Int. Journal of Business Science and Applied Management, Volume 18, Issue 2, 2023
Exploring Willingness to Adopt Contact Tracing Applications: A
Study with Norwegian Citizens
Christian Ødeskaug
Department of Information Systems, University of Agder and Sopra Steria
Biskop Gunnerus gate 14A, Oslo, 0185, Norway
Tel: +47 410 07 881
Email: christian.odeskaug@soprasteria.com
Tord Vetle Gjertsen
Department of Information Systems, University of Agder and Experis Academy
Lakkegata 53, Oslo, 0187, Norway
Tel: +47 458 85 686
Email: tord@gjertsen.org
Samrat Gupta
Indian Institute of Management Ahmedabad
#63, KLMDC, IIM, Ahmedabad, 380015, India
Tel: 07971524957
Email: samratg@iima.ac.in
Ilias O. Pappas
Information Systems, Agder
Postboks 422, 4604 Kristiansand, Norway
Tel: +4738141449
Email: ilias.pappas@uia.no
Abstract
Amid discussions on the efficacy of digital contact tracing (DCT) during COVID-19, the Norwegian Institute of
Public Health's application, Smittestopp, faced criticism for perceived privacy intrusions. Despite its relaunch
without GPS-tracking, skepticism persisted due to initial issues. This study proposes a model to assess DCT
adoption, focusing on Norwegian citizens' privacy concerns, trust, and risk beliefs, particularly towards
Smittestopp. The moderating role of emotions is also examined. Findings indicate that privacy concerns
inversely affect trust and enhance risk beliefs. Trust and perceived advantages bolster the intention to use the
application, while risk beliefs reduce it. Negative emotions moderate the relationship between risk beliefs and
intention to use, whereas positive emotions amplify the influence of perceived benefits on app usage intention.
Intention to use led to actual utilization of the Smittestop app. These insights increase our understanding of how
DCT apps are perceived in a country in which citizen trust in government is high, while offering significant
implications for managing future crises and contagion spread.
Keywords:
digital contact tracing, information privacy concerns, human emotions, COVID-19, quantitative
research
Int. Journal of Business Science and Applied Management / Business-and-Management.org
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1. INTRODUCTION
Digital contact tracing (DCT) is a technology utilized by many countries and has been an important asset in
the fight against the COVID-19 virus (Sun & Viboud, 2020). Governments across the world tried to develop
DCT-applications as a public health practice to track, identify and notify victims of the COVID-19 disease.
According to a simulation model at the time, COVID-19 is a pandemic that can only be stopped if at least 10%
of the population is tested every day under highly regulated testing conditions (Cebrian, 2021). With this being
hard to accomplish, many different DCT-solutions were proposed instead. These have been shown to vary in
efficiency, privacy, and data collection implications
(Riemer et al., 2020). For example, Germany invested
significantly in their Corona-Warn-app, France supervised a free easy-to-use StopCovid-app and Ireland
released an application with a notably high uptake (Martin et al., 2020). An extensive study has been conducted
on Australia’s own DCT-solution, the COVIDSafe-app, focusing on the citizens' willingness to adopt the
application and share personal information (Lin et al., 2021). The Australian application, COVIDSafe, raised
privacy concerns amongst its national citizens despite the application enforcing personal information and
privacy protection (idem). The pandemic led to the transformation of different fields within work and life, with
new digital tools and services being developed (Dwivedi et al., 2020), while raising the need for more
responsible digital transformations (Pappas et al., 2023). As the world is moving on from the pandemic, it is
important to get a better understanding of how citizens respond to digital tools based on emerging technologies
(Lu, 2021; Pappas et al., 2018), especially ones designed for the public good (Pappas et al., 2023), since recent
studies show that citizens are likely to resist using tools for DCT (Prakash & Das, 2022), even though there is a
general consensus that they are useful and successful in contact tracing. Contact tracing, followed by isolation
or treatment is a crucial preventive measure in the fight against infectious diseases. It has the potential to be
quite effective in circumstances when there are not many people affected. This is why it is frequently employed
in the fight against novel invasive infections and sexually transmitted diseases (Cebrian, 2021; Eames and
Keeling, 2003). As a response, this study has focused on the Smittestopp-app, which is Norway’s DCT solution,
to investigate Norwegian citizens' perception of digital contact tracing applications in Norway.
Though Norway and other countries are now more experienced in handling a global pandemic, it is
important to examine previous instances and evaluate the effectiveness of measures taken to prevent the disease,
as new waves are to be expected (Osuchowski et al., 2020). By examining how DCT was utilized during the
pandemic, greater preparations can be made in a post-pandemic world for future emergencies. Research has
shown that individual differences influence uptake more than application design (Li et al., 2021). Some policies
have been proposed to increase uptake, but whether they have had an effect remains to be seen (Chen & Thio,
2021). Lin et al. (2021) highlight the need for more research on contact tracing applications in different
countries and its impact on willingness to utilize them by further exploring citizens’ privacy attitudes. As there
is currently a lack of research regarding privacy and trust beliefs in online and governmental services after
COVID-19 (Prakash & Das, 2022), we draw on existing studies and the Internet Users' Information Privacy
Concerns (IUIPC) model, to examine the adoption of the Smittestopp-application in Norway. We have
conducted a conceptual replication (Dennis & Valacich, 2014) of the work by Lin et al. (2021), as we adopt part
of their model and test it in a different context. Also, we extend that model by testing the moderating effects of
emotions. Without people partaking in using these apps, such solutions are inevitably deemed unsuccessful.
Thus, we propose the following Research Question (RQ): “How do privacy concerns, trusting and risk beliefs,
relative advantage, and emotions affect citizens’ willingness to adopt contact tracing applications?”
To address our RQ, we designed a study with citizens from Norway in order to examine their perceptions
regarding privacy and trust, as well as their emotions in regard to the adoption of DCT applications. In our study
we include users who adopted the government contact tracing application Smittestopp, as well as those who
ignored it or refused to use it. We regarded all Norwegians as suitable contributors to this research as the
application was designed for everyone living in the country. We drew on existing theories by surveying
questionnaire answers regarding IUIPC, awareness, collection, control, relative advantage, trusting/risk beliefs
and human emotions. Our findings show that both trust and relative advantage from using the application
increase intention to use it, while risk beliefs reduced intention to use the application. Additionally, we found
that negative emotions moderate the relation between risk beliefs and intention to use, while positive emotions
moderate the relation between relative advantage and intention to use.
The paper is structured as follows: the next section describes the Smittestopp-application in Norway and
offers the theoretical background of the study. Next, we present our research model and hypotheses, followed by
the research method and findings. The paper concludes with a discussion and an outline of the contribution to
relevant research on DCT for future studies.
Christian Ødeskaug, Tord Vetle Gjertsen, Samrat Gupta and Ilias O. Pappas
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2. BACKGROUND
2.1 Smittestopp
The first iteration of Smittestopp, the official Norwegian DCT-application, was launched on April 16th
2020 after a relatively rushed development by the Norwegian Institute of Public Health (FHI) (Lintvedt, 2021).
This iteration of Smittestopp used Bluetooth and Global Positioning System (GPS) technology, in contrast to
most other contact tracing applications, which only use Bluetooth. Along with GPS data, this iteration of
Smittestopp also stored operating system numbers, phone models and details of registered encounters. FHI
stored any data about users' movement anonymously and was only accessed by authorized personnel of FHI
(Martin et al., 2020). Centralized data storage, along with location-based data, was considered to be large-scale
surveillance and monitoring of the Norwegian population (Lintvedt, 2021). The first version of Smittestopp was
deactivated on June 16th 2020 due to the rising privacy concerns and lack of transparency for citizens (Martin et
al., 2020). Other concerns included low user friendliness, downloading errors and high battery use even when
the application was not actively being used (Sandvik, 2020).
The Ministry of Health and Care Services in Norway released a second version of the application on
December 21st 2020, which was a new application under the same name ‘Smittestopp’, built on the GAEN-
framework and Danish source code from Denmark’s Smittestop-app (Lintvedt, 2020). The focus of this iteration
of Smittestopp was decentralization and the protection of personal privacy, removing the GPS-technology
previously used, only relying on Bluetooth, and storing data locally. The development process was considered
open, with external developers and activists being invited onto the project, and the source code being available
publicly on GitHub (Lintvedt, 2020). FHI themselves rendered this approach as a brand-new technological
solution, and emphasized the point that, despite the identical name, these two iterations had almost nothing in
common (Folkehelseinstituttet (2022). The first iteration of Smittestopp raised concerns about being harmful,
while the second iteration was criticized for being both harmless and useless (Lintvedt, 2021, p. 69). There is
now a third and current iteration of Smittestopp, with mostly performance related upgrades and quality of life
improvements.
2.2 Related work
Recent studies in the area have examined the use of DCT applications in order to understand the underlying
reasons for their adoption or resistance. It was found that the main impediments to the adoption of DCT apps are
concerns about security and privacy, a lack of trust in the government, the cost of installation, inability to install
apps/activate Bluetooth, lack of access to a smartphone or compatible OS, and a lack of willingness to go into
quarantine, to test or to report results (Altmann et al., 2020; Blom et al. 2021; Kaspar, 2020; Sharma et al.,
2020). Additionally, protection of family and friends, responsibility to the community, knowing the risk,
reducing deaths, etc. were reasons for their adoption, while concerns about surveillance; the risk of hacking,
concerns about disclosing information about location/people in contact, difficulty in installation, etc. were
reasons against the use of DCT app (O’Callaghan et al., 2021).
The main determinants of adoption concern technical factors, usability and use outcomes. Specifically,
technical factors include relative advantage, design and compatibility (Huang et al., 2022; Lin et al., 2021;
Trang et al., 2020) Outcome beliefs and usability factors concern self-oriented and societal benefits, trusting
beliefs, effort expectancy, performance expectancy, the value of information disclosure and social influence
(Lin et al., 2021; Kaspar, 2020; Sharma et al., 2020; Walrave et al., 2021; Hassandoust et al., 2021; Fox et al.,
2021). The stronger the perception of crisis severity, the efficacy of the app and personal capabilities, the higher
the likelihod of adoption (Kaspar, 2020; Sharma et al., 2020; Walrave et al., 2021; Trkman et al., 2021). There is
also a correlation between attitude towards the DCT app use and the expected personal and community-related
outcomes of sharing information (Sharma et al., 2020).
Adoption intention can also depend on individual differences, such as innovativeness and voluntariness
(Hassandoust et al., 2021; Trang et al., 2020), as well as situational factors, such as facilitating conditions, social
influence, and personal hygiene (Saw et al., 2021). However, neither demographic nor situational factors were
significantly associated with app downloads (Saw et al., 2021).
We present the findings of some recent studies on the usage of DCT in Table 1. Those studies were used to
bring a theoretical foundation into our study when developing our hypotheses.
Int. Journal of Business Science and Applied Management / Business-and-Management.org
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Table 1. Overview of Recent Studies on Digital Contact Tracing
Author
(year)
Objective/Context
Methodology
Theory
Results/Findings
Munzert et
al. (2021)
To measure actual usage
of a DCT and find the
differences in uptake
among different groups, as
well as examining reasons
for higher uptake.
Quantitative
Survey, SEM
Randomized
Intervention
Higher rates of uptake were revealed among
respondents with increas
ed risk of severe
illness, but lower for those with a heightened
risk of exposure to the disease. Informative
and motivational video messages have a very
limited effect o
n uptake, but more findings
suggest that small monet
ary incentives
strongly increase uptake of DCT.
Garousi et
al. (2022)
Identify main problems
users report in regards to
DCT apps and focus on
the “software in society”
aspects of the apps.
Qualitative
review
analytics tool
UTAUT
Users are generally dissatisfied with the apps
that were studied, except for the Scottish app.
Issues reported were mostly related to doubts
that the DCT apps actually work and high
battery consumption.
Oldeweme
et al.
(2021)
To investigate how
uncertainty reduction
measures increase
adoption of DCT apps and
how their use affects
percepti
on of different
risks.
Quantitative
Survey
URT
Uncertainty reduction measures like
transparency dimensions,
disclosure and
accuracy, as well as trust in government and
social influence, foster the adoption process.
The use of DCT apps reduced the perceived
privacy and performance risks, but did not
reduce social risks and health related
pandemic concerns.
Li et al.
(2021)
To investigate the effects
of app design choices and
individual differences on
DCT app adoption
intentions.
Quantitative
Survey
Privacy
Calculus
Individual differences played a more
important role than app design choices.
Certain app designs could lead to inequality of
acceptance from people. Analysis showed that
someone’s percept
ion of the public health
benefits offered by the app and the adoption
willingness of other people had a larger effect
in explaining the observed effects of app
design choices and individual differences than
their perception of the app’s securi
ty and
privacy risks.
Chen &
Thio
(2021)
To characterize DCT
systems developed around
the world and compare
uptake rates with different
technologies and more.
Qualitative
Study
MAST
framework
Drivers and barriers are found and discussed.
Suggestions for policymakers are also made in
regards to how to influence barriers and
drivers in order to increase uptake.
2.3 Theoretical Background
This study applies and extends the Informational Unified Privacy Concerns (IUIPC) model by examining
the impact of privacy concerns, trust, and risk beliefs on the intention to use digital contact tracing applications,
specifically the Smittestopp app in Norway. It also explores the moderating role of positive and negative
emotions on these relationships. The study aims to validate and generalize the original model in a different
cultural and application-specific context, contributing to the understanding of technology adoption dynamics.
The construct of Internet Users' Information Privacy Concerns (IUIPC) consists of three dimensions,
awareness, collection, and control. These three dimensions each represent different types of concerns (Malhotra
et al., 2004). Awareness refers to the degree to which a consumer is concerned about their awareness of
organizational information privacy practices. Collection describes a person’s concern about the amount of
individual-specific data that others may possess in relation to the benefits that are received. Control refers to
whether a person has control over their personal information by having the power to modify, approve or opt out
of a service (Malhotra et al., 2004). A recent study using IUIPC shows that Chinese users prefer the collection
of personalized data, while German and Americans highly prefer anonymity (Utz et al., 2021). The IUIPC
model has also been used in studies when extracting users’ thoughts from Twitter and other social media sites to
uncover privacy concerns during COVID-19. (Bhatt et al., 2022). We draw on the recent work of Lin et al.
(2021), and seek to examine the role of IUIPC, which has been shown to be a good tool to explain variance in a
Christian Ødeskaug, Tord Vetle Gjertsen, Samrat Gupta and Ilias O. Pappas
5
person's willingness to interact with and use different technologies and services (Bélanger & Crossler, 2011), on
citizens trust and risk beliefs, as well as on their intention to use a DCT-application.
Trust is considered both a fundamental and critical constituent of all human relationships, and various
conceptualizations of trust have been defined, including positive beliefs, personal traits, action, and social
structure (Das & Teng, 2004). Trust beliefs have often been discussed in literature that touches upon technology
acceptance and are typically found to be positively related with the intention to use technology in various
contexts (Beldad & Hegner, 2018; Shin, 2021; Oldeweme et al., 2021). Some studies have also found that a
successful launch of mobile applications to fight the pandemic relies strongly on citizens' trust in the technology
itself (Parker et al., 2020). Trust has often been conventionally linked to risk, as the logic of risk occupies an
indisputably important position in defining trust (Das & Teng, 2004). Studies have disagreed on
conceptualizations of risk, but most definitions suggest ideas such as uncertainty and/or variance in outcomes
(especially losses) of some significance (Das & Teng, 2004). Risk beliefs have often been divided into
performance risks, privacy risks and social risks (Oldeweme et al., 2021). Finally, relative advantage was
described as the degree to which an innovation is perceived as being better than the idea it stems from, often
guaranteeing economic profitability (Rogers, 1995). Relative advantage has been found to be positively related
to intention to encourage knowledge sharing in an IT support climate and has been found to positively affect
intention to use COVIDSafe (Lin & Lee, 2006; Lin et al., 2021).
Emotions have an important role when making decisions and individuals may turn to their emotions as a
source of information, in the absence of clear information (DeSteno et al., 2004). Sudden changes in society
have also been shown to affect one’s emotions, with recent studies examining the role of emotions during the
pandemic COVID-19 in order to get insight into public sentiment regarding governmental management policies
(Choudrie et al. 2021). Furthermore, various studies have examined their role in influencing users’ behavioural
intentions in various types of e-services, either directly, indirectly, or as a moderator (Chang et al., 2014; Pappas
et al., 2016; 2017). We have measured the emotions of our participants in regards to the Smittestopp-application
through an initial statement to examine if they moderate the effect of other constructs on intention to use the
application. Similar to past studies (Pappas et al., 2020), emotions here were divided into two basic categories,
positive and negative, which will allow us to obtain a more complete understanding of how individuals felt
regarding the use of the Smittestopp-app.
3. RESEARCH MODEL AND HYPOTHESES
Trust factors, such as the ability to trust and integrity, are affected by privacy violations (Martin, 2018).
Willingness to disclose information to a service mediates the relationship between trust and the service (Kumar
et al., 2018). If a user has had a positive or negative experience with the service, trust has been shown to be
affected accordingly. Consumers will have different privacy boundaries for different types of personal
information that they are required to share; there is a negative relation between trust and privacy concerns (Xie
& Karan, 2019). We argue that it is important to examine this relationship in the context of DCT considering the
type of data (e.g., proximity data, health data, location data, timestamps) required for such apps to be able to
function properly. IUIPC defines several concerns and has been shown to have negative relations to trust
(Malhotra et al., 2004). By examining the impact of IUIPC on trusting beliefs regarding DCT-adoption, we
aimed to uncover why Norwegians are hesitant to download and use Smittestopp to mitigate the spread of
COVID-19. We propose the following hypothesis:
H1. Citizens’ information privacy concerns will have a negative effect on their trusting beliefs regarding
the use of contact tracing applications.
Consumers’ privacy concerns are typically expected to affect their risk beliefs in various contexts when it
comes to different types of e-services that are directly aimed to the end user (Maseeh et al., 2021; Pappas, 2018;
Pappas et al., 2013). As internet users' information privacy concerns are based on a person's awareness of,
control over and thoughts about collection, there is ample reason to believe that risk beliefs will be affected. For
example, when examining social media applications, findings show that users' privacy concerns were
significantly related with their risk concerns related to the possibility of their private information being revealed
(Fakey et al., 2020; Lankton & Tipp, 2013). A person’s awareness of a technology may affect their view of the
risks involved with using it, but this will depend on the type of technology and the context in which it was used.
With this, we propose:
H2. Citizens’ information privacy concerns will have a positive effect on their risk beliefs regarding the use
of contact tracing applications.
Lin et al. (2021) reaffirmed support for their own hypothesis on trusting beliefs having a negative impact
on risk beliefs, having found that trust had a negative effect on risk, and instead increased the intention to use
the Australian COVIDSafe application. Most of the prior studies that touched upon trust beliefs did not suggest
that beliefs had any correlation with trust (Hassandoust et al., 2021; O’Callaghan et al., 2021; Duan & Deng,
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2021). Trust in government and social influence have previously fostered the adoption process of DCT-
applications, and that usage of the said applications reduced perceived privacy and performance risks (Altmann
et al., 2020; Oldeweme et al., 2021). For example, when examining the factors that determine the motivation for
using the DCT apps it was found that trust in the app was associated with app usage (Kaspar, 2020). Another
study found that trusting beliefs increase adoption intentions (Lin et al., 2021). Also, Touzani et al. 2021 found
that trust in political representatives was also associated with the willingness to use DCT apps. Thus, we
propose the following:
H3. Trusting beliefs will have a negative effect on risk beliefs.
Several studies found that risk concerns and beliefs have a negative impact on intention to download and
utilize a DCT-application (Hassandoust et al., 2021; O’Callaghan et al., 2021; Duan & Deng, 2021). Risk is
often mentioned as a factor of concern regarding privacy and security (Altmann et al., 2020) as well as concerns
surrounding self-disclosure leading to the possibilities of getting hacked, or data getting leaked (O’Callaghan et
al., 2021). Using the application could mean protecting yourself, family, and friends from COVID-19
(Hassandoust et al., 2021), while not adopting the application could also imply protecting your family and
friends from potential personal data leakage and privacy violations (O’Callaghan et al., 2021). Thus, we
propose:
H4. Risk beliefs will have a negative effect on citizens’ intention to use the Smittestopp-app.
Several studies suggest different findings are divided on whether trusting beliefs have a positive or negative
influence on intention to use. It was found that a general lack of trust in government, as well as concerns about
privacy and security, were the main impediments against the use of DCT-applications (Altmann et al., 2020).
Contrarily, other researchers have argued that trust in technology, as well as in the application itself, was
associated with adoption intentions for DCT-applications (Lin et al., 2021; Kaspar, 2020). For instance, the
disclosure of transparency dimensions and accuracy, as well as trust in government and social influence were
found to foster the adoption process (Oldeweme et al., 2021). Trust in political representatives was also found to
be associated with the willingness to use DCT apps (Touzani et al., 2021). The severity and vulnerability of data
misuse were also associated with motivation to use the DCT app (Kaspar, 2020). Trust in government and
technology have been major determinants on intention to use DCT to reduce infection spread (Prakash et al.,
2021). Thus:
H5. Trusting beliefs will have a positive effect on citizens’ intention to use the Smittestopp-app.
Relative advantage and perceived self-benefits have been shown to positively influence individuals'
willingness to download and use DCT-applications in the past (Lin et al., 2021; Walrave et al., 2020; Trang et
al., 2020). Lin et al. (2021) concluded that relative advantage would increase intention to use, as most
Australians would be willing to embrace mobile digital technology instead of manual paper-based solutions.
Munzert et al. (2021) found that even the smallest amounts of monetary incentives could strongly increase the
uptake and usage of DCT-applications. If a user can perceive self-benefits as a result of adopting Smittestopp,
they might also absorb the benefits that Smittestopp brings to the society. With this prior knowledge, we
propose:
H6. Relative advantage will have a positive effect on citizens’ intention to use the Smittestopp-app.
Intention to use has previously been shown to affect the use of a DCT-app (Oldeweme et al., 2021). For
example, one study found that the importance of individual differences over app design decisions was greater on
DCT app usage intention. Certain app designs may result in differences in usage intention (Li et al., 2021).
Other studies found that high convenience design influences DCT app usage intention (Trang et al., 2020) and
perceived crisis severity also impacts DCT app usage (Trkman et al., 2021). It is expected that a person's
intention to use a service increases the possibility of them engaging with the service by downloading and using
it, asit has been well documented in the technology acceptance literature. Intention to use should not be
confused with actual use. Exploring this relation can uncover whether the intentions of Norwegian users reflect
the actual uptake of Smittestopp. All the previously defined theories and hypotheses are expected to ultimately
affect intention to use, as seen in Figure 2. For this research to further benefit DCT-research and societal needs,
it is important to see if all these intentions lead to actual use. We then propose:
H7. A citizens’ intention to use the Smittestopp-app will have a positive effect on downloading and using
the Smittestopp-app.
Emotions have been shown to affect intention to use and the adoption of technology in various contexts
(Beaudry & Pinsonneault, 2010; Pappas et al., 2016). The moderating role of positive and negative emotions has
been discussed in previous studies (Pappas et al., 2017) in the context of e-service adoption. Negative emotions
have had significant effects on intention to adopt new systems (Zheng & Montargot, 2021). Furthermore,
Christian Ødeskaug, Tord Vetle Gjertsen, Samrat Gupta and Ilias O. Pappas
7
positive emotions have been shown to be related to perceived benefits (Ding & Chai, 2015). As previously
noted, relative advantage is a user’s perception of the advantages that come with using a DCT-app, also known
as perceived benefits. We seek to explore and examine the moderating role of positive and negative emotions on
the relationship among trusting beliefs, risk beliefs, relative advantage, and intention to use. Thus, we propose
the following hypotheses:
Positive emotions will moderate the relationship of a citizen's (H8a) trust beliefs, (H9a) risk beliefs, and
(H10a) relative advantage with their intention to use.
Negative emotions will moderate the relationship of a citizen's (H8b) trust beliefs, (H9b) risk beliefs, and
(H10b) relative advantage with their intention to use.
Figure 1. Research Model with Hypothesis Indicators
4. RESEARCH METHOD
4.1 Sampling
Using a deductive approach, we undertook a literature review, from which we gathered recent relevant
theory. We conducted a conceptual replication (Dennis & Valacich, 2014) of the work by Lin et al. (2021), as
we adopt part of their model and test it in a different context. Also, we extend that model by testing the role of
positive and negative emotions as a moderator. Thus, we propose13 hypotheses, 6 of which are sub-hypotheses
of H7 and H8. To obtain data to test these hypotheses, we conducted a survey. Aiming to reach a large and
broad sample, we developed an online questionnaire to collect sufficient data. Data collection lasted from
February 2022 to March 2022, following a convenient snowball sampling method. The questionnaire was first
administered to a small number of friends and colleagues, as a pre-test. In this way, we were able to correct
typos and mistranslations, reformulating the questions which were unclear to many. Then, we distributed our
survey to even more participants, distributing them to friends, family, and colleagues, who in return distributed
the survey to people they knew as well. We also released it on different social media and Norwegian online
communication channels to garner widespread attention on platforms where background and demographics
would differ. Data cleaning was conducted to remove incomplete surveys. We ended up with 189 respondents to
our questionnaire.
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Table 2. Users’ Demographic Profile
As seen in Table 2, most of the participants are between 18 and 34 years old. Among our participants,
about 47% had used the Smittestopp-app before. With this split, we explored whether previous usage of the app
impacted the users’ privacy concerns and emotions. The split between risk group respondents was also usable
as we have an almost 40/60 split, with the lower percentage belonging to those who are at risk.
4.2 Measures
First, we collected data on demographics and asked some general questions regarding the use of contact
tracing applications to control for their previous experience. The second part of the questionnaire included
questions based on theories described in the background section. We adapted most items and questions from Lin
et al. (2021), as well as their IUIPC model when constructing our questionnaire. Items for positive and negative
emotions were adopted from past studies that have examined emotions in different online settings (Pappas et al,
2017; Pappas et al., 2020). The questions were translated and rewritten to fit the Norwegian government, using
Smittestopp as the contact tracing application instead of the Australian COVIDSafe-app. The last set of
questions in the survey presented a statement, followed by 20 emotions to capture how respondents felt about
using the application. The participant could resonate with the emotion by answering anything from strongly
disagree (1) to strongly agree (7) on a 7-point Likert scale. For clarification, some items from trust, risk, and
emotions, were removed due to low loadings. Each of our used items can be found chronologically in Table 3,
along with the questions asked and the analyzed data loadings.
Table 3. Measured Items with Related Loadings
Questions
Loadings
The Norwegian government seeking information online should disclose the
way the data are collected, processed, and used.
0.81
A good consumer online privacy policy should have clear and conspicuous
disclosure.
0.80
It is important to me that I’m aware of and knowledgeable about how my
personal information is used.
0.80
Citizen online privacy is a matter of consumers’ right to control their decisions
about how their information is collected, used, and shared.
0.74
Citizen control of personal information lies at the heart of consumer privacy.
0.83
Online privacy is invaded when control is unwillingly reduced as a result of a
marketing transaction.
0.81
It bothers me when the Norwegian government asks me for personal
information online.
0.90
Age
Frequency
Population of municipality
Frequency
< 24
67 / 35.5%
100 – 999
2 / 1.1%
25 - 34
66 / 34.9%
1 000 - 4 999
24 / 12.7%
35 - 44
36 / 19.0%
5 000 - 9 999
12 / 6.3%
45 - 54
12 / 6.3%
10 000 - 19 999
23 / 12.2%
55 - 64
5 / 2.6%
20 000 - 39 999
17 / 9.0%
65 - 74
1 / 0.5%
40 000 - 99 999
44 / 23.3%
75 or older
2 / 1.1%
100 000 or more
67 / 35.4%
Gender
Owns a smartphone
Female
76 / 40.2%
Yes
187 / 98.9%
Male
111 / 58.7%
No
2 / 1.1%
Other
2 / 1.1%
Used Smittestopp
Education
Yes
89 / 47.1%
Primary school
4 / 2.1%
No
100 / 52.9%
High school
46 / 24.3%
Risk group
Vocational school
14 / 7.4%
Yes
72 / 38.1%
University or college
124 / 65.6%
No
117 / 61.9%
Did not want to share
1 / 0.5%
Functions turned off
Wifi
31 / 16.4%
Bluetooth
76 / 40.2%
Christian Ødeskaug, Tord Vetle Gjertsen, Samrat Gupta and Ilias O. Pappas
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When the government asks me for personal information, I sometimes think
twice before providing it.
0.83
It bothers me to give personal information to many Norwegian government
agencies.
0.92
I’m concerned that the Norwegian government collects too much personal
information about me.
0.80
The government is trustworthy in handling Smittestopp information from
Smittestopp-app
0.84
The government tells the truth and fulfill promises related to (my information)
provided by me.
0.91
I trust that Norwegian government keeps my best interests when handling my
personal data
0.88
In general, it is risky to give (my information) to the Smittestopp-app.
0.81
There is high potential for loss associated with giving (my information) to the
Norwegian government.
0.79
There is much uncertainty associated with giving personal info to the
Norwegian government.
0.87
Providing the Norwegian government with (my information) will involve
unexpected problems.
0.83
Downloading Smittestopp enhances the Norwegian government’s effectiveness
with contact tracing.
0.83
Downloading Smittestopp improves the quality of contact tracing.
0.94
Downloading Smittestopp enables the government to trace coronavirus cases
more quickly.
0.91
Overall, I find downloading Smittestopp to be advantageous for contact
tracing.
0.90
It is worth it to download Smittestopp
0.94
I will strongly recommend others to download Smittestopp
0.93
Have you used the Smittestopp application during the COVID-19 pandemic?
(Yes/No)
Downloading and using the Smittestopp-application makes me feel:
(POS)
Pleasure
0.85
Joy
0.89
Pride
0.89
Amusement
0.76
Relief
0.86
(NEG)
Anger
0.83
Shame
0.70
Regret
0.91
Guilt
0.90
Fear
0.92
5. DATA ANALYSIS AND FINDINGS
5.1 Analysis and validity
For the analysis, we used SmartPLS 3.0. For content validity, we determined the importance of the
questionnaire content by ensuring face validity, as Lin et al. (2021) had already successfully used several of
these questions. We also examined construct reliability and discriminant and convergent validity. Reliability
testing, based on the Cronbach alpha indicator, shows acceptable indices of internal consistency since all
constructs exceed the cut-off threshold of 0.70. The AVE for all constructs ranges between 0.534 and 0.882,
exceeding the cut-off threshold of 0.50. Finally, all correlations are lower than 0.80 and square root AVEs for all
constructs are larger than their correlations. Our findings are presented in Table 4.
Int. Journal of Business Science and Applied Management / Business-and-Management.org
10
Table 4. Descriptive statistics and correlations of latent variables
Construct
Construct
Mean
SD
CR
AVE
IUIPC
Intention
Relative
advantage
Risk
Trust
IUIPC
5.37
1.37
0.85
0.534
0.659
INT
3.65
1.62
0.86
0.882
-0.183*
0.939
RA
4.86
1.59
0.92
0.809
-0.102*
0.755**
0.899
Risk beliefs
3.48
1.59
0.87
0.729
0.594**
-0.393**
-0.274**
0.854
TR
4.86
1.72
0.89
0.829
-0.361**
0.522**
0.413**
-0.601**
0.910
Note: Diagonal elements (in bold) are the square root of the average variance extracted (AVE). Off diagonal elements
are the correlations among constructs (all correlations are significant, **p< 0.01; *p<0.05). For discriminant validity,
diagonal elements should be larger than off-diagonal elements. IUIPC, Internet Users Information Privacy Concerns;
INT, Intention to Use; RA, Relative Advantage; R, Risk; TR, Trust, POS; Positive Emotions, NEG; Negative Emotions
Regarding emotions, our sample showed on average relatively low positive and negative emotions, with
mean values of 2.77 (S.D. = 1.56) and 2.55 (S.D. = 1.62), respectively. For actual usage, which was measured
with a single item and a yes/no question, about half of the sample reported that they had used the application.
The estimated path coefficients of the structural model were examined to evaluate our hypotheses. Figure 2
presents the analysis of the research model.
5.2 Tested hypotheses
The findings offer support for H1-H7, related to the direct effects, while the moderating effect of emotions
is significant only in 2 (H9b, H10a) out 6 relations. The findings are presented in Figure 2. In detail, internet
users' information privacy concerns (IUIPC) have a negative effect on trusting beliefs (-0.361, p < 0.01) (H1),
while they have a positive effect on risk beliefs (0.435, p < 0.001) (H2). Further, trusting beliefs have a negative
effect on risk beliefs (-0.445, p < 0.001) (H3). In turn, risk beliefs have a negative effect on intention to use the
Smittestopp-application (H4), while trusting beliefs (H5) and relative advantage (H6) both have a positive effect
on citizens’ intention to use the Smittestopp-application. Finally, intention to use had a positive effect (0.421, p
< 0.001) (H7) on the actual use of the Smittestopp-application. Square multiple correlations (R
2
) are presented
in Figure 2 as well. The R
2
for trusting beliefs is 0.13, for risk beliefs it is 0.52, for intention to purchase it is
0.78, and for usage it is 0.18. Values higher than 0.26 imply a high effect of the predictors of the aforementioned
factors.
Regarding the moderating effects, positive emotions have a moderating effect on the relation of relative
advantage with intention to use (H10a), but not on the relation of trust beliefs and risk beliefs with intention to
use, respectively (H8a, H9a). Negative emotions had a moderating effect on the relation of risk beliefs with
intention to use (H8b), but not on the relation of trust beliefs and relative advantage, with intention to use,
respectively (H9b, H10b).
In short, all the hypotheses were accepted except for H7a/H7c and H8a/H8b. Despite some low
coefficients, all the accepted hypotheses are still significant enough to support the hypotheses. With the lowest
coefficient at 0.102 and the highest at 0.781 there are varying degrees of effect. The t-values reflect the path
coefficients well, with the lowest value of 2.212 and the highest value at 16.426.
Figure 2. Research Model with Path Coefficients
Christian Ødeskaug, Tord Vetle Gjertsen, Samrat Gupta and Ilias O. Pappas
11
6. DISCUSSION
The potential and development of DCT to slow the spread of a disease had been quietly explored for over a
decade before the COVID-19 pandemic thrust the technology into the spotlight. However, real life social
networks and the complexity of humans has made this potential hard to achieve (Cebrian, 2021). This paper has
explored Norwegian citizens’ concerns, trust, and risk beliefs regarding the adoption of digital contact tracing
(DCT) applications, more specifically the Smittestopp-app. We drew on recent studies which called for more
research on DCT-applications (Prakash & Das, 2022), and proposed a model based on the work by Lin et al.
(2021), who conducted a study in Australia. We applied their model in a different context, that is in Norway,
and extended it by considering the moderating role of emotions, as they have been shown to be important in
decision making and the adoption of e-services in different contexts (Lu et al., 2021; Pappas et al., 2017).
Our findings show that all the direct relations are significant, with IUIPC having stronger effects on
trusting and risk beliefs, showing that that privacy concerns play an important role in citizens' trusting beliefs,
which in turn can reduce their risk beliefs. The above findings are in accordance with prior studies and reflect
the interrelations among privacy, trust, and risk (e.g. Kaspar, 2020). The effects of trusting and risk beliefs on
intention to use are both significant, but the effect size is smaller. This can be explained, by the fact that the
effect of relative advantage on intention to use is very large (0.781). Also, the very high R-square (0.78)
suggests that these factors explain intention to purchase well. They show that Norwegian citizens will have high
intentions to use DCT applications if they perceive strong benefits. The weaker effects of trust and risk could
also be explained by the fact that since Norwegians typically havee high trust in the government (OECD, 2017),
their personal trusting and risk beliefs will have a weak effect on an application that is developed and
recommended by the government. Indeed, even though Norway performed well in handling this crisis
(Christensen & Lægreid 2020), and citizens' intention to use the DCT app was high, this did not translate into
actual usage, since the effect of intention to use on actual use was significant but relatively weak. This may
suggest that due to all the measures taken by the government leading to a relatively good control of the crisis,
citizens did not feel the need to use the DCT app.
Further, we examined the moderating role of emotions on three relations. In detail, we examined both
positive and negative emotions and tested how they influence the relations of trusting beliefs, risk beliefs, and
relative advantage on intention to use the DCT app. Positive emotions moderate only the relation between
relative advantage and intention to use, suggesting that any gains or benefits from using the app will only be
enhanced if a citizen has an overall positive attitude towards the app. On the other hand, negative emotions only
moderate the relation between risk beliefs and intention to use, indicating that if someone feels anger or fear
when using the app, their uncertainty will increase, thus their intention to use it will drop further. The above
findings may be explained by the relatively low values for positive and negative emotions, showing that citizens
in our sample did not experience strong positive or negative emotions related to the use of the Smittestopp app.
In addition, the high trust in the government (OECD, 2017) may explain why emotions do not influence the
effect of trust on intention to use.
6.1 Research implications
Lin et al. (2021) called for research to test the IUIPC model, and, accordingly, we expanded the research to
Smittestopp and Norway, a country in which citizens’ trust in the government is not only high, but also higher
than in many other countries (OECD, 2017). We conducted a conceptual replication of their work, adopted part
of their model and tested it in a different context. Also, we extended that model by testing the role of positive
and negative emotions as a moderator. Thus, our study provides partial external third-party validation of the
results of the original study towards a generalization of the original contribution into a different context. The
findings show that not all results are replicated, suggesting that it may not be possible to generalise some of
these in the context of Norway, raising the need for additional replication activities in this area.
Comparing our findings with previous studies, we found that information privacy concerns relate to trust
and risk regarding technology acceptance (Bélanger & Crossler, 2011; Oldeweme et al., 2021). We found that
trust led to the intention to use DCT-applications, which can be backed by similar studies (Lin et al., 2021;
Kaspar, 2020). Risk beliefs, on the other hand, had a negative impact on intention to use, supporting previous
studies (Hassandoust et al., 2021; O’Callaghan et al., 2021; Duan & Deng, 2021). Nonetheless, in our study, risk
did have a negative impact on intention to use. This is unlike Lin et al. (2021), where that hypothesis was not
supported. This difference could be because of differences between the Norwegians’ and Australians’ values
and beliefs, or differences in the two DCT-applications' reputation and design. Relative advantage also increased
the intention to use DCT-apps, supporting studies where superior innovative solutions encouraged information
and knowledge sharing (Lin & Lee, 2006; Lin et al., 2021).
We differ from the study of Lin et al. (2021) by adding the concepts of positive and negative emotions and
we obtained significant results in 2 out of 6 sub-hypotheses, thus, extending their findings with new insight.
Testing for moderating effects, we found that emotions indeed had significant effects on risk beliefs (negative
emotions), and relative advantage’s relation to intention to use (positive emotions). By exploring positive and
Int. Journal of Business Science and Applied Management / Business-and-Management.org
12
negative emotions (Chang et al., 2014; Pappas et al., 2016; 2017), our study shows that emotions can indeed be
integrated into research models as moderators. Additionally, our implications support previous studies where
risk beliefs negatively influenced the adoption of DCT-apps (Hassandoust et al., 2021; Duan & Deng, 2021), in
some cases to protect communities and other people (O’Callaghan et al., 2021). Our findings also strengthen
studies where negative emotions have impacted the use of new systems (Zheng & Montargot, 2021). Since the
initial outbreak of COVID-19, individuals experienced huge amalgamations of 85 thought processes and
emotions due to big changes financially, physically and to the society (Choudrie et al., 2021). Our research
implies that emotions regarding users’ information privacy concerns and Smittestopp are results of these sudden
outbursts of feelings originating from the pandemic. In future research, other human aspects could be taken into
consideration when investigating reasons for technology-adoption.
6.2 Practical implications
This study contributes to the work conducted at the Norwegian Institute of Public Health (FHI) by showing
the important role of privacy concerns, advantages and emotions on intention and use. Privacy is paramount,
thus managers designing and implementing digital contact tracing apps need to prioritize user privacy, as
concerns over privacy have a significant impact on user trust and perceived risks. By addressing privacy
concerns proactively, managers can build user trust and mitigate risk beliefs, thereby encouraging app adoption
and use. Next, it is important to emphasize the benefits. The study found that the perceived benefits or
advantages of using a DCT app have a strong influence on the intention to use it. Managers should thus clearly
communicate the benefits of using the app to potential users, including how it contributes to public health efforts
and personal safety. Also, managing emotions can influence the overall adoption of DCT apps. The influence of
positive and negative emotions on app adoption suggests that managers need to consider emotional factors in
their design and communication strategies. For example, fostering positive emotions about the app can enhance
its perceived benefits, while addressing potential sources of negative emotions, like fear or uncertainty, can
prevent these feelings from discouraging use.
By answering our RQ we see how Norwegians perceive DCT-applications. However, these findings may
point to how citizens perceive innovative digital solutions as a bigger concept. The Norwegian government
should look at Smittestopp as an important experience, and plan digital solution strategies ahead of time. In this
way, the population can be sufficiently prepared, well-informed and encouraged to adopt innovative digital
technology to circumvent potential global calamities in the future. Policy makers should understand that high
levels of trust in government can influence citizens' willingness to adopt and use government-endorsed
technologies like DCT apps. Therefore, maintaining and promoting public trust, through transparency, regular
communication, and effective crisis management, can enhance the effectiveness of public health initiatives that
rely on technology adoption.
6.3 Limitations and recommendations
The study suffers from some limitations, as with every empirical study. The survey questions may be
considered as too complicated. To address this issue, the first version of the questionnaire was pre-tested and
corrections to the wording were made to reduce possible misunderstandings or unclear parts. Occasionally we
received some feedback from people who needed further explanation on the questions. Further, most of our
respondents were young adults already exposed to online behaviour and they might not be representative of the
Norwegian population. However, our sample includes participants from all age groups and with different
experiences. Also, our results are based on self-reported data, so citizens' actual behaviour might be different.
Future studies should include other methods of data collection.
From our newfound experience from research on DCT-adoption, we propose the following
recommendations for research: Firstly, we suggest other researchers use and refine the research model used in
this study. They may explore other human factors as well as human emotions, as similar factors determined our
results. Researchers may also utilize a mixed methods approach, for instance a survey with questionnaire and
follow-up interviews. Semi-structured interviews can highlight the knowledge of different individuals. Also, the
findings could be applied in different contexts that relate to crisis management (Nizamidou and Vouzas, 2018)
to capture users’ perceptions. Further, in our study we have a relatively small sample considering that this
application is aimed at all citizens in the country. Thus, future studies should aim for a larger and more
representative sample. However, to partially remedy this, we have included in our study users that downloaded
the application as well as users that declined to use it. Future studies may also consider focus groups, for
instance based on geographical differences or age groups, then compare the findings from the different focus
groups. Focus groups can help practitioners design better marketing strategies, such as by following stealth
marketing techniques, to increase the adoption of such services and applications (Manika et al., 2021). Adjusting
the research accordingly based on the pandemic situation is also important. This research may not be limited to
COVID-19 alone and can be used for similar major crises in the future.
Christian Ødeskaug, Tord Vetle Gjertsen, Samrat Gupta and Ilias O. Pappas
13
By following these recommendations, new knowledge could collectively contribute to a better
understanding of citizens’ willingness to adopt DCT-applications and help governments and organizations to
enhance their services. This, in turn, could benefit the population, and possibly save countless lives, depending
on the situation. One can only speculate how many lives could have been saved if Smittestopp was a perfect
DCT-app used by everyone in Norway from the beginning.
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