Determinants of Digital Insurance Adoption among Micro-Entrepreneurs
in Uganda
MUTYA TOMASI*, ILANKADHIR M.
Faculty of Management, SRM Institute of Science and Technology,
Kattankulathur, Tamil Nadu-603203,
INDIA
*Corresponding Author
Abstract: - The insurance industry is constantly evolving with the help of technological advancements across the
globe. The purpose of this study was to explore the critical factors that influence the adoption of digital insurance
among microentrepreneurs in Uganda. The study involved 209 participants. The study used a modified DOI theory
as a framework and analyzed the data using structural equation modeling (IBM SPSS Amos 23.0). The results of
the study indicated that knowledge of digital insurance, relative advantage, and perceived trust have a significant
positive impact on digital insurance adoption among micro-entrepreneurs in Uganda. Conversely, the study found
that perceived social influence had no significant impact. This study adds valuable insights to the literature on
digital insurance and microentrepreneurs and aids policymakers and managers in understanding the influential
factors for implementation.
Key-Words: - Insurance, digital insurance, DOI theory, Entrepreneurship, microentrepreneurs, Perceived trust,
Social influence, relative advantage, Uganda.
Received: April 7, 2023. Revised: February 12, 2024. Accepted: March 15, 2024. Published: April 18, 2024.
1 Introduction
Businesses worldwide are showing an increasing
interest in digital insurance for sustainability,
continuity, and safety. According to [1] and [2],
digital insurance refers to the provision and operation
of insurance and related financial services using
digital solutions. For example, individuals and
organizations can use their mobile phones to access
property and health insurance products anytime and
anywhere. As a result, insurance businesses now
prefer to use automated digital systems to offer
insurance services and products to people and
institutions conveniently. Compared to traditional
insurance systems, digital insurance solutions are
frequently more affordable and can reach
underserved and unserved communities promptly [2].
Digital insurance is believed to enhance financial
transaction security and prevent losses, [3], [4],
making it possible for micro-entrepreneurs to address
risk issues and grow their businesses quickly with a
digital strategy.
Digital insurance offers customers the
convenience they desire in an insurance service. By
going digital, customers can save time and effort
when conducting transactions, [5] and [6]. The
traditional branch insurance system is expensive,
time-wasting, and bureaucratic. This hinders
microentrepreneurs from accessing and using
insurance services on demand. For instance,
microentrepreneurs in Uganda have to travel more
than 20 kilometers to reach insurance branches, [7].
The [7], report classifies microenterprises as
businesses with a workforce of fewer than four
individuals and a capital investment of less than 10
million Uganda shillings. Most of them are located in
rural or hard-to-reach areas. Yet, the branch
insurance system tends to target established and
wealthy businesses that can pay fair premiums,
leaving microbusiness owners open to financial risks
despite being crucial to Uganda's economy. As a
result, microenterprises prioritize financial benefits
like uncalculated loans over risk management, [4].
But with digital insurance, microentrepreneurs can
have access to efficient and effective insurance
services for business growth, [3], [8]. Despite this
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call, insurance companies and governments have a
limited understanding of the factors determining
digital insurance adoption among
microentrepreneurs.
Although microentrepreneurs confront
significant risks in developing countries, there has
been limited attention to the utilization of digital
insurance despite having access to technology [3],
[9]. [10], highlighted the neglect of digital insurance
by prominent authors, particularly when it comes to
microentrepreneurs in low-income countries like
Uganda. Moreover, prior studies focused on major
economies like China [4], [11], Germany [12] and
India [13]. Despite [3]'s study being of Ugandan
origin, it did not delve into micro-entrepreneurship.
Therefore, the study aims to fill these gaps in the
existing literature and provide specific
recommendations to enhance the operations of
microentrepreneurs. The study employs a modified
diffusion of innovation model to explore its purpose.
[14], asserts that the diffusion of innovation model
has strong prediction capabilities for the acceptance
of new technologies.
2 Literature Review
2.1 Microentrepreneurs
[15], defines micro-entrepreneurs as startups because
their businesses have a capital base of less than ten
million Uganda Shillings and employ less than five
individuals. Essentially, startups are newly
established businesses that operate with limited
resources in the early stages of development, [16],
[17]. Innovative ideas motivate these entrepreneurs,
who are prepared to take risks to turn their vision into
a successful venture, [18]. Despite encountering
multiple obstacles, micro-entrepreneurs significantly
contribute to job creation, innovation, and the overall
economic development of Uganda. Some studies,
[18], [19], [20], [21] put micro-enterprises in the
same category as small and medium-sized businesses
(SMEs). However, [17], a study of 379 businesses of
different sizes in Northern Uganda found that micro-
entrepreneurship is defined by using the right
technological resources available in the community.
Thus, ensuring their protection through digital
insurance is vital. The existing branch insurance
model favors larger and more prosperous businesses
that can afford higher premiums while neglecting the
financial vulnerabilities of microbusiness owners.
Particularly in low-income countries characterized by
low digital insurance functionality. Consequently,
microentrepreneurs tend to prioritize access to loans
over risk management strategies. [4], state that digital
insurance offers comprehensive and easily accessible
insurance choices for microbusiness owners.
Through the utilization of digital insurance,
microentrepreneurs may proficiently and successfully
handle risks to enable business advancement, [3].
Adopting this novel methodology has the potential to
foster financial stability and sustainability, aspects
that traditional insurance suppliers often overlook,
[21].
2.2 Digital Insurance
According to [1] and [2], the concept of digital
insurance involves utilizing advanced technologies to
provide insurance services. According to [11], it is a
way to improve business processes in the insurance
industry. This means that customers can access
insurance products and services anytime and
anywhere through online systems. Today, a
reasonable number of insurance companies have
invested in information technology to speed up sales
processes, [22]. Previous studies have shown that
online peer-to-peer insurance can provide customers
with the desired level of security to guarantee
business success, [23], [24]. However, there is a
notable surge in scientific research concerning
insurance technology. [10], called on authors to
improve their interest in the field of digital finance.
This literature gap has been more evident among
microentrepreneurs in developing countries. Yet,
[25], has emphasized that digital insurance can
transform the insurance industry. Microenterprises
are not exceptional. A study by [13], has noted the
need for insurance companies and governments to
prioritize digital transformation efforts to address
insurance customers’ changing demands. This is
because the digital insurance industry has the
potential to stabilize operational efficiency and
effectiveness when serving insurance customers
globally, [2], [25]. On that note, insurance regulators
are working on digital insurance policies to
strengthen the insurance industry, [26]. If developing
countries like Uganda prioritize digital innovations in
the insurance sector, it can lead to increased adoption
of digital insurance solutions by customers, thereby
establishing a stable and dependable trajectory for the
industry. However, digital insurance adoption is still
low overall, particularly in developing nations like
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Uganda, [4]. Also, [12], found that digital penetration
was low across the insurance industry, highlighting
the need for continued advancement. To help micro
business owners adopt digital insurance, we employ
the diffusion of innovation theory to examine crucial
factors in this study. Table 1 shows a list of insurance
providers in Uganda.
Table 1. Insurance companies in Uganda.
Life insurance companies
Non-life insurance companies
Microinsurance companies
CIC Africa, ICEA, Jubilee, Liberty
(Assurance), Metropolitan, NIC
(Assurance), Prudential
(Assurance), Sanlam, and UAP Old
Mutual (Assurance)
AIG, Alliance Africa, APA, Britam,
CIC, Excel, First Insurance,
Goldstar, ICEA General, Liberty
General, Mayfair, MUA, NIC
General, Pax, Rio, Sanlam General,
Statewide, The Jubilee, Trans
Africa, UAP Old Mutual
Grand micro, Edge micro
Source: author compilation
2.3 Diffusion Innovation Theory
[14], defines the diffusion of innovation (DOI) as a
process of communicating a novel idea through
channels within a social group or system. Societies
across economies desire great change to improve
well-being. Technology has proved to be a great
pillar in this effort of community transformation,
[27]. Factors such as compatibility, relative
advantage, trialability, observability, and complexity
are the baseline for the DOI theory that enhances
society's desire to adopt new technology, [28], [29].
We observe from previous studies that relative
advantage has the greatest influence on customers in
the process of adopting technology to cause
community change, [29], [30]. Relative advantage
spells out the convenience associated with adopting
technology to a business community, [30]. Similarly,
in this study, we argue that compatibility,
observability, trialability, and complexity are
grounded on social influence. Individuals learn from
each other new ways of doing business or addressing
their financial interests, [31]. Furthermore, when
individuals share information, confidence levels
increase, leading to perceived trust. This perceived
trust encourages members of the groups to have a
significant influence on the choices of others,
especially regarding new technology, which moves
businesses across the globe and builds knowledge.
On that note, this study modifies the DOI model to
indicate that perceived trust, social influence,
knowledge of digital insurance, and relative
advantage have a significant effect on the adoption of
new technology among microentrepreneurs in
developing countries characterized by low levels of
technology adoption and usage.
2.4 Hypothesis Development
Digital insurance is a modern transformative tool in
the insurance sector that helps customers experience
a user-friendly environment that enables maximized
utilitarian value, [32]. With digital insurance,
customers can experience lower transaction costs,
quick, and easy operations, [2]. As such, customers
are more than willing to adopt and use innovative
technologies, [33]. Therefore, microentrepreneurs
can enhance their experiences by investing in
technological advancements, [34]. This aligns with
[35] study, which stipulates that novel technology
saves time and money when utilized in business
operations. On that note, innovative technology
transforms customers' perceptions based on the
relative advantages. Against such a backdrop, the
study hypothesizes that:
H1: Relative advantage has a positive impact on the
adoption of digital insurance among micro-
entrepreneurs.
The relationship between individuals and the
surrounding community embeds perceived social
influence. For example, an individual can adopt a
new technology based on the reactions they receive
from their family, peers, and work colleagues, [36],
[37]. As a result, the power of social cohesion creates
an everlasting influence on individuals in a given
society to adopt new technology for the sake of
inclusive well-being. According to [36] and [37],
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social decisions bond members and make them work
together for the common good. The adoption of
innovative technology is not exceptional. On a
similar note, [38], study revealed that perceived
social influence leads to high rates of technological
adoption. Based on such a background, the study
hypothesizes that:
H2: Perceived social influence has a positive effect
on the adoption of digital insurance among micro-
entrepreneurs.
Trust is fundamental to ensuring consistent
business operations. According to [32], perceived
trust involves a person’s confidence, belief, and
dependence on individuals within their immediate
surroundings. People tend to develop a sense of trust
in the community of their interest. Against such a
backdrop, it can be understood that customers can
easily and quickly adopt and use a new technology
based on honesty and self-assurance from business
practitioners. On that note, businesses need to
emphasize the provision of services rather than just
focusing on increasing profits to improve their
customers’ confidence and mitigate the occurrence of
any kind of misunderstanding. According to [3],
insurance companies provide transparent payout and
rejection procedures to streamline operations for all
stakeholders using digital insurance. In addition, the
study conducted by [39], revealed that customers’
perceptions of trust have an impact on adoption.
Therefore, the level of customer trust determines the
usefulness of an insurance system. Based on such a
discussion, the study hypothesizes that:
H3: Perceived trust has a positive effect on the
adoption of digital insurance among micro-
entrepreneurs.
Knowledge of digital insurance refers to an
individual’s understanding of how digital systems
operate in the insurance sector, [40]. On this note,
knowing digital insurance plays a significant role in
the adoption process. A previous study by [41],
found that embracing a digital agenda can enhance
people's knowledge of the insurance industry.
According to [2], it involves a process for an
individual in the micro-business sector to obtain
knowledge of digital insurance. When people become
conversant with digital operations in the insurance
sector, [4], the adoption and usage of digital
insurance will increase in the shortest time. Based on
such a discussion, the study hypothesizes that:
H4: Knowledge of digital insurance has a positive
impact on the adoption of digital insurance among
micro-entrepreneurs.
3 Methodology
The study adopted a scale from previous studies for
measurement. We obtained the scale items from
previous studies and modified them to meet the
purpose of the study. Relative advantage (four items)
from [32], social influence (four items) from [36],
perceived trust (three items) from [3], knowledge of
digital insurance (three items) from [42], and digital
insurance adoption (three items) from [43]. We
employed a Likert scale (Strongly agree, agree,
neutral, disagree, and strongly disagree).
Additionally, we subjected the designed
questionnaire to expert opinion for validity check.
This involved an academician in the field of
insurance and a practitioner. Their opinions were
incorporated. Furthermore, the questionnaire was
printed out and distributed to microentrepreneurs in
Mbale city, Mbale district, and Sironko district.
These areas are disaster-prone and are experiencing
rapid technological change, especially in insurance.
This highlights the necessity of digital insurance. We
employed two screening questions, "Do you have an
insurance account?" and "Do you have internet
services?" to determine eligibility for the study.
(modified from [43]). We allowed individuals who
passed the screening questions to complete the
questionnaire. We selected the participants using
purposive and snowball sampling techniques to
ensure we obtained the right respondents for the
study, [44], [45]. This involved visiting
microentrepreneur businesses and conducting
referrals to identify respondents. A total of 254
questionnaires were issued, with 209 valid responses
received and analyzed, resulting in an 82.3%
effective rate (Table 2). We utilized AMOS 23.0
structural equation modeling for analysis due to its
strong predictive power.
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4 Study Results
Table 2. Demographic data
Category
Number
Percentage
Cumulative %
Gender
Female
Male
139
70
66.5
33.5
66.5
100
Age
20-30
30-40
40-50
50-60
60 and above
40
41
31
63
34
19.1
19.6
14.8
30.1
16.3
19.1
38.8
53.6
83.7
100
Education
Primary
Secondary
Bachelor degree
Master degree
26
98
82
3
12.4
46.9
39.2
1.4
12.4
59.3
98.6
100
Experience
Less than 5 years
5-10
10-15
15-20
20 and above
25
49
58
37
40
12
23.4
27.8
17.7
19.1
12
35.4
63.2
80.9
100
Table 3. Measurement model summary
Constructs
Items
Factor
Loading
Relative advantage AVE (.837), α (.935), CR (.954),
Digital insurance services save time.
.909
Digital insurance services are cost-effective.
.922
I can easily access digital insurance services.
.921
I can perform a transaction anywhere with digital insurance.
.907
Perceived social influence AVE (.822), α (.929), CR
(.949)
My peers encouraged me to use digital insurance services.
.897
I use digital insurance services because my friends do.
.903
People I value influence my decision on digital insurance
services.
.916
I believe digital insurance services are good for everyone.
.911
Perceived Trust: AVE (.783), α (.920), CR (.915)
Digital insurance services are reliable.
.846
Digital insurance services are handled with care.
.903
I have faith in the services of digital insurance.
.904
Knowledge of digital insurance AVE (.688), α (.880), CR
(.869)
I am aware of and understand digital insurance services.
.829
I can use digital insurance services.
.862
I can share digital insurance information with others.
.797
Digital Insurance Adoption: AVE (.706), α (.912), CR
(.900)
I will continue interacting with digital insurance platforms.
.866
I prefer to use digital insurance services.
.918
I will use digital insurance services more often.
.797
Model Fit: CMIN/DF (1.713), CFI (0.976), NFI (0.945), IFI (0.976), TLI (0.968), RMR (0.062), RMSEA (0.59)
Table 4. Descriptive Statistics and Correlation Matrix
Mean
Std D
1
2
3
4
5
Relative advantage (1)
4.084
1.062
.954c
Perceived social influence (2)
3.785
1.225
.428**
.907 c
Perceived trust (3)
3.823
1.225
.401**
.460**
.885 c
Knowledge of Digital Insurance (4)
4.242
.901
.422**
.362**
.368**
.830 c
.840 c
Digital Insurance Adoption (5)
4.160
.9222
.515**
.465**
.495**
.677**
∗∗
Correlation is significant at the.01 level; standard deviation = c AVE Square root of the latent construct.
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Table 5. Construct path analysis
Hypothesis relationship
(β)
SE
Relative Advantages Digital Insurance Adoption
.231*
.076
Perceived social influence Digital insurance adoption
.102 ns
.062
Perceived Trust Digital Insurance Adoption
.194*
.061
Knowledge of Digital Insurance Digital Insurance Adoption
.309**
.061
**p<.01, *p<.05, CMIN/DF (2.063) (p<.001), CFI (0.966), NFI (0.936), IFI (0.966), RMSEA (0.072), TLI (0.952), RMR (0.063), ns=not
significant.
4.1 Measurement Model Analysis
We conducted a confirmatory factor analysis using
AMOS 23 to determine whether the observed
variables were valid indicators for the study
constructs (Table 3). The study examined a total of
five measurement models, with results displayed in
Table 3. These results indicate that all constructs had
Cronbach alpha coefficients greater than 0.7 and
model fit indices greater than 0.9. Additionally, the
RMR and RMSEA were less than 0.08, aligning with
the recommended guidelines for scale reliability,
[46], [47]. Table 3 also revealed AVE values greater
than 0.68 and CR values greater than 0.7, which
fulfill the recommended guidelines for convergent
validity, [48], [49]. Table 4 also showed that the
square root of the AVE was higher than each
construct correlation coefficient. This supported the
discriminative validity of the scale. On a similar note,
construct correlation coefficient values ranged from
0.362 to 0.677, indicating the absence of multi-
collinearity, [49], [50].
4.2 Path Analysis
We used the AMOS 23 structural equation model for
this study to examine how relative advantage,
perceived social influence, perceived trust, and
knowledge of digital insurance influence digital
insurance adoption in Uganda. CMIN/FD (2.063) is
less than 3, model fit indices above 0.9 (CFI (0.966),
NFI (0.936), IFI (0.966), and TLI (0.952), RMR
(0.063), and RMSEA (0.072) are all less than 0.08.
This meets the standards and means the model is fit,
[47], [48], [49], [51], [52]. Also, Table 5 shows that
relative advantage (H1) (β=0.231, p<.01), perceived
trust (H3) (β=0.194, p<.01), and knowledge of digital
insurance (H4) (β=0.309, p<.001) all have a positive
effect on people's decisions to adopt digital
insurance. Therefore, we found support for
hypotheses H1, H3, and H4. However, perceived
social influence (H2) (β=0.102, p>.05) was found to
have an insignificant impact on digital insurance
adoption. Therefore, the study did not support
hypothesis H2. On the other hand, the R2 value of
digital insurance adoption was 0.56. Thus, the study
model explained 56% of the variations in digital
insurance adoption.
5 Discussion
Insurance plays a vital role in safeguarding
businesses against risks, and this trend is expanding
across the globe, [2], [3], [40]. Business owners aim
to provide their customers with top-notch services
and products while maximizing profits, and having
the right insurance coverage is essential to achieving
these objectives. It is imperative to develop an
approach that is both affordable and practical for
everyone, particularly those living in underprivileged
areas. Digital insurance has emerged as a promising
solution due to its cost-effectiveness and wider reach,
especially in developing countries like Uganda [12],
[41]. To ensure its successful implementation, it is
crucial to understand the driving forces behind
consumer adoption of digital insurance, [4], [53].
Based on the modified theory of innovation
diffusion, this study highlights relative advantage,
perceived social influence, perceived trust, and
knowledge of digital insurance as key factors in its
adoption.
The study's results (Table 5) revealed that
customers' knowledge of digital insurance
significantly influenced its adoption. This
emphasizes the significance of having a fundamental
understanding of insurance and the digital system to
interact with online insurance products and services
conveniently (as noted by [4], [32]). When customers
have a better understanding of insurance and
associated digital systems, it builds confidence and
can help people in low-income economies greatly
because it enables them to avoid pricey branch visits
and work around the clock, [2]. Armed with the
appropriate knowledge, consumers can pay their
premiums promptly, report fraud through chatbots
and other online chat systems, and easily request
reimbursements when needed. Consequently,
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increased internet literacy is pushing the insurance
industry towards digitization, [40].
The study's findings indicate that relative
advantage follows customers' knowledge of digital
insurance as a key factor in its adoption (Table 5).
Microbusiness owners are not only willing but also
eager to embrace digital insurance services, provided
that they are quick, safe, secure, and affordable. By
contrast with traditional branch-based insurance,
digitalization can offer greater convenience in paying
monthly premiums. These results align with previous
research by [38], [39] and [43], which demonstrated
that customers embrace digital services when they
provide cost savings, faster transactions, and
enjoyable digital interactions. To facilitate the
adoption of digital insurance, insurance companies
should focus on employing cutting-edge tools that
benefit low-income individuals, such as
microentrepreneurs.
The results (Table 5) also indicate that perceived
trust has a significant positive influence on the
adoption of digital insurance. Against such a
backdrop, micro-entrepreneurs are more likely to
switch their interests from traditional branch
insurance, which is riskier, especially when insurance
consumers grow to trust the insurance processes on
digital platforms, [2]. By doing this, insurance
customers' knowledge of online systems can grow,
giving them more confidence to adopt digital
insurance. The study findings support, [3], position
that insurance companies should permit open payouts
and denials. If customers can access digital systems
at any time and from any location, trust improves and
provides more opportunities for microentrepreneurs
to adopt digital insurance. This is consistent with
[39], study, which revealed that perceived trust
affects the adoption of technological innovations. On
the other hand, the rise in online financial fraud
across the globe has reduced customer trust levels.
Thus, it is necessary to strengthen platforms for
consumer redress to emerging risks, [40].
Finally, the study revealed that perceived social
influence does not play a significant role in the
adoption of digital insurance by microentrepreneurs
in Uganda. This result conflicts with earlier research
on financial technology by [32], in Indonesia. This
could be because an individual's peers or family in
low-income countries like Uganda have minimal
influence due to limited knowledge relating to digital
insurance. Secondly, the insurance sector is still at
the infantry stage in developing countries which may
undermine the power of social influence. Against
such a backdrop, social influence is not a significant
factor in the adoption of digital insurance. This aligns
with the argument of [36] and [54] that perceived
social influence only affects the adoption of a
technology that is widely familiar to the majority of
the population. Therefore, social influence does not
significantly impact the adoption of digital insurance
among microentrepreneurs in Uganda.
5.1 Theoretical Implications
The insurance industry is undergoing rapid evolution
to align with global economic trends, particularly
those concerning financial technology. To keep pace
with these developments, the industry has adopted
digital systems that facilitate quick insurance
transactions. As such, this academic study delves into
the factors that may influence insurance customers'
adoption of digital insurance to contribute to the
existing literature and enhance insurance managers'
understanding of the models that can advance the
industry. The study also expands knowledge of the
relative advantage, perceived social influence,
perceived trust, and the general understanding of
digital insurance. Furthermore, gaining a clear
understanding based on the diffusion of innovation
theory, especially in the context of the insurance
industry, is crucial. Additionally, this research on the
uptake of digital insurance among
microentrepreneurs in a low-income country like
Uganda expands the geographical scope of
entrepreneurship and digital insurance literature from
a demand perspective.
5.2 Managerial implications
From a managerial perspective, insurance managers
should adopt digital systems that are easy for micro-
entrepreneurs to comprehend. With the right
information, insurance companies can help their
customers avoid costly branch insurance offices that
are not available around the clock. Micro-
entrepreneurs can easily report fraud through
chatbots and other online chat systems, pay
premiums on time to avoid penalties, and request
reimbursements when necessary if they have access
to the right information. Governments should also
regulate insurance companies to ensure that
customers benefit from digital insurance. Micro-
entrepreneurs are not only willing but also eager to
adopt and use digital insurance services that are
quick, safe, secure, affordable, and sustainable in the
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short and long term. For example, when
microentrepreneurs conduct insurance transactions in
real time, they are more likely to have repeat
business and serve as references to promote the use
of digital technology in the insurance market. In
addition, insurance policymakers and managers
should ensure reliable and uninterrupted access to
digital insurance systems at all times and places.
Customers of insurance are more likely to adopt open
and transparent digital insurance. Finally,
governments should strengthen consumer rights and
redress platforms to protect customers against
financial fraud and foster trust.
5.3 Limitations and Future Research
The insurance industry is in a state of flux, with new
technologies emerging daily. It's worth noting,
however, that the findings of this study may not be
entirely reflective of changing consumer behavior
over time, as it was based on a cross-sectional
survey. That being said, this research is valuable
because there is limited data available on the factors
that influence microentrepreneurs when it comes to
adopting digital insurance. Moving forward, a
longitudinal study would be beneficial in detecting
cause-and-effect relationships. Additionally, the
sample size for this study was small, consisting of
only 209 Uganda-based microentrepreneurs, despite
the growing number of digital insurance users in the
country. Nevertheless, this study provides valuable
insights into digital insurance adoption in low-
income countries like Uganda. There is ample
opportunity for future studies to expand on this
research and explore the topic in greater detail,
including larger sample sizes and comparative
studies. It's worth noting that this study focused
primarily on demand factors from the customer
perspective without exploring the supply side of the
insurance companies. Nevertheless, as the first study
of its kind to examine the determinants of digital
insurance adoption from the microentrepreneur's
point of view, it represents a significant contribution
to the field. Moving forward, researchers could study
the determinants of digital insurance adoption among
small, medium, and large entrepreneurs while also
exploring different theories and models, such as the
planned behavior model.
5.4 Conclusion
To provide customers with services that are both
simple and economical, the insurance industry needs
to embrace technological advancements, [2]. Insurers
should strive to make their digital platforms as
convenient as possible to create a sense of delight
and value for their customers. This research indicates
that knowledge of digital insurance, perceived trust,
and relative advantage are key determinants of its
adoption among microentrepreneurs. Indeed, ease of
use, minimal effort, confidence, belief, and
knowledgeability when using digital insurance all
have a positive influence on its adoption. Moreover,
the global coverage, pleasant interface, and
availability of fun and enjoyment anytime and
anywhere offer significant benefits that increase
customer adoption of digital insurance. Although
perceived social influence is not a significant factor
in economies with less insurance coverage,
policymakers and insurance company management
should still invest resources to ensure that digital
insurance users can work in groups to experience
maximum utilitarian and hedonic values based on
logic and reason. This will ultimately enhance the
adoption of digital insurance.
References:
[1] Nicoletti, B. (2016). Digital insurance:
Business innovation in the post-crisis era.
Springer,
https://doi.org/10.1057/9781137553270.
[2] Xuheng, Z. (2023). Discussion on the value-
added space of digital transformation of
insurance industry. Academic Journal of
Business & Management, 5(6),
https://doi.10.25236/AJBM.2023.050608.
[3] Kiwanuka, A., & Sibindi, A. B. (2023).
Insurance Inclusion in Uganda: Impact of
Perceived Value, Insurance Literacy and
Perceived Trust. Journal of Risk and Financial
Management, 16(2), 81,
https://doi.org/10.3390/jrfm16020081.
[4] Fu, Z., Zhou, Y., Li, W., & Zhong, K. (2023).
Impact of digital finance on energy efficiency:
Empirical findings from China. Environmental
Science and Pollution Research, 30(2), 2813-
2835, https://doi.org/10.1007/s11356-022-
22320-5.
[5] Tokar, M., Kravtsov, Y., Shybirina, S., &
Khmarska, I. (2023). Digital aspects of the
Ukrainian economic development. Financial
Engineering, vol. 1, pp.137-145,
https://doi.org/10.37394/232032.2023.1.13.
Financial Engineering
DOI: 10.37394/232032.2024.2.9
Mutya Tomasi, Ilankadhir M.
E-ISSN: 2945-1140
111
Volume 2, 2024
[6] Tomasi, M., & Ilankadhir, M. (2024). Mobile
Banking Adoption: A Closer Look at the Role
of Online Convenience Dimensions. Int.
Journal of Business Science and Applied
Management, 19(1), pp. 47-58.
[7] Ministry of Trade, Industry and Cooperatives
(2015) Sustainable MSMEs for Wealth
Creation and Socio -Economic Transformation,
[Online]. https://www.mtic.go.ug (Accessed
Date: April 10, 2024).
[8] Aleksandrova, A., Ninova, V., & Zhelev, Z.
(2023). A Survey on AI Implementation in
Finance,(Cyber) Insurance and Financial
Controlling. Risks, 11(5), 91,
https://doi.org/10.3390/risks11050091.
[9] Liu, W., Wang, B., Wang, C., & Han, K.
(2023). The effect of financial literacy on rural
households insurance participation: evidence
from farmers in southwest China. Asia-Pacific
Journal of Accounting & Economics, 30(1),
139-155,
https://doi.org/10.1080/16081625.2021.191516
5.
[10] Gomber, P., Koch, J. A., & Siering, M. (2017).
Digital Finance and FinTech: current research
and future research directions. Journal of
Business Economics, 87, 537-580,
https://doi.org/10.1007/s11573-017-0852-x.
[11] Hu, X., Wang, Z., & Liu, J. (2022). The impact
of digital finance on household insurance
purchases: Evidence from micro data in China.
The Geneva Papers on Risk and Insurance-
Issues and Practice, 47(3), 538-568,
https://doi.org/10.1057/s41288-022-00267-5.
[12] Eckert, C., Eckert, J., & Zitzmann, A. (2021).
The status quo of digital transformation in
insurance sales: an empirical analysis of the
German insurance industry. Zeitschrift für die
gesamte Versicherungswissenschaft, 110(2-3),
133-155, https://doi.org/10.1007/s12297-021-
00507-y.
[13] Kumar, P., Taneja, S., Mukul, & Özen, E.
(2023). Digital Transformation of the
Insurance Industry–A Case of the Indian
Insurance Sector. The Impact of Climate
Change and Sustainability Standards on the
Insurance Market, Chapter 6, 85-106,
https://doi.org/10.1002/9781394167944.ch6.
[14] Rogers, E. M., & Singhal, A. (2003).
Empowerment and communication: Lessons
learned from organizing for social change.
Annals of the International Communication
Association, 27(1), 67-85,
https://doi.org/10.1080/23808985.2003.116790
22
[15] Uganda Investment Authority (2023),
Entrepreneurship development for SMEs,
[Online].
https://www.ugandainvest.go.ug/sme/
(Accessed Date: April 10, 2024).
[16] Tomasi, M. (2020). Perspective of Financial
Literacy on Agribusiness Performance in
Uganda; A Close Look at Farmers’ Attitude
and Social Media Platforms, Saudi Journal of
Business and Management Studies, pp.74-83,
https://doi.org/10.36348/sjbms.2020.v05i01.01
0.
[17] Okello Candiya Bongomin, G., & Ntayi, J.
(2020). Trust: mediator between mobile money
adoption and usage and financial inclusion.
Social Responsibility Journal, 16(8), 1215-
1237. https://doi.org/10.1108/SRJ-01-2019-
0011
[18] Frimpong, S. E., Agyapong, G., & Agyapong,
D. (2022). Financial literacy, access to digital
finance and performance of SMEs: Evidence
From Central region of Ghana. Cogent
Economics & Finance, 10(1), 2121356,
https://doi.org/10.1080/23322039.2022.212135
6
[19] Tomasi, M., & Muyelero, E. (2019).
Entrepreneurial Attitude; A Fundamental Root
for Firm Performance in Uganda a Close Look
at Business Alertness, Case Study of Industrial
Division Mbale, Scholars Journal of
Economics, Business and Management, Dec.,
2019; 6(12): 583-592, DOI:
10.36347/sjebm.2019.v06i12.006.
[20] Thathsarani, U. S., & Jianguo, W. (2022). Do
Digital Finance and the Technology
Acceptance Model Strengthen Financial
Inclusion and SME Performance?. Information,
13(8), 390,
https://doi.org/10.3390/info13080390.
[21] Xie, C., & Liu, C. (2022). The nexus between
digital finance and high-quality development of
SMEs: evidence from China. Sustainability,
14(12), 7410,
https://doi.org/10.3390/su14127410.
[22] Mustafina, A. A., Kaigorodova, G. N.,
Alyakina, P. D., Velichko, N. Y., & Zainullina,
M. R. (2020). Digital technology in insurance.
Financial Engineering
DOI: 10.37394/232032.2024.2.9
Mutya Tomasi, Ilankadhir M.
E-ISSN: 2945-1140
112
Volume 2, 2024
In Digital transformation of the economy:
Challenges, trends and new opportunities.
Trends and New Opportunities. Advances in
Intelligent Systems and Computing, vol 908.
Springer, Cham, https://doi.org/10.1007/978-3-
030-11367-4_65.
[23] Arumugam, M., & Cusick, K. (2008). General
Insurance 2020: Insurance for the Individual.
Sydney: Institute of Actuaries of Australia,
[Online].
https://actuaries.asn.au/Library/GIS08_8b_Pap
er_Arumugam_General%20Insurance%202020
.pdf (Accessed Date: April 10, 2024).
[24] Moenninghoff, S. C., & Wieandt, A. (2013).
The future of peer-to-peer finance.
Schmalenbachs Zeitschrift für
betriebswirtschaftliche Forschung, 65, 466-
487, https://doi.org/10.1007/BF03372882.
[25] Cosma, S., & Rimo, G. (2024). Redefining
Insurance through Technology: achievements
and perspectives in Insurtech. Research in
International Business and Finance, 102301,
https://doi.org/10.1016/j.ribaf.2024.102301.
[26] Infantino, M. (2024). A comparative study of
automated quantification in digital insurance.
International Journal of Digital Law and
Governance, https://doi.org/10.1515/ijdlg-
2024-0003.
[27] Sahin, I. (2006). Detailed review of Rogers'
diffusion of innovations theory and educational
technology-related studies based on Rogers'
theory. Turkish Online Journal of Educational
Technology-TOJET, 5(2), 14-23, [Online].
https://eric.ed.gov/?id=EJ1102473 (Accessed
Date: April 10, 2024)..
[28] Ali, M., Raza, S. A., Puah, C. H., & Amin, H.
(2019). Consumer acceptance toward takaful in
Pakistan: An application of diffusion of
innovation theory. International Journal of
Emerging Markets, 14(4), 620-638,
https://doi.org/10.1108/IJOEM-08-2017-0275.
[29] Menzli, L. J., Smirani, L. K., Boulahia, J. A., &
Hadjouni, M. (2022). Investigation of open
educational resources adoption in higher
education using Rogers’ diffusion of
innovation theory. Heliyon, 8(7),
https://doi.org/10.1016/j.heliyon.2022.e09885.
[30] Sin, K. Y., Osman, A., Salahuddin, S. N.,
Abdullah, S., Lim, Y. J., & Sim, C. L. (2016).
Relative advantage and competitive pressure
towards implementation of e-commerce:
Overview of small and medium enterprises
(SMEs). Procedia Economics and Finance, 35,
434-443, https://doi.org/10.1016/S2212-
5671(16)00054-X.
[31] Moga, L. M., Durac, L., & Simbanu, I. (2023).
Incentive Factors for Social Entrepreneurship
Adoption Based on Diffusion of Innovation
Theory. Acta Universitatis Danubius.
Œconomica, 19(1), 232-248, [Online].
https://www.ceeol.com/search/article-
detail?id=1164354 (Accessed Date: April 10,
2024).
[32] Zakariyah, H., Salaudeen, A. O., Othman, A.
H. A., & Rosman, R. (2023). The determinants
of financial technology adoption amongst
Malaysian waqf institutions. International
Journal of Social Economics, Vol. 50 No. 9,
pp. 1302-1322, https://doi.org/10.1108/IJSE-
04-2022-0264.
[33] Mutya, T., & Josephine, A. (2018). Financial
management a wheel to financial performance
of local governments in Uganda: a case study
of Tororo Municipal Council. Journal of
Business & Financial Affairs, 7(02), 2167-
0234, https://doi.org/10.4172/2167-
0234.1000330.
[34] Alhumaid, K., Naqbi, S., Elsori, D., &
Mansoori, M. (2023). The adoption of artificial
intelligence applications in education.
International Journal of Data and Network
Science, 7(1), 457-466,
http://dx.doi.org/10.5267/j.ijdns.2022.8.013.
[35] Junglas, I., Goel, L., Ives, B., & Harris, J.
(2019). Innovation at work: The relative
advantage of using consumer IT in the
workplace. Information Systems Journal,
29(2), 317-339,
https://doi.org/10.1111/isj.12198.
[36] Koul, S., & Eydgahi, A. (2020). The impact of
social influence, technophobia, and perceived
safety on autonomous vehicle technology
adoption. Periodica Polytechnica
Transportation Engineering, 48(2), 133-142,
https://pp.bme.hu/tr/article/view/11332.
[37] Soelton, M., Marta, P., Thoullon, M. S.,
Yuliantini, T., Saratian, E. T. P., & Arief, H.
(2023). The Knowledge Sharing Anomaly to
Improve Organizational Citizenship Behavior.
WSEAS Transactions on Financial
Engineering, 1, 326-344,
https://doi.org/10.37394/232032.2023.1.31.
Financial Engineering
DOI: 10.37394/232032.2024.2.9
Mutya Tomasi, Ilankadhir M.
E-ISSN: 2945-1140
113
Volume 2, 2024
[38] Park, J., Ahn, J., Thavisay, T., & Ren, T.
(2019). Examining the role of anxiety and
social influence in multi-benefits of mobile
payment service. Journal of retailing and
consumer services, 47, 140-149,
https://doi.org/10.1016/j.jretconser.2018.11.01
5.
[39] Singh, N., & Sinha, N. (2020). How perceived
trust mediates merchant's intention to use a
mobile wallet technology. Journal of retailing
and consumer services, 52, 101894,
https://doi.org/10.1016/j.jretconser.2019.10189
4.
[40] Uganda Insurance Authority, (2022). Digital
adoption; the viable growth lever for
businesses, economy, [Online].
https://ira.go.ug/ (Accessed Date: April 10,
2024).
[41] Bohnert, A., Fritzsche, A., & Gregor, S.
(2019). Digital agendas in the insurance
industry: the importance of comprehensive
approaches. The Geneva Papers on Risk and
Insurance-Issues and Practice, 44, 1-19,
https://doi.org/10.1057/s41288-018-0109-0.
[42] Asif, M., Khan, M. N., Tiwari, S., Wani, S. K.,
& Alam, F. (2023). The impact of fintech and
digital financial services on financial inclusion
in india. Journal of Risk and Financial
Management, 16(2), 122,
https://doi.org/10.3390/jrfm16020122.
[43] Shankar, A., & Rishi, B. (2020). Convenience
matters in mobile banking adoption
intention? Australasian Marketing Journal
(AMJ), 28(4), 273-285,
https://doi.org/10.1016/j.ausmj.2020.06.008.
[44] Guarte, J. M., & Barrios, E. B. (2006).
Estimation under purposive sampling.
Communications in Statistics-Simulation and
Computation, 35(2), 277-284,
https://doi.org/10.1080/03610910600591610.
[45] Noy, C. (2008). Sampling knowledge: The
hermeneutics of snowball sampling in
qualitative research. International Journal of
Social Research Methodology, 11(4), 327-344,
https://doi.org/10.1080/13645570701401305.
[46] West, S. G., Wu, W., McNeish, D., & Savord,
A. (2023). Model fit in structural equation
modeling. In R.H. Hoyle (Ed.), Handbook of
Structural Equation Modeling (2nd Ed.)
Guilford Press, pp. 184-205.
[47] Hu, L. T., & Bentler, P. M. (1999). Cutoff
criteria for fit indexes in covariance structure
analysis: Conventional criteria versus new
alternatives. Structural Equation Modeling: A
Multidisciplinary Journal, 6(1), 1-55,
https://doi.org/10.1080/10705519909540118.
[48] Bentler, P. M., & Bonett, D. G. (1980).
Significance tests and goodness of fit in the
analysis of covariance structures.
Psychological bulletin, 88(3), 588,
https://doi.org/10.1037/0033-2909.88.3.588.
[49] Hair Jr, J. F., Sarstedt, M., Ringle, C. M., &
Gudergan, S. P. (2017). Advanced issues in
partial least squares structural equation
modeling. saGe publications,
https://doi.org/10.3926/oss.37.
[50] Lindner, T., Puck, J., & Verbeke, A. (2020).
Misconceptions about multicollinearity in
international business research: Identification,
consequences, and remedies. Journal of
International Business Studies, 51, 283-298,
https://doi.org/10.1057/s41267-019-00257-1.
[51] McDonald, R. P., & Ho, M. H. R. (2002).
Principles and practice in reporting structural
equation analyses. Psychological methods,
7(1), 64, https://doi.org/10.1037/1082-
989X.7.1.64.
[52] Steiger, J. H. (2007). Understanding the
limitations of global fit assessment in structural
equation modeling. Personality and Individual
differences, 42(5), 893-898,
https://doi.org/10.1016/j.paid.2006.09.017.
[53] Rahman, A. M., & Islam, S. (2022). Can
Voluntary Insurance ensure risk-free digital-
banking in Chinese-economy: seeking
attentions?. Journal of Chinese Economic and
Business Studies, 20(2), 139-158,
https://doi.org/10.1080/14765284.2021.192979
2.
[54] Bruno, J. M., Bianchi, E. C., & Sánchez, C.
(2022). Determinants of household recycling
intention: The acceptance of public policy
moderated by habits, social influence, and
perceived time risk. Environmental Science &
Policy, 136, 1-8,
https://doi.org/10.1016/j.envsci.2022.05.010.
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