Smart Cities and Forced Trust: Citizens’
Attitudes Towards Smart City Innovations
University of Turku
Department of Computing
Master of Science (Tech) Thesis
Security of Networked Systems
January 2025
Suvi-Tuuli Hyvönen
The originality of this thesis has been checked in accordance with the University of Turku quality assurance
system using the Turnitin OriginalityCheck service.
UNIVERSITY OF TURKU
Department of Computing
Suvi-Tuuli Hyvönen: Smart Cities and Forced Trust: Citizens’ Attitudes To-
wards Smart City Innovations
Master of Science (Tech) Thesis, 51 p., 15 app. p.
Security of Networked Systems
January 2025
Smart cities are cities that implement smart innovations and applications to improve
the everyday-life of their citizens. Innovations can be, for instance smart infrastruc-
ture, smart education, smart governance, smart healthcare and smart citizens. The
different dimensions of smart cities are human dimension, technological dimension
and institutional dimension.
The smart city we will observe in this thesis, is the city of Salo, which is a small
smart city on a world’s scale. The city of Salo is implementing smart systems and
innovations, and the question we wanted to ask is, how the citizens see innovations,
when their trust is forced. We created a survey questionnaire which tries to help
understanding citizens’ attitudes towards new smart applications.
At first, we did a literature review on trust and forced trust and tried to solve
the ethics of the latter. The second part was to create the survey questionnaire for
the citizens of Salo and to expand it to cover other participants in Finland. The re-
sults showed that there weren’t a lot of differences between gender groups. However,
between the age groups there were some differences, when it came to the factor of
forced trust. Most of the comparison groups also saw forced trust as a supposition
and non-optional factor when they had to place their trust in technologies.
Keywords: smart city, trust, forced trust, Salo smart city
Contents
1 INTRODUCTION 1
1.1 RESEARCH PROBLEMS . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 SALO SMART CITY PROJECT . . . . . . . . . . . . . . . . . . . . 3
1.3 RESEARCH QUESTIONS AND THESIS
STRUCTURE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2 TRUST AND FORCED TRUST 6
2.1 TRUST . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2 FORCED TRUST . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.3 FACTORS AFFECTING TRUST . . . . . . . . . . . . . . . . . . . . 8
2.3.1 GDPR and national regulations in Finland . . . . . . . . . . . 9
2.3.2 User’s previous experiences . . . . . . . . . . . . . . . . . . . . 10
2.3.3 User’s prior technical knowledge and social pressure . . . . . . 11
2.4 THE ETHICS OF TRUST AND FORCED
TRUST . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3 SMART CITIES AND DIGITAL TRANSFORMATION 14
3.1 DIGITAL TRANSFORMATION . . . . . . . . . . . . . . . . . . . . 14
3.2 SMART CITIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.3 SMALL SMART CITIES . . . . . . . . . . . . . . . . . . . . . . . . . 18
3.4 FUTURE TRENDS . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
i
4 METHODOLOGY 22
4.1 QUESTIONNAIRE DESIGN AND DATA COLLECTION . . . . . . 22
4.2 BEHAVIOURAL-REASONING THEORY . . . . . . . . . . . . . . . 23
4.2.1 Innovation Diffusion Model . . . . . . . . . . . . . . . . . . . 24
4.2.2 Innovation Resistance Model . . . . . . . . . . . . . . . . . . . 25
4.3 TECHNOLOGY ACCEPTANCE MODELS . . . . . . . . . . . . . . 26
4.3.1 Technology Readiness Index 2.0 . . . . . . . . . . . . . . . . . 26
4.3.2 Unified Theory of Acceptance and Use of Technology . . . . . 26
4.3.3 Additional Factors . . . . . . . . . . . . . . . . . . . . . . . . 27
4.4 MEASURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
5 STUDY AND DISCUSSION 33
5.1 RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.1.1 Gender comparison . . . . . . . . . . . . . . . . . . . . . . . . 38
5.1.2 Age groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
5.2 DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
5.3 OTHER STUDIES ON SMALL SMART CITIES . . . . . . . . . . . 48
6 CONCLUSIONS 50
6.1 ANSWERS TO RESEARCH QUESTIONS . . . . . . . . . . . . . . . 50
6.2 POTENTIAL FUTURE WORK . . . . . . . . . . . . . . . . . . . . . 51
References 52
Appendices
A Research questionnaire A-1
ii
List of Figures
3.1 Digital transformation process . . . . . . . . . . . . . . . . . . . . . . 15
3.2 EDGI ratings of UN member states . . . . . . . . . . . . . . . . . . . 15
3.3 Smart city objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
3.4 Smart cities top 10 comparison . . . . . . . . . . . . . . . . . . . . . 20
4.1 The model for intention to use technology . . . . . . . . . . . . . . . 24
4.2 Technology Readiness Index 2.0 . . . . . . . . . . . . . . . . . . . . . 29
4.3 Innovation Diffusion Model . . . . . . . . . . . . . . . . . . . . . . . . 30
4.4 Innovation Resistance Model . . . . . . . . . . . . . . . . . . . . . . . 31
4.5 Additional factors for the questionnaire . . . . . . . . . . . . . . . . . 32
5.1 The participant level of education . . . . . . . . . . . . . . . . . . . . 34
5.2 The participant work situation . . . . . . . . . . . . . . . . . . . . . . 34
5.3 Insecurity, Technology Readiness Index 2.0 . . . . . . . . . . . . . . . 35
5.4 Trust in Technology from Additional factors . . . . . . . . . . . . . . 36
5.5 Forced Trust from Additional factors . . . . . . . . . . . . . . . . . . 37
5.6 Perceived Security from Additional factors . . . . . . . . . . . . . . . 37
5.7 Perceived Privacy from Additional factors . . . . . . . . . . . . . . . 38
5.8 Men’s view on Insecurity . . . . . . . . . . . . . . . . . . . . . . . . . 39
5.9 Men’s view on Trust in Technology . . . . . . . . . . . . . . . . . . . 39
5.10 Men’s view on Forced Trust . . . . . . . . . . . . . . . . . . . . . . . 40
5.11 Women on Insecurity . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
iii
5.12 Women on Trust in Technology . . . . . . . . . . . . . . . . . . . . . 41
5.13 Women on Forced Trust . . . . . . . . . . . . . . . . . . . . . . . . . 41
5.14 Ages 20 to 29 on Insecurity . . . . . . . . . . . . . . . . . . . . . . . 42
5.15 Ages 20 to 29 on Trust in Technology . . . . . . . . . . . . . . . . . . 42
5.16 Ages 20 to 29 on Forced Trust . . . . . . . . . . . . . . . . . . . . . . 43
5.17 Ages 20 to 29 on Perceived Security . . . . . . . . . . . . . . . . . . . 43
5.18 Ages 30 to 39 on Trust in Technology . . . . . . . . . . . . . . . . . . 44
5.19 Ages 30 to 39 on Forced Trust . . . . . . . . . . . . . . . . . . . . . . 44
5.20 Ages 30 to 39 on Perceived Privacy . . . . . . . . . . . . . . . . . . . 45
5.21 Ages 40 to 78 on Insecurity . . . . . . . . . . . . . . . . . . . . . . . 45
5.22 Ages 40 to 78 on Trust in Technology . . . . . . . . . . . . . . . . . . 46
5.23 Ages 40 to 78 on Forced Trust . . . . . . . . . . . . . . . . . . . . . . 46
5.24 Ages 40 to 78 on Perceived Security . . . . . . . . . . . . . . . . . . . 47
iv
1 INTRODUCTION
Forced trust is a relatively new term first introduced in Soviet Russia and after
that in a few publications from the University of Turku. Smart city as a concept is
again a developing term, and these smart cities aim to provide modern and futuristic
aspects to handle cities government and their citizens’ well-being.
How to combine trust, forced trust, and smart cities is a rising dilemma when
smart cities are being developed and designed. Since smart cities handle sensitive
data of the city’s services and especially about its citizens and their way of living, it
is vital for the city that its citizens trust in the city’s and its decision-makers’ ways
to handle sensitive data.
In the following chapters trust, forced trust and smart cities are explained more
in detail. In addition, it is discussed how the relationship between a smart city and
its citizens’ trust could develop in the future and how both parties could positively
and productively benefit by working in symbiosis.
This thesis is written to develop especially the city of Salo’s future smart city
services and the city has funded the research. The aim is also that Salo smart
city project will benefit from this research. To understand better the acceptance
of new smart city technologies we will create a survey questionnaire from existing
models and their factors. Because there is no prior work similar to ours we will also
have to create some additional factors for the survey. Lastly we will analyze the
questionnaire participant answers.
2 1.1 RESEARCH PROBLEMS
1.1 RESEARCH PROBLEMS
When talking about smart cities, technologies and services are usually designed on
the city level without the citizens participating in the design of smart systems. This
creates the situation where the citizens might be forced to trust in the technologies,
them wanting those or not. The citizens can for sure give their opinions and desires
about smart applications and services their city would provide, but in the end the
city’s decision-makers and technology or service providers have the end responsibility
of these designs.
The most optimal situation would be that the citizens trust the services their city
is providing and they would trust that the city and its service providers are designing
the technologies for the benefit of the citizens. When the citizens are forced to trust
their decision-makers and third parties blindly, this can create problems accepting
the provided smart technologies and services. This again can have an affect on
using the smart implementations, misusing them or in extreme cases the citizens
distrusting their decision-makers and eventually moving to another city.
While designing smart cities, it is therefor essential to keep in mind that there
are different people living in a city. The people are from different backgrounds, they
might have cultural differences, as well as different political and sociological views
and they usually are of different age groups. For instance, for older generations it
can be difficult to use even other modern technologies, not to mention smart city
technologies like mobile apps designed to support a city’s decision-making though
this is not the case for all. Younger people again could be more accepting towards
new technologies and towards learning to use them.
The models and theories used in this study to evaluate citizens’ acceptance to-
wards smart city technologies and services should provide new perspectives to these
problems and possibly facilitate the possible smart city designs. While there is very
little literature about forced trust in smart cities or even towards other modern
1.2 SALO SMART CITY PROJECT 3
technologies it is however difficult to compare these research models to other ones.
There is only a handful of literature about forced trust but this thesis can still make
a base for all the future researches to come.
1.2 SALO SMART CITY PROJECT
Salo is a midsize city in the Southern Finland and the city used to be the hometown
of the telephone giant Nokia’s factory. On the world’s scale Salo can be referenced
to be a small city. The termination of Nokia’s operation’s in Finland made the
company cut off many of their employees, and from 2010 until 2013 Nokia reduced
hundreds of employees at their factory in Salo which affected heavily on the city’s
taxation and unemployment rate [1]. Nowadays Salo has approximately 52 000
residents and 5000 companies. The unemployment rate in March 2021 was 13,3
percent and geographically the Salo area is 2 168 km²’s [2].
The population of Salo has been declining for years [2], which has lead to the
decision-makers in Salo to start new projects to improve or maintain the attrac-
tiveness of their city. Salo Smart City project discussed in this thesis is one of the
ongoing future projects, and this thesis aims to provide new helpful aspects to the
city of Salo in their Smart City Project.
The city of Salo has promised the following to their future smart city: smart gov-
ernance, smart education, smart healthcare, smart building, smart mobility, smart
infrastructure, smart technology, smart energy and smart citizen [3].The project col-
laboration with the University of Turku also aims to produce researched knowledge
about designing a smart city, the cybersecurity of a smart city and about the data
transfer that is required for a smart city [4].
The decision-makers of Salo have also decided that their citizens would benefit
from a smart city app that would, for instance, be a platform for the communication
of citizens, provide information about the parking slots in the city area and provide
4
1.3 RESEARCH QUESTIONS AND THESIS
STRUCTURE
a more suitable way to participate to the city’s decision-making. The application
would be developed for different kind of online services as well as for smart devices.
The idea is also to have different features for different groups like for the Salo citizens
and for tourists and visitors. [3].
While most of the Salo Smart City project’s features require a huge amount of
data it will be important to have some kind of knowledge base. Properly managing
and protecting the knowledge base’s data will be vital when maintaining the conti-
nuity of the smart features as well as protecting the city’s and its citizens’ sensitive
information. For the continuity and possibility to improve smart applications and
services it is also important that the data is reusable. This again can create trust
issues towards the smart applications and services which we are examining in our
study and which will be covered in Chapter 5. [3]
1.3 RESEARCH QUESTIONS AND THESIS
STRUCTURE
The aim of this thesis is to provide new views on smart cities and the trust and
forced trust the citizens of these cities show and feel towards smart city services and
applications. Research questions of the thesis are the following:
• RQ1: What is trust and especially forced trust, and the ethics of these two?
• RQ2: What are smart cities and small smart cities?
• RQ3: How does forced trust affect on the citizen perspective and their accep-
tance of smart city services and applications?
This Introduction chapter provides general thoughts about this thesis, an over-
look on Salo smart city as well as the research problems about forced trust and
1.3 RESEARCH QUESTIONS AND THESIS
STRUCTURE 5
smart cities. Chapter 2, Trust and Forced Trust, explains the concepts and dif-
ferences between trust and forced trust and the factors affecting these. Chapter 2
also covers ethical view towards the situation where citizens are forced to trust their
decision-makers and the smart city’s ability to provide secure services protecting the
citizens’ data.
Chapter 3, Smart Cities and Digital Transformation, covers the idea and con-
cept of smart cities and digital transformation and defines especially the concept of
small smart cities. As a continuation Chapter 4, Methodology, handles the models
and theories to measure the citizens’ attitudes towards smart cities and in general
towards technology.
Chapter 5, Study and Discussion, provides the study’s results and discusses about
the possible effects on the results. Chapter 5 provides general discussion of the topic
as well. Chapter 6, Conclusions, concludes this thesis and the Salo smart city case
study. In Conclusions there is also a discussion about the possibilities to new smart
cities as well as the potential views and suggestions for researches covering the same
topic of forced trust towards smart cities in the future.
2 TRUST AND FORCED TRUST
2.1 TRUST
Since one of our main interests in this thesis is forced trust, we must first define
what trust itself means. The definition is not so easy since trust can have multiple
meanings depending on the literature at hand as well as from which point of view
we are looking at the term and the context in which the term is used. The trust we
handle in this thesis is an abstract concept and not a verb and something to do so
we can focus on trust as a noun.
Many modern dictionaries refer in their definitions that trust is something be-
tween people, within people and between people and objects. Trust is therefore
interpersonal-reliant as well as internal-reliant in humans’ mind. In Cambridge
Dictionary trust as a noun of belief is "the belief that you can trust someone or
something"[5]. It is relationship that is "based on trust and understanding". When
the context is different the definition varies a little. For example, the noun of trust
in business English is "a belief that you can depend on someone or something" [5].
According to the Merriam-Webster dictionary again trust is for instance "assured
reliance on the character, ability, strength, or truth of someone or something" and
"one in which confidence is placed" [6].
Merriam-Webster dictionary mentions also the antonyms for trust: mistrust and
distrust. Mistrust refers to the "absence of trust" and to a situation when there is
2.2 FORCED TRUST 7
no confidence in someone or something [6]. Another verb that could be used instead
of mistrust is distrust. For example "she had a distrust in the system". Mistrust
and distrust could be then considered as synonyms.
The history of trust as a noun can be tracked to circa 1200 when it has been used
in Old Norse (the predecessor of modern Scandinavian languages). The then used
word traust meant "reliance on the veracity, integrity, or other virtues of someone or
something; religious faith" [7]. Therefore we could deduce that trust has something
to do with faith so trust is faith towards someone or something.
With these definitions above we can understand what is plain trust. In the case
of the Smart City of Salo the ideal objective is to have trust between citizens and
objects (the citizens’ trust towards smart city technologies and implementations) as
well as between people (the citizens’ trust towards the city’s decision-makers). Next
we can define what means the situation, where trust is not optional but mandatory:
forced trust.
2.2 FORCED TRUST
Forced trust as a term is a relatively new one. Most of the early definitions of forced
trust refer to the Soviet Union or to the Republic of China and to their societies as a
kind of Orwellian dystopias. One of these early definitions from 2013 by Tikhomirov
[8] describes forced trust in relation with the Soviet Union "as a central feature of
Communist modernity". He argues that "Forced trust represents a paradox that
contributed to the collapse of the Soviet state: an illiberal system was promoting a
liberal subject who was forced to trust in the state and the party but, at the same
time, experienced their limited autonomy by generating personal meanings, interests
and needs as a part of life under the dictatorship." [8].
When searching scientific publications and more recent studies about forced trust
in information era only few can be found as Halla-Aho has explained in his thesis
8 2.3 FACTORS AFFECTING TRUST
[3]. According to Halla-Aho, only three articles before his, refer to forced trust
with information technology: Hakkala [9], Hakkala et al.[10], and Madhisetty and
Williams [11].
According to Hakkala [9] forced trust is a situation where a user has no other
choice than to trust the system and to "a type of situational trust in which the
party in the position of forced trust has no other choice but to trust all aspects of
the provided system". According to Hakkala et al. forced trust concept "depict a
situation where an entity – whether a customer, an organization or even a govern-
mental agency – does not have a privilege to choose but is instead mandated to use
a dictated information system." [10].
Another view of forced trust is presented by Madhisetty and Williams who dis-
cuss forced trust with the privacy of shared photos and videos. According to them
forced trust is "trust that is unclear if it is real trust by the content publisher or a
belief that no harm will be done after publication" [11]. The latest publication by
Halla-Aho refers to forced trust with smart cities and describes forced trust as "a
situation where a truster has no choice but to trust a trustee, or services provided by
the said trustee, with no or minuscule ability to influence the function or behaviour
of the target of trust, i.e. the trustee or the services." [3].
In this thesis we will also be using the terms truster and trustee. These are
defined by Hakkala et al. as follows: "the trustor is the party who is placing trust
on someone (or something) else, while the trustee is the target of this trust" [9]. In
our case the trustors are the citizens of Salo and the trustees are the decision-makers
of Salo and the smart city implementations and technologies.
2.3 FACTORS AFFECTING TRUST
There are several aspects on what affects on people’s trust when it comes to tech-
nology. The examples, from a more societal point of view, are national regulations
2.3 FACTORS AFFECTING TRUST 9
in Finland and European Union’s GDPR, user’s previous technological experiences,
user’s prior technological knowledge and societal pressure.
2.3.1 GDPR and national regulations in Finland
When users’ sensitive and personal information is handled with information systems,
regional and national regulations for handling users’ data is needed for public and
private companies. Sanctions must be then defined beforehand since this could
prevent most efficiently the misuse of users’ data. Some warning examples have been
seen for instance with the introduction of EU’s GDPR. For example the French data
regulator CNIL fined Google in 2019 for 50 million euros for "lack of transparency,
inadequate information and lack of valid consent regarding ads personalisation" [12].
On GDPR’s official website there are ten different criteria to define the amount and
severity of a GDPR fine [13].
The General Data Protection Regulation, shortly GDPR, was first introduced
in May 25 2018 and it is used in the area of the European Union. On GDPR’s
website it is stated that the regulation is "the toughest privacy and security law in
the world" [14]. One of the most important aspects of the regulation is that the user
has a right to withdraw their personal data at any time from any service provider.
The client has also right to know for which purpose their data is being used for.
In Finland there are some national regulations about data privacy. For instance
handling a Finnish person’s social security number is permissible only when a per-
son has accepted the handling of their social security number or when the handling
is justified in the law. Some exceptions are however permitted for example when
it comes to historical or scientific research or statistics. Another exception is pub-
lic sector and as Halla-Aho mentioned in his thesis, it is said in the Finnish data
protection act, that: "An administrative fine cannot be imposed on central govern-
ment authorities, state enterprises, municipal authorities, autonomous institutions
10 2.3 FACTORS AFFECTING TRUST
governed by public law, agencies operating under Parliament or the Office of the
President of the Republic, or the Evangelical Lutheran Church of Finland and the
Orthodox Church of Finland or their parishes, parish unions and other bodies."[15].
Another exception is when a registrar needs the social security number and some
other sensitive information for their services to fulfill their duties. The companies
and institutions handling peoples’ private information must however always protect
the rights of their customers and for instance pseudonymisation and encryption of
the data is mandatory. In the Finnish data protection law the sanctions for data
misuse are defined as well. [15]
2.3.2 User’s previous experiences
There are some previous studies about companies misusing their consumers’ data
and systems due to the difficulty and inadequate education of their personnel. For
instance a private hospital in Australia implemented new information system in
2015 and failed to educate their employees using the systems. This lead to misusing
the systems and their patient data. The personnel found a way to create shortcuts
to the new difficult systems, and in the end this created funding problems to the
hospital and in addition their patients’ trust towards the hospital itself. The case
was published for teaching purposes, but is based on real-life just the names changed.
[16]
Another good example from real life is the Finnish psychotherapy center Vas-
taamo case. In 2020 there was a huge data leak from a psychotherapy center Vas-
taamo which resulted from poorly handled client database. Thousands of clients got
affected by this and their personal information as well as their personal psychother-
apy session information was leaked to tor network, where it was for everyone to see
or to be downloaded [17].
These cases are good examples of why national requirements are needed and how
2.4 THE ETHICS OF TRUST AND FORCED
TRUST 11
past experiences could affect users’ or clients’ trust towards information systems in
general. For instance after the Vastaamo leakage it could be very hard ever again
to trust on any company, private or public, to handle personal information and to
even try psychotherapy again.
2.3.3 User’s prior technical knowledge and social pressure
Another thing to keep in mind is that some people do not have any experience or
knowledge about technicalities and how and why their data is handled. For instance
elder people who have not been growing up with computers and smart phones might
be negative towards new technologies because of their lack of knowledge. Another
group is people in countries that do not have stable internet connections, computers
or even phones. How can one trust a system they have never used before?
American Psychological Assosiation, APA’s definition of social pressure is heavily
linked to group pressure. A person might have a huge pressure for instance to belong
to a group which could affect on their views on forced trust. People search for social
approval on others in their group (ethical, religional, geographical, etc.) and if the
others in their group are trusting or distrusting new smart city innovations, it is
more likely one person looks at the situation through group’s point of view. [18]
2.4 THE ETHICS OF TRUST AND FORCED
TRUST
While the ethics is a vast term, in this thesis we focus on the ethics of trust and forced
trust. As mentioned in Chapter 2.1, trust can be seen almost as a religion when
people "put their fate" in a system. In other words this could be seen as a reliance
towards smart city innovations and towards the third parties who handle the data.
Another interesting theory is that trust can be seen valuable from a philosophical
12
2.4 THE ETHICS OF TRUST AND FORCED
TRUST
point of view. Trust is something of an value for both parties the trustor and the
trustee. For instance smart city’s recycling system could benefit from multiple users
and their data, as well as the users could benefit from the recycling system and its
developments. [19]
When it comes to forced trust it’s harder to find bibliography to handle the
ethical view. However, Hakkala [9] points out the concept of Panopticon and it
seems to suit this thesis as well. The idea of Panopticon is based on the work of
Jeremy Bentham in the 18th century. It focuses on the view of surveillance society
and is described to be a circular prison where every cell is visible to the supervisor in
the center. In the 20th century this idea was used for instance by George Orwell in
his book Nineteen Eighty-Four. In our case the prisoners could be seen as the smart
city citizens, the trustors, and the supervisor as the smart city innovation provider,
the trustee. Bentham pointed out that the prisoners could not know when they are
under surveillance and this could encourage them to behave in better ways. Again
taking the recycling example from the previous chapter: the smart city citizens
know that their recycling data is being surveilled, and this could have an affect on
their recycling habits. Positive or negative is yet to be discovered since the citizens
could throw unwanted waste material to their neigbors’ or to someone else’s trash
if they would not want to be linked to that waste. The positive outcome could
again be recycling more coherently if knowing that someone is surveilling the waste
management process. [9] [20]
One objection to continuous surveillance is privacy and whether the trustors
have privacy if they live in Panopticon. It can be assumed that the more there is
trust, the less there is need for privacy. The argument can go to other way as well
and it can also be assumed that the more there is pressured surveillance, the less
there is trust. When it comes to smart cities the most optimistic view would then
be that the citizens know there is no extra surveillance nor surveillance of anything
2.4 THE ETHICS OF TRUST AND FORCED
TRUST 13
in vain and the smart city system providers trust that the citizens or the trustors
are being honest with their data, e.g. with waste management. Knowing there is no
punishment of wrongdoing would lead to more trust between the trustors and the
trustee as well. [20]
Some other objections are with independent autonomy, authority and e.g. social
sorting. These concepts will yet to be discovered with smart cities. For instance how
will the usage of smart city innovations divide citizens based on their socioeconomic
status, age or religious background? Who is the highest authority when it comes to
handling citizen data - the product designers, the citizens themselves or the city’s
decision-makers? How will continuous surveillance of citizen data affect the trustors
autonomy and free will? These questions will have to be considered in the future
when implementing smart city technologies and working together with the citizens
to create the most functional and trustworthy city for everyone.
3 SMART CITIES AND DIGITAL
TRANSFORMATION
Currently there is a rising amount of smart cities around the world and it has been
predicted that many will be developed in the future. The dimensions of smart cities
include, according to Cocchia et al.[21], technological dimension, human dimension
and institutional dimension. Another categorization can be done with the defini-
tion of Yin et al. [22] with technical infrastructure, domain application, system
integration and data processing. While smart cities focus around urban areas and
improving the quality of life for the citizens, we should also view the concept of
digital transformation since the applications that come out of digital revolution are
used in the creation of smart cities.
3.1 DIGITAL TRANSFORMATION
Digital transformation is a broader term than a smart city and it can be applicable to
private and public sectors, to companies and individuals. Digital transformation has
digitization and digitalization as its basis. Digitization means transferring analog
data into digital form and digitalization again involves using digital technologies to
improve for instance business processes, like new software platforms. Digital trans-
formation goes beyond specific project level and can affect the whole organization.
The digital transformation process is portrayed in figure 3.1 [23]
3.1 DIGITAL TRANSFORMATION 15
Figure 3.1: Digital transformation process
A good example about digital transformation is e-government. EGDI (E-Government
Development Index) of United Nations is a good measure of e-governments, and it is
calculated with three independent component averages: the Online Services Index
(OSI), the Telecommunications Infrastructure Index (TII) and the Human Capital
Index (HCI). At the moment, Europe has the highest EDGI value with 0,85 (the
world average 0,64) portrayed in figure 3.2. It has also been stated, that higher-
income countries tend to have higher EDGI values. [24]
Figure 3.2: EDGI ratings of UN member states [24]
When we compare the top e-governments, two countries that pop out are Den-
mark (ranked world number 1) and Estonia (ranked world number 2). Denmark
has multiple comprehensive portals for its citizens, and it "emphasizes cross-sector
16 3.2 SMART CITIES
collaboration, integrating public, private and civil society efforts". The country
has also focused on strengthening its cybersecurity. When it comes to Estonia the
country has had proactive services for years and is a pioneer in "integrating AI,
cybersecurity and – 5G". It has been stated that the citizens in Estonia can do
basically anything online. [24]
Finland as an e-government has had the world rank of 9 in 2024 [24]. The Finnish
Digitalisation program, which is handled by the Finnish Ministry of Finance, has
stated that during the years 2019-2023 the amount of digital services in use was 162
and in progress there were 224 services. The themes for the digitized online services
for private persons were social security, healthcare, education, employee services,
family and relationships, culture and freetime, etc. The themes for businesses again
were establishing business, acting as an employer, businesses monetary support,
taxation, etc. [25][26]
3.2 SMART CITIES
The definitions of a smart city vary by different authors and researches and there
are multiple definitions for smart cities. Based on the literature searched for this
thesis, the most popular one is that for the city to be smart it must have five of the
following (covered also in the figure 3.3)[3]:
• Smart governance (the city’s governance is organized in a smart way)
• Smart education (the citizens’ education utilizes smart implementations)
• Smart healthcare (the healthcare is designed around smart technologies)
• Smart building (the city’s building projects are designed using smart imple-
mentations)
3.2 SMART CITIES 17
• Smart mobility (the city’s mobility, e.g. public transportation, is organized in
a smart way)
• Smart infrastructure (the infrastructure, e.g. water distribution is organized
in a smart manner)
• Smart technology (the overall technology of the city is smart)
• Smart energy (the energy distribution is organized in a smart way)
• Smart citizens (the citizens use e.g. smart applications to participate in the
city’s decision-making )
• Smart waste management (the city’s waste management is organized in a smart
way)
• Smart agriculture (the agricultural operations utilize smart implementations)
Since smart cities are based on technological solutions, sensors and sensor net-
works that handle different kind of data, it also important to recognize the tech-
nological aspects which are expected from smart cities and the handling of their
data. According to Harrison et al. [27] it is vital to emphasize on three features:
the near-real-time data obtained from the sensors, the interconnections of services
and technologies inside a city and an intelligence analysis of the data handling, ana-
lyzing, optimising and visualising. To summarize all these definitions it can be said
that the definition varies from the point of view you are looking at it. For example
the sociological and psychological views are very different compared to the technical
views mentioned above.
18 3.3 SMALL SMART CITIES
Figure 3.3: Smart city objectives
3.3 SMALL SMART CITIES
The city of Salo which is discussed in this thesis, can be described to be a small city
for example when compared to the top 10 smart cities mentioned in the previous
chapter. According to Halla-Aho [3] small smart cities are usually more agile since
the governance and the amount of decision-makers is smaller than in larger cities
and metropolitan areas. A small city’s population can also be more homogeneous
and the cultural background can be very limited compared to bigger cities, like
Singapore, which has residents from different cultures around the world.
While the city’s governance and decision-making can be easier to organize in
3.4 FUTURE TRENDS 19
small cities, it can create some difficulties and limitations as well. For instance in
Salo the population is aging since many of the working aged people are moving
to bigger cities. This can lead to the assumption that the citizens might not be
technology oriented and technology-driven. The education can be however easier,
since there is less population to educate and the social distance between the citizens
and the decision-makers is generally smaller than in bigger cities with millions of
inhabitants. In smaller cities like in Salo the residents might also experience that
they can contact the city’s government more easily and have an opportunity to make
an impact on the services that already exist or are about to be designed.
3.4 FUTURE TRENDS
The increasing amount of studies about smart cities can indicate the development
of smart cities gaining more popularity. While most of the implementations are
done in bigger cities and metropolitan areas this could also lead to smaller cities
following the trend. The ten leading smart cities in 2024 were from 1 to 10: Zürich,
Oslo, Canberra, Geneva, Singapore, Copenhagen, Lausanne, London, Helsinki and
Abu Dhabi. The list is also portrayed in figure 3.4. The cities are divided into four
groups by the Human Development Index (HDI) score. By the IMD Smart City
Index 2024: "within each HDI group, cities are assigned a ‘rating scale’ (AAA to
D) based on the perceptions-score of a given city compared to the scores of all other
cities within the same group". [28] The groups are:
• Highest HDI: AAA-AA-A-BBB-BB
• Second highest HDI: A-BBB-BB-B-CCC
• Third highest HDI: BB-B-CCC-CC-C
• Fourth highest HDI: CCC-CC-C-D
20 3.4 FUTURE TRENDS
None of the cities mentioned above cover yet all the definitions for a city to be
smart, but all of them cover at least one definition of a smart city. For instance
London has the ambition to provide open access to WiFi in public buildings and on
the streets, Oslo is trying to cut its emissions with smart energy distribution and
Singapore provides its citizens some smart housing possibilities. [28] [29]
Figure 3.4: Smart cities top 10 HDI comparison by IDM Smart City Index Report
2024 [28]
The smart city we will review more in-depth from the top 10 is Finland’s capital
Helsinki since it’s a city in Finland and thus linkable to the city of Salo. However
there are differences with the two cities since Helsinki is the capital of Finland and
there are 1,7 million inhabitants in the Helsinki-Uusimaa region. The area consists
of 26 municipalities which size varies from 600 000 inhabitants to 2000. All the
municipalities are agile and function as a platform. The region is the second most
innovative region in Europe, and was the second best smart city in the IMD Smart
City Index 2020 comparison. The area also won European Enterpreneurial Region
(EER) label in 2021-2022. [30] [31]
The three priorities for Helsinki-Uusimaa in 2030 are:
1. Climate change mitigation - carbon neutrality by 2035
3.4 FUTURE TRENDS 21
2. Economic competitiveness - increasing research and development areas
3. Citizen well-being - achieving employment rate of 80% by the end of 2030
The smart city project is providing applications for the Helsinki main area as well
as to the more rural areas of the Uusimaa region. The heart of the smart city
development has been Helsinki’s Kalasatama residential area which is developed
with the cooperation of its citizens. Helsinki actually counts so much on its citizens
that the city is adhering MyData principle and the citizens are the owners of their
own data. [30] [32]
One of their main themes is citizens’ city, and this covers for example transporta-
tion, housing, urban planning and healthcare which they desire to design together
with the citizens with data that has been made public [30]. One interesting ongo-
ing project for the citizens that could also benefit the citizens of Smart City Salo,
is gamificated walking tour for the senior citizens. During the walking tour there
are stopping points where there might be some information about the surround-
ing nature or history and some stopping points are for physical exercise designed
especially for the elder citizens. Another interesting project is a light installation
which entices the citizens to go out and to be part of diverse installation. Both of
these projects are part of bigger Kauko project which designs to shape the city with
citizens’ well-being innovations. [33]
4 METHODOLOGY
4.1 QUESTIONNAIRE DESIGN ANDDATA COL-
LECTION
The research questionnaire was organized as a voluntarily web questionnaire done
with survey and reporting platform Webropol, and the models mentioned in the
proceeding chapters were handled with different statements to which the respondent
had to choose option describing them the best. The statements had an option to
be answered according to the 5-point Likert scale which had five options: strongly
disagree, disagree, neither agree nor disagree, agree, and strongly agree. All the
Likert scale questions were mandatory for the participants, since all the questions
were vital to the models used in our survey. The questionnaire items are included
in the Appendices of this thesis.
At the start of the questionnaire we asked what were the respondent’s general
attitudes towards technology to unfold the respondents’ level of competence in tech-
nology. Only in the following page of the questionnaire it was explained what are
smart cities and after this the questions were more smart city related. The term
forced trust wasn’t used at all publicly since this could have affected possibly in a
negative way to the respondents’ answers.
After the questionnaire survey had been open to be answered approximately
eleven months the amount of answers was 99. During the first month the question-
4.2 BEHAVIOURAL-REASONING THEORY 23
naire was open solely to the citizens of Salo, after which the amount of Salo citizens’
answers was 20. It was then decided that the questionnaire should be opened to the
public and other citizens’ of Finland since 20 answers was too low. We started to
promote the questionnaire via social media and email and were able to gather 79
more answers.
4.2 BEHAVIOURAL-REASONING THEORY
According to Westaby [34] modern theories that are linked to behavioural intentions,
are based on the Theory of Reasoned Action by Fishbein & Ajzen [35], and the
Theory of Planned Behavior by Ajzen [36]. These theories cover from a psychological
point of view, how a person’s belief concepts affect to their global motives and this
way to their intentions, and thus to their behavior. Westaby also notes there are
multiple other studies on the sociology field. [34]
In his study Westaby introduces a whole new model based on its predecessors:
the Behavioral Reasoning Theory (BRT). While the traditional behavioral models
explained how belief concepts such as behavioral, normative and control beliefs
together with global motives create intention, Westaby adds the concepts of reasons
and values as an influence in addition to the original objects. The reasoning theory
from his earlier work with Fishbein [37] creates the basis for this hypothesis by
suggesting reasons being behind people’s actions. Through a set of studies tested
with different scenarios he comes to the same conclusion with his newer study that
"reasons serve as important linkages between people’s beliefs, global motives (e.g.,
attitudes, subjective norms and perceived control), intentions and behavior." [34]
Two models that land under concept of Behavioural Reasoning Theory and which
we are using in our study, are Innovasion Diffusion Model (IDM) and Innovation
Resistance Model (IRM). As Westaby introduced in his study [34], the reasons in
BRT can be divided into factors for and factors against covered in the figure 4.1.
24 4.2 BEHAVIOURAL-REASONING THEORY
Figure 4.1: The model for intention to use technology
4.2.1 Innovation Diffusion Model
Innovation Diffusion Model is based on the Diffusion of Innovation (DOI) Theory by
Rogers [38] and the model’s creator has been publishing new versions of the original
model throughout the years. In his sociological theory Rogers states how innovation
(e.g. new idea) is received in public after the knowledge of the innovation has spread
over a population. The spreading process is diffusion which does not happen all at
once, but through social stages. The objects affecting diffusion are:
1. What is perceived as an innovation
2. What are the means of communication
3. Time used in this process
4. The social system in general
In their work, Rogers suggests how innovation adaption depends on the factors of
relative advantage, compatibility, trialability, observability and complexity. These
are also the factors we will review in our study as the factors for. [38]
4.2 BEHAVIOURAL-REASONING THEORY 25
4.2.2 Innovation Resistance Model
Innovation Resistance Model’s base is the opposite from IDM. When IDM con-
centrates on the positive and assumes that at some point people will accept new
innovations, IRM focuses on the resistance towards new innovations. The model
was first discussed by Ram and Sheth [39] to understand the underlying reasons of
customers’ rejection of innovations. To understand better whether the citizens of
Salo would accept or reject smart city innovations it is good for us to take IRM
under the study as well.
The functional barriers Ram and Sheth list are:
• Usage barrier
• Value barrier
• Risk barrier
The psychological barriers again, are:
• Tradition barrier
• Image barrier
The usage barrier reflects the negativities in use, e.g. that the innovation usage is
too different from the one people are used to. Value barrier is straight comparable
to the price-value and risk barrier represents the risks new innovations can bring
to the person(s) using those. Tradition barrier refers to the difference a user would
have to make to their traditions in order to use new innovation. And at last image
barrier is the possible negative appearance a user might receive even before using
the innovation. [39]
26 4.3 TECHNOLOGY ACCEPTANCE MODELS
4.3 TECHNOLOGY ACCEPTANCE MODELS
In the comparison of IDM and IRM, IDM is about the factors for acceptance and
IRM is about the factors against acceptance. The other models we decided to use in
the Salo Smart City study are Technology Readiness Index 2.0 (TRI 2.0) and some
parts of the Unified Theory of Acceptance and Use of technology (UTAUT).
4.3.1 Technology Readiness Index 2.0
Technology Readiness Index was first introduced in 2000 by Parasuraman who has
later updated their model to meet the modern requirements of what technology
nowadays offers to us. The TRI 2.0 was updated by Parasuraman and Colby [40]
who have added some items to the Technology Readiness scale of 36 items first
introduced with the TRI 1.0. The new list contains 45 items which disperse under
four categories:
• Optimism
• Innovativeness
• Discomfort
• Insecurity
All the items focus on users’ personal characteristics and of the four, optimism
and innovativeness are motivators for technological readiness while discomfort and
insecurity are inhibitors. [40]
4.3.2 Unified Theory of Acceptance and Use of Technology
The first version of the UTAUT was developed by Venkatesh et al. [41] and it
handled the subject of technology employee usage of solutions. The new version of
4.3 TECHNOLOGY ACCEPTANCE MODELS 27
this model the UTAUT2 by Venkatesh et al. [42] was designed to target consumers
instead of employees. In the original model there were four key items:
• Performance expectancy
• Effort expectancy
• Social influence
• Facilitating conditions
For consumers performance expectancy means the expected outcome of performance
from the product and effort expectancy explains how effortlessly the product can
be used. Social influence measures the significance of a customer’s social circle in
relation to the usage of the product (e.g., "Does my caregiver believe I should use
the product?"), and facilitating conditions explores if the customer have enough
helpful resources and guides to use the product. [41]
The new factors, that were added to UTAUT2 are: hedonic motivation, price
value and habit. Hedonic motivation means literally the hedonistic side of using
a product, and wether using it is e.g. fun or pleasurable. Price value is about the
monetary cost in relation to the usage of a product, and habit means if the customer
is able to create a habit using the product. In our study we handle the items social
influence and price value since these perspectives fit our study the best. [42]
4.3.3 Additional Factors
This thesis being a new study and not having any research to use as its basis the
creation of the questionnaire had its difficulties. To create more depth to the study
analysis we added some factors from other studies, which would benefit our study:
• Trust in technology
• Trust in government
28 4.4 MEASURES
• Openness to change
• Forced trust
• Perceived security
• Perceived privacy
In addition to these, we also included some dependent variables: Acceptance and
Quality of Life.
4.4 MEASURES
Our study questionnaire consisted of seven parts. The first part was non-optional
questions about the respondents basic knowledge about smart cities and smart in-
novations. The second part included the TRI 2.0 questions and the third part
dependent variables’ questions. The fourth part was the IDM questions which were
the factors for change and the fifth part the IRM and the factors against change.
The sixth part included additional factors and the last seventh part was non-optional
moderators: gender, age, education level, urban area citizen/rural, living with family
or single and city worker or not.
The first model we used, was the Technology Readiness Index 2.0. The TRI 2.0
measures technological readiness and acceptance. The four categories mentioned
earlier in section 4.2.1 are Optimism, Innovativeness, Discomfort and Insecurity
which are portrayed more in detail in figure 4.2.
4.4 MEASURES 29
Figure 4.2: TRI 2.0
Dependent variables are the Quality of Life (QOL) and the Acceptance (ACP).
The QOL in living and working environments (e.g. in a smart city) can impact
on new innovations, political decision-making, cultural life and overall change. So
the better the acceptance and trust towards smart city services/technologies, the
better the experienced quality of life. The Acceptance again refers to the citizens’
acceptance towards new SC services/technologies. The Acceptance is linked with
the quality of life and citizens’ acceptance increases the experienced quality of life.
According to the Innovation Diffusion Model a person’s acceptance and adop-
tion of innovation would be influenced by the following factors: Relative Advantage
(RLA), Compatibility (COM), Complexity (CPL), Trialability (TRI) and Observ-
ability (OBS). From the UTAUT 2 model we also added Price Value (PV) for mea-
30 4.4 MEASURES
suring monetary costs of innovation. The details of these factors are portrayed in
figure 4.3.
Figure 4.3: Innovation Diffusion Model with Price Value
Like mentioned in the earlier section 4.1.2, the Innovation Resistance Model again
handles the concepts of Usage Barriers (UB), Value Barriers (VB), Risk Barriers
4.4 MEASURES 31
(RB), Tradition Barriers (TB) and Image Barriers (IB). These are the factors against
new innovations and described in figure 4.4.
Figure 4.4: Innovation Resistance Model
Additional factors we used were Social Influence (SI) from the UTAUT model,
and the others were Trust in Technology, Trust in Government, Forced Trust, Per-
ceived Security and Perceived Privacy. These factors are represented in figure 4.5.
32 4.4 MEASURES
Figure 4.5: Additional factors
Moderators for the questionnaire were gender, age, education, citizen or not, city
worker or not and living with family or single.
5 STUDY AND DISCUSSION
5.1 RESULTS
After the questionnaire had been open for 11 months the amount of answers was 99.
20 of the answers were from the Salo citizens and 79 from other parts of Finland. The
answers were then analyzed with Webropol. The answers were originally gathered
with Webropol so the analyze was made with it as well.
Over 50% of the answers were by female participants on both answer pools. The
median age of the participants was 46 years for the citizens of Salo, and 27 years for
the extended questionnaire. From the Salo citizens the highest level of education
was university degree with 45%, and for the rest of the Finland it was the same with
49,4%. 65,8% of the participants from around Finland were students and most part
of the Salo citizens were employed (70%). Most people lived in the city area and
Salo’s city workers were only 5% (n=2) of the answers from Salo citizens.
When viewing the answers for the first part, TRI 2.0, most of the answers were
positive. For optimism 38% of answers agreed, the innovativeness agreed 36,4%,
discomfort agreed nor disagreed 28,3% and insecurity was surprisingly 29,9% with
most people agreeing to be insecure with trusting technology (fig 5.3).
34 5.1 RESULTS
Figure 5.1: Level of education (n=99)
Figure 5.2: Work situation (n=99)
5.1 RESULTS 35
Figure 5.3: Insecurity from TRI 2.0
With dependent variables, acceptance and quality of life, 43,3% were agreeing
with acceptance related questions. Quality of life containing 15 questions, 42,4% of
the answers weren’t agreeing nor disagreeing.
The third part was the IDM and the factors for innovation. With price value
54,1% were agreeing, with relative advantage 41,3% were agreeing and with compat-
ibility 42,8% were agreeing. Complexity showed similar positive trend with 35,9%
disagreeing as well as trialability agreeing with 39,3%. The last question about
observability was agreed with 43,5% of respondents.
Fourth part of the questionnaire was about the IRM. Usage barriers had a posi-
tive outcome with 40,2% agreeing and value barriers the same with 40,9% agreeing.
Risk barriers continued with the same trend with 26,9% of answers disagreeing with
risks. Tradition barriers were met with opinion of valuing more non-traditional
ways with 34,2% of answers disagreeing with traditional ways. The respondents
also disagreed with having image barriers (41,5%).
Fifth part consisted of additional factors like trust and forced trust. The first
factor trust in technology was met with median answer to be 3. This cut the
36 5.1 RESULTS
answers in half with people neither agreeing nor disagreeing (fig 5.4). Trust in
government was again viewed as positive with 40,8% agreeing to trust in government.
Forced trust showed most of the participants feeling they should trust in smart city
innovations nevertheless with 41,4% agreeing the statements (fig 5.5). Perceived
security was viewed with mixed state with most respondents neither agreeing nor
disagreeing (fig 5.6). Then again perceived privacy was viewed more positively with
41,3% trusting their private information would be safe with smart city innovations
and applications (fig 5.7). The last factor social influence was met with mixed
feelings and people agreed nor disagreed with 56,5%.
Figure 5.4: Trust in Technology from Additional factors
5.1 RESULTS 37
Figure 5.5: Forced Trust from Additional factors
Figure 5.6: Perceived Security from Additional factors
When viewing the answers the notable thing is, that the respondents had an
overall positive view towards technology and smart city innovations. However the
respondents had mixed responses with trusting the security of smart city applications
but still they trusted their private information to be safe with the possible smart
city applications which was contradictory. Forced trust was seen as a supposition
and people felt they would have to trust smart city innovations no matter what.
38 5.1 RESULTS
Figure 5.7: Perceived Privacy from Additional factors
5.1.1 Gender comparison
When viewing the answers given by males, factors that stood out were insecurity
from the TRI 2.0 (median 4.0 agreeing in fig 5.8) and perceived security was also
met with distrust by 34,3% disagreeing. Again in contradiction, perceived privacy
was met with most men agreeing. Trust in technology from additional factors was
met not disagreeing nor agreeing as we can see from figure 5.9. Forced trust was
met with the median answer of 4, and the participants saw that they would have to
trust the technologies nevertheless (fig 5.10).
When viewing the answers by women, insecurity was pointing out again like
with the overall score and with men’s score with 36% agreeing to be insecure with
technologies (fig 5.11). Trust in technology was met with more negativity and 36,9%
were disagreeing with the trust while the median answer was still 3, not agreeing
nor disagreeing (fig 5.12). And again like with men perceived privacy was met with
most women agreeing that the systems would keep their private information safe
(50% agreeing). Forced trust was seen as a must be supposition again with most
women agreeing they should trust the applications and innovations nevertheless as
represented in figure 5.13.
5.1 RESULTS 39
Figure 5.8: Men’s view on Insecurity
Figure 5.9: Men’s view on Trust in Technology
40 5.1 RESULTS
Figure 5.10: Men’s view on Forced Trust
Figure 5.11: Women on Insecurity
5.1 RESULTS 41
Figure 5.12: Women on Trust in Technology
Figure 5.13: Women on Forced Trust
With both gender groups factors that stood out was insecurity and forced trust.
The participants had trust issues towards the systems and that malicious parties
would not misuse the information. In contradiction perceived privacy from ad-
ditional factors was met with approval and both genders agreed to believe their
private information would however be kept safe in smart applications and systems.
With the factor of forced trust neither groups had any disagreement and forced trust
was seen as a supposition.
42 5.1 RESULTS
5.1.2 Age groups
The second comparison was made between three different age groups: 20 to 29, 30
to 39 and 40 to 78. Within the age group of 20 to 29 years old the first question
that stood out was insecurity from the TRI 2.0 with 31,5% of answerers agreeing
to the harms of technologies (fig 5.14). The second strongest opinion was strongly
agreeing with 24,2%.
Figure 5.14: Ages 20 to 29 on Insecurity
Again like in the other comparisons, trust in technology was met in neutral way
with most participants neither agreeing nor disagreeing as pictured in the figure
5.15.
Figure 5.15: Ages 20 to 29 on Trust in Technology
Trust in government was again agreed with most participants trusting and the
participants saw forced trust as a must (fig 5.16). Perceived security was seen in a
5.1 RESULTS 43
negative way like in the overall score of all participants (fig 5.17). However perceived
privacy was met with agreement with most of the respondents trusting their private
information to be safe with smart technologies.
Figure 5.16: Ages 20 to 29 on Forced Trust
Figure 5.17: Ages 20 to 29 on Perceived Security
The age group 30 to 39 years old showed similar trend with insecurity. With trust
in technology this age group showed results of most of the people neither agreeing
nor disagreeing with the questions like the previous groups. This is portrayed in the
figure 5.18.
44 5.1 RESULTS
Figure 5.18: Ages 30 to 39 on Trust in Technology
Forced trust was also met with most people agreeing they would have to trust
smart city innovations nevertheless, as seen in the figure 5.19.
Figure 5.19: Ages 30 to 39 on Forced Trust
Same trend continued with this age group when it came to perceived security
(most people disagreeing) but surprisingly perceived privacy showed mixed results
with neither agreeing nor disagreeing (fig 5.20).
5.1 RESULTS 45
Figure 5.20: Ages 30 to 39 on Perceived Privacy
The last comparison was made in the age group of 40 to 78 years old. The
first surprising result was with the factor insecurity which showed most participants
strongly agreeing and agreeing with insecurity (the other groups just agreeing). This
is portrayed in the figure 5.21.
Figure 5.21: Ages 40 to 78 on Insecurity
Another surprising element was that the older participants had an overall more
positive view on trust in technology (fig 5.22). This age group was also the first to
46 5.1 RESULTS
show that they weren’t agreeing nor disagreeing with forced trust by 32,0% being
neutral about the forced trust statements (fig 5.23).
Figure 5.22: Ages 40 to 78 on Trust in Technology
Figure 5.23: Ages 40 to 78 on Forced Trust
This was also the first group that didn’t agree nor disagree with perceived secu-
rity, as seen with figure 5.24. With perceived privacy the results were same as with
other age groups and they mostly agreed (46,7%).
5.2 DISCUSSION 47
Figure 5.24: Ages 40 to 78 on Perceived Security
5.2 DISCUSSION
At first we need to identify the fact that our sample size from the questionnaire
was low (n=99). Most of the participants were also relatively young and only 3
participants were over 61 years old so observing the results from senior citizens’
point of view could not be done so in depth we wanted. The amount of participants
who were Salo city-workers or who lived in rural areas was also low so comparison
of these groups could not be done.
There weren’t any differences when it came to the gender groups and perceived
security was seen in a negative way. However most of the respondents trusted their
private information to be safe with smart city innovations and they had mixed overall
trust in technology. With the factor of forced trust there weren’t any disagreement
and both of the groups believed they would have to trust the systems nevertheless.
When it came to age groups the results followed the same trend as with the
gender groups. The only thing that stood out was that the last age group 40-79
trusted more in technology. This was also the only group that answered not agreeing
nor disagreeing to the forced trust statements.
48 5.3 OTHER STUDIES ON SMALL SMART CITIES
5.3 OTHER STUDIES ON SMALL SMART CITIES
AND THE CITIZEN PERSPECTIVES
One interesting study that touches our topic is by Suopajärvi [43] and it ponders the
question of how the senior citizens handle the aspect of being a smart city citizens
in the city of Oulu in Northern Finland. The main point of the study is that the
elder citizens want to be included within the aspects of a smart city ideology but on
their own terms and to make the decision of being a smart city citizen voluntarily
and not by being forced to it. [43]
In the study Suopajärvi interviewed senior citizens aged 61 to 87. Most of the
participants were women and recruited from computer courses. With interviews
Suopajärvi found out that most women seniors were concerned about the decreasing
amount of human interaction when using for instance online services like banking.
Going to a physical bank also affected their physical exercising which decreased
with the use of online services. Through their discussions they also found out two
things that were missing from Oulu: cross-generational sense of community, as well
as communication between the city and the senior citizens. Some notions were made
by the elderly and they suggested that teenagers could teach them computer skills.
The elderly could then teach the teenagers some other skills like baking. This way
the senior citizens could have face-to-face learning and physical exercise going to
classes as well. [43]
With our study of the smart city of Salo we didn’t have enough senior citizens
to answer to our questionnaire. We can then conclude that more research should be
done and more citizens from different backgrounds and age groups should be taken
into consideration when building smart city applications. For instance Suopajärvi
arranged workshops with some of the senior citizens of Oulu which meant many
things for the elderly: "making a difference, belonging to a community and receiv-
5.3 OTHER STUDIES ON SMALL SMART CITIES 49
ing information". It was also concluded that the senior citizens perceive high-tech
innovations in a good manner but would not like to be forced to use the new systems.
"By respecting the history of the city through the infrastructure, the current city
would simultaneously respect the life histories of its elderly citizens." [43]
6 CONCLUSIONS
6.1 ANSWERS TO RESEARCH QUESTIONS
In Chapter 2 we defined what is trust, forced trust and the ethics of these. We
determined that to trust is to put belief in something, to put value in something.
With forced trust we observed the idea of Panopticon and the example of waste
management in a smart city. We also considered privacy as a part of the ethicality
of forced trust.
In Chapter 3 we took a look on digital transformation, smart cities and small
smart cities. We defined the factors that must be present for a city to be smart. The
factors included for instance smart governance and smart infrastructure. When it
comes to small smart cities we made the conclusion, that Salo is a small smart city
on the world’s scale where the population is aging. This can lead to better communi-
cation between city’s decision makers and/or to some resistance when implementing
new smart applications and ideologies.
In Chapter 5 we took a look on our questionnaire and how the survey participants
reacted to forced trust and other factors we handled in our questionnaire. Within
the gender groups there weren’t a lot of differences with the results. Within the age
groups there were some differences and surprisingly older participants were more
trusting towards technology. They also didn’t see forced trust in as agreeing manner
as the younger age groups.
6.2 POTENTIAL FUTURE WORK 51
6.2 POTENTIAL FUTURE WORK
When discussing about the future work for smart cities and the citizens’ trust and
attitudes towards these cities, we have to acknowledge that there aren’t any prior
work handling this aspect. When more studies are being done and the more re-
liability is got with more studies and amount of respondents in studies, the more
accurate answers and conclusions are get from these studies.
Since there is no prior work done about the subject handled in this thesis it is hard
to compare the results to anything. Also the low amount of responses to the survey
questionnaire doesn’t create dependability usually required for qualitative research.
Cultural differences and age cohorts must be included in the discussion as well since
these could not be handled with our study. The opinions and attitudes could differ
a lot in western cultures and for instance in eastern cultures. Some other differences
could also appear with cultures more religious or when talking about collectivity of
eastern cultures versus individualism linked to western cultures.
After these aspects we can conclude that altogether more research about this
subject is required. More cross-cultural surveys and more surveys in general is
recommended. This thesis and survey can however act as a good basis for future
research and the models used in the questionnaire survey can probably be used in
other surveys handling the same subject.
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Appendix A Research questionnaire
P e o pl e’ s vi e w s t o w ar d S m art Cit y S er vi c e s a n d T e c h n ol o gi e s
Hi y o u!
I a m a m a st er d e gr e e st u d e nt at t h e D e p art m e nt of C o m p uti n g, U ni v er sit y of T ur k u. A s a p art of m y t h e si s, I a m
st u d yi n g citi z e n s' vi e w s t o w ar d s s m art cit y s er vi c e s a n d t e c h n ol o gi e s, a n d t hr o u g h t h e s ur v e y , I will c oll e ct d at a
t h at will pr o vi d e i n si g ht s i nt o citi z e n s' p er c e pti o n s r e g ar di n g s m art cit y s er vi c e s a n d t e c h n ol o gi e s. T h e r e s ult s
fr o m t h e st u d y will al s o b e u s e d f or r e s e ar c h a n d t o g e n er at e str at e gi c i n si g ht s t h at will b e t a k e n i nt o
c o n si d er ati o n b y t h e Cit y of S al o f or t h eir s m art cit y pr oj e ct.
 
Y o ur p arti ci p ati o n i s of ut m o st i m p ort a n c e t o m e. S o, s p ar e 1 5- 2 0 mi n ut e s of y o ur ti m e a n d p arti ci p at e i n t hi s
st u d y b y c o m pl eti n g t hi s s ur v e y . T h er e i s n o ri g ht or wr o n g a n s w er t o a n y q u e sti o n. Pl e a s e, r e a d t h e i n str u cti o n s
i n e a c h p art t o a n s w er t h e q u e sti o n o pti o n s
N o i d e ntif yi n g i nf or m ati o n i s b ei n g c oll e ct e d, s o w e c a n n ot k n o w w h o a n s w er e d w h at i n t hi s s ur v e y . T h e d at a
c oll e cti o n i s a n o n y mi z e d a n d, t h u s, c a n n ot a n d will n ot b e u s e d t o i d e ntif y y o u fr o m t h e r e s p o n s e s. T h er ef or e, w e
r e q u e st y o u t o a n s w er t h e q u e sti o n s a s h o n e stl y a s p o s si bl e.
T h e d at a will b e a n al y z e d b y o ur r e s e ar c h t e a m m e nti o n e d b el o w a n d will b e u s e d f or r e s e ar c h p u bli c ati o n s. I n
c a s e y o u h a v e a n y q u eri e s, ki n dl y dir e ct t h e m t o m e at st m h y v @ ut u.fi (t h e si s w or k er a n d r e s e ar c h a s si st a nt).
T h a n k y o u i n a d v a n c e!
R e s e ar c h T e a m:
- S e p p o Virt a n e n, A s s o ci at e Pr of e s s or
- Ali F ar o o q, P o st d o ct or al R e s e ar c h er
- A ntti H a k k al a, U ni v er sit y T e a c h er
- S u vi- Tu uli H y v ö n e n, R e s e ar c h A s si st a nt
1.  Pl e a s e, fill o ut t h e f oll o wi n g t o p arti ci p at e t h e st u d y . *
Y e s N o
I u n d er st a n d t h e p ur p o s e of t hi s st u d y. 
*
I u n d er st a n d t h at m y a n s w er s ar e u s e d
a n o n y m o u sl y i n t h e st u d y .  *
I' m p arti ci p ati n g t hi s st u d y v ol u nt aril y.  *
P a r t 1:
 M a n d at or y q u e sti o n s ar e m ar k e d wit h a st ar (*)
In this part, you can tell with your own words, what smart services/technologies you know that exists already.
2. What smart services/technologies do you know already? Write freely in the text field below.
3. What smart services/technologies do you wish more to your city of resedence? Write freely in the text
field below.
4. What smart services/technologies do you believe people would need? Write freely in the text field
below.
Part 2:
In this part, we present some common statements about technolgy in general to understand you as a user of
technology.
Please, read every statement and choose one, which describes you the best. As a scale we are using the
following:
1. Strongly disagree
2. Disagree
3. Neither agree nor disagree
4. Agree
5. Strongly agree
5. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
Technology gives me more freedom of
mobility.  *
Technology gives people more control over
their daily lives.  *
Technology makes me more productive in
my personal life.  *
Products and services that use the newest
technologies are much more convenient to
use.  *
Communications technology and the
Internet help people build stronger
relationships.   *
6. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
Other people come to me for advice on
new technologies.  *
In general, I am among the first in my circle
of friends to acquire a new technology
when it appears.  *
I keep up with the latest technological
developments in my areas of interest.  *
I can usually figure out new high-tech
products and services without help from
others.  *
7. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
Technical support lines/support staff are
generally not helpful because they don’t
explain things in terms I understand.   *
Sometimes, I think that technology services
are not designed for use by ordinary
people.  *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
There is no such thing as a manual for
high-tech technologies that is written in
plain language.  *
Many new technologies have health or
safety risks that are not discovered until
after people have used them.  *
8. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
People are too dependent on technologies
to do things for them.  *
Too much technology distracts people to a
point that is harmful.  *
Technology lowers the quality of
relationships by reducing personal
interaction.  *
The human touch is very important when
doing business with a company  *
New technology makes it too easy for
governments and companies to spy on
people.  *
What does a smart city mean?
Smart city can cover, for instance, the following:
- Smart government and education (A city's governance and citizens' education is organized in a smart way)
- Smart building (New building projects in a city have been organized in a smart way)
- Smart traffic (For instance, a city's public transportation has been organized in a smart way)
- Smart infrastructure (For instance, a city's waste management has been organized in a smart way)
- Smart technology (For example, a city is using smart technology in their projects)
- Smart energy distribution (For example, a city's energy distribution has been organized in a smart way)
- Smart citizens (For example, the citizens have a possibility to use smart applications, like mobile apps for
handling their city-related matters)
Please, keep in mind the definition of a smart city when answering to the following questions. We are referencing
to this definition of a smart city in the following statements when talking about smart services and technologies.
Part 3:
Now that you know the definition of a smart city, we would like to know your opinion about smart cities.
Please, read every statement and choose one, which describes you the best. As a scale we are using the
following:
1. Strongly disagree
2. Disagree
3. Neither agree nor disagree
4. Agree
5. Strongly agree
9. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
I would consider using SC
services/technologies when they are
available in the market.   *
I would recommend SC
services/technologies to my family and
peers.  *
I would encourage others to use SC
services/technologies.  *
I have positive things to say about SC
services/technologies.  *
10. Due to SC services/technologies, *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
A city will become a safer place to live in.  *
The administrative services will help people
efficiently.  *
The state of the streets and buildings will
become better.  *
The mobility infrastructure will improve.  *
There will be more green spaces (parks,
plantations, etc.).  *
There will be better cleanliness.  *
There will be better cultural facilities.  *
The trust between people would improve.  *
The quality of the air will improve.  *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
I will lead a satisfied life.  *
My household financial situation will
improve.  *
I will be satisfied with the place where I
live.  *
the trusting environment among people will
improve.  *
People will be more united.  *
The public administration of a city can be
trusted.  *
Part 4:
In this part we present some statements to understand your opinions towards SC services/technologies.
Please, read every statement and choose one, which describes you the best. As a scale we are using the
following:
1. Strongly disagree
2. Disagree
3. Neither agree nor disagree
4. Agree
5. Strongly agree
11. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
I feel that using SC services/technologies
can better cater to my living requirements
(e.g. safety, reliability, security or
convenience needs).   *
I feel that using SC services/technologies
can confer cost-savings.  *
I feel that using SC services/technologies
can be pleasant.  *
I feel that using SC services/technologies
can have positive effects on the
environment and society.  *
12.
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
Using SC services/technologies would
enable me to accomplish tasks more
quickly.  *
Using SC services/technologies would
improve my quality of life.  *
Using SC services/technologies would
make my work easier.  *
Using SC services/technologies would be
more advantageous compared to
conventual city services.  *
Using SC services/technologies would be
environmentally friendly option.  *
13. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
Using SC services/technologies would be
compatible with my lifestyle.  *
Using SC services/technologies would fit
well with my current living habits.  *
Using SC services/technologies would be
compatible with my needs.  *
Using SC services/technologies would suit
me well.  *
Using SC services/technologies would be
in line with my everyday life.  *
14. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
SC services/technologies would be difficult
to use.   *
SC services/technologies would be
frustrating to use.  *
SC services/technologies would require a
lot of effort to use.  *
15. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
I feel it is would be easy to try out SC
services/technologies.   *
I know where I could go to try out various
functions of SC services/technologies.  *
I could be permitted to try out with SC
services/technologies for long enough
period.  *
I would be able to experiment with SC
services/technologies when necessary.  *
16. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
I believe I could explain to others how to
use SC services/technologies.  *
I would have no difficulty telling others
about the process of using SC
services/technologies.  *
I believe I could communicate to others
about the benefits of using SC
services/technologies.  *
Part 5:
In this part, we present more statements to understand your opinions towards SC services/technologies.
Please, read every statement and choose one, which describes you the best. As a scale we are using the
following:
1. Strongly disagree
2. Disagree
3. Neither agree nor disagree
4. Agree
5. Strongly agree
17. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
The use of SC services/technologies would
be convenient for me.  *
Using SC services/technologies would
require new behavior/s.  *
SC services/technologies would fit well with
the way I like to get things done.  *
Use of SC services/technologies would be
completely compatible with my needs.  *
18. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
SC services/technologies would not offer
any advantage or benefit compared to the
services I am currently using.  *
In my view, SC services/technologies are
superior to current city
services/technologies products.  *
SC services/technologies would offer
advantages not offered by current city
services/technologies.  *
SC services/technologies would solve
problems that cannot be solved with
current city services/technologies.  *
19. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
I fear that others might judge me for using
SC services/technologies.  *
SC services/technologies will increase my
household budget.  *
I have some doubts about SC
services/technologies.  *
Using SC services/technologies might
result in negative consequences.  *
20. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
I find the traditional ways of living better
than living would be with SC
services/technologies.   *
I would prefer to carry out my everyday
chores through traditional means rather
than using SC services/technologies.  *
I am so used to traditional means to do my
everyday living that I could find it difficult to
move to SC services/technologies  *
The SC services/technologies match my
values and norms.  *
21. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
SC services/technologies will be too
complicated to be useful.  *
I believe SC services/technologies will be
difficult to use.  *
I have only positive feelings towards SC
services/technologies  *
I don't like SC services/technologies.   *
Part 6:
In this part, we present again more statements to understand your opinions towards SC services/technologies.
Please, read every statement and choose one, which describes you the best. As a scale we are using the
following:
1. Strongly disagree
2. Disagree
3. Neither agree nor disagree
4. Agree
5. Strongly agree
22.
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
I trust the security of the SC
services/technologies.  *
I trust the legal/technical infrastructure of
SC services/technologies is sufficient in
protecting my information.  *
I trust the devices that collect and process
my data while I am using SC
services/technologies.  *
I can count on SC services/technologies to
protect my information.  *
23. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
I trust in public departments and
institutions.  *
I trust in city’s capabilities in providing safe
SC services/technologies.  *
I trust that citizens’ interest is city’s first
priority.  *
I trust city’s procedures to protect my
personal information.  *
24. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
I will have to trust the SC
services/technologies no matter what.  *
I will have to count on SC
services/technologies to protect my
personal information nonetheless.  *
I will have no option but to trust SC
services/technologies.  *
There is no option but to trust the public
departments when it comes to SC
services/technologies.  *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
No matter what, I will end up trusting City’s
procedures to protect my privacy while
using SC services/technologies.   *
25. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
I am confident that the private information I
provide with SC services/technologies will
be secured.  *
I believe that inappropriate parties may
deliberately view the information I provide
to SC services/Technologies.  *
I believe the information I provide with SC
services/technologies will not be
manipulated by inappropriate parties.  *
26. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
I think that the SC services/technologies
will not provide my personal information to
other entities without my consent.  *
I think that the SC services/technologies
will not use my personal information for
other purposes without my authorization.  *
I think that the SC services/technologies
show concern for the privacy of its users.  *
27. *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
People who are important to me think that I
should use SC services/technologies.  *
People who influence my behavior think
that I should use SC
services/technologies.  *
Strongly
disagree Disagree
Neither agree nor
disagree Agree
Strongly
agree
People whose opinions I value prefer that I
use SC services/technologies.  *
Part 7: Demographics
Please, fill out the following information about yourself. The data collection is done anonymously so you cannot
and will not be connected to the answers you provide.
28. Your gender: *
Male Female Other / Prefer not to tell
  *
29. If you chose the option "Other", you can fill in additional information below:
30. Your age: *
Please, write your age in numbers, like 18 or 36. Do not write your year of birth.
31. Choose your highest level of education: *
32. If you chose the option "Other", you can fill in additional information below:
Elementary school
Vocational school/trade school
High school
Lower university degree
Higher university degree
Doctoral degree
Other
33. Are you: *
34. If you chose the option "Other", you can fill in additional information below:
35. Do you live: *
In a city area In sparsely populated area Other
  *
36. If you chose the option "Other", you can fill in additional information below:
37. Your housing situation: *
Living alone Living with family Other form of housing
  *
38. If you chose the option "Other", you can fill in additional information below:
Student
Employed
Enterpreneur
Unemployed
Pensioner
Other