International Journal of Information Management Data Insights 4 (2024) 100254
Contents lists available at ScienceDirect
International Journal of Information
Management Data Insights
journal homepage: www.elsevier.com/locate/jjimei
Continuance usage intention of e-wallets: Insights from merchants
Mia Deanna Sara binti Mohd Reza a, Siow-Hooi Tan a, *, Lee-Lee Chong b, Hway-Boon Ong c
a
Faculty of Management, Multimedia University, Malaysia
School of Accounting and Finance, Asia Pacific University of Technology and Innovation, Malaysia
c
Faculty of Arts and Social Sciences, University of Nottingham Malaysia, Malaysia
b
A R T I C L E I N F O
A B S T R A C T
Keywords:
E-wallet
Merchants
Network externalities
Satisfaction
Continuance usage
The aim of this study is to examine the factors that impact merchants’ inclination to persist in utilizing e-wallets
as a payment system in Malaysia. The study integrates the Unified Theory of Acceptance and Use of Technology
(UTAUT) model with the Expectation Confirmation Model (ECM). Additionally, it includes three other con­
structs: awareness, online customer service, and network externalities. A total of 146 survey responses were
collected and subsequently analyzed using PLS-SEM. The findings revealed that awareness and online customer
service exert positive influences on performance expectancy and effort expectancy, respectively. It was deter­
mined that performance expectancy significantly and positively affects satisfaction. The study showed that effort
expectancy, network externalities, and satisfaction positively affect merchants’ continuous intention to use the ewallet system. Conversely, performance expectancy was not identified as a significant predictor of continuance
usage intention of e-wallets.
1. Introduction
MasterCard Impact Study 2020, Malaysia leads Southeast Asia in
e-wallet adoption, with 40% usage, surpassing countries like the
Philippines (36%), Thailand (27%), and Singapore (26%) (Ismail,
2021). Despite the country’s efforts to recover from the COVID-19
pandemic and its economic repercussions, Malaysians are encouraged
to embrace the "new normal," which includes contactless payment
practices. This shift towards a digital lifestyle, where e-wallets play a
pivotal role, is crucial, particularly as COVID-19 cases have recently
surged by 57.3%, with 3626 cases reported from November 19 to
November 25, 2023 (Trisha, 2023).
E-wallets streamline transactions for consumers by consolidating
credit cards, cash, and various payment platforms into one convenient
device. Meanwhile, merchants, particularly within the context of microand small-medium enterprises, which represent a significant portion of
businesses in Malaysia, are compelled to integrate cashless payment
technologies into their strategies to remain competitive (Aziz, 2022).
The success of e-wallet adoption hinges on both consumers and
merchants embracing this payment method. Satisfying current e-wallet
users and ensuring their continued usage is paramount for the technol­
ogy’s long-term success (Zhao & Lu, 2012). While Malaysia aims for a
cashless society by 2025, merchants’ decisions regarding e-wallet usage
could significantly impact this timeline (Poon, 2023). However, existing
research predominantly focuses on consumer behaviors, leaving a
The concept of cashless payment or contactless payment has been a
major topic worldwide over the past few years, with multiple contactless
payment methods already being utilized across the globe. Among these
methods, the e-wallet stands out as receiving significant attention from
the public as well as support from the government. Accenture reported
that in the year 2018, 56% of consumers were aware of e-wallets, while
Juniper Research shared that global e-wallet spending rose by 32% in
2017 (Are Digital Wallets the Future of Payments, 2019). The popularity
of e-wallets is also evident in Canada, where over two-thirds of Cana­
dians are choosing to adopt e-wallets as payment options compared to
cheques and other traditional methods (Are Digital Wallets the Future of
Payments, 2019).
Likewise, the adoption of contactless payment transactions in
Malaysia has seen a notable surge, especially following the emergence of
COVID-19 and the subsequent Movement Control Order. Initially, in
2019, only 8% of the population utilized e-wallets as a payment method
(Tan, 2019). However, according to the CEO of Boost, just one and a half
months after the implementation of the Movement Control Order
(MCO), the user base increased by almost half a million new users
(Birruntha, 2020). Furthermore, the user base of Touch ’n Go eWallet
surged tenfold throughout 2020 (Yunus, 2020). According to the
* Corresponding author.
E-mail address: shtan@mmu.edu.my (S.-H. Tan).
https://doi.org/10.1016/j.jjimei.2024.100254
Received 5 August 2023; Received in revised form 18 May 2024; Accepted 20 May 2024
Available online 29 May 2024
2667-0968/© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).
M.D.S.M. Reza et al.
International Journal of Information Management Data Insights 4 (2024) 100254
notable gap in understanding merchants’ perspectives on continuous
adoption intentions (Dahlberg et al., 2015; Lee et al., 2019; Moghavvemi
et al., 2021; Yeh, 2020).
Furthermore, Yan et al. (2021) underscored that despite the initial
surge in adoption, a pattern of exponential growth followed by a sharp
decline is commonly observed across various technological innovations,
whether they cater to hedonic gratifications or work-related produc­
tivity. Therefore, there is a pressing need for a deeper understanding of
the factors influencing continued usage.
Recent research in the Information Systems (IS) domain has identi­
fied two prominent streams: pre-adoption theories such as the Tech­
nology Acceptance Model (TAM), the Unified Theory of Acceptance and
Use of Technology (UTAUT), and post-acceptance theories exemplified
by models like the Expectation-Confirmation Model (ECM) (Oliver,
1980), post-acceptance model of IS continuance (Bhattacherjee, 2001).
These streams delve into users’ behaviors and outcomes post-adoption,
including satisfaction and continuous usage of IS (Mishra et al., 2023).
Notably, the Post-Acceptance Model of IS Continuance posits that
cognitive beliefs (e.g., perceived usefulness, performance expectancy)
and affect (satisfaction) significantly influence IS continuance (Bhatta­
cherjee, 2001).
Moreover, researchers have augmented post-acceptance models with
new variables such as perceived ease of use, performance expectancy,
and other constructs like trust, enjoyment, and attitude, offering fresh
insights into consumers’ diverse usage behaviors and expectations
across emerging technologies (Ambalov, 2018; Dağhan & Akkoyunlu,
2016; Nguyen et al., 2021). However, identifying the pertinent external
variables remains an ongoing challenge, as noted by Matemba and Li
(2018). To further explore the dynamics of post-adoption behavior in
the context of e-wallet usage among merchants in Malaysia, our study is
guided by the following research questions:
categorized into two primary areas. Dominant theories in the preadoption behavior models include the Technology Acceptance Model
(TAM), hybrid models, and the Unified Theory of Acceptance and Use of
Technology (UTAUT) (Dahlberg et al., 2008). In contrast, the second
category investigates post-adoption behaviors, utilizing theories like
expectation-confirmation theory (ECT, Oliver, 1980), post-acceptance
model of IS continuance (Bhattacherjee, 2001), and technology
continuance theory (TCT, Foroughi et al., 2019; Liao et al., 2009) to
explore outcomes such as satisfaction and ongoing usage of IS.
For pre-adoption literature, the TAM, initially proposed by Davis
(1989), has been extensively utilized in technology acceptance research.
UTAUT, developed by Venkatesh et al. (2003), has demonstrated su­
perior explanatory power, elucidating approximately 70% of the vari­
ance in behavioral intention and 50% in technology use (Dwivedi et al.,
2019). Researchers continue to make conscious efforts to develop,
validate, and extend the existing theories and frameworks to meet the
challenges of the ever-changing technology landscape. Notably, studies
employing the UTAUT model have investigated various aspects of
technology acceptance, mobile learning management system (Alfalah,
2023; Chaudhry et al., 2023), learning management system (Al-Ma­
mary, 2022a, 2022b), digital healthcare technologies (Edo et al., 2023),
mobile shopping (Lu et al., 2017), e-wallet and mobile payment (Dar­
agmeh et al., 2021; Singh, 2020) and more.
Another stream of literature, post-adoption studies, on the other
hand, emphasizes that systematic advances and innovations in tech­
nology have ensured that the long-term success of IS hinges on its
persistent usage rather than one-time use (Bhattacherjee, 2001). Hence,
post-adoption theories and frameworks are equally important as the
pre-adoption theories. The ECM has been applied in a wide range of
studies, including consumer satisfaction, post-purchase behavior, and
service continuance (Bhattacherjee, 2001). According to the ECM, users’
intention to repurchase a product or continue using a service is primarily
driven by their level of satisfaction with that product or service. Oliver
(1980) interpreted satisfaction as “the summary psychological state
resulting when the emotion surrounding disconfirmed expectations is
coupled with the consumers’ prior feelings about the consumption
experience” (Bhattacherjee, 2001). In other words, when consumers
have low expectations and perceive high performance, it leads to a
higher level of confirmation, which positively influences satisfaction
and the intention to continue using the product or service.
In existing pre- and post-adoption studies, most studies investigate
chosen variables aligning with well-established models like UTAUT or
ECM. However, some studies opt for relevant variables from existing
research without adhering to specific theories or models in predicting IS
usage intention, demonstrating the continued relevance and applica­
bility of established theoretical frameworks in contemporary research.
Based on the systematic literature review conducted by Ramli and
Hamzah (2021), some previous studies on e-wallet adoption chose to use
relevant variables from validated existing research to apply in their
study, instead of building on any theories or models when developing
their framework. For example, Singh (2020) did not specify the theories
adopted in their studies. However, it should be noted that most of the
chosen variables are relevant to well-known models or theories, like the
TAM or UTAUT.
These arguments are similar to those noted by Hubona and Geitz
(1997), Abdul Rahman et al. (2023), and Ho et al. (2023) in which they
observed that revising these models with external variables can influ­
ence the proportions of usage frequency and usage amount variances.
Hence, it is crucial to incorporate both individual and external variables
to comprehensively understand user behavior.
In this study, we integrate existing models by adding three con­
structs: network externalities, awareness, and online customer service to
investigate the predictors of e-wallet continued usage from the mer­
chant’s perspective. We selected the three variables for the following
reasons.
Firstly, this study diverges from the norm by adopting the construct
RQ1. What are the key factors influencing merchants’ intentions to
continue adopting e-wallets in Malaysia?
RQ2. How do network externalities, awareness, and online customer
service impact merchants’ perceptions and intentions regarding e-wallet
usage in Malaysia?
This study aims to examine the influence of network externalities,
awareness, and online customer services on the continuous adoption of
e-wallets within the context of Malaysia’s evolving cashless society.
Notably, we prioritize the construct of network externalities, specifically
emphasizing direct network externalities, which denote increased
derived value with the expansion of a product or service’s user base
(Zhao & Lu, 2012), over the traditional construct of social influence. In
parallel, within the framework of exploring performance expectancy
(PE) and effort expectancy (EE) within the Unified Theory of Acceptance
and Use of Technology (UTAUT), it is imperative to acknowledge that
they are subject to the influence of external factors, as highlighted by
Hubona and Geitz (1997), Kar (2021), Mishra et al. (2023), and Neves
et al. (2023). This underscores the importance of incorporating external
variables into the model. In light of these gaps, our study aims to address
this challenge by integrating network externalities, awareness, and on­
line customer services into our model. By doing so, we seek to enhance
our understanding of users’ satisfaction and their intention to continue
using e-wallets. Through this investigation, we aspire to contribute to
the development of cashless ecosystems in Malaysia and beyond, thus
influencing the future landscape of digital payments in the region.
2. Literature review
Understanding the factors influencing technology adoption and
continued usage has become imperative for both scholars and practi­
tioners. To address this, researchers have proposed several theoretical
models to elucidate the complexities involved in technology acceptance
and use. Research on the adoption of information systems can be
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International Journal of Information Management Data Insights 4 (2024) 100254
of network externalities in lieu of social influence as delineated in the
Unified Theory of Acceptance and Use of Technology (UTAUT). In
contemporary research, social influence has been pivotal in studies
concerning technology acceptance. The distinction between network
externalities and social influence is grounded in their differing per­
spectives: the former emanates from an economic standpoint, while the
latter is rooted in psychological or sociological frameworks. Social in­
fluence predominantly concerns the immediate impact of users’ net­
works on their decision-making processes, encapsulating how
individuals conform to the expectations of their peers (Kanat et al.,
2020; Wattal et al., 2010). Conversely, network externalities encompass
the broader network effects within a given system. In the context of
two-sided markets such as e-wallet platforms, which involve both con­
sumers and merchants, the efficacy of the system hinges upon engaging
both parties. Previous research has demonstrated the significant influ­
ence of network externalities on user attitudes and satisfaction towards
platform-based mobile payment services (Lee et al., 2019). Despite this,
the specific relationship between network externalities and merchants’
continuous intention to use e-wallets remains unexplored, particularly
in the Malaysian context.
Another pertinent variable introduced in this study is awareness,
which has garnered attention in various domains, including technology
adoption and environmental conservation. Mishra et al. (2014) eluci­
dated its impact on the acceptance of Green Information Technology
among IT professionals, while Cudjoe et al. (2020) highlighted its role in
fostering waste sorting intentions among residents. Within the realm of
e-wallet adoption, Singh and Sinha (2020) underscored the importance
of awareness in influencing perceived usefulness. However, their ex­
amination primarily focused on consumers, leaving a gap in under­
standing its implications for merchants’ adoption intentions. Thus,
investigating the influence of awareness on merchants’ adoption in­
tentions is crucial for comprehensively assessing the dynamics of
e-wallet acceptance.
Lastly, the inclusion of online customer service as a variable stem
from its established significance in determining user satisfaction across
various contexts. Deyalage and Kulathunga (2019) and Zeng et al.
(2009) have underscored its impact on overall satisfaction levels, while
Boateng et al. (2016) examined its role in internet banking adoption.
Online customer service, as an extension of traditional customer sup­
port, plays a pivotal role in assuring users of assistance in virtual set­
tings. Despite its recognized importance, its specific impact on
merchants’ satisfaction with e-wallets remains underexplored, particu­
larly in the Malaysian context. Therefore, integrating the concept of
online customer service into the study framework will enable a
comprehensive evaluation of its influence on merchants’ satisfaction
and effort expectancy in utilizing e-wallets.
et al., 2021). As long as a technology or service has the potential to
enhance users’ life or work, their positive perception of it persists,
fostering their desire to continue its use (Gu et al., 2019). Similarly,
within the context of e-wallet, users’ favorable perceptions on the use­
fulness significantly influence the users’ intention to maintain usage.
Regarding continuous intention, it is worth noting that performance
expectancy also exerts a positive influence on users’ satisfaction (Akdim
et al., 2022; Alalwan, 2020; Daragmeh et al., 2021; Gu et al., 2019; Lu
et al., 2023; Si et al., 2022). This suggests that when users perceive the
technology’s benefits and advantages aligning with their initial expec­
tations, they tend to experience higher level of satisfaction. Therefore,
the formulated hypotheses are as below:
H1.
Performance expectancy positively influences satisfaction
H2. Performance
intention
expectancy
positively
influences
continuous
Effort expectancy is also a key variable within the Unified Theory of
Acceptance and Use of Technology (UTAUT) model. In this study, effort
expectancy is defined as the extent to which merchants perceive the ease
of utilizing the e-wallet (Venkatesh et al., 2003). In continuous intention
study, effort expectancy has been found to positively influence the
continuous intention of e-government (Razak et al., 2017) and elec­
tronic health records (Alsyouf & Ishak, 2018). Particularly noteworthy is
its prominent role in predicting e-government continuous intention.
Effort expectancy also plays a significant role for users who engage in
extensive face-to-face interactions or activities. For instance, nurses,
who dedicate substantial time to patient care and treatment, find ease of
use crucial (Alsyouf & Ishak, 2018). A technology or system that is that
is user-friendly not only saves their time but also bolsters their intent to
continue using it. Perceived ease of use, akin to effort expectancy in
definition, has also been shown to positively impact satisfaction and
repurchase intention (Wilson et al., 2021). The perception and judge­
ment of customers regarding the difficult level of adopting a new system
or technology significantly affect both satisfaction and the intention to
use it continuously. Notably, effect expectancy has also exhibited sub­
stantial influence on users’ satisfaction with platforms such as computer
(Wilson et al., 2021) and social mobile apps (Akdim et al., 2022). In light
of these considerations, the formulated hypotheses are as below:
H3.
Effort expectancy positively influences satisfaction
H4.
Effort expectancy positively influences continuous intention
Similarly, facilitating conditions is also a key construct in the Unified
Theory of Acceptance and Use of Technology (UTAUT) model. In this
study, it is construed as the extent to which merchants believe there is
organisational and technical infrastructure available to support e-wallet
usage (Venkatesh et al., 2003). Notably, factors such as inadequate
promotion and engagement from service providers and regulatory body
(BNM), lack of sufficient support and training from the service pro­
viders, and infrastructure and technological issues have been identified
as barriers hindering mobile payment adoption among merchants in
Malaysia (Moghavvemi et al., 2021). Facilitating conditions have been
associated with positive outcomes in various contexts. For instance, it
has been observed to foster the continuous intention of electronic health
records (Alsyouf & Ishak, 2018). The assertion that when users of a
particular system or technology perceive better than anticipated access
to resources and assistance, their favorable perception of facilitating
conditions intensifies. Consequently, this enhanced perception propels
their intention to continue in using the system or technology (Alsyouf &
Ishak, 2018). Therefore, the hypothesis formulated is as follows:
3. Hypothesis development
In this section, the hypotheses for the full model are developed to
illustrate the directional relationships between constructs.
The variable “performance expectancy” is a pivotal element within
the Unified Theory of Acceptance and Use of Technology (UTAUT)
model. In this study, it is defined as the extent to which merchants
perceive that using the e-wallet will enhance their job performance
(Venkatesh et al., 2003). In the past, this construct has consistently been
recognized as important in determining usage intention (Matemba & Li,
2018; Singh & Sinha, 2020; Singh et al., 2020). From the merchants’
standpoint, the technology’s usefulness is often cited as a fundamental
factor driving its adoption (Singh & Sinha, 2020). Furthermore, the
construct “performance expectancy” has demonstrated its importance in
predicting the intention to continue using various technologies,
including mobile shopping (Lu et al., 2017), electronic health records
(Alsyouf & Ishak, 2018), smart home services (Gu et al., 2019), mobile
food ordering apps (Alalwan, 2020), social mobile apps (Akdim et al.,
2022), and even consumers’ e-wallet continuance intention (Daragmeh
H5.
Facilitating conditions positively influences continuous intention
This study defines awareness as the degree of knowledge and un­
derstanding retailers possess regarding the benefits, utility and limita­
tions of the e-wallet (Singh & Sinha, 2020). Notably, this construct has
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International Journal of Information Management Data Insights 4 (2024) 100254
externalities, a notable principle merges: the higher the demand or
usage on one side of the market, the higher the corresponding demand or
usage on the opposite side. This interdependence illustrates the dynamic
influence of network externalities on both ends of the market.
In addition, network externalities have previously demonstrated
their importance in predicting retailers’ intention to adopt crypto pay­
ment (Jonker, 2019). Furthermore, the construct of network external­
ities has been identified as a significant direct predictor of retailers’
satisfaction and an indirect predictor of continued intention to use
platform-based mobile payment services through the construct of
satisfaction (Lee et al., 2019). Similarly, network externalities have been
found to play a pivotal role not only in driving blog usage, but also in
sustaining continued blog usage (Wattal et al., 2010). Given these in­
sights, the following hypotheses are postulated:
previously been employed by Singh and Sinha (2020) in their research of
merchants’ perception and adoption of the e-wallet. The authors found
that awareness significantly contributes to predicting perceived useful­
ness. It’s been noted that a technology that enjoys widespread recog­
nition and high awareness significantly impacts merchants’ perception
of its usefulness. Furthermore, IT professionals exhibiting a high level of
awareness concerning Green Information Technology (GIT) have been
observed to find the technology easy, essential and advantageous
(Mishra et al., 2014). They also place importance on GIT considerations
when purchasing hardware and software. In a related context, a study
focusing on waste sorting intention found that this construct played a
significant role in predicting residents’ intention to sort waste (Cudjoe
et al., 2020). They revealed that most of their respondents were aware of
the benefits of waste sorting. The e-wallet, ass a technology advance­
ment, offers users numerous advantages. From the perspective of mer­
chants, these advantages encompass improved payment processing
time, enhanced convenience and the ability to attract customers (Mog­
havvemi et al., 2021). As supported by previous studies, heightened
awareness among merchants about the advantages, utility and limita­
tions of the e-wallet is likely to foster a perception of its significant
advantages. Hence, the hypothesis posited is as follows:
H6.
H9.
H10. Network externalities positively influence continuous intention
Satisfaction is a construct from Expectation Confirmation Theory
(ECT), which is usually employed in the context of post-purchase
behavior and service continuance. It is also associated with Expecta­
tion Confirmation Model (ECM), predominantly used within the realm
of Information Systems (IS) continuance intention (Bhattacherjee,
2001). In this study, satisfaction is defined as the extent to which mer­
chants perceive that the e-wallet meets or exceeds their expectations
(Wilson et al., 2021). Previous research has consistently demonstrated
that satisfaction plays a pivotal role. It has been found to positively
correlate with customers repurchase intention in online shopping (Rita
et al., 2019) and e-commerce (Daragmeh et al., 2021). Scholars from
both studies emphasize that a satisfied customer is more likely to engage
in repeated transactions with the seller. Furthermore, satisfaction has
also been seen to positively influence the continuous usage intention of
e-learning (Roca et al., 2006), micro-blogging services (Zhao & Lu,
2012), smart home services (Gu et al., 2019), mobile food ordering apps
(Alalwan, 2020), Chinese mobile games (Lei & Lee, 2020), e-wallet
commerce (Daragmeh et al., 2021), social mobile apps (Akdim et al.,
2022) and mobile health applications (Lu et al., 2023). It is widely un­
derstood that early adopters of new technology tend to evaluate and
compare their expected outcomes with the actual outcomes. Conse­
quently, the intention to continue using the technology is significantly
impacted by the level of satisfaction they experience (Alalwan, 2020).
Therefore, the hypothesis proposed is as follows:
Awareness positively influences performance expectancy
In this study, the construct “online customer service” is defined as the
extent to which merchants perceive the availability of online support
provided by e-wallet providers prior to or during their utilization of the
e-wallet (Rahi et al., 2019). Previous research has indicated that
customer service plays a substantial role in predicting customer satis­
faction with online services (Zeng et al., 2009). The author emphasized
that in an internet-based market, accurate services and prompt delivery
are elements that customers come to expect. Continuing on this trajec­
tory, customer service has also demonstrated a positive influence on
online customer satisfaction within the context of online shopping
(Deyalage & Kulathunga, 2019). A lack in customer support and delayed
responses have been identified as factors leading to customer dissatis­
faction. Moreover, customer service has been found to be a significant
predictor of effort expectancy in the domain of internet banking (Rahi
et al., 2019). Boateng et al. (2016) previously utilised the construct of
customer service in their exploration of internet banking adoption
intention. In their study, online customer service was regarded as an
extension of traditional customer service. While latter pertains to
brick-and-mortar stores and involves assistance at a physical help desk
or call center, online customer service is geared towards services
rendered in virtual, online settings (Boateng et al., 2016). Their findings
revealed that customers perceive online customer service as enabling
banks to provide assistance in the event of encountering problems (Rahi
et al., 2019). This underscores the significance of customer service as a
predictor of users’ satisfaction and effort expectancy. In addition, it is
important to note that the impact of customer service extends beyond
traditional brick-and-mortar stores and holds relevance in virtual or
online contexts. In light of these insights, the hypotheses developed are
as follows:
H7.
Online customer service positively influences effort expectancy
H8.
Online customer service positively influences satisfaction
Network externalities positively influences satisfaction
H11. Satisfaction positively influences continuous intention
Taking all these discussions together, the current study conceptual
framework was developed as presented in Fig. 1.
4. Research design and method
4.1. Sampling method
This study utilised the cluster sampling technique, specifically the
double cluster sampling. Compared to the other probability sampling
methods, it is not essential to have a sampling frame from the entire
sampling unit when utilizing cluster sampling (Sharma, 2017). It is a
feasible method to use when the population is too large. This is a major
reason why the cluster sampling is deemed to be suitable for this study.
The population of merchants registered with an e-wallet service pro­
vider is too large to be obtained. For example, Touch ’n Go eWallet was
said to have over 250,00 merchants registered under them, while Boost
has over 205,000 merchants nationwide (Yunus, 2020). The first step in
conducting cluster sampling is separating the population into clusters,
and then arbitrarily choosing the cluster to be used. Another step is
added for double cluster sampling which is randomly selecting the
members within the selecting clusters. As the topic of this study is on the
continuous intention of e-wallet usage among merchants, the sampling
This study defines network externalities as the extent to which
merchants perceive that the utility they derive from the e-wallet will
increase as more people utilize the same e-wallet (Zhao & Lu, 2012).
These network externalities hold significant relevance in a two-sided
market, a context where there exist two distinct demand sides
(Jonker, 2019). This characteristic aptly applies to the e-wallet scenario,
where service providers must promote the technology to both consumers
and merchants. The reason behind this necessity lies in the fact that
transactions can only transpire effectively when both sides actively
engage with the system. In accordance with the concept of network
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M.D.S.M. Reza et al.
International Journal of Information Management Data Insights 4 (2024) 100254
Fig. 1. Research model.
frame were acquired from the list of merchants within the Klang Valley
area that are registered under three of the most well-known e-wallet in
Malaysia, which are Touch ’n Go eWallet, Boost and GrabPay (Mog­
havvemi et al., 2021). Klang Valley was chosen due to the number of
populations. According to the World Population Review, Klang Valley
has a population of 7,996,830 in 2020. Not only that, Klang Valley was
also said to be the most populous city in Malaysia, being the only
Malaysian city that contains a population of above 1 million.
brought on by financial incentives and to encourage objective responses,
participants were not compensated for their contributions. To ensure
participant privacy and confidentiality, ethical issues were given top
priority throughout the study. This study utilized G*Power 3.1 for power
analysis to determine the required sample size, as recommended by Hair
et al. (2019). The analysis suggested a minimum sample size of 138.
Despite sending over 3000 emails to the merchants, only 152 responded.
After filtering, 146 responses were retained. While the response rate was
low, it surpassed the minimum sample size needed for this study. Due to
time constraints, we proceeded with the analysis, considering the
collected data sufficient for our objectives. The process of compiling
lists, obtaining email addresses, and sending out requests to merchants
took approximately six months, from January to June of 2022.
4.2. Data collection method
The primary data for this research were collected through surveys.
Initially, lists of merchants registered under major e-wallet service
providers in Malaysia, namely Touch ‘n Go eWallet, Boost, and GrabPay,
were compiled into an Excel sheet and randomized. Subsequently, the
prepared survey was emailed to the merchants following the random­
ized sequence. All participants gave their informed consent, confirming
that they were taking part voluntarily and that they had the freedom to
stop the study at any moment. In order to avoid any potential biases
4.3. Instrument development
There are two parts to the questionnaire. Part A includes the back­
ground information for the respondents, while part B contains questions
about the theoretical framework’s proposed constructs. A cover page
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International Journal of Information Management Data Insights 4 (2024) 100254
was included to clearly specify the criteria for the target respondents on
the front of the questionnaire. All items in the survey questions are
adapted and validated in earlier work of literature, and the details are as
shown in the Table 1. The background information used nominal scale
while the constructs used 5-point Likert scales. The five-point Likert
scale ranges from strongly disagree (1) to strongly agree (5).
Table 1
Constructs and items.
Construct
Item
Item Description
Source
Performance
Expectancy
PE1
I find e-wallet to be useful
for my business
I find that using the system
has improved the speed of
transactions between me
and my customers
I find that using the e-wallet
has improved the
productivity of my business
I find that using the e-wallet
increases my chance of
completing important tasks
I find the process of learning
how to use the e-wallet to be
easy
I find that it is easy to
become skilful at using the ewallet
I find the e-wallet to be easy
to use
I find the method to use the
e-wallet to be clear and
understandable
I have the resources
necessary to use the system
I have the knowledge
necessary to use the system
E-wallet is compatible for
my business
I can get help from others
when I have difficulties
using the e-wallet
I am aware on how to use the
e-wallet effectively
I am aware of the limitations
of the e-wallet
I am aware of the current
status of e-wallet usage
among merchants
I think my customers are
aware that e-wallet can be
utilize for transactions at my
store
I will like staffs to be
available to assist me online
when I encounter problems
while using the e-wallet
I will like to have easy access
to staffs online when I
encounter problems while
using the e-wallet
I believe that it is easy to
receive help online when I
encounter problems while
using the e-wallet
I instantly receive online
replies in regards to any
problems that I encounter
I will like online customer
service when using the ewallet
From my observation, the
number of e-wallet users are
large
I find that many of my
friends and family members
are using the e-wallet
I find that many of my
competitors are using the ewallet
I find that many of my
customers are using the ewallet
Venkatesh et al.
(2003), Alalwan
(2020), Lu et al. (2017)
PE2
4.4. Analysis technique
PE3
This section explains the stages of analysis implemented in this
paper. The data were analyzed using SmartPLS, which is a tool used for
statistical analysis, namely PLS-SEM. SmartPLS is a variance-based
model that consists of measurement and structural models (Hair et al.,
2017). The measurement model describes the variables and their in­
dicators, while the structural model elucidates the relationship between
the exogenous and endogenous constructs. There are multiple advan­
tages to using this technique. It requires only a small sample size and
does not require the fulfillment of distributional assumptions (Hair
et al., 2019). Compared to other methods, PLS is also said to provide
more accurate results if the sample size is less than 250. The sample size
for this study is 146, and the result of the normality test showed that the
assumption of normal distribution is not met. This serves as the moti­
vation to use this technique.
PE4
Effort
Expectancy
EE1
EE2
EE3
EE4
Facilitating
Condition
5. Results
FC1
FC2
FC3
5.1. Respondents’ demographic
FC4
This section will discuss the demographic profile of the respondents,
as well as the e-wallet utilised by the respondents for their business.
Table 2 shows the respondents’ demographic profile.
As seen from Table 2, 53.4% of the respondents were male, while
46.6% of the respondents were female. There were only slightly more
male respondents than female respondents. Most response was received
from respondents between the age of 26–35 years, which is at 45.2%,
followed by 36–25 years, at 33.6%, and 46–55 years at 13.7%. The
lowest are those aged less than 25 and above 55, at 4.1% and 3.4%
respectively. In continuation, a large proportion of the respondents were
Chinese and Malay, making up 47.3% and 41.8% of the overall response
respectively. Only 4.8% were Indians, while 6.2% were from different
ethnicities than the ones mentioned. 61% of the respondents are from
the food and beverage industry, and followed by 11% from the service
industry. These two industries make up a large proportion of the re­
spondents. As for the number of employees, 45.2% has 1–4 employees,
while 44.5% has 5–29 employees. In continuation, 42.5% of the re­
spondents have turnover below RM 300,000, 38.4% have turnover be­
tween RM300,000 to less than RM1 million and 11.6% have turnover
between RM1 million to less than RM3 million.
According to SME Corp Malaysia, service and food and beverage
industry with less than 5 full time employees or with turnover less than
RM 300,000 are considered to be micro enterprises. Meanwhile, service
and food and beverage industry with 5 to less than 30 employees or
turnover between RM300,000 to less than RM3 million are considered to
be small enterprises. Thus, it can be said that the respondents of this
study are mainly micro and small enterprises.
Awareness
AW1
AW2
AW3
AW4
Online
Customer
Service
OCS1
OCS2
OCS3
OCS4
OCS5
Network
Externalities
NE1
NE2
5.2. Measurement model analysis
This study performs a variety of tests to validate the measurement
model for the constructs examined. The first step was to analyze the
indicator reliability, as well as internal consistency. An indicator is
considered to have high absolute contribution if the outer loading is
above 0.70, while a construct with composite reliability (CR) above 0.6
is deemed to have acceptable internal reliability, and above 0.70 is
deemed to have good internal reliability (Hair et al., 2019).
Table 3 shows the result for indicator loading, composite reliability
NE3
NE4
Venkatesh et al.
(2003), Alalwan
(2020)
Venkatesh et al.
(2003), Alalwan
(2020)
Singh and Sinha (2020)
Boateng et al. (2016),
Deyalage and
Kulathunga (2019),
Rahi et al. (2019)
Kim et al. (2017), Luo
et al. (2021), Zhao and
Lu (2012)
(continued on next page)
6
M.D.S.M. Reza et al.
International Journal of Information Management Data Insights 4 (2024) 100254
HTMT values between all the constructs used in this study. All of the
HTMT values are below 0.9. This means that the discriminant validity
has been met.
Table 1 (continued )
Construct
Item
Item Description
Source
Satisfaction
SF1
I am generally pleased with
the e-wallet
I am very satisfied with the
e-wallet
I am happy with the e-wallet
I find that choosing the ewallet for my business
transaction was a good
choice
I intend to continue using
the e-wallet for my business
in the future
I intend to encourage my
customers to use the e-wallet
for transactions more
frequently in the future
I intend to take advantage of
the e-wallet for my business
activities
I predict that I would
continue using the e-wallet
for my business in the future
Alalwan (2020), Kim
et al. (2017)
SF2
SF3
SF4
Continuous
Intention
CI1
CI2
CI3
CI4
5.3. Structural model analysis
The findings of the structural model are presented in Table 5. The
structural model used a 5000-sample re-sample bootstrapping proced­
ure. As reported in Table 5, one can conclude that the relationship be­
tween performance expectancy and satisfaction (H1) (t-stats=2.751, p <
0.05), effort expectancy and continuous intention (H4) (t-stats=2.809, p
< 0.05), facilitating condition and continuous intention (H5) (tstats=3.782, p < 0.05), awareness and performance expectancy (H6) (tstats=10.050, p < 0.05), online customer service and effort expectancy
(H7) (t-stats=4.354, p < 0.05), network externalities and continuous
intention (H10) (t-stats=1.899, p < 0.05) and satisfaction and contin­
uous intention (H11) (t-stats=9.182, p < 0.05) are significant. In addi­
tion, all the lower and upper limit for confidence the interval of the
mentioned hypotheses is not 0, which confirms the findings. Meanwhile,
the relationship between performance expectancy and continuous
intention (H2) (t-stats=0.306, p > 0.05), effort expectancy and satis­
faction (H3) (t-stats=1.621, p > 0.05), online customer service and
satisfaction (H8) (t-stats=1.156, p > 0.05) and network externalities and
satisfaction (H9) (t-stats=0.941, p > 0.05) are not supported.
In continuation, by looking at the path coefficients it can be seen that
out of all the significant relationships, the effect of awareness on per­
formance expectancy is the highest (0.663). Furthermore, satisfaction
has the largest effect on continuous intention (0.616), followed by effort
expectancy (0.214). Although network externalities have a significant
relationship with continuous intention, the effect is not as strong as the
other two variables (0.118). Additionally, facilitating condition was
seen to have a stronger effect on satisfaction (0.346) compared to per­
formance expectancy (0.255). Lastly, online customer service has quite a
strong positive effect on effort expectancy (0.462).
Table 6 shows the level of R2 and Q2. R2 is a statistical measure that
indicates the proportion of the variance for a dependent variable that is
explained by an independent variable or multiple independent variables
in a regression model. Hence, it is interpreted as 44.0% of the variability
of performance expectancy is explained by the variability of variable
awareness. This shows weak R2 since the value is between 0.25 and 0.5.
Next, 63.2% of the variability of satisfaction is explained by the vari­
ability of variables effort expectancy, performance expectancy, facili­
tating condition, online customer service and network externalities.
Alalwan (2020),
Venkatesh et al. (2012)
(CR) and average variance extracted (AVE). From the table, all in­
dicators have a loading value above 0.70. This means that all of the
indicators are showing high absolute contributions. In continuation, all
the constructs were found to have composite reliability (CR) above 0.7.
CR above 0.7 means that the construct has good internal reliability. All
of the constructs used are explained well by their respective indicators.
The last column of Table 3 shows the average variance extracted
(AVE) of the variables used. AVE is used to analyze the convergent
validity. All of the variables can be seen to have an AVE above 0.5. An
AVE of above 0.5 means that the level of variance captured by the
constructs is higher than half of the variance of its’ indicators (Hair
et al., 2014). Furthermore, performance expectancy, effort expectancy,
facilitating conditions, awareness, network externalities, satisfaction
and continuous intention have an AVE of above 0.7, which is considered
to be high.
The last step was to test the discriminant validity. Discriminant
validity is used to ensure that the variables in the model are not
redundant from each other. This can be done by looking at the HTMT
value. The threshold value for HTMT is 0.90 (Franke & Sarstedt, 2019).
Discriminant validity is considered to be met when the HTMT value of
the construct is below the stated threshold value. Table 4 shows the
Table 2
Respondents’ demographic profile.
Profile
Gender
Male
Female
Age
<=25
26–35
36–45
46–55
>55
Ethnicity
Malay
Chinese
India
Others
No. of employees
1–4
5–29
30–75
75–199
200 and above
Other
Frequency (n = 146)
Percentage (100%)
78
68
53.4
46.6
6
66
49
20
5
4.1
45.2
33.6
13.7
3.4
61
69
7
9
41.8
47.3
4.8
6.2
66
65
8
3
3
10
45.2
44.5
5.5
2.1
2.1
6.8
Profile
Industry
Service
Food and beverage
Home living
IT, digital and lifestyle
Household goods and groceries
Health, beauty and fitness
Pharmacy
Convenience store
Education
Entertainment and leisure
Eyewear
Fashion
Other
Turnover
<RM 300,000
RM 300,000 < RM 1 million
RM 1 million < RM 3 million
RM 3 million < RM 15 million
> RM 15 million
7
Frequency (n = 146)
Percentage (100%)
16
89
3
2
4
9
2
1
2
4
1
3
10
11.0
61.0
2.1
1.4
2.7
6.2
1.4
0.7
1.4
2.7
0.7
2.1
6.8
62
56
17
8
3
42.5
38.4
11.6
5.5
2.1
M.D.S.M. Reza et al.
International Journal of Information Management Data Insights 4 (2024) 100254
These results are between 0.50 and 0.75, which shows that it is mod­
erate. The only result that showed high level of R2 is continuous inten­
tion with 77.2% of its’ variability being explained by the variability of
variables effort expectancy, performance expectancy, network exter­
nalities, and satisfaction. Meanwhile, only 21.3% of the variability of
effort expectancy is explained by the variability of variable online
customer service. Next. Q2 measures whether the model has a predictive
relevance or not. A value above 0 means that the model has predictive
relevance. Table 6 shows the Q2 for constructs performance expectancy
(PE), effort expectancy (EE), satisfaction (SF) and continuous intention
(CI). All the constructs have Q2 above 0 which means that there exists
predictive relevancy for all the constructs.
Table 3
Measurement model.
Construct
Item
Loading
Composite
Reliability (CR)
Average variance
extracted (AVE)
Performance
Expectancy
PE1
0.870
0.942
0.803
PE2
PE3
PE4
EE1
EE2
EE3
EE4
FC1
0.904
0.930
0.878
0.927
0.930
0.951
0.957
0.923
0.969
0.886
FC2
FC3
FC4
AW1
AW2
AW3
AW4
OCS1
0.909
0.904
0.847
0.864
0.850
0.837
0.851
0.870
OCS2
OCS3
OCS4
OCS5
NE1
0.884
0.800
0.741
0.847
0.865
NE2
NE3
NE4
SF1
SF2
SF3
SF4
CI1
CI2
0.940
0.925
0.948
0.955
0.963
0.955
0.923
0.931
0.940
CI3
CI4
0.944
0.958
Effort Expectancy
Facilitating
Condition
Awareness
Online Customer
Service
Network
Externalities
Satisfaction
Continuous
Intention
0.942
6. Findings and discussions
0.803
0.913
0.723
0.917
0.689
0.957
0.947
0.973
0.901
0.970
0.889
It was found that H1, H4, H5, H6, H7, H10, and H11 are supported,
while H2, H3, H8 and H9 are not supported. External variables, namely
awareness and online customer service, exerted positive influences on
performance expectancy and effort expectancy, respectively. In a related
vein, performance expectancy and facilitating condition were found to
positively impact satisfaction, while effort expectancy, network exter­
nalities and satisfaction were found to positively influence continuous
intention.
6.1. Performance expectancy
The finding concerning performance expectancy and satisfaction
mirror the findings of a study conducted by Alalwan (2020). Alalwan
(2020) arrived at a parallel conclusion, discovering that performance
expectancy significantly influences customers satisfaction in the context
of mobile food ordering apps. This is attributed to the enhanced flexi­
bility that mobile food ordering apps provide compared to conventional
methods. This rationale can be applied to the e-wallet. The e-wallet, in
its capacity, provides merchants heightened security and expedited
transactions when compared to traditional payment methods. Moreover,
with the advent of the COVID-19 pandemic, the significance of con­
tactless payment has been amplified. This elevation in importance ren­
ders the e-wallet a particularly favorable payment alternative for
merchants. By embracing the e-wallet, merchants can substantially
reduce physical interactions with customers, thereby promoting both
safety and health. The analytical findings underscore the observation
that merchants who have personally utilized the e-wallet and directly
Table 4
Discriminant validity.
PE
EE
FC
AW
OCS
NE
SF
CI
PE
EE
FC
AW
OCS
0.748
0.758
0.729
0.534
0.659
0.734
0.712
0.796
0.737
0.496
0.682
0.717
0.763
0.768
0.504
0.709
0.779
0.728
0.499
0.649
0.728
0.760
0.573
0.517
0.538
NE
SF
CI
Table 6
Level of R2 and cross validated redundancy (Q2).
0.635
0.675
0.882
PE= performance expectancy, EE = effort expectancy, FC = facilitating condi­
tions, AW = awareness, OCS = online customer service, NE = network exter­
nalities, SF = satisfaction, CI = continuous intention.
Construct
R2
Q2
Continuous Intention
Satisfaction
Performance Expectancy
Effort Expectancy
0.772
0.632
0.440
0.213
0.670
0.548
0.323
0.185
Table 5
Hypothesis testing.
Hypothesis
Relationship
Std.Beta
Std.Dev
T-Value
P-Value
BCI LL
BCI UL
Decision
H1
H2
H3
H4
H5
H6
H7
H8
H9
H10
H11
PE → SF
PE → CI
EE → SF
EE → CI
FC → CI
AW → PE
OCS → EE
OCS → SF
NE → SF
NE → CI
SF → CI
0.255
0.021
0.167
0.214
0.346
0.663
0.462
0.085
0.070
0.118
0.616
0.092
0.069
0.105
0.077
0.094
0.066
0.106
0.071
0.075
0.062
0.067
2.751
0.306
1.621
2.809
3.782
10.050
4.354
1.156
0.941
1.899
9.182
0.003
0.380
0.053
0.002
0.000
0.000
0.000
0.128
0.173
0.029
0.000
0.111
− 0.094
− 0.006
0.096
0.187
0.542
0.267
− 0.023
− 0.054
0.023
0.505
0.408
0.132
0.339
0.349
0.489
0.758
0.617
0.214
0.195
0.226
0.726
Supported
Not Supported
Not Supported
Supported
Supported
Supported
Supported
Not Supported
Not Supported
Supported
Supported
8
M.D.S.M. Reza et al.
International Journal of Information Management Data Insights 4 (2024) 100254
experienced its advantages exhibit a notably high level of satisfaction
with the technology. Furthermore, consumers have begun prioritizing
cashless and online transactions, instigated by the COVID-19 pandemic.
As a response, more merchants are opting to integrate the e-wallet into
their payment methods. This strategic shift is largely driven by uncer­
tainty surrounding whether pandemic-induced shifts in consumer
behavior are temporary or indicative of more lasting change (Gomes,
2020).
On the other hand, performance expectancy was found to be insig­
nificant in predicting continuous intention. During their study of uni­
versity students’ behavioural intention to use e-learning during the
COVID-19 pandemic, Mailizar et al. (2021) found perceived usefulness
to be insignificant in predicting behavioural intention towards
e-learning use. A reason for this was said to be due to resistance towards
new technology not being as important as it previously was. In addition
to that, their study was also conducted during COVID-19 pandemic
where remote learning is utilised. Due to this, the perceived usefulness
may become less important in contributing to their decision on tech­
nology usage. Similarly, the COVID-19 pandemic has affected the
e-wallet usage in Malaysia (Ojo et al., 2022). Consumers were said to
start prioritizing cashless, as well as online transactions. Because of this,
more merchants have started to adopt the e-wallet as a payment method
as they were not sure if the pandemic-associated consumer behavior is
episodic, or more permanent in nature (Gomes, 2020). Although the
Movement Control Order (MCO) has been eased, Malaysians are still
encouraged to practise the “new normal”, which includes contactless
payment. This could be the reason why the performance expectancy is
not seen as a crucial factor in merchants’ continuous intention of the
e-wallet.
6.3. Facilitating condition
The positive impact of facilitating condition on continuous intention
aligns with findings from other studies (Alsyouf & Ishak, 2018). For the
utilization of the e-wallet, the primary resource that merchants require
is a bank account. With just a bank account, merchants can easily reg­
ister their business with any e-wallet service provider, acquiring a QR
code in the process. Customers can then simply scan this QR code for
payments, streamlining the process for both customers and merchants.
Notably, the e-wallet is subject to transaction limits, both per transaction
and on a monthly basis. Consequently, its suitability varies among
businesses, as not all align with these limits. The majority of respondents
in this study are drawn from the food and beverages industry, where
transaction amounts typically fall within the e-wallet’s per transaction
limit. This congruence renders the e-wallet compatible for a significant
portion of respondents. The user-friendly conditions for e-wallet usage
contribute to merchants’ favorable perception of facilitating conditions.
This, in turn, contributes to a satisfactory experience with the e-wallet.
6.4. Awareness
Awareness was found to have a positive significant impact on per­
formance expectancy. This can be interpreted as a higher level of
awareness on the e-wallet can increase the merchants’ perception on the
usefulness of the e-wallet. This is confirmed by Singh and Sinha (2020)
who found awareness to be an important predictor of perceived use­
fulness. When merchants are educated on multiple different aspects of
the e-wallet, they are more prone to perceive the e-wallet as being
useful. This is because the e-wallet has a lot of advantages. Firstly, the
e-wallet provides merchants with better security due to physical money
not being involved in the transactions. This can result in the reduction of
theft. In addition to that, the e-wallet also provides a more convenient
and faster transaction (Shaw, 2014). The reason is because handphones
are usually readily held at hand, compared to physical money that are
kept in wallets, pockets or handbags. Some other benefits of the e-wallet
are the low processing costs, reward system, customer data control, and
operability (Singh & Sinha, 2020). Merchants that have high ‘awareness’
are merchants that have knowledge on these aspects of e-wallet. This is
why a higher level of awareness results in a higher perception of e-wallet
usefulness.
6.2. Effort expectancy
Furthermore, the study revealed that effort expectancy exhibited
insignificance in predicting satisfaction. Although numerous studies
have emphasized the significance of effort expectancy, or perceived ease
of use, as a pivotal predictor of satisfaction (Wilson et al., 2021a,
2021b), there are instances where findings mirror those of the present
study. Alalwan (2020), for instance, discovered effort expectancy to be
inconsequential in predicting users’ satisfaction with mobile food
ordering apps. A plausible explanation provided was that customers
might overlook the complexity associated with these apps in favor of
reaping their benefits. The functional advantages offered by a technol­
ogy are often deemed sufficient in forecasting user satisfaction (Ven­
katesh et al., 2012). It can thus be inferred that merchants’ satisfaction is
substantially swayed by how the e-wallet’s benefits augment their work
performance, rather than solely focusing on system intricacies. In
contrast, the study identified a positive influence of effort expectancy on
continuous intention Lu et al. (2017) emphasized the paramount
importance of effort expectancy as a predictor of mobile shopping’s
continuous intention. The notion of perceived ease of use, analogous to
effort expectancy, frequently figures in the exploration of e-commerce
(Yan et al., 2021). This is largely due to tasks that could be accomplished
through alternative, more straightforward methods compared to tradi­
tional approaches. In addition to that, Alsyouf and Ishak (2018)
underscored the affirmative impact of effort expectancy on the contin­
uous intention to use electronic health records. This is particularly
relevant in healthcare contexts where professionals, like nurses, exten­
sively interact with patients. These professionals might resist using
systems that consume excessive time. Correspondingly, merchants
invest significant time interacting with customers. If they perceive the
e-wallet as cumbersome to use, demanding more time than traditional
methods, their inclination to continue using it in the future may
diminish.
6.5. Online customer service
The extended construct, online customer service, was found to have
no significant influence on predicting satisfaction. This outcome sug­
gests that the quality of online customer service does not notably impact
merchants’ satisfaction levels with the e-wallet. In a study by Rita et al.
(2019), customer service was identified to play a pivotal role in pre­
dicting service quality, which in turn influenced customer satisfaction in
the context of online shopping. There have also been studies indicating a
direct positive connection between customer service and customer
satisfaction (Deyalage & Kulathunga, 2019; Zeng et al., 2009). All of the
results mentioned contradicts the result of this study. One potential
explanation for this discrepancy could be attributed to the ease of using
the e-wallet. Online customer service is typically employed to offer
assistance to users encountering issues with the system. If merchants are
adept at technology and perceive the e-wallet to be user-friendly, they
might not consider customer service as essential. This suggests that not
all merchants necessitate online customer service. This observation
aligns with a statement by Wolfinbarger and Gilly (2003) asserting that
customer service is not universally required by all customers. Conse­
quently, the presence or quality of online customer service may not
significantly influence their satisfaction with the e-wallet. Nevertheless,
the construct of online customer service does exert an indirect impact on
satisfaction through the construct of effort expectancy.
9
M.D.S.M. Reza et al.
International Journal of Information Management Data Insights 4 (2024) 100254
6.6. Network externalities
of e-wallets in the future, it becomes imperative for service providers to
develop a system that effectively meets the needs and expectations of
merchants.
Furthermore, network externalities were also found to be insignifi­
cant in predicting satisfaction. This suggests that the level of satisfaction
among merchants regarding the e-wallet is not influenced by the number
of users. Interestingly, the relationship between network externalities
and satisfaction has yielded conflicting outcomes. For instance, Lee et al.
(2019) established network externalities as a significant predictor of
retailers’ satisfaction with platform-based mobile payment services. In
contrast, a parallel outcome to the present study was reported by Li et al.
(2015), where network externalities were found to lack significance in
predicting satisfaction within business-to-business (B2B) platforms. This
distinction could potentially arise from the fact that B2B platform users,
being predominantly enterprises, tend to exhibit greater rationality,
emphasizing utility over user count. Furthermore, an analogous situa­
tion emerges in the study by Lei and Lee (2020), who found the
perceived number of peers to be insignificant in predicting mobile
gamers’ satisfaction. However, the perceived number of peers in this
context aligns with the construct of network externalities, revealing
divergent results. Similarly, a study investigating the satisfaction of
mobile instant messaging observed that network externalities did not
directly influence user satisfaction, but rather operated through medi­
ating variables like network quality and network intimacy (Kim et al.,
2017). As elucidated by Li et al. (2015), the insignificance observed in
this study might be attributed to merchants placing a higher priority on
the utility of the e-wallet rather than the sheer number of users.
Although not statistically significant in predicting satisfaction,
network externalities do exert a significant positive influence on
continuous intention. This implies that when merchants perceive a
substantial number of e-wallet users, their inclination to persist in using
the e-wallet intensifies. This outcome aligns with findings by Lee et al.
(2019) in where they found that network externalities positively
affected consumers’ intent to continue using platform-based mobile
payment services. Retailers’ continuous intention was also found to be
influenced by network externalities through the construct of satisfac­
tion. The increased adoption of e-wallets among Malaysian merchants
during the COVID-19 pandemic can be attributed to changing consumer
behavior driven by factors such as the Movement Control Order (MCO)
and the need for social distancing. This alteration in behavior resulted in
a surge in cashless transactions and online shopping. Consequently, the
surge in e-wallet adoption appears to be closely linked to the growing
number of consumers embracing the system. This observation could
elucidate why network externalities emerge as a significant predictor of
merchants’ continuous intention. The substantial consumer utilization
of e-wallets potentially fosters a sense of assurance among merchants,
motivating them to persist with the technology - a factor contributing to
their adoption.
6.8. Contributions to theory and literature
Firstly, this study is conducted on the perspectives of merchants
which has been less explored in comparison to the consumers (Dahlberg
et al., 2008; Moghavvemi et al., 2021). Hence, this study is able to
contribute to the gap in existing literature where not much interest and
focus were aimed towards the merchants. In continuation, this study
utilised the Unified Theory and Use of Technology (UTAUT) model, as
well as Expectation Confirmation Model (ECM). Three constructs,
namely performance expectancy, effort expectancy and facilitating
condition are from the UTAUT model, while the construct satisfaction is
from ECM. The construct social influence from UTAUT model is replaced
with network externalities. The reason for this is because network ex­
ternalities have frequently been found to be significant in predicting
continuous intention. However, it has not been tested in the context of
merchants’ continuous usage intention of the e-wallet.
The difference between network externalities and social influence is
that one is from the economic perspectives, while the other is from the
psychological, or sociological perspectives. Social influence is the effect
of the users’ immediate network, and how those people influence their
decision (Kanat et al., 2020). It refers to how the user performs a certain
action to conform the expectations of others (Wattal et al., 2010).
Meanwhile, network externalities are the effect of the overall network
(Kanat et al., 2020). A typical network good is said to have little use in
isolation (Gowrisankaran & Stavins, 2004). This explains the situation
with the e-wallet where if merchants were to adopt the e-wallet as a
payment system, but no customers are utilizing the e-wallet for trans­
actions, the e-wallet will have little to no use to the merchants. Due to
this, network externalities were judged to be a suitable variable to be
used in this study. The result of the analysis indeed confirms the sig­
nificance of the construct network externalities on merchants’ contin­
uous intention of the e-wallet. This shows the importance of network
externalities not only in the study of two-sided market, but also when
studying continuous usage intention where post-acceptance expectation
is important.
In addition, the UTAUT model was also extended by adding another
construct which is online customer service. Few research has found this
variable to be an important predictor of satisfaction (Deyalage & Kula­
thunga, 2019; Zeng et al., 2009) and effort expectancy, or perceived ease
of use (Rahi et al., 2019). It was reasoned that customer service is
equally important in virtual stores, as well as physical stores (Boateng
et al., 2016). This study found that while online customer service is a
significant predictor of effort expectancy, it is not significant in pre­
dicting merchants’ satisfaction. However, it does positively impact effort
expectancy which is a significant predictor of satisfaction.
Furthermore, only one out of three constructs from the UTAUT
model that were used in this study, namely effort expectancy were found
to be significant in predicting merchants’ continuous intention of the ewallet. On the other hand, performance expectancy and facilitating
conditions were found to be insignificant in predicting continuous
intention. The result for performance expectancy is contrary to that from
multiple previous research. The reason may be due to the COVID-19
pandemic which ‘forced’ merchants to start adopting the e-wallet for
their business to adapt to the changing pandemic-associated consumer
behavior (Gomes, 2020). Similarly, the result of previous study con­
ducted by Mailizar et al. (2021) who found perceived usefulness to be
insignificant in predicting behavioural intention towards e-learning use
during COVID-19 pandemic. This finding shows that perception on the
usefulness of a technology may not be important in predicting behav­
ioural intention, or continuous intention during urgent times such as the
COVID-19 pandemic which is another contribution to existing literature.
6.7. Satisfaction
Lastly, the study unveiled a positive correlation between satisfaction
and continuous intention. This implies that a heightened level of satis­
faction among merchants with the e-wallet corresponds to a higher
likelihood of their sustained intention to use it. This finding resonates
with research by Gu et al. (2019), who observed that satisfaction played
a pivotal role in influencing users’ intent to persist with smart home
services. Similarly, Lei and Lee (2020) ascertained that satisfaction
significantly impacted Chinese gamers’ intention to continue engaging
in mobile gaming. Furthermore, Daragmeh et al. (2021) established a
positive linkage between satisfaction and the continuous usage of
e-wallets. The significance of satisfaction in fostering ongoing engage­
ment can be attributed to the concept of loyalty (Lei & Lee, 2020).
Satisfied users tend to exhibit loyalty by persistently utilizing a system.
This outcome also concurs with the Expectation Confirmation Model
(ECM), which underscores users’ satisfaction as a critical factor driving
repurchase or reuse intention. Consequently, to ensure the sustained use
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International Journal of Information Management Data Insights 4 (2024) 100254
6.9. Implications
7. Conclusions
The e-wallet is a system that has been growing in terms of popularity
for a while now. A few years back, the adoption rate of the e-wallet in
Malaysia was said to be very low, with only 8% of the population uti­
lizing it as a payment method (Tan, 2019). However, the COVID-19
pandemic that started in the year 2020 has caused a jump in the num­
ber of e-wallet usage, both among consumers and merchants. The first
reason is to follow the norm of social distancing. Next, the merchants
needed to adjust to the changing consumer behavior, especially since
they are not able to bet if it’s episodic, or more permanent in nature
(Gomes, 2020). In addition to that, cashless digital payment, including
the e-wallet, has become a must if merchants want to stay relevant in the
competitive environment. An increase in the adoption of e-wallet is
good, as that is exactly what the government is aiming for. However, it
should also be noted that one of the biggest reasons for the increase in
adoption rate, especially among merchants, is due to the COVID-19
pandemic and Movement Control Order (MCO). It is also said that
Malaysia is expected to reach a cashless society by 2025 (Aziz, 2022).
Therefore, it is important to gain understanding on merchants’ percep­
tion of the e-wallet after adopting it, and if they would like to continue
using it in the future.
Firstly, the satisfaction of the merchants in relation to the e-wallet is
an important factor in determining the continuous usage intention. To
satisfy the merchants, it is important to develop a system that fulfills the
needs of the merchants. Merchants put a lot of importance on the per­
formance expectancy of the e-wallet. Some of the advantages are better
security, as well as faster transactions compared to traditional payment
methods. In addition to that, the e-wallet, which is a cashless transaction
method, is able to help merchants reduce contact with the customers
which in turn will ensure their safety and health. Nowadays, this aspect
becomes even more important, as transmission of diseases can occur
through physical contact. Not only that, mobile payment transactions
were said to be able to increase impulse buying behavior among con­
sumers, which in turn raises the sales of the merchants (Mallat & Tuu­
nainen, 2008). This is due to the fact that mobile devices are frequently
near the consumers. Therefore, it is important for the providers to
continuously improve these aspects of the e-wallet, and ensure that it is
more ‘useful’ compared to other transaction methods. Not only that, it is
also important for e-wallet service providers to spread awareness and
knowledge on different aspects of the e-wallet. Additionally, providers
can also think of ways to help the merchants promote higher use of
e-wallet among the customers of their business. This in turn can help
raise merchants’ perception of the usefulness of the e-wallet.
Furthermore, it is also important to note that effort expectancy can
influence merchants’ decision on e-wallet continuous intention. This
means that merchants’ perception on how easy it is to use the e-wallet
can influence their decision to continue using it in the future. Therefore,
there is a need to ensure that the system is simple to use for all users. One
of the factors that influence their perception of ease of use is the online
customer service. While e-wallet is generally quite simple to use, there
are still chances that problems can occur during the process of the
merchants using the e-wallet. Compared to traditional methods like
cash, it is more likely for problems to occur when using technology. By
ensuring the merchants that they will be provided with customer service
that is not only quick to response, but is knowledgeable and can solve
any of their problems will help ease their worries, and further enhances
their perception on the effort expectancy of the e-wallet. This will so­
lidify their continuous usage intention. Lastly, the e-wallet service pro­
viders should also focus on raising the adoption rate among consumers.
Due to the concept of network externalities, higher consumer adoption
will not only result in higher adoption among merchants, but also higher
intention to continue using the e-wallet in the future.
The study’s findings revealed that merchants’ continuous intention
to use the e-wallet is influenced by three key factors: effort expectancy,
network externalities, and satisfaction. Conversely, the level of satis­
faction experienced by merchants is determined by two factors: per­
formance expectancy and facilitating conditions. Notably, among these
factors, satisfaction exerts the most significant impact on merchants’
continuous intention.
As a result, it becomes paramount to ensure the e-wallet’s ongoing
utility superiority over alternative payment methods. Equally important
is the establishment of organizational and technical infrastructure that
can effectively support the integration and use of e-wallets among
merchants in Malaysia. By addressing these aspects, service providers
can optimize merchant satisfaction, thereby fostering their continued
intention to utilize the e-wallet.
Merchants’ satisfaction with the e-wallet plays a pivotal role in
shaping their intention to use it continuously. To ensure merchant
satisfaction, it becomes crucial to develop a platform that caters to their
specific needs. Merchants attach significant importance to the perfor­
mance attributes of the e-wallet. Thus, efforts should be directed to­
wards enhancing security measures and expediting transactions, thereby
outperforming traditional payment methods. Furthermore, it’s worth
noting that mobile payment transactions have been shown to stimulate
impulse buying behaviors among consumers, consequently boosting
merchants’ sales. Therefore, continuous improvement in these areas is
imperative, maintaining the e-wallet’s competitive edge over alternative
transaction avenues. In addition to enhancing the e-wallet’s perfor­
mance, there is a pressing need to raise awareness regarding its various
dimensions. This includes providing guidance on how to use the e-wallet
effectively, communicating its limitations, and updating users about its
current status. Providers should also explore strategies to encourage
merchants to promote greater usage of the e-wallet among their cus­
tomers. This collaborative effort could significantly enhance merchants’
perception of the e-wallet’s performance, leading to greater satisfaction.
The perception of merchants regarding the effort required to use the
e-wallet holds a considerable sway over their ongoing usage decision.
Therefore, prioritizing a user-friendly system is essential. Among the
factors shaping their effort perception, online customer service stands
out. Despite the e-wallet’s general ease of use, potential glitches can
arise during merchants’ interactions with the system. Unlike conven­
tional methods such as cash transactions, technological tools are more
prone to issues. Demonstrating prompt and knowledgeable customer
service can assuage their concerns and bolster their perception of the ewallet’s user-friendliness. This, in turn, solidifies their commitment to
its continued use. Lastly, e-wallet service providers should focus on
bolstering adoption rates among consumers. Driven by the concept of
network externalities, increased consumer adoption not only spurs
greater merchant adoption but also amplifies their intent to continue
using the e-wallet.
7.1. Limitations and future recommendations
This study has several limitations. Firstly, its findings may not
generalize to the broader merchant population in Malaysia due to the
sample’s restriction to the Klang Valley area. Furthermore, a significant
portion of the respondents in this study originate from the food and
beverages industry. In addition, while this study provides valuable in­
sights, the small sample size warrants caution in generalizing the find­
ings. To address this, future research could replicate the study in various
states across Malaysia or gather a more diverse sample from merchants
nationwide. Future research endeavors should also consider integrating
qualitative component, such as interviews or focus group discussions
with merchants, to complement the quantitative analysis, thereby
providing a more holistic understanding of their perceptions, experi­
ences, and motivations regarding e-wallet adoption and usage. Besides
11
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International Journal of Information Management Data Insights 4 (2024) 100254
that, future research could conduct a cost-benefit analysis of e-wallet
adoption for merchants, providing recommendations to enhance adop­
tion and continuous usage. This would aid policymakers, e-wallet pro­
viders, and merchants in making informed decisions about the benefits
and strategies for e-wallet adoption in Malaysia.
Moreover, this study primarily utilizes the Unified Technology
Acceptance and Use of Technology (UTAUT) model, supplemented by a
few additional variables. As a result, the scope of constructs considered
is limited. To enrich the depth of comprehension, future inquiries could
broaden the model’s scope by incorporating technological attributes,
contextual factors, or both, to examine their interaction with continuous
intention. Furthermore, exploring the impact of government policies,
regulations, and economic conditions on e-wallet adoption and contin­
uous usage in Malaysia holds promise. Alternatively, research could
delve into external constructs influencing performance expectancy and
effort expectancy.
Lastly, the correlation between network externalities and satisfaction
remains uncertain. This study yielded insignificance in their relationship
with satisfaction. Subsequent research might contemplate re-evaluating
this variable’s link to merchants’ satisfaction regarding the e-wallet.
This could involve mediating it with network quality and network in­
timacy or introducing merchant size, industry type, or demographic
factors, which might influence the relationships between the identified
constructs and continuous intention to use e-wallets as moderating
factors within the framework.
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Declaration of competing interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.
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