ArticlePDF Available

Exploring Consumers' Intention to Adopt Mobile Payment Systems in Ghana

  • Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development
  • Ghana Communication Technology University

Abstract and Figures

In this paper, we examined consumers’ intention to adopt and use mobile payment method in Ghana. Data for the study was obtained from a sample of 260 respondents through online and direct survey using structured questionnaire. Structural Equation Modeling was used to analyse the data through SPSS v.22 and SmartPLS v.3. Findings with regards to the determinants of mobile payment system adoption indicate that perceived security, attitude and perceived usefulness play active roles in consumers decision to adopt mobile payment method in Ghana. Also, perceived usefulness and perceived ease of use have a significant and positive influence on consumers’ attitude towards mobile payment adoption. Further, subjective norm was found to influence perceived usefulness and perceived ease of use of mobile payment adoption in Ghana. The study contributes to literature on mobile payment system from developing country context. The study proffered some recommendations.
Content may be subject to copyright.
DOI: 10.4018/IJESMA.285547
Volume 14 • Issue 1
Copyright © 2022, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
*Corresponding Author
Masud Ibrahim, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Ghana*
Robert Ebo Hinson, University of Ghana, Ghana & University of Kigali, Rwanda & Durban University of Technology,
South Africa
Arthur Stephen, Valley View University, Ghana
In this paper, the authors examined consumers’ intention to adopt and use mobile payment methods in
Ghana. Data for the study was obtained from a sample of 260 respondents through online and direct
survey using structured questionnaire. Structural equation modeling was used to analyse the data
through SPSS v.22 and SmartPLS v.3. Findings with regards to the determinants of mobile payment
system adoption indicate that perceived security, attitude, and perceived usefulness play active roles
in consumer decisions to adopt mobile payment methods in Ghana. Also, perceived usefulness and
perceived ease of use have a significant and positive influence on consumer’s attitude towards mobile
payment adoption. Further, subjective norm was found to influence perceived usefulness and perceived
ease of use of mobile payment adoption in Ghana. The study contributes to the literature on mobile
payment systems from a developing country context. The study proffered some recommendations.
Consumer Behaviour, Ghana, Mobile Payment, Structural Equation Modeling, Technology Acceptance, Theory
of Planned Behavior
Today, life has become dependent on electronic gadgets, which mainly consists of mobile devices
such as the laptop, smartphone, and other electronic gadgets. In recent times, mobile phones enable
us to engage in routine functions such as making payments for our shopping and other transactions
(Sharma & Gupta, 2019). The introduction of the Information and Communication Technology
(ICT), for instance, has created an opportunity for consumers to pay for products and services online
and offline using mobile phones known as mobile payments or M-payment. Customers carry out
large transactions through wireless and wired data transmission networks, with the support of mobile
devices and mobile databases to give consumers access as well as convenience to large amounts of
products and services.
According to Guo and Bouwman. (2016), M-payment is the initiation and confirmation of
payment by wireless Some scholars also explained that M-payment could be defined as “any personal
Volume 14 • Issue 1
or commercial activity involving an electronic device connected to a telecommunication network to
complete an economic transaction” (Liébana-Cabanillas, Ramos de Luna, & Montoro-Ríos, 2017).
The introduction of technologies like CDMA (Code Division Multiple Access) supporting 3G/4G
for mobile telecommunications by companies like MTN, VODAFONE, AIRTEL/TIGO, in Ghana
has created an enabling platform for consumers and sellers to accept and use their mobile phones to
pay or accept payment for goods and services in Ghana. Integrating payment systems developed in
different parts of the world is a challenge due to the lack of ICT knowledge and limited bargaining
power with intermediaries. Because of the low quality of existing means of payment in some developing
countries, that open more significant windows of opportunity for the future use of mobile payment
(Asongu & Nwachukwu, 2018).
Unlike the developed countries, Ghana and some other developing countries have still not
developed a model that allows for the use of e-cards (debit or credit cards) for business transactions.
So, consumers and businesses mostly rely on cash for payment methods and settling of debts. This
situation is worrying as it poses and exposes consumers to some risk including health, theft and loss of
valuable money as a result of carrying physical cash in a purse or wallet. There is the need, therefore,
to consider other safer methods of carrying cash without subjecting consumers to the above dangers.
One of such ways is the use of mobile payment method.
Mobile payments have been in existence in the developed economies for some time now and
have been linked to improving business transaction. A recent study by Accenture shows that in the
coming years, there would be a decrease in the traditional payment method in favour of an increased
digital payment (Accenture.Consulting, 2015). The study further predicted a significant increase in
the use of retail apps (8%), Apple Pay™/Samsung Pay™ (7%) and PayPal (6%) (Liébana-Cabanillas
et al., 2017). Also, a study by eMarket indicates mobile payment transaction in 2016 reached $27.05
billion, with customers spending an average of $721.47 annually (eMarket, 2015). The reason for
the sharp rise in mobile payment sales, according to the report, is due to the rapid growth of the use
of mobile payment technology.
Notwithstanding the abundance of literature on M-payment in the developed economies, few
empirical studies have been carried out on mobile payment usage in developing market (Muriu,2017).).
As to whether consumers’ aim towards e-payment can be construed to M-payment remains mostly
unidentified. For that matter, the understanding of mobile users’ intention to adopt M-payment system
in developing economies such as Ghana appears to be sparse or non-existent. This study, therefore,
seeks to breach the gap in the literature on M-payment studies in developing economies such as
Ghana. Hence, the major objective of this study is to find out the determinants of mobile payments
system adoption intentions among consumers in Ghana.
M-Payment Adoption
E-payment or electronic payment is a form of payment which is generally defined as “a payer’s transfer
of a financial claim on a party acceptable to the recipient” (Antwi, Hamza, & Bavoh, 2015). It is a
worldwide phenomenon that enables individuals to engage in online transactions globally anywhere
and at any time ( Kasemsap, 2016)), thereby enhancing both domestic and international trade (Hussain,
Mollik, Johns, & Rahman, 2019) Lin and Nguyen (2001) defined e-payment as “payments initiated
through the automated clearinghouse, commercial card systems and electronic exchanges”.
Forrest (2011) defines M-payment as “a financial transaction started by a mobile phone without
utilizing the voice function”. Garntner (2012) also sees M-payment as “a transaction performed through
mobile phone and payment mechanism that incorporate banking and telecommunication based on
the telecom’s billing system and interactive voice response system” (Garntner, 2012). In this paper,
we define mobile payment as payment through communication technology that enables mobile users
to make payment using mobile devices through SMS or internet services.
Volume 14 • Issue 1
According to Dahlberg, Mallat, Ondrus, and Zmijewska (2008), M-payment is another method
of e-payment which enables payment for goods and services through the Internet and communication
technology (Dahlberg et al., 2008). Past studies have indicated that the increasing usage of mobile
payment and related activities is due to the ubiquitous nature of the technology that transcends time
and space (Carlsson, Walden, & Bouwman, 2006). As noted by Tinga, Yacobb, Liew, and Lau (2015),
M-payment structure takes the opportunity of wireless and communication technologies which allows
payments through platforms such as SMS message, WAP online billing, PIN transmission, Mobile Web,
direct-to-subscriber bill and direct to credit cards transaction via mobile phones (Kim, Mirusmonov,
& and Lee, 2010). Customers are, therefore making mobile payment the preferred payment method
due to its effectiveness (Dewan & Chen, 2005).
Zhao and Kurnia (2014), mentioned that four methods to access M-payment are through
“message or browser payment, application-based payment, contactless payment and hybrid payment”
(Deloitte, 2012). The first two methods use what is referred to as remote payment, and the other two
use what is termed as a proximity payment method (Zhao & Kurnia, 2014). From the objectives of a
transaction, M-payment can be grouped under three modes, i.e. peer-to-peer payment, consumer-to-
business payment and business-to-business payment (Deloitte, 2012). Also, from the provider’s side,
M-payment can be categorized into mobile network operator centric, financial institution centric and
third-party operator centric (Lu, Yang, Chau, & Cao, 2011). These three operators, mobile network
operator, financial operator and third-party operator, form a sort of network which provides the mobile
payment transaction system. The mobile network provides the communication infrastructure through
mobile and data service. The banking or financial service operators provide the remote or proximity
payment by storing a client’s bank card information on a mobile phone chip and using the mobile
wireless communication technology and radio frequency technology (Zhao & Kurnia, 2014). On the
other hand, the third-party platform utilizes an intermediary to provide the mobile payment services
which integrate communication network from mobile network operators and payment accounts from
the financial institutions (Lu et al., 2011).
Factors influencing technology adoption and consumer intentions and Attitude in the context of
traditional customers have been researched extensively in the literature. Both empirical and theoretical
review shows that the theories of Reasoned Action (TRA) (Ajzen & Fishbein, 2005), Technology
Acceptance Model (TAM) (Davis, 1989) and Theory of Planned Behaviour (TPB) (Ajzen, 1991)
are among the most popular theories used to explain online shopping behaviour (Limayem, Hirt, &
Cheung, 2007). For the purpose of this research work, we adopted the technology acceptance model
(TAM) and the theory of reasoned action (TRA) as the main theoretical anchor for this study.
The TRA has been used extensively as a significant determinant of consumer actions or behavior,
both online and offline. The TRA, as proposed by Ajzen and Fishbein (2005), emphasizes that an
individual’s behaviour is as a result of Attitude that is formed by perceptions or norms. It further
explains that intentions are the outcome of attitudes and social aspects or subjective norms (Dennis,
Merrilees, Jayawardhena, & Wright, 2009). The TRA model argues, for example, that, decision to
perform an action, in this case, to use the mobile payment for transactions can be influenced by
friends and associates. Shim, Eastlick, Lotz, and Warrington (2001) assert that social influences are
very significant for e-shopping, but e-retailers have challenges in satisfying this need. Rohm and
Swaminathan (2004) found that social interaction was a significant motivator for e-shopping. Parsons
(2002) concurred by concluding that social influence from outside home and peer groups influence
consumer behavioral intentions.
The technology acceptance model, on the other hand, by has been widely adopted in many fields
to examine technology adoption (Dennis, 2005). The TAM claims that Attitude of customers towards
the use of new technology is influenced by the perceived effectiveness, usefulness and ease of use of
the technology (Davis, 1989). The TAM is said to have been derived from the TRA (Dennis, Newman,
Volume 14 • Issue 1
Brakus, & Wright, 2010). The usefulness of technology relates to consumer’s opinion that the use of
the said technology will enhance their shopping and information seeking outcome (Chen, Gillenson,
& Sherrell, 2002). Usefulness is also seen in the image components of product selection, customer
service and delivery or fulfilment in the role of functional attributes of the product (Dennis et al.,
2009). Ease of use, on the other hand, relates to the degree to which the said technology is seen to
involve exerting minimum energy in carrying out the task of using the technology (Chen et al., 2002).
Social influences according to Liébana-Cabanillas et al., (2017) and Venkatesh & Bala, (2008) are in
the form of subjective norms and are used as factors both in models of technology acceptance and in
their usage (Liébana-Cabanillas et al., 2017; Venkatesh & Bala, 2008). It is defined as the degree to
which an individual sees his or her action been influenced by other people close to him or her. Thus,
how an individual perceives the opinion of people close to him when considering to perform certain
action (Venkatesh & Bala, 2008). There are two main underlying sets of factors involved in this.
First, the beliefs the consumer has in the person’s he sees as his reference point when considering an
action; and second, the desire to act in accordance to how his references behave (Herrero, García, &
Rodríguez del Bosque, 2005). From this, some scholars have identified a direct and positive relationship
between “subjective norms and ease of use” (López-Nicolás, Molina-Castillo, & Bouwman, 2008),
usefulness” (Zhang, Yue, & Kong, 2011) and, “intention to use” (Shin, 2009). Based on the above
assertion, we propose the following hypotheses:
Hypothesis 1: Subjective norm would have a positive and direct influence on of ease of use of mobile
payment method.
Hypothesis 2: Subjective norm would have a positive and direct influence on the usefulness of the
mobile payment method.
Many research works in recent time have demonstrated that perceived usefulness has a significant
direct relationship with mobile payment adoption (Amoroso & Magnier-Watanabe, 2012; Kim et
al., 2010; Liébana-Cabanillas et al., 2017; Meharia, 2012; Zhao & Kurnia, 2014). The influence of
perceived usefulness on the intention to adopt a particular technology has been researched extensively.
Wong and Hiew (2005) in their study revealed that mobile commerce transaction is influenced
significantly by the perception of the usefulness of the mobile devices such as “personalization,
ubiquity, localization, timeliness and network stability”. Also, Teoh, Chong, and Chua (2013) found
that the perceived usefulness largely determined consumers’ intention to use mobile commerce in
Malaysia (Mun, Khalid, & Nadarajaha, 2017). Thus, consumers would adopt M-payment if they
consider it to be a more efficient payment method to achieve their desired outcomes. We, therefore,
propose the following hypotheses:
Hypothesis 3: Perceived usefulness would influence consumer’s Attitude towards the intention to
use the mobile payment method.
The ease of use refers to an individual’s perception that “using a particular system will be effortless
or, simply, easy to handle” (Davis, 1989). This is considered as one of the most influential
Volume 14 • Issue 1
determinants of new technology adoption. User may find, for instance, the use of a particular
technology tedious and complex due to the nature of the technology, including its features which
might be difficult to navigate through. As such, the mobile payment service platform should be
easy to use by consumers. Many research works have been carried out in different context to
explore the effect of the perceived ease of use on perceived usefulness of a product (Hernández,
2010; Liébana-Cabanillas, Muñoz-Leiva, Ibáñez-Zapata, & Rey-Pino, 2012; Mun et al., 2017).
For Davis, Bagozzi, and Warshaw (1989), the ease of use dimension of adoption has a double
impact. First, it’s perceived influence on Attitude, and second, it’s utility as shown by the TAM.
We, therefore, propose the following hypotheses:
Hypothesis 4: The perceived ease of use would influence the perceived usefulness in the adoption
of mobile payment method.
Hypothesis 5: The perceived ease of use would influence Attitude towards the intention of mobile
payment method.
Empirical findings on technology adoption have expanded the use of the TAM to include Attitude
(Davis, 1989). Some studies have shown that beliefs and attitudes predict intentions (Tinga et al., 2015;
Wang, Sun, Lei, & Toncar, 2009). Behavioural intention is sometimes understood in the context of
how Attitude influences actual behaviour (Huang, Lee, & Ho, 2004), and how intention and behaviour
would be negatively influenced by negative Attitude (Stevenson, Bruner, & Kumar, 2000). According
to Polatoglu and Ekin (2000), explain that decision to adopt a product by consumers is influenced
partly by their Attitude towards the product, i.e. their convictions about the importance and perceived
usefulness of the product (Liébana-Cabanillas et al., 2017). As a result, it is expected that consumers’
Attitude would facilitate transactions and reduce the obstacles to adoption of the terms of trade
(Pavlou, 2002a, 2002b), and more specifically, the intention to use mobile payment systems (Schierz,
Schilke, & Wirtz, 2010). In this study, Theory of Reasoned Action (TRA) and Theory of Planned
Behavior (TPB) is adopted to determine whether or not the Attitude of consumers toward mobile
payment influences their intent to adopt mobile payment method. We, therefore, hypothesize thus:
Hypothesis 6: Attitude is an antecedent of intention to use the mobile payment method.
Mobile devices, despite their importance in recent times, have come under severe threat in recent times.
As noted by Jain and Gupta (2019), mobile devices are prone to new attacks like smishing which is
a security attack performed by sending fake messages to steal personal credentials of mobile users.
Ashrafi & Ng, (2008) are of the view that security and the perception of risk are the major factors
that inhibit perceived intention to adopt electronic payment systems. When consumers perceive any
concern about the security of a platform or technology, it makes it hard for them to want to use it.
Consumers can only consider mobile payment service as secure when they are satisfied with the level
of transactions done in a secured manner. Wan and Che (2004) assert that perceived security exerts a
significant influence on consumers acceptance of technology (Mun et al., 2017). Thus, it is essential
to enhance the security features of electronic payment systems, especially new systems, to generate
consumer confidence in trying these new services and systems. We hypothesize thus:
Hypothesis 7: Perceived security would influence consumers’ intention to adopt mobile payment
Volume 14 • Issue 1
This study was undertaken to establish the determinants of consumers’ intention to adopt and use
mobile payment method as a payment option for goods and services in Ghana. A convenient sampling
method was used to select respondents from Kumasi, Ghana’s largest city in terms of population
and business presence. Three hundred (300) respondents were sampled for this study; however, 260
responses were found to be useable after the initial screening and data cleaning. The adoption of the
convenience sampling technique for the data collection was as a result of the difficulty in estimating
the sample size as well as identifying the population of the study. A self-administered, structured
questionnaire was developed, pre-tested and finally administered to the respondents through personal
contact by researchers. The researchers used informed consent form to seek for the permission of
respondents and assured them of anonymity and confidentiality of their responses.
A Likert scale which ranged from 1 = “strongly disagree to 5 = strongly agree” was used. The
questions were adapted from similar studies. The questionnaire was designed in three (3) different
parts. The first part (section A) measured the demographic characteristics of the respondents; Part
I (section B) and Part III (section C) measured the main variables, i.e. the independent variables
(subjective norm, perceived ease of use, perceived usefulness, Attitude and perceived security) and
dependent variable (behavioural intention).
The questionnaire consisted of closed-ended questions for the constructs, five-point Likert scales,
and socio-demographic data. Scales for the study were adapted from Venkatesh and Davis (2000),
Mun et al. (2017) and Liébana-Cabanillas et al. (2017) to measure subjective norms about mobile
payment systems. The Attitude to use scale was adapted from research conducted by Schierz et al.
(2010) and Liébana-Cabanillas et al. (2017). The usefulness scale was adapted from the work of
Bhattacherjee (2001), Mun et al. (2017) and Liébana-Cabanillas et al. (2017). The perceived ease of
use scale was adapted from Davis et al. (1989), Venkatesh and Davis (2000) and Liébana-Cabanillas
et al. (2017). The perceived security scale was adapted Liébana-Cabanillas et al. (2017) and Zhao
and Kurnia (2014). Finally, the intention to use scale was adapted from Davis (1989), Venkatesh and
Davis (2000), Liébana-Cabanillas et al. (2017) and Mun et al. (2017).
Figure 1. Conceptual model and hypotheses of the study
Volume 14 • Issue 1
The collected data was analyzed using the Statistical Package for Social Sciences (SPSS v,22) and
SmartPLS 3. The data was first coded and screened for outliers or any other variation in the data set.
Descriptive analysis was used for the demographic variables and the hypotheses tested using structural
equation modelling (SEM). Data validation was done through content and construct validations.
Confirmatory factor analysis was also used to purify the measures, assess the unidimensionality of
the scale items and assess discriminant validity among the constructs (see Table 2).
Some demographic variables were collected in this study: gender, age, level of education, type of
accounts and average income per year, and these results are summarized in Table 1. In terms of gender,
60.8% of the respondents were males, and 39.2% were females. With regards to age, 26.2% of the
respondents were between 18 and 24 years; 32.3% were between 25 and 29 years; 19.2% were between
the ages of 30 and 34; 13.5% were between 35 and 39 years, and 8.5% were 40 years and above. In
terms of education, about 53.9% of them had undergraduate degrees; 25% had a Masters’ degree;
4.6% PhD degree; 10.8% had basic level education, and 5.8% had other qualification. With regards to
the employment status of the respondents, 46.2% are employed; 13.8% are self-employed; 5.4% are
unemployed, and 34.6% are students. About 25% of the respondents earned a monthly income below
GHC 500; 34.6% of the respondents earned monthly income between GHC 400 to 1000; 30% earn
monthly income between GHC 1000 and 5000, and 10.9% earn monthly income above GHC 5000.
Regarding the payment option frequently used by respondents, about 50% indicated they use cash;
10.4% use cards (debit/credit cards); 10.8% indicated they use cheque; about 23% indicated mobile
money, and 5.8% indicated they use electronic payments. On the preferred payment method, 32.2%
indicated cash; 10.4% indicated cards; 5% indicated cheque, and 36.2% indicated mobile money and
16.2% indicated electronic payments (see table 1).
The confirmatory factor analysis is used to test the model’s fitness with the data. The measurement
model consisted of the latent constructs Subjective Norm, Perceived Ease of Use, Perceived Usefulness,
Perceived Security, Attitude and Intention to use.
Construct reliability measures the extent of the internal consistency of the measures used, and it
was assessed through the item factor loadings with the acceptable value of 0.70 and through Cronbach’s
alpha with the acceptable level of 0.7 (Hair, Ringle, & Sarstedt, 2011; Ringle, Wende, & Becker,
2015). From Table 2, all of the constructs have item loadings higher than the recommended 0.70.
All the variables returned Cronbach alphas above 0.70, indicating that these multiple measures
are highly reliable for the measurement of each construct (see Table 2). Construct validity “assesses
the degree to which a measurement represents and logically connects the observed phenomenon to
the construct through the fundamental theory” (Fornell & Larcker, 1981a). It is also assessed through
convergent validity and discriminant validity (Ringle et al., 2015). Convergent validity was considered
adequate since the average variance extracted (AVEs) and composite reliability (CR) satisfied the
minimum of 0.50 and 0.70 respectively (Fornell & Larcker, 1981b; Ringle et al., 2015).
Discriminant analysis requires a factor to correlate higher than with any other construct on its
scale (Messick, 1988). From table 3, it is clear that all the factors loaded higher than any other factor
on their scales. Innovativeness on its scale had a value of about 0.9, which is higher than any other
construct on that scale. ATTD has a value of (0.8), BI (0.8), PEOU (0.8), PSEC (0.8), PU (0.8) and
SN (0.8).
Volume 14 • Issue 1
The structural model was assessed through the regression weights, t-values and the p-values for the
significance of t-statistics (Chin, 2010; Ringle et al., 2015). The results of the structural model for
testing the research hypotheses are presented in Table 4.
A test of the hypothesis was carried out using the bootstrapping method with 5000 samples to
assess consumers’ behavioural intention to adopt mobile payment in Ghana. In the first model, we tested
the effect of subjective norm on perceived ease of use and perceived usefulness of mobile payment
adoption. Subjective norm had a significant and positive effect on both variables; PEOU (β = 0.173;
t= 2.16; p < 0.032) and PU (β = 0.298; t= 3.78; p < 0.000) and this led to the acceptance of H1 and
H2 respectively. This means that SN has a greater effect on perceived usefulness than on perceived
ease of use of mobile payment adoption by consumers. Also, when subjective norm increases by 1%,
perceived usefulness and perceived ease of use mobile payment by consumers increase by 29.8%
and 17.3% respectively. Thus, a consumer’s intention to adopt mobile payment system is influenced
Table 1. Demographics of respondents (N=260)
Note: 1 GHC = $0.0.17 USD (Currency exchanger, 21/10/2020)
Volume 14 • Issue 1
indirectly by the perception of other people about the mobile payment system. The influence of social
norms on m-payment adoption in the Ghanaian context might be due to the extended family system
that exists in Ghana. This finding is instructive in the sense that, consumers form their decision to
either adopt or not to adopt a particular technology; in this case mobile payment method based on
the judgment of what their social circle thinks about the product. This supports the assertion by some
researchers that consumers’ intention to adopt a particular technology is dependent on two factors,
i.e. the belief and trust the consumer has for his or her reference, and second, the desire to imitate
what his references do in terms of action taken towards a product (Herrero et al., 2005). This finding
however, contradicts that of Shankar and Datta (2018) where subjective norms (SN) and personal
innovativeness (PI) were found to have no significant impact on m-payment adoption intention in India.
Again, in the second model, the study assessed the effect of perceived usefulness on attitude and
consumer behavioural intention of mobile banking adoption. Perceived usefulness had a significant
and positive effect on Attitude and BI (p < 0.001). Perceived usefulness had a positive and significant
Table 2. Item loading and construct reliability
Notes: FL – Item Loadings, ATT – Attitude, SN – Subjective Norm, PEOU – Perceived Ease of Use, PU – Perceived Usefulness, PS – Perceived Secu-
rity, BI – Behavioral Intention; AVE-Average variance extracted, CR- Composite reliability, CA – Cronbach’s alpha
Table 3. Discriminant Validity
ATTD 0.830 
BI 0.019 0.817 
PEOU 0.463 -0.039 0.779
PSEC 0.332 -0.108 0.291 0.814 
PU 0.551 -0.059 0.538 0.414 0.831 
SN -0.018 0.687 -0.092 -0.130 -0.088 0.830
Volume 14 • Issue 1
effect on Attitude (β = 0.438; t= 6.08; p < 0.000) and this led to the acceptance of H3. Also, perceived
usefulness had a positive and significant effect on BI (β = 0.122; t= 2.03; p < 0.044), and this led to
the acceptance of H4. The Beta scores mean that, when PU increases by 1%, Attitude towards mobile
payment adoption increases by 43.8%. Also, when PU increases by 1%, consumer behavioural intention
towards mobile payment adoption increases by 12.2%. This finding also shows the importance of
perceived usefulness in product decision making. It means that consumers’ intention to adopt mobile
payment method as a payment option is influenced by how useful the service is to the consumers
in achieving a desired result or outcome. That is, the consumer would derive some benefits in using
the new technology as compared to using the traditional method of payment. This supports what
Wong and Hiew (2005) found that the perception of the usefulness of the mobile devices such as
personalization, ubiquity, localization, timeliness and network stability greatly influence the adoption
of mobile commerce.
Figure 2. Results of structural modelling on M-Payment adoption
Table 4. Results of hypotheses test
Paths Beta SD t-value p-value
ATTD -> BI 0.275 0.066 4.132 0.000
PEOU -> ATTD 0.245 0.056 4.407 0.000
PEOU -> PU 0.634 0.038 16.623 0.000
PSEC -> BI -0.026 0.073 0.352 0.725
PU -> ATTD 0.459 0.062 7.437 0.000
SN -> PEOU 0.257 0.064 4.016 0.000
SN -> PU 0.133 0.039 3.422 0.001
Volume 14 • Issue 1
In the third model, the effect of PEOU on Attitude and perceived usefulness was also assessed.
PEOU had a significant and positive effect on Attitude and PU (p < 0.001). Perceived ease of use
had a positive and significant effect on Attitude (β = 0.167; t= 2.29; p < 0.024), and this led to the
acceptance of H5. Also, PEOU had a positive and significant effect on PU (β = 0.584; t= 8.42; p
< 0.000), and this led to the acceptance of H6. The Beta scores mean that, when PEOU increases
by 1%, perceived usefulness of mobile banking adoption increases by 58%. Consumers thus would
adopt mobile payment method if they perceive the system as very easy to navigate. Perceived ease
of use is thus regarded as one of the most important determinants of new technology adoption. The
platform should, therefore, be designed in a way that consumers would find it easy and comfortable to
use. Once consumers find the new technology easy to use and also realize the benefits as mentioned
above, consumers would have no problem in switching from the traditional mode of payments method
to mobile payment option.
Finally, in the fourth model, an assessment of the effect of perceived security and Attitude on
consumers’ behavioural intention towards mobile payment adoption was also carried out. The two
variables, perceived security and Attitude, had a significant and positive effect on behavioural intention
(p < 0.001). Attitude had a positive and significant effect on BI (β = 0.227; t= 3.28; p < 0.001); this
also led to the acceptance of H7. Also, perceived security had a positive and significant effect on BI
(β = 0.158; t= 5.04; p < 0.000), and this led to the acceptance of H8. The Beta scores mean that,
when Attitude increases by 1%, consumer intention towards mobile payment adoption increases by
22.7%. Again, when perceived security increases by 1%, consumer intention towards mobile payment
adoption increases by 15.8%. This finding shows that perceived security had more influence on
consumer intention to adopt mobile payment method than perceived usefulness and Attitude. This is
because the issue of perceived security is one of the important factors that influence new technology
adoption. Failure to convince consumers about how safe and secured their transaction would have
a negative effect on the drive to get consumers to adopt mobile payment system. As Ashrafi & Ng
(2008) noted, the issue of perceived security and the perception of risk are the major factors that deter
Figure 3. Bootstrapping the hypotheses for M-Payment adoption
Volume 14 • Issue 1
people from wanting to engage in or adopt electronic payment systems. Thus, consumers consider
the security of the new technology foremost before any other reason to arrive at a decision to adopt
or not to adopt new technologies.
This study focused on the determinants of consumers’ adoption of mobile payment adoption from
Ghana. Findings with regards to the determinants of mobile payment system adoption indicate that
Attitude, perceived security and perceived usefulness play active roles in consumers decision to
adopt new technology. Business owners and marketers, therefore, can grow their business further
by promoting the use of M-payment to complement cash payment and payments options already in
existence. They can also enhance the service quality by ensuring that the transaction is carried out
successfully, ensuring that the process is easy and also expanding the accessibility and availability
of the service.
This finding also revealed that perceived usefulness influences consumers’ attitude towards mobile
payment adoption more than perceived ease of use. This could be important to businesses that want
to adopt mobile payment systems to focus their communication more on the benefits of adoption of
the new payment method to consumers which includes ease of payment, convenience and security.
This study proffers some recommendations to businesses and marketers interested in adopting mobile
payment systems, especially in developing countries. First and foremost, business owners must find
a way of encouraging consumers to accept mobile payment as a payment option by adjusting their
habit of a mode of payment from cash or cards to paying through mobile phones.
Secondly, one of the findings in this study indicates that consumers place much emphasis on the
issue of security. Perceived security is an essential factor in the acceptance of new technologies by
consumers. Due to this perception, businesses and all other agents involved in the implementation
of mobile payment systems must see to the implementation of adequate security measures to win
consumer trust in the system and increase the chances of adoption and use of mobile payment system
as a payment method.
Additionally, government, businesses, and organizations should encourage the acceptance and
use of the m-payment system to complement existing payment methods and augment consumers’
payment behaviour. Moreover, managers and marketers must recognize the implication of cultural
values on intention towards M-payment system adoption.
This research offers a modest contribution to industry and research related to M-payment adoption.
First, it allows researchers and practitioners to explore the enthusiastic response of consumers about
mobile payment services, especially from developing country context where this payment option
is still in its infancy stage. With regards to the industry players, the results of the study can help
potentially them to better understand consumers’ expectations and factors that affect their decision
to use M-payment. As a result, mobile service providers can offer better and improve strategies for
implementing and promoting M-payment systems.
Volume 14 • Issue 1
Accenture Consulting. (2015). North America consumer digital payments survey.
Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes,
50(2), 179–211. doi:10.1016/0749-5978(91)90020-T
Ajzen, I., & Fishbein, M. (2005). The Influence of Attitudes on Behavior. In D. Albarracín, B. T. Johnson, &
M. P. Zanna (Eds.), The Handbook of Attitudes Mahwah (pp. 173–221). Erlbaum.
Amoroso, D. L., & Magnier-Watanabe, R. (2012). Building a Research Model for Mobile Wallet Consumer
Adoption: The Case of Mobile Suica in Japan. Journal of Theoretical and Applied Electronic Commerce Research,
7(1), 13–14. doi:10.4067/S0718-18762012000100008
Antwi, S. K., Hamza, K., & Bavoh, S. W. (2015). Examining the Effectiveness of Electronic Payment System
in Ghana: The Case of e-ZWICH in the Tamale Metropolis. Research Journal of Finance and Accounting, 6(2),
Asongu, S. A., & Nwachukwu, J. C. (2018). Comparative human development thresholds for absolute and
relative pro-poor mobile banking in developing countries. Information Technology & People. Advance online
publication. doi:10.1108/ITP-12-2015-0295
Bhattacherjee, A. (2001). An empirical analysis of the antecedents of electronic commerce service continuance.
Decision Support Systems, 32(2), 201–214. doi:10.1016/S0167-9236(01)00111-7
Carlsson, C., Walden, P., & Bouwman, H. (2006). Adoption of 3G+ services in Finland. International Journal
of Mobile Communications, 4(4), 369–385. doi:10.1504/IJMC.2006.008947
Chen, L., Gillenson, M. L., & Sherrell, D. L. (2002). Enticing online consumers: An extended technology
acceptance perspective. Information & Management, 39(8), 705–719. doi:10.1016/S0378-7206(01)00127-6
Chin, W. (2010). How to write up and report PLS analyses. In Handbook of partial least squares: concepts,
methods and applications (pp. 655 – 690). Springer. doi:10.1007/978-3-540-32827-8_29
Dahlberg, T., Mallat, N., Ondrus, J., & Zmijewska, A. (2008). Past, Present and Future of Mobile Payments
Research: A Literature Review. Electronic Commerce Research and Applications, 7(2), 165–181. doi:10.1016/j.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information
Technology. Management Information Systems Quarterly, 13(3), 319–340. doi:10.2307/249008
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison
of Two Theoretical Models. Management Science, 35(8), 982–1003. doi:10.1287/mnsc.35.8.982
Deloitte. (2012). Mobile Payments: A Deloitte Analysis. Deloitte.
Dennis, C. (2005). Objects of Desire: Consumer Behaviour in Shopping Centre Choice. Palgrave.
Dennis, C., Merrilees, B., Jayawardhena, C., & Wright, T. L. (2009). E‐consumer behaviour. European Journal
of Marketing, 43(9/10), 1121–1139. doi:10.1108/03090560910976393
Dennis, C., Newman, A., Brakus, J. J., & Wright, L. T. (2010). The mediating effects of perception and emotion:
Digital signage in mall atmospherics. Journal of Retailing and Consumer Services, 17(3), 205–215. doi:10.1016/j.
Dewan, S. G., & Chen, L. D. (2005). Mobile payment adoption in the US: A cross-industry, crossplatform
solution. Journal of Information Privacy and Security, 1(2), 4–28. doi:10.1080/15536548.2005.10855765
eMarket. (2015). Mobile payments will triple in the US in 2016, nearly one in five smartphone users will use mobile
payments by next year. Press release.
Volume 14 • Issue 1
Fornell, C., & Larcker, D. F. (1981a). Evaluating structural equation models with unobservable variables and
measurement error. JMR, Journal of Marketing Research, 18(1), 39–50.
Fornell, C., & Larcker, D. F. (1981b). Evaluating structural equation models with unobservable variables and
measurement error. JMR, Journal of Marketing Research, 18(1), 39–50.
Forrest. (2011). Mobile Payments Enter A Disruptive Phase. Forrest.
Gartner. (2012). Forecast: Mobile Payments, Worldwide, 2009-2016. Author.
Guo, J., & Bouwman, H. (2016). An analytical framework for an m-payment ecosystem: A merchants׳ perspective.
Telecommunications Policy, 40(2-3), 147–167.
Hair, J., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a Silver Bullet. Journal of Marketing Theory
and Practice, 19(2), 139–151.
Hernández, J. (2010). Análisis y modelización del comportamiento de uso de las herramientas Travel 2.0 [Analysis
and modeling of use behaviour of Travel 2.0 tools]. Universidad de Granada.
Herrero, A., García, M. M., & Rodríguez Del Bosque, I. (2005). The propensity to innovate in electronic commerce
B2C adoption: An analysis based on the theory of reasoned action. Paper presented at the XVII Encuentro de
Profesores Universitarios de Marketing, Madrid, Spain.
Huang, J. H., Lee, C. Y. B., & Ho, S. H. (2004). Consumer attitude toward gray market goods. International
Marketing Review, 21(6), 598–614.
Hussain, M., Mollik, A. T., Johns, R., & Rahman, M. S. (2019). M-payment adoption for bottom of pyramid
segment: An empirical investigation. International Journal of Bank Marketing.
Jain, A. K., & Gupta, B. B. (2019). Feature Based Approach for Detection of Smishing Messages in the Mobile
Environment. Journal of Information Technology Research, 12(2), 17–35.
Kasemsap, K. (2016). Investigating the roles of mobile commerce and mobile payment in global business. In
Securing transactions and payment systems for m-commerce (pp. 1–23). IGI Global.
Kim, C., Mirusmonov, M., & Lee, I. (2010). An Empirical Examination of Factors Influencing the Intention to
Use Mobile Payment. Computers in Human Behavior, 26, 310–322.
Liebana-Cabanillas, F. (2012). El papel de los sistemas de pago en los nuevos entornos electrónicos [The role of
payment systems in the new electronic environments] [Doctoral Thesis]. Department of Marketing and Market
Research. Universidad de Granada.
Liébana-Cabanillas, F., Muñoz-Leiva, F., Ibáñez-Zapata, J. A., & Rey-Pino, J. (2012). The role of mobile payment
systems in electronic commerce. Paper presented at the Acts of 41ª EMAC Conference, Lisbon, Portugal.
Liébana-Cabanillas, F., Ramos de Luna, I., & Montoro-Ríos, F. (2017). Intention to use new mobile payment
systems: A comparative analysis of SMS and NFC payments. Economic Research-Ekonomska Istraživanja,
30(1), 892–910. doi:10.1080/1331677X.2017.1305784
Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How Habit Limits the Predictive Power of Intentions:
The Case of IS Continuance. Management Information Systems Quarterly, 31(4), 705–737.
Lin, C., & Nguyen, C. (2001). Exploring e-payment Adoption in Vietnam and Taiwan. Journal of Computer
Information Systems, 51(4), 49.
López-Nicolás, C., Molina-Castillo, F. J., & Bouwman, H. (2008). An assessment of advanced mobile services
acceptance: Contributions from TAM and diffusion theory models. Information & Management, 45, 359–364.
Lu, Y., Yang, S., Chau, P. Y. K., & Cao, Y. (2011). Dynamics Between the Trust Transfer Process And Intention
to Use Mobile Payment Services: A Cross-environment Perspective. Information & Management, 48, 393–403.
Meharia, P. (2012). Assurance on The Reliability Of Mobile Payment System And Its Effects On Its’ Use: An
Empirical Examination. Accounting and Management Information Systems, 11, 97–111.
Volume 14 • Issue 1
Messick, S. (1988). Validity. In R. L. Linn (Ed.), Educational Measurement (3rd ed.). Macmillan.
Mun, P. Y., Khalid, H., & Nadarajaha, D. (2017). Millennials’ Perception on Mobile Payment Services in
Malaysia. Paper presented at the 4th Information Systems International Conference, ISICO 2017, Bali, Indonesia.
Muñoz, F. (2008). La adopción de una innovación basada en la Web [The adoption of a web-ased innovation]
(PhD Thesis). Universidad de Granada, Spain.
Muriu, M. D. (2017). Strategy Implementation and Performance of Mobile-Commerce In Kenya’s Commercial
Banks (Doctoral dissertation). United States International University-Africa.
Parsons, A. G. (2002). Non-functional motives for online shoppers: Why we click. Journal of Consumer
Marketing, 19(5), 380–392.
Pavlou, P. A. (2002a). A theory of planned behavior perspective to the consumer adoption of electronic commerce.
Management Information Systems Quarterly, 30, 115–143.
Pavlou, P. A. (2002b). What drives electronic commerce? A theory of planned behavior perspective. Academy
of Management Proceedings.
Polatoglu, V. N., & Ekin, S. (2000). An empirical investigation of the Turkish consumers’ acceptance of Internet
banking services. International Journal of Bank Marketing, 19(4), 156–165.
Ringle, C. M., Wende, S., & Becker, J. M. (Producer). (2015). SmartPLS 3. Retrieved from
Rohm, A. J., & Swaminathan, V. (2004). A typology of online shoppers based on shopping motivations. Journal
of Business Research, 57(7), 787–487.
Schierz, P. G., Schilke, O., & Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment
services: An empirical analysis. Electronic Commerce Research and Applications, 9, 209–216.
Shankar, A., & Datta, B. (2018). Factors affecting mobile payment adoption intention: An Indian perspective.
Global Business Review, 19(3_suppl), S72-S89.
Sharma, K., & Gupta, B. B. (2019). Towards Privacy Risk Analysis in Android Applications Using Machine
Learning Approaches. International Journal of E-Services and Mobile Applications, 11(2), 1–21.
Shim, S., Eastlick, M. A., Lotz, S. L., & Warrington, P. (2001). An online prepurchase intentions model: The
role of intention to search. Journal of Retailing, 77(3), 397–416.
Shin, D. H. (2009). Towards an understanding of the consumer acceptance of mobile wallet. Computers in
Human Behavior, 25, 1343–1354.
Stevenson, J. S., Bruner, G. C., & Kumar, A. (2000). Webpage background and viewer attitudes. Journal of
Advertising Research, 40(1/2), 29–34.
Teoh, W. M. Y, Chong, S. C, & Chua, J. W. (2013). Factors affecting consumers’ perception of electronic
payment: an empirical analysis. Internet Research, 23(4).
Tinga, H., Yacobb, Y., Liew, L., & Lau, M. W. (2015). Intention to Use Mobile Payment System: A Case of
Developing Market by Ethnicity. Paper presented at the 6th International Research Symposium in Service
Management, IRSSM-6 2015, UiTM Sarawak, Kuching, Malaysia.
Venkatesh, V., & Bala, H. (2008). Technology Acceptance model 3 and a research agenda on interventions.
Decision Sciences, 39, 273–315.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four
longitudinal field studies. Management Science, 46, 186–204.
Wan, G., & Che, P. (2004). Chinese air travelers’ acceptance towards electronic ticketing. Proceedings of
Engineering Management Conference.
Wang, Y., Sun, S., Lei, W., & Toncar, M. (2009). Examining Beliefs and Attitudes toward Online Advertising
among Chinese Consumers. Direct Marketing: An International Journal, 3(1), 52–66.
Volume 14 • Issue 1
Masud Ibrahim is currently PhD Candidate at the School of Finance and Economics, Jiangsu University, China. He
is also a lecturer at the Department of Management Studies Education, University of Education, Winneba. He has
over 8 years experience in teaching and research. He has published extensively in top peer reviewed journals. His
research interests include: Innovation management, Entrepreneurship; Financial services marketing; Hospitality
& Tourism Marketing; and Electronic marketing.
Stephen Arthur is a Lecturer at Valley View University. He is a PhD candidate at Adventist University of the
Philippines. His research interest is entrepreneurship, innovations, and small business development. He is currently
working on his PhD Dissertation on Social Support, Entrepreneurial Competencies, Business Opportunities and
Entrepreneurial Intentions of university students in Ghana.
Wong, C. C., & Hiew, P. L. (2005). Diffusion of mobile entertainment in Malaysia: Drivers and barriers.
Enformatika, 5, 263–266.
Zhang, A., Yue, X., & Kong, Y. (2011). Exploring culture factors affecting the adoption of mobile payment.
Proceedings of the International Conference on Mobile Business.
Zhao, Y., & Kurnia, S. (2014). Exploring Mobile Payment Adoption in China. Paper presented at the Pacific
Asia Conference on Information Systems (PACIS 2014).
ResearchGate has not been able to resolve any citations for this publication.
Full-text available
Smishing is a security attack that is performed by sending a fake message intending to steal personal credentials of mobile users. Nowadays, smishing attack becomes popular due to the massive growth of mobile users. The smishing message is very harmful since its target to financial benefits. In this article, the authors present a new feature-based approach to detect smishing messages in the mobile environment. This approach offers ten novel features that distinguish the fake messages from the ham messages. In this article, the authors have also identified the nineteen most suspicious keywords, which are used by the attacker to lure victims. This article has implemented these features on benchmarked dataset and applied numerous classification algorithms to judge the performance of the proposed approach. Experimental outcomes indicate that proposed approach can detect smishing messages with the 94.20% true positive rate and 98.74% overall accuracy. Furthermore, the proposed approach is very efficient for the detection of the zero hour attack.
Full-text available
In the early of 21st century, mobile payment became a hot topic after the burst of the internet, however its services are considered in their infancy stage and still quite new to the consumers in Malaysia. Therefore, there is a need to investigate the factors affecting consumers’ intention especially among the millennials to use mobile payment services in Malaysia which encourage the development of mobile payments as an innovative alternative payment method. In this study, perceived usefulness, perceived ease-of-use, perceived credibility and social influence were examined to identify the relationships with the consumers’ intention to use mobile payment services in Malaysia. The Extended Technology Acceptance Model (TAM) was used to construct the research framework of this study. Self-administered questionnaire was as the data collection tool in this study and 300 samples from Peninsular Malaysia were collected for data analysis. The findings show that all suggested factors have significant impact in affecting the consumers’ intention to use mobile payment services in Malaysia with perceived usefulness proved to be the strongest determinant. The implication and limitation of this study were discussed at the end of this paper.
Full-text available
The rapid growth of mobile technology among the world’s population has led many companies to attempt to exploit mobile devices as an additional tool in the business of sales. In this sense, the main objective of our study resides in comparing the factors that determine the acceptance by consumers of the SMS (Short Message Service) and NFC (Near Field Communication) mobile payment systems as examples of means of future payment. The model used in our research applies the classic variables of the Technology Acceptance Model, as well as that of Perceived Security, a model deriving from the review of the major relevant recent literature. The results achieved in this study demonstrate that there are differences in the factors that determine the acceptance in each of the systems, as well as the level of the Intention to Use. Finally, we highlight the main implications for management and cite some strategies to reinforce this new business in the context of new technical developments.
Full-text available
Purpose The purpose of this paper is to assess the correlations between mobile banking and inclusive development (poverty and inequality) in 93 developing countries for the year 2011. Design/methodology/approach Mobile banking entails the following: “mobile phones used to pay bills” and “mobile phones used to receive/send money”, while the modifying policy indicator includes the human development index (HDI). The data are decomposed into seven sub-panels based on two fundamental characteristics: regions (Latin America, Asia and the Pacific, Central and Eastern Europe, and Middle East and North Africa) and income levels (upper middle income, lower middle income and low income). Findings The results show that at certain thresholds of the HDI, mobile banking is positively linked to inclusive development. The following specific findings are established. First, the increased use of mobile phones to pay bills is negatively correlated with: poverty in lower-middle-income countries (LMIC), upper-middle-income countries (UMIC) and Latin American (LA) countries, respectively, at HDI thresholds of 0.725, 0.727 and 0.778 and inequality in UMIC and LA with HDI thresholds of, respectively, 0.646 and 0.761. Second, the increased use of mobile phones to send/receive money is negatively correlated with: poverty in LMIC, UMIC and Central and Eastern European (CEE) countries with corresponding HDI thresholds of 0.631, 0.750 and 0.750 and inequality in UMIC, CEE and LA at HDI thresholds of 0.665, 0.736 and 0.726, respectively. Practical implications The findings are discussed in the light of current policy challenges in the transition from the UN’s Millennium Development Goals to Sustainable Development Goals. Originality/value The authors have exploited the only macroeconomic data on mobile banking currently available.
Android-based devices easily fall prey to an attack due to its free availability in the android market. These Android applications are not certified by the legitimate organization. If the user cannot distinguish between the set of permissions requested by an application and its risk, then an attacker can easily exploit the permissions to propagate malware. In this article, the authors present an approach for privacy risk analysis in Android applications using machine learning. The proposed approach can analyse and identify the malware application permissions. Here, the authors achieved high accuracy and improved F-measure through analyzing the proposed method on the M0Droid dataset and completed testing on an extensive test set with malware from the Androzoo dataset and benign applications from the Drebin dataset.
Purpose The purpose of this paper is to examine m-payment adoption for the bottom of pyramid (BoP) segment in a developing country context. Design/methodology/approach A questionnaire was distributed to 247 BoP customers in Bangladesh. Data were analysed by employing confirmatory factor analysis and Structural Equations Modelling. Findings The results show that performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC), habit and social influence (SI) significantly influence the BoP segment’s behavioural intention (BI). It is revealed that PE, lifestyle compatibility (LC), SI and habit have relatively stronger effects being higher predictor of intentions. Again EE and FC have relatively lower effects on m-payment BI. On the other hand, hedonic motivation (HM) and price value (PV) are two non-significant predictors of m-payment adoption. Practical implications The study recommends that financial institutions, such as banks and other non-banking service firms, need to know the antecedents affecting BI suggested by the unified theory of acceptance and use of technology (UTAUT2) theory along with “LC”. This will increase m-payment adoption for the BoP segment in developing countries. Originality/value To the extent of researcher’s knowledge, none of the previous studies using the UTAUT2 theory to examine m-payment adoption for BoP segment. This study contributes empirical data to the predominantly theoretical literature by offering a deeper understanding of the inclusion of LC, which is one of the significant antecedents in explaining BoP segment’s m-payment adoption.
This study aims to identify the factors affecting mobile payment (m-payment) adoption intention in India by proposing a conceptual framework based on technology acceptance model (TAM). In addition to construct of TAM, four user-centric constructs have been added to evaluate m-payment adoption intention in India. The proposed research framework was empirically tested by data collected from 381 potential m-payment service users, through online and offline survey. Data were analysed using structural equation modelling (SEM) technique. The results exhibit that perceived ease of use (PEOU), perceived usefulness (PU), trust, and self-efficacy (SE) have a significant positive impact on m-payment adoption intention. However, subjective norms (SN) and personal innovativeness (PI) have no significant impact on m-payment adoption intention. Findings of the study have important theoretical and practical implications, particularly to understand important user-centric factors affecting m-payment adoption.
This chapter aims to investigate the roles of mobile commerce (m-commerce) and mobile payment (mpayment) in global business, thus revealing the overview of m-commerce; m-commerce and Technology Acceptance Model (TAM); m-commerce and trust; the concept of m-payment; the importance of mcommerce in global business; and the importance of m-payment in global business. The operation of m-commerce and m-payment is needed for modern organizations that seek to serve suppliers and customers, increase business performance, strengthen competitiveness, and achieve continuous success in global business. Therefore, it is required for modern organizations to investigate their m-commerce and m-payment, develop a strategic plan to regularly check their practical advancements, and immediately respond to m-commerce and m-payment needs of customers in modern organizations. The chapter argues that applying m-commerce and m-payment has the potential to enhance business performance and reach strategic goals in global business.