures Center of Excellence” (No.

CZ.02.1.01/0.0/0.0/16 019/0000822).

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