Perceptions towards Cryptocurrency Adoption: A case of Saudi Arabian Citizens - IBIMA ...
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
IBIMA Publishing
Journal of Electronic Banking Systems
http://ibimapublishing.com/articles/JEBS/2021/110411/
Vol. 2021 (2021), Article ID 110411, 17 pages, ISSN: 2165-9982
DOI: 10.5171/2021.110411
Research Article
Perceptions towards Cryptocurrency Adoption:
A case of Saudi Arabian Citizens
Saad ALAKLABI1,2 and Kyeong KANG1
1
University of Technology, Sydney, Australia
2
Shaqra University, Saudi Arabia
Correspondence should be addressed to: Saad ALAKLABI; saad.alaklabi@student.uts.edu.au
Received date: 18 November 2020; Accepted date: 22 January 2021; Published date: 2 July 2021
Academic Editor: Mohamad Aidil Bin Hasim
Copyright © 2021. Saad ALAKLABI and Kyeong KANG. Distributed under Creative Commons
Attribution 4.0 International CC-BY 4.0
Abstract
The global financial market is influenced by relatively new technologies such as cryptocurrencies;
namely Bitcoin, Ethereum, Litecoin, and others. Cryptocurrencies are a challenging area in
finance that requires additional attention from the academic community as they can have a
potentially large impact on society and the economy. This study aims to investigate the usability
of digital money among the citizens of Saudi Arabia. Various factors that are related to user
behavior and have an impact on user intent towards cryptocurrencies based on a combined
approach are analyzed. The basis from which the authors started is The Theory of Reasoned
Action (TRA), together with four other constructions: perceived risk (consisting of privacy risk,
financial risk, and security risk), perception of enjoyment, perceived usefulness, and personal
innovation. The method used to collect the data is a questionnaire. The results showed that
variables such as subjective norms, security risk, perception of utility, and enjoyment influence
the adoption and use of cryptocurrencies. These variables include the perception of pleasure as
well as the perception of utility.
Keywords: Cryptocurrency, Digital currency, Bitcoin, Technology Adoption, TRA
Introduction cryptocurrencies was almost $ 800 billion
(Alzahrani and Daim, 2017) while in May
A cryptocurrency is a digital currency 2019, bitcoin reached a market
which represents digital records of certain capitalization of nearly $ 100 billion
values stored in digital databases. The goal (Kaspersky, 2019). Some estimates suggest
of developing cryptocurrencies is to that by 2024, the number of Bitcoin users
suppress printed money from the market will reach as high as 200 million (Alzahrani
and to establish a system that will not be and Daim, 2017). According to the
under the supervision and control of the Kaspersky Lab report, only 10% of people
state and government. Bitcoin is the first understand the meaning, significance, and
cryptocurrency that was developed in 2009 system of cryptocurrencies, while 35% of
(Satoshi, 2008) whose value is extremely people believe that cryptocurrencies are
growing; this is why it is often called the just a trend (Kaspersky, 2019). The data
digital gold. In 2017, the value of from this report has shown that 19% of
___________________
Cite this Article as: Saad ALAKLABI and Kyeong KANG (2021), “Perceptions towards
Cryptocurrency Adoption: A case of Saudi Arabian Citizens ", Journal of Electronic Banking
Systems, Vol. 2021 (2021), Article ID 110411, DOI: 10.5171/2021.110411
Journal of Electronic Banking Systems 2
__________________________________________________________________________
people were hacked, and 15% of correct conclusions. The TRA model is
respondents were victims of reliable in determining users' affinity
cryptocurrency fraud. The lack of rigorous towards the use of cryptocurrencies,
standards that can prevent fraud and especially since it is a new technology. This
hacking of cryptosystems leads to concerns research introduces three new aspects of
and a lack of trust (Kaspersky, 2019) when this model:
it comes to the use of cryptocurrencies.
Also, the biggest obstacles to 1. It explores the factors that
understanding this whole system are the influence the intention of Saudi
ignorance of computer technology, the citizens to become cryptocurrency
terminology that is almost exclusively in users.
English, as well as the lack of knowledge 2. The study includes participants
about cryptocurrencies (Kaspersky, 2019). who use social networks such as
Twitter, which implies that they
Before implementing any new technology, are technologically literate.
it is necessary to assess the possibility of its 3. This study includes participants
adoption. The founder and pioneer of the who already have some prior
Bitcoin Investment Trust, Barry Silbert, knowledge of cryptocurrencies,
argues that the adoption of which will provide new insights
cryptocurrencies is a process that occurs in into how people who already know
five phases (Charalambos et al., 2015): (i) the new technology perceive it and
the experimentation phase, (ii) the early how likely they are to become
adoption phase, (iii) the venture capital users.
phase, (iv).) wall street phase and (c) global
consumer adoption phase. However,
although theoretically, these phases are Theoretical Background and Model
necessary, the actual adoption of Development
cryptocurrencies depends on many other
factors specific to each country and its Related Works
economy. This research aims to assess how
people in Saudi Arabia view the process of Many studies have used these models or a
adopting cryptocurrencies and what combination of these models to investigate
intentions they have. To achieve this, the influential factors not only in the field of
authors explored the TRA and related cryptocurrencies but also in other areas.
factors, namely subjective norms (SN), Concerning cryptocurrency adoption, the
attitude (AT), and intent to adopt authors aimed to investigate the degree of
cryptocurrency (IACC). Besides, they acceptance of blockchain technology for
investigated the perceived risk (PR), financial transactions. The study involved
perceived usefulness (PU), perceived 277 participants, of whom 72% were men
enjoyment (PE), and personal innovation and 28% were women (Albayati, Kim and
(PI). TRA's model explains how the various Jeung Rho, 2020). This study's findings
factors associated with one's attitude relate showed that trust is the main variable
to a particular behavior. According to this influencing the acceptance of a new
model, each individual will act without technology, while regulatory support and
inhibitions and restrictions after the experience affect trust (Albayati, Kim and
intention's formation, and changes can Jeung Rho, 2020). In contrast, in the work
occur by including additional explanations. of Ku-Mahamud et al. (2019), the results
This theory has shown high validity with showed that most respondents believe that
the possibility of comparing the results blockchain technology and
obtained in other studies. In this research, cryptocurrencies are stable and secure. The
TRA will be the basis on which the authors study aimed to analyze the factors
will try to get answers to the formed influencing the adoption of
hypotheses. This model has a good cryptocurrencies (i.e., Awareness,
foundation and literature support and Adoption, and Trust) in Malaysia on a
allows authors to identify gaps and reach sample of 304 respondents (Ku-Mahmud et
_______________
Saad ALAKLABI and Kyeong KANG, Journal of Electronic Banking Systems,
DOI: 10.5171/2021.1104113 Journal of Electronic Banking Systems
__________________________________________________________________________
al., 2019).
In the study of Ayedh et al. (2020),
Sohaib et al. (2019) developed a model by elements affecting the investment in the
analyzing factors such as technological Bitcoin market were investigated. The
readiness (optimism, innovation, study covered 200 Muslim respondents
discomfort, and uncertainty), acceptance of (25% male and 75% female) in Malaysia,
technology, perceived ease of use and and the factors have been investigated
utility, and intention to use cryptocurrency using SEM. The factors that were
on a sample of 160 participants (56% men determined were extracted from TPB, TAM,
and 44% women). The main impacts were and the diffusion of innovations theory. It
estimated using partial least squares SEM was observed that facilitating conditions,
(PLS-SEM), while Artificial Neural awareness, and compatibility have a
Networks (ANN) were used to rank the tremendous effect on making investments
most significant factors (Sohaib et al., in Bitcoin [25]. On the contrary, trust,
2019). The results of the study showed that profitability, subjective norms, and ease of
perceived ease of use is positively use had been discovered not to have a
correlated with optimism, while perceived widespread effect on Bitcoin funding
ease of use is negatively correlated with (Ayedh et al., 2020).
discomfort, followed by uncertainty. The
results also showed that perceived ease of Al Shehhi, MayadaOudah and Zeyar Aung
use has the strongest effect on perceived (2014) analyzed the factors that affect the
utility, while perceived utility has a highly popularity and value of cryptocurrency.
significant positive effect on the intention The study looked at eight cryptocurrencies:
to use cryptocurrencies (Sohaib et al., Bitcoin, Litecoin, Ripple, Peercoin,
2019). Dogecoin, Kittehcoin, Darkcoin, and
Vertcoin. The sample included 134 online
The adoption of bitcoin from the users, with 95.5% male and 4.5 % female
monetary exchange attitude was participants. Studies show that young
investigated by Wood et al. (2018) using participants choose cryptocurrency based
TAM and the development innovation on name and logo. Additionally,
diffusion theory. The study was conducted participants believe in cryptocurrency
on 121 respondents and showed that considering that ease of mining, strong
relative advantage, easy use, visibility, and community, privacy, anonymity, value and
compatibility have a big positive impact popularity (Al Shehhi, MayadaOudah and
on bitcoin utilization (Wood et al., 2017). Zeyar Aung, 2014).
Wood et al. (2017) explored the seen Zarifis et al. (2018) Investigated consumer
advantage and chance related to bitcoin confidence in digital currency transactions
utilization. The authors created TAM based using a sample of 41 participants (23 men
on a test of 86 respondents (95% were and 18 women). The results suggest that
male). The results showed that the those who understand technological
fluctuating esteem, the hazard of money- innovations have more confidence in these
related misfortunes, and the need for technologies than those who do not. It has
customer assurance are the most factors also been shown that confidence can be
influencing people’s intention to utilize boosted if the government is involved in
bitcoin. However, ease of utilizing has the regulating such technologies (Zarifis et al.,
weakest impact on bitcoin utilization 2018).
(Abramova & Böhme, 2016). The
acceptance of Bitcoin was also examined in The factors associated with Litecoin
the work of Lee Won (2018), utilizing TAM, cryptocurrency were examined using a
which included 224 respondents. The sample of 119 participants (Gibbs, and
conclusions showed that seen convenience SuwareeYordchim, 2014). This study
has the most grounded impact on the explores four main factors. The first factor
intention to utilize Bitcoin (Lee Won, recommends that future professional
2018). training should be included in Litecoin
_______________
Saad ALAKLABI and Kyeong KANG, Journal of Electronic Banking Systems,
DOI: 10.5171/2021.110411Journal of Electronic Banking Systems 4
__________________________________________________________________________
development, while the second one where nbi are normative beliefs connected
suggests that the concept of digital to a certain outcome i, and mci is the
currency should be more understandable, motivation to comply to the particular
and its benefits should be presented. The behavior.
third factor indicates the need for
education in cryptocurrency, while the last Attitudes can be defined as beliefs towards
factor indicates that the respondents did a particular behavior (Ajzenm and
not know what Litecoin was, which in turn Albarracín, 2007). When these beliefs come
indicates the need for education (Gibbs and together, they create a positive, negative, or
SuwareeYordchim, 2014). neutral attitude toward behavior (Ajzenm
and Albarracín, 2007). The literature
Model Development suggests that if a person believes that the
result of a particular behavior will be
To evaluate cryptocurrency users' positive (Ajzenm and Albarracín, 2007;
behavior, the authors adopted the TRA Fishbein, 1967), he/she will develop a
model and included three additional positive attitude towards that behavior,
constructs - PR, PU, and PE. TRA was and vice versa. A study by Agustina (2019)
developed by Fishbein in 1967 and aimed showed that this behavior significantly
to explain the relationship between a affects the intent to use cryptocurrency
particular subject or action and human trading applications. Therefore, to examine
attitudes toward human behavior the effect of attitude on Saudi citizens'
(Fishbein, 1967). It is used to predict intention to adopt cryptocurrencies, the
actions based on people's behavior and following hypothesis has been proposed:
past behavior. The main concepts of TRA
are attitude, subjective norms, and H1: Attitude has a positive effect on the
behavioral objectives. intention to adopt cryptocurrencies.
The purpose of the behavior is the main Behavior is also influenced by subjective
factor influencing behavior and is driven by norms, which can be defined as "perceived
attitudes and norms. If the attitude towards social pressure to perform or not perform
that behavior is strong, and if subjective the behavior" (Ajzen and Albarracín, 2007).
norms allow such behavior, the person will These social pressures stem from
behave. The behavioral objective (Hale et expectations from major groups and
al., 2002) can be expressed as: individuals' views, shaping the perception
of the individual's behavior. People mingle
with their environment and social sector.
= +
Therefore, it is important to consider the
need to conform to others' perceptions
following subjective standards (Fishbein
where AB is a person's attitude toward
and Ajzen, 1975). Social influence has been
behavior, SN is a person's subjective norm
found to influence behavioral intention to
related to a particular behavior, and W is
introduce cryptocurrency. In this study, the
the weights. The attitude towards AB
following hypothesis is proposed:
behavior (Ajzen and Albarracín, 2007) can
be expressed as:
H2: Subjective norm has a significant
= ∑ positive effect on introducing
cryptocurrency.
where bi is the strength of the belief that a
As mentioned above, in addition to TRA
particular behavior will have a certain
constructs, this study also looked at PR, PU,
outcome i, and ei is the evaluation of and PE. PR shows how consumers are
outcome i. Furthermore, the subjective aware of the risks associated with using a
norm can be expressed as: certain technology. This can be defined as
the notion of the undesirable consequences
= ∑ of purchasing or using a particular
_______________
Saad ALAKLABI and Kyeong KANG, Journal of Electronic Banking Systems,
DOI: 10.5171/2021.1104115 Journal of Electronic Banking Systems
__________________________________________________________________________
product/technology (Faqih, 2016). PR dependent on the user's capabilities and
covers many aspects, including privacy cannot be used independently of other
risk, security risk, and financial risk. components to explain the use of a
Privacy risk is the privacy of one’s particular technology. Therefore,
information, and security risk refers to considering the importance of the
one’s uneasiness about using certain combined approach, the authors will
technologies. Economic risk is related to investigate the relationship between PU,
the cost of using a particular technology. In trends and the purpose of adopting
previous studies, PR uses several cryptocurrencies, and propose the
technologies, including mobile banking following hypotheses:
(Thakur and Srivastava, 2014; Kishore and
Sequeira, 2016), internet banking (Martins, H5: Perceived Usefulness has a
Oliveira and Popovič, 2014) and e- significant positive effect on attitude.
commerce (Belkhamza and Wafa, 1970; Lai H6: Perceived Usefulness has a
and Tang, 2018), as well as consumer significant positive effect on the intention
purchasing intent (David et al., 2001; to adopt cryptocurrency.
Kannungo and Jain, 2004.). It is shown to
influence intent. Considering that PE can be defined as "engaging in an
cryptocurrencies carry potential risks that activity" because of an individual's interest
can affect user attitudes and behavior, the or performance. Numerous studies have
following hypotheses are proposed: shown that PE influences using
technologies such as mobile services (Moon
H3a: Privacy Risk has a significant and Kim, 2001), mobile learning (Al-Zoubi
and Ali, 2019; Huang, Lin and Chuang,
negative effect on attitude.
2007), and financial services. When
H3b: Security Risk has a significant
considering cryptocurrencies, it is
negative effect on attitude.
understood that the repurchase of bitcoins
H3c: Financial Risk has a significant
and other cryptocurrencies is significantly
negative effect on attitude.
affected by enjoyment. PE has been found
H4a: Privacy Risk has a significant
to have a strong influence on perceived
negative effect on the intention to adopt
efficacy (Shrestha and Vassileva, 2019).
cryptocurrency.
Therefore, to investigate the impact of
H4b: Security Risk has a significant
adopting PE and cryptocurrency in Saudi
negative effect on the intention to adopt
Arabia, the following hypotheses have been
cryptocurrency.
suggested:
H4c: Financial Risk has significant
negative effect on the intention to adopt
H7: Perceived Enjoyment has a
cryptocurrency.
significant positive effect on attitude.
H8: Perceived Enjoyment has a
PU is interested in people's opinions about
significant positive effect on the intention
how behavior improves people's
to adopt cryptocurrency.
performance (Davis, 1989). Davis found
that PU has a weak relationship with
Researchers believe that Personal
attitude (Davis, 1989). He added that the
Innovation (PI) is one of the personality
intention to adopt this technology has a
traits that play a role in adopting
strong and direct impact on PU. PU is also
technology (Agarwal and Prasad, 1998). It
affected by the cost-effectiveness model
is defined as "the degree to which an
(Davis, 1989). This is explained by the fact
individual or other adoption units adopt
that people make decisions regarding a
new ideas relatively earlier than other
certain technology based on the effort
members of the social system" (Rogers
required to use that technology along with
2003, p. 22). Personal innovation can also
its benefits. Also, PU has been shown to
be used to reach a group of people who are
have a significant impact on using
normally at risk of using an innovation. The
cryptocurrencies (Ajay, Shrestha and
link between personal innovation and
Vassileva, 2019). PUs are so subjective
behavioral intentions is present in the
(Davis at al., 1989) that they are highly
_______________
Saad ALAKLABI and Kyeong KANG, Journal of Electronic Banking Systems,
DOI: 10.5171/2021.110411Journal of Electronic Banking Systems 6
__________________________________________________________________________
literature (Lu, 2014). As discussed in the security literature suggested
literature review, PI was included to contextualizing the use of public relations.
predict people's behavioral intention to use For example, public relations can be used
technology. For example, individual differently depending on the context and
differences, including the level of risk and innovation under study. The following
personal innovation, have been associated hypotheses were proposed:
with implementing e-commerce
technologies (Agarwal and Prasad, 1998; H9: Personal innovation will have a
Alalwan et al., 2018; Thakur and Srivastava, positive effect on attitudes towards the
2014; Williams, 2018) and they are also adoption of cryptocurrency in Saudi Arabia.
used in the context of electronic commerce
in Saudi Arabia (Al-Jabri, 2015) and mobile H10: Personal innovation will have a
learning (Al-Hujran, Al-Lozi & Al-Debei, positive effect on Saudi Arabia's intention
2014). Besides, among previous studies to introduce cryptocurrency.
that confirmed the importance of
intellectual property, there were several The proposed model is presented in Figure
concerns for which the information 1.
Figure 1: The proposed model
Research Methodology was created consisting of three parts:
questions related to demographic data,
profiles of knowledge about
The research methodology included a cryptocurrencies, and model building
survey consisting of validated elements and questions. Survey responses were collected
concepts from previous studies. The from September to November 2019.
proposed model is a combination of factors According to social media statistics
related to TRA (i.e., subjective standard, published by Global Media Insight (2019),
attitude, and intent to adopt the 56% of Saudi Arabia's population have
technology) and perceived risk, usefulness, active Twitter accounts (18.96 million
enjoyment and personal innovativeness (as people), so a link to the survey was posted
shown in Figure 1). All constructs consist of on Twitter and cryptocurrency users
several elements from the literature. shared it (that is, users who tweeted and
commented on cryptocurrencies). The
The survey was conducted by a selection criteria included cryptocurrency
questionnaire method. An online survey users who lived in Saudi Arabia, used
_______________
Saad ALAKLABI and Kyeong KANG, Journal of Electronic Banking Systems,
DOI: 10.5171/2021.1104117 Journal of Electronic Banking Systems
__________________________________________________________________________
Twitter, and were 18 years of age or older. cryptocurrencies rely on the Internet, and
The Qualtrics platform was used to poll the first cryptocurrency, Bitcoin, was
participants on the Internet, encouraging developed in 2009, it has become more
participants to participate in the survey. attractive to young people (Alaeddin and
After receiving 562 participants, Altounjy, 2018).
incomplete questionnaires were removed,
resulting in 368 questionnaires included in In terms of nationality and language, 88%
the analysis. Respondents agreed to of the respondents are Saudi Arabians.
participate by filling out the question. The Therefore, 88% of them are expected to
questionnaire was anonymous and kept speak Arabic, and 12% are expected to
secret throughout the study. speak English (Table 1). Besides, 61% of
the respondents have a bachelor's degree,
The data collected were analyzed using followed by 19% with a graduate degree
SPSS, and the SEM was constructed using and 12% with a university degree. Only 8%
AMOS. of the respondents have a high school
degree.
Results
Descriptive statistics In terms of location, the maximum number
of participants who participated in this
survey and knew about cryptocurrencies is
Table 1 shows the descriptive statistics of
in the central (35%) and western (24%)
the respondents' profiles. It can be seen
regions of the country. This is in line with
that 95% of the respondents are male. This
current development statistics. The central
percentage represents the population of
region of Saudi Arabia has the highest
people using cryptocurrencies.
Human Development Index in the country,
followed by the north and west regions. In
Considering the respondents' age, it can be
addition, 15% of the respondents are from
seen that 45% of the respondents are 30-
the east part of the country, 14% are from
39 years old, followed by 20-29 years old
the north, and 13% are from the south.
(36%) and 40-49 years old (16%). Since
Table 1: Descriptive statistics of the dataset
Item Values Frequency Percentage
Gender Male 367 95.3
Female 18 4.7
Age < 20 7 1.9
20-29 130 35.6
30-39 165 45.2
40-49 59 16.2
≥ 50 4 1.1
Nationality Saudi 337 88.2
Non-Saudi 45 11.8
User
English 47 12.2
language
Arabic 339 87.8
Education High school 29 7.8
College degree 44 11.9
Bachelor’s degree 226 61.1
Postgraduate degree 71 19.2
Part of Saudi Center 130 35.0
South 48 12.9
West 87 23.5
North 52 14.0
_______________
Saad ALAKLABI and Kyeong KANG, Journal of Electronic Banking Systems,
DOI: 10.5171/2021.110411Journal of Electronic Banking Systems 8
__________________________________________________________________________
Item Values Frequency Percentage
East 54 14.6
cryptocurrencies, followed by 21.5% of the
Cryptocurrency Knowledge Profile participants who rank themselves in the
initial rank. Only 9.3% of the participants
In relation to the cryptocurrency said that they are cryptocurrency experts,
knowledge profile, namely participants' while 0.3% said that they do not know
knowledge of cryptocurrencies, various cryptocurrency. These findings confirm the
aspects were reviewed (Table 2). It is need for this technology and the
important to note that the questions in this participants' interest in learning more
section attempt to gauge participants' about it and entering the cryptocurrency
familiarity with cryptocurrencies. First, market. More than half of the respondents
participants were asked if they had a (52.7%) have already participated in
technical background. Percentages of cryptocurrency activities such as trading,
participants are almost evenly distributed investing, analytics, etc., mostly with
because 52% of them have a technical Bitcoins (10.9%), followed by Ethereum
background, and 48% do not have a (9.6%). In practice, this situation means
technical background. This is an interesting that people with practical knowledge of
finding as it suggests that participants may cryptocurrency may differ in their
be interested in cryptocurrencies responses. Therefore, an additional study
regardless of their professional or of respondent representation is necessary
educational background. Also, participants to determine statistical bias. The other
had to rate their knowledge of types of cryptocurrencies (REBL, Litecoin,
cryptocurrencies, and the results showed Tron and others) are much less
that most participants (69%) knew about represented in the observed population.
Table 2: Cryptocurrency knowledge profile
Item Values Frequency Percentage
Do you have any technology background? Yes 184 47.8
No 201 52.2
How do you classify your knowledge about
No knowledge 1 0.3
cryptocurrency?
Beginner 83 21.5
Knowledgeable 266 68.9
Expert 36 9.3
Have you ever participated in cryptocurrency
Yes 202 52.7
activities?
No 181 47.3
Which cryptocurrency activity have you
Bitcoin 42 10.9
participated in?
Ethereum 37 9.6
REBL 15 3.9
Litecoin 14 3.6
Tron 11 2.8
XRP 7 1.8
Binance 7 1.8
Cardano 5 1.3
_______________
Saad ALAKLABI and Kyeong KANG, Journal of Electronic Banking Systems,
DOI: 10.5171/2021.1104119 Journal of Electronic Banking Systems
__________________________________________________________________________
Item Values Frequency Percentage
Others 66 17.1
confirms the element's reliability. The FR
Construct Reliability and Internal construct consists of five items with an
consistency alpha value of 0.884. For PE, the obtained
alpha value is 0.913, with four items. The
The reliability of the first scale needs to be PU consists of five items with an alpha
verified to work with new factors. value of 0.908, while SN construction has
Cronbach developed Cronbach's Alpha as a an alpha value of 0.844 with two items.
measure of the internal consistency of the Looking at the perspective, Cronbach's
test/scale [62]. It can take values in the Alpha got a value of 0.90 with five
range of 0 to 1, 1 indicating good reliability. construction items. Finally, the IACC
However, Cronbach's most popular alpha construction consisted of four items, valued
values range from 0.70 to 0.95 (Nunnally, at 0.887.
1994).
Considering each item factor’s loading, all
Cronbach's first construction had an alpha loads are above 0.6, which indicates a
PR of five items, valued at 0.92, indicating strong relationship between constructs and
the items' high reliability inside the constructs items. These results are
construction. The SR consists of two items presented in Table 3.
with an alpha value of 0.817, which
Table 3: Reliability of constructs
Latent variable Indicators Factor loading Cronbach’s alpha
PR PR1 0.783 0.920
PR2 0.934
PR3 0.876
PR4 0.849
PR5 0.752
SR SR1 0.645 0.817
SR2 0.976
FR FR1 0.7 0.884
FR2 0.897
FR3 0.834
FR4 0.724
FR5 0.615
PE PE1 0.802 0.913
PE2 0.9
PE3 0.908
PE4 0.772
PU PU1 0.793 0.908
PU2 0.853
PU3 0.908
PU4 0.903
PU5 0.637
SN SN1 0.643 0.844
SN2 0.959
SN3 0.713
_______________
Saad ALAKLABI and Kyeong KANG, Journal of Electronic Banking Systems,
DOI: 10.5171/2021.110411Journal of Electronic Banking Systems 10
__________________________________________________________________________
Latent variable Indicators Factor loading Cronbach’s alpha
SN4 0.909
SN5 0.785
PI PI1 0.761 0.805
PI2 0.731
PI3 0.804
AT AT1 0.787 0.901
AT2 0.812
AT3 0.813
AT4 0.734
AT5 0.768
IACC IACC1 0.765 0.887
IACC2 0.888
IACC3 0.67
IACC4 0.594
Model Results [64]. The TLI, CFI, and IFI values should be
close to 1 to indicate the best fit, as shown
The following table shows the in the results of Table 4 (Hair et al., 2010).
compatibility indices of the structural The RMSEA shows a good fit, as the value is
model. The Chi-Square value of the less than 0.05 (Hair et al., 2010). The most
conceptual model is significant (χ2 = important measures to note is the AIC or
1114.486, p = 0.000), ensuring a good Akaike Information Criterion. Taking this
model fit. The GFI value shows a value into account, the model obtained a
satisfactory fit with a value greater than 0.8 score of 1324.49.
Table 4: Model results
Fit indices Value
χ2 1114.486
df 636
ANOVA p 0.000
GFI 0.865
TLI 0.949
CFI 0.953
IFI 0.954
RMSEA 0.044
AIC 1324.486
_______________
Saad ALAKLABI and Kyeong KANG, Journal of Electronic Banking Systems,
DOI: 10.5171/2021.11041111 Journal of Electronic Banking Systems
__________________________________________________________________________
intent to adopt cryptocurrencies," is also
Hypothesis Testing supported (t = 2.189, p = 0.029). The
construction of subjective norms related to
It can be observed the t-value and its cryptocurrencies was studied in the work
corresponding significance (p-value) are of Mutambara (2019) having a negative
used to decide whether to accept or reject effect, but not statistically significant. On
the hypothesis (Table 6). the contrary, Schaupp and Festa (2018)
found that subjective norms are an
The first hypothesis, "Attitude has a important factor influencing the intent to
significant positive impact on the intent to use cryptocurrencies. This supports the
adopt cryptocurrencies," is supported authors’ assumptions and hypothesis.
based on significant t-values (t = 9,116, p =
0.000). This result supports most of the There was not enough evidence to support
results in the literature. In particular, the assumption that privacy risk has a
Doblas (2019) found that attitudes have a significant negative effect on behavior (t =
significant impact on adopting −1.405, p> 0.05), nor does security risk
cryptocurrencies. "One unit increase in have a significant negative effect on
attitude increases the probability of hiring behavior. (t = -0.556, p = 0.578). This
11.49 times, while other variables are finding is consistent with the literature
constant”. Kings, Wang, Dou and Zhou (Walton and Johnston, 2018) where
(2008) also found that attitudes have a researchers found that the security risk
significant impact on product adoption, and does not affect attitudes to the intent to use
Mutamarba (2019) found a significant bitcoin. The H3c hypothesis, "Financial risk
positive effect of attitudes on the intent to has a significant negative effect on
adopt cryptocurrencies. behavior”, does not support 95% of the
confidence interval (t = .61.648, p = 0.099),
The second hypothesis, "subjective norms so it can be rejected. Furthermore, there
have a significant positive effect on the
_______________
Saad ALAKLABI and Kyeong KANG, Journal of Electronic Banking Systems,
DOI: 10.5171/2021.110411Journal of Electronic Banking Systems 12
__________________________________________________________________________
was not enough evidence that the adoption et al. (2020) found a statistical effect of
of cryptocurrency (t = 0.503, p = 0.615) is strategic orientation, social impact, self-
impacted by privacy. Still, there was also efficacy, and novelty on two mediation
evidence that cryptocurrency (t =2.510, variables (perceived usefulness and ease of
p=0.012) is negatively affected by a use). Furthermore, they found that the two
security risk. 2.510, p = 0.012). mediation variables have a significant
effect on adopting blockchain technology
Considering H4c, it cannot be concluded (Nuryyev et al., 20120). The results
that the adoption of cryptocurrency is obtained in this study validate these
negatively affected by the severity of the findings, as the perceived utility has a
financial risk, as the value exceeds 0.05, significant effect on adopting
while the t value is less than ±2. These cryptocurrency. Furthermore, Mendoza-
results are in line with some studies in the Tello et al. (2018) have found that the most
literature which show that the intention to influential factor in adopting
use PR construct is not important enough cryptocurrency is perceived usefulness.
to explain using cryptocurrency (Oliva,
Pelegrín-Borondo and Matías-Clavero, Predictable enjoyment also positively
2019; Gibbs and Yordchim, 2014). This affects the trend (t = 5.241, p = 0.000) and
means that people who use the intensity of adopting cryptocurrency (t
cryptocurrencies expect to be at risk, so = 4.558, p = 0.000). PE has been found to
they may not feel threatened by risk as an influence the decision to use technology in
important factor when deciding to use numerous studies, including the significant
cryptocurrencies. These results also show influence of PE on the intent to repurchase
that people are generally more concerned bitcoins (Athar Nadeem et al., 2020),
about losing money and information (i.e., mobile instant messaging (GuychNuryyev
security risk) than current costs (i.e., et al., 2020), social networks (Zong, Yang
financial risk) and losing personal and Bao, 2019), or use of blockchain
information (i.e., privacy risk). technology (Shrestha and Vassileva, 2019).
Finally, individual innovation's positive
This study found that the perceived effect on trends is not conducive to a 95-
usefulness (t = 5.499, p = 0.000) was confidence interval (t = 1.900, p = 0.057),
positively correlated with the intention to thus this assumption is rejected. The same
adopt cryptocurrency (t = 4.558, p = 0.000). effect was observed in the last hypothesis,
Considering the factors that influence the where the effects of individual innovation
adoption of cryptocurrency, this is in line on adopting cryptocurrency were
with some of the literature findings, where examined. The results show that this
PU positively affects the intensity and hypothesis is not supported (t = 1.640, p =
behavior of cryptocurrency adoption 0.100).
(Sohaib et al., 2019; Won, 2018). Albayati
Table 6: Hypothesis test results
Hypothesis Path Path t-value p-value Result
coefficient
H1 AT → IACC 0.565 9.116 0.000 Supported
H2 SN → IACC 0.058 2.182 0.029 Supported
H3a PR → AT -0.080 -1.405 0.160 Not supported
H3b SR → AT -0.031 -0.556 0.578 Not supported
H3c FR → AT -0.093 -1.648 0.099 Not supported
H4a PR → IACC 0.026 0.503 0.615 Not supported
H4b SR → IACC 0.126 2.510 0.012 Supported
H4c FR → IACC -0.022 -0.432 0.665 Not supported
_______________
Saad ALAKLABI and Kyeong KANG, Journal of Electronic Banking Systems,
DOI: 10.5171/2021.11041113 Journal of Electronic Banking Systems
__________________________________________________________________________
Hypothesis Path Path t-value p-value Result
coefficient
H5 PU → AT 0.255 5.499 0.000 Supported
H6 PU → IACC 0.201 4.558 0.000 Supported
H7 PE → AT 0.262 5.241 0.000 Supported
H8 PE → IACC 0.068 4.558 0.000 Supported
H9 PI → AT 0.079 1.900 0.057 Not supported
H10 PI → IACC 0.061 1.640 0.100 Not supported
Discussion and Conclusion and the consumer's satisfaction from using
such technology.
The purpose of this research is to assess
the factors influencing the adoption of The goal of this paper is to identify the
cryptocurrencies. In particular, this study factors affecting cryptocurrency adoption
used an integrated approach by combining through a questionnaire involving
the TRA model with three other constructs, questions related to TRA. There were more
namely PR, PU, and PE, to observe the males than females in the sample, which
influence of these factors on can be considered a limitation of the study;
cryptocurrency users' attitudes and their however, this is also consistent with the
intention to use them. Eight hypotheses literature findings, such as in the work of
were tested using data from a survey. The Shehhi, Oudah and Aung (2014) which
results showed that the intention to investigated the reasons for choosing
introduce cryptocurrency is influenced by cryptocurrency using a sample of
attitudes, subjective norms, perceived respondents of which 95% were male.
benefits, and enjoyment. As for personal Another study that examined
innovation, privacy risk, and financial risk, cryptocurrencies, in particular, found that
which are the dimensions of perceived risk, the usefulness of bitcoins included more
they were found to be not associated with men than women (75% of the sample),
the intention to adopt cryptocurrency; confirming that cryptocurrencies were
however, the security risk was found to mostly male-dominated. Women are also
affect behavioral intent. In light of represented in the cryptocurrency trade
attitudes, this study shows that perceived (Alshamsi, and Andras, 2019). A study by
risk does not affect users' attitudes Vejacka and Palova (2019) examined
towards using cryptocurrencies. In gender differences among Slovak citizens,
contrast, perceived usefulness and which affect their attitudes towards
perceived entertainment significantly affect cryptocurrencies. Male respondents
consumers’ attitudes. These results are not generally have more information about
surprising. Cryptocurrency represents a cryptocurrencies, using them more
relatively new technology, so not enough frequently for payments. Cryptocurrencies
information is available to the general are more likely to be adopted by men than
population. That being said, consumers are women. In general, men were found to be
expected to be influenced by others' more positive about cryptocurrencies than
opinions (i.e., thematic theories). women (Vejacka and Palova, 2019), which
Furthermore, consumers are attracted to explains why women are underrepresented
technologies they can understand and and generally not interested in
which help them work faster.. When cryptocurrencies.
deciding to use cryptocurrencies,
consumers are more concerned about the Another possible limitation of this study is
security of their data and accounts. The that the sample was composed of younger
intention to adopt cryptocurrencies in people; hence the results might not
Saudi Arabia is influenced by the represent the older population well.
consumer's attitude, which is greatly Comparing these proportions to the
influenced by the benefits of technology proportion of educated people aged
_______________
Saad ALAKLABI and Kyeong KANG, Journal of Electronic Banking Systems,
DOI: 10.5171/2021.110411Journal of Electronic Banking Systems 14
__________________________________________________________________________
between 20-39 years old, the participants usefulness of cryptocurrency in developing
in this study have higher educational such systems.
degrees, and respondents with high school
degrees or college degrees have a small References
representation in the sample compared to
the known data of the General Authority • Abramova, S., &Böhme, R. (2016)
for Statistics in Saudi Arabia. This shows Perceived benefit and risk as
that people who know about multidimensional determinants of
cryptocurrency are well educated bitcoin use: a quantitative
compared to the Saudi population. The exploratory study.
majority of people who were involved in • Agarwal, R., & Prasad, J. (1998) A
the study are highly educated, and their conceptual and operational
behavior may differ from the general definition of personal
population because it was shown that innovativeness in the domain of
educated people are more prone to information
adopting new technologies easier (Welch, technology. Information systems
1970; Lleras-Muney and Lichtenberg, research, 9(2), pp. 204-215.
2002; Riddell and Song, 2017). • Agustina, D. (2019) Extension of
Additionally, the study focused on people Technology Acceptance Model
who already know about cryptocurrency so (Etam): Adoption of
that the results can be applied only to a Cryptocurrency Online Trading
specific population segment. This may add Technology. JurnalEkonomi, 24(2),
biases to the results, as the opinions are not pp. 272-287.
referring to the general population. Hence • Al Shehhi, A., Oudah, M., & Aung, Z.
future studies will focus on other (2014) Investigating factors
population segments. behind choosing a cryptocurrency.
In 2014 IEEE international
This research has several implications. This conference on industrial
study's results can be used by engineering and engineering
governments, corporations, and other management (pp. 1443-1447).
decision-makers by incorporating the IEEE.
experimental factors into the development • Alaeddin, O., &Altounjy, R. (2018)
of cryptocurrency systems and strategies. Trust, technology awareness and
Special attention should be paid to security satisfaction effect into the
risks by regulating the use of intention to use cryptocurrency
cryptocurrencies so that users have a clear among generation Z in
understanding of the security risks they Malaysia. International Journal of
may face and how they can be protected Engineering & Technology, 7(4.27),
from them. Also, users are more likely to pp. 8-10.
embrace the new technology if they can see • Albayati, H., Kim, S. K., & Rho, J. J.
its benefits. It is, therefore, necessary to (2020) Accepting financial
provide accurate information about the transactions using blockchain
system. Since the model must offer the technology and cryptocurrency: A
possibility of connecting the practical and customer perspective
theoretical aspects, the model's implication approach. Technology in
also includes the possibility of connecting Society, 62, 101320.
the model with real situations. Since the • Alharbi, A., Kang, K.,
presented model provides sufficient &Hawryszkiewycz, I. (2016) The
outcomes to be used and understood for Influence of Trust and subjective
various technology-related studies, new Norms on Citizens Intentions to
research in cryptocurrency adoption Engage in E-participation on E-
should be able to use this model as a government Websites. arXiv
theoretical basis. Finally, developers and preprint arXiv:1606.00746.
decision-makers must consider the • Alshamsi, A., & Andras, P. (2019)
User perception of Bitcoin
_______________
Saad ALAKLABI and Kyeong KANG, Journal of Electronic Banking Systems,
DOI: 10.5171/2021.11041115 Journal of Electronic Banking Systems
__________________________________________________________________________
usability and security across • Fishbein, M., &Ajzen, I. (1975)
novice users. International Journal Belief, attitude, intention, and
of Human-Computer Studies, 126, behavior Reading. MA: Addison-
pp. 94-110. Wesley, pp. 913-927.
• Al-Zoubi, S. I., & Ali, M. (2019) E- • Fishbein, M., Ajzen, I., Albarracin,
mobile Acceptance Using Unified D., &Hornik, R. (2007) A reasoned
Theory of Acceptance and Use of action approach: Some issues,
Technology (UTAUT): Research on questions, and
Universities in Jordan. Annals of clarifications. Prediction and
Emerging Technologies in change of health behavior: Applying
Computing (AETiC), Print ISSN, pp. the reasoned action approach, pp.
2516-0281. 281-295.
• Ayedh, A., Echchabi, A., Battour, M., • Gibbs, T., &Yordchim, S. (2014)
& Omar, M. (2020) Malaysian Thai perception on Litecoin
Muslim investors’ behaviour value. International Journal of
towards the blockchain-based Social, Behavioral, Educational,
Bitcoin cryptocurrency Economic, Business and Industrial
market. Journal of Islamic Engineering, 8(8), pp. 2613-5.
Marketing. • Global Data Lab, Subnational
• Belkhamza, Z., &Wafa, S. A. (1970) Human Development Index, 2019.
The effect of perceived risk on the https://globaldatalab.org/shdi/sh
intention to use e-commerce: The di/SAU/?levels=1%2B4&interpola
case of Algeria. The Journal of tion=0&extrapolation=0&nearest_
Internet Banking and real=0
Commerce, 14(1), pp. 1-10. • GlobalMediaInsight. (2019) Dubai
• Davis, F. D. (1989) Perceived Web Design & Development Agency,
usefulness, perceived ease of use, Social Media, SEO, Mobile Websites
and user acceptance of information - GMI, UAE. [online] Available at:
technology. MIS quarterly, pp. 319- https://www.globalmediainsight.c
340. om.
• Doblas, M. P. (2019) Awareness • Hale, J. L., Householder, B. J., &
and attitude towards Greene, K. L. (2002) The theory of
cryptocurrencies in relation to reasoned action. The persuasion
adoption among college students handbook: Developments in theory
in a private tertiary institution in and practice, 14, pp. 259-286.
Cagayan De Oro City, • Huang, J. H., Lin, Y. R., & Chuang, S.
Philippines. International Journal T. (2007) Elucidating user
of Advanced Research and behavior of mobile learning. The
Publications, 3(4), pp. 15-19. electronic library.
• Faqih, K. M. (2016) An empirical • Kannungo, S., & Jain, V. (2004)
analysis of factors predicting the Relationship between risk and
behavioral intention to adopt intention to purchase in an online
Internet shopping technology context: Role of gender and
among non-shoppers in a product category.
developing country context: Does • Kaspersky.com. (2019) Uncharted
gender matter?. Journal of territory: why consumers are still
Retailing and Consumer wary about adopting
Services, 30, pp. 140-164. cryptocurrency. [online] Available
• Fishbein, M. (1976) A behavior at:
theory approach to the relations https://www.kaspersky.com/blog
between beliefs about an object /cryptocurrency-report-2019/.
and the attitude toward the object. • Kishore, S. K., &Sequeira, A. H.
In Mathematical Models in (2016) An empirical investigation
Marketing (pp. 87-88). Springer, on mobile banking service
Berlin, Heidelberg.
_______________
Saad ALAKLABI and Kyeong KANG, Journal of Electronic Banking Systems,
DOI: 10.5171/2021.110411Journal of Electronic Banking Systems 16
__________________________________________________________________________
adoption in rural Karnataka. Sage Y. S., Lin, H. T., & Wu, L. F. (2020)
Open, 6(1), pp.1-21. Blockchain Technology Adoption
• Ku-Mahamud, K. R., Omar, M., Behavior and Sustainability of the
Bakar, N. A. A., &Muraina, I. D. Business in Tourism and
Awareness, Trust, and Adoption of Hospitality SMEs: An Empirical
Blockchain Technology and Study. Sustainability, 12(3), pp.
Cryptocurrency among Blockchain 1256.
Communities in Malaysia. • Riddell, W. C., & Song, X. (2017)
• Lai, C. H., & Tang, T. (2018) From The role of education in
information behaviors to disaster technology use and adoption:
preparedness: Navigating Evidence from the Canadian
individuals' general and disaster workplace and employee
curation in US, China, and survey. ILR Review, 70(5), pp.
Australia. Computers in Human 1219-1253.
Behavior, 88, pp. 37-46. • Schaupp, L. C., &Festa, M.
• Lleras-Muney, A., & Lichtenberg, F. (2018)Cryptocurrency adoption
R. (2002) The effect of education on and the road to regulation.
medical technology adoption: are In Proceedings of the 19th Annual
the more educated more likely to International Conference on Digital
use new drugs (No. w9185). Government Research: Governance
National Bureau of Economic in the Data Age, pp. 1-9.
Research. • Shrestha, A. K., &Vassileva, J.
• Martins, C., Oliveira, T., &Popovič, (2019) User Acceptance of Usable
A. (2014) Understanding the Blockchain-Based Research Data
Internet banking adoption: A Sharing System: An Extended
unified theory of acceptance and TAM-Based Study. In 2019 First
use of technology and perceived IEEE International Conference on
risk application. International Trust, Privacy and Security in
Journal of Information Intelligent Systems and
Management, 34(1), pp. 1-13. Applications (TPS-ISA) pp. 203-
208.
• Mendoza-Tello, J. C., Mora, H., • Sohaib, O., Hussain, W., Asif, M.,
Pujol-López, F. A., &Lytras, M. D. Ahmad, M., &Mazzara, M. (2019) A
(2018) Social commerce as a PLS-SEM neural network approach
driver to enhance trust and for understanding cryptocurrency
intention to use cryptocurrencies adoption. IEEE Access, 8, pp.
for electronic payments. IEEE 13138-13150.ž
Access, 6, pp. 50737-50751. • Thakur, R., & Srivastava, M. (2014)
• Mutambara, E. (2019) Predicting Adoption readiness, personal
FinTech innovation adoption in innovativeness, perceived risk and
South Africa: the case of usage intention across customer
cryptocurrency. African Journal of groups for mobile payment
Economic and Management Studies, services in India. Internet Research.
1, pp. 30-50. • Walton, A., & Johnston, K. (2018)
• Nadeem, M. A., Liu, Z., Pitafi, A. H., Exploring perceptions of bitcoin
Younis, A., & Xu, Y. (2020) adoption: the South African virtual
Investigating the repurchase community
intention of Bitcoin: empirical perspective. Interdisciplinary
evidence from China. Data Journal of Information, Knowledge
Technologies and Applications. & Management, 13.
• Nunnally, J. C. (1994) Psychometric • Wang, G., Dou, W., & Zhou, N.
theory 3E. Tata McGraw-hill (2008) Consumption attitudes and
education. adoption of new consumer
• Nuryyev, G., Wang, Y. P., products: a contingency
Achyldurdyyeva, J., Jaw, B. S., Yeh,
_______________
Saad ALAKLABI and Kyeong KANG, Journal of Electronic Banking Systems,
DOI: 10.5171/2021.11041117 Journal of Electronic Banking Systems
__________________________________________________________________________
approach. European Journal of survey for business. International
Marketing,1/2 ,pp. 238-254. Business Management, 11, pp.
• Welch, F. (1970) Education in 1278-1288.
production. Journal of political • Zarifis, A., Efthymiou, L., Cheng, X.,
economy, 78(1), pp. 35-59. & Demetriou, S. (2014 ) Consumer
• Won-jun, L. trust in digital currency enabled
(2018).UnderstandingCounsumer transactions. In International
Acceptance of Fintech Service: An Conference on Business Information
Extension of the TAM Model to Systems, pp. 241-254.
Understand Bitcoin. IOSR Journal • Zong, W., Yang, J., & Bao, Z. (2019)
of Business and Social network fatigue affecting
Management, 20(7), pp. 34-37. continuance intention of social
• Wood, J., Jang, H., Lenskiy, A., & networking services. Data
Khan, G. F. (2017) The diffusion Technologies and Applications. 53,
and adoption of bitcoin: a practical pp. 123-139.
_______________
Saad ALAKLABI and Kyeong KANG, Journal of Electronic Banking Systems,
DOI: 10.5171/2021.110411You can also read
