Electronic Commerce Research and Applications 60 (2023) 101275
Contents lists available at ScienceDirect
Electronic Commerce Research and Applications
journal homepage: www.elsevier.com/locate/elerap
Understanding the continuous usage of mobile payment integrated into
social media platform: The case of WeChat Pay
Xuguang Li a, Xuekun Zhu b, Yingying Lu a, Dingyu Shi b, Weihua Deng c, *
a
Institute of Information Management, Shandong University of Technology, 266Xincun West Road, Zibo City 255000, China
Department of Information Resource Management, Business School, Nankai University, 94 Weijin Road, Tianjin 300071, China
c
Department of Information Management, College of Public Administration, Huazhong Agricultural University, No.1. Shizishan Street, Hongshan District, Wuhan
430070, China
b
A R T I C L E I N F O
A B S T R A C T
Keywords:
Mobile payment
WeChat Pay
Perceived value
Perceived entertainment value
Social media
Continued usage intention
Media system dependency
WeChat Pay has proven extremely popular among consumers in the growing market of China. This paper ex­
plores the influencing factors upon its continued use. Both the survey data from 568 WeChat Pay users and semistructured interview with 30 interviewees were utilized. Drawing on the stimulus-organism-response (S-O-R)
model, this paper constructs a model to understand how social influence and platform factors affect users’
perceived value and satisfaction and, ultimately, influence their continuous usage intention of WeChat Pay. It
reveals that social influence and platform factors can indirectly promote continuous usage intention through
perceived value (PV), which consists of tangible functional values and intangible values (i.e., perceived enter­
tainment value, interactive value and social value). Especially, intangible values have a much stronger impact on
users’ satisfactions than tangible value. The perceived entertainment value from Red Envelope games is the
strongest factor of PV. Several implications for academia and practitioners are offered.
1. Introduction
Given the widespread use of mobile devices and users’ needs for
secure, reliable, and economical payment, mobile payment services
(MPS) have increasingly become part of everyday life (Miao and Jaya­
kar, 2016). Mobile payments are a novel payment mode for goods,
services, and invoices in transactions via mobile devices like smart­
phones (Dahlberg et al., 2008). The WeChat Pay service, launched into
the Chinese mobile payment market by Chinese IT company Tencent in
2013, has added a novel mode of mobile payment that offers a digital
wallet incorporated into the WeChat social media platform. WeChat Pay
has proven extremely popular amongst consumers in a growing market.
It occupied a 38.47% share of China’s mobile payment market, which
was valued at 18.56 billion yuan in 2020 (IResearch, 2020). The total
number of active user accounts of WeChat and WeChat Pay, combined,
has reached over 800 million, and 75.6% of WeChat users frequently use
WeChat Pay for payment (WATCH, 2021). The WeChat Pay service has
been described by Munger (2018) as one of the few rivals of multina­
tional financial service companies such as American Express, Master­
card, and Visa. Moreover, it is becoming a widely accepted idea that
social media is developing toward multi-purpose service platforms that
incorporate a wide variety of features and functions (Yang et al., 2012).
Therefore, the success of WeChat Pay deserves attentions from aca­
demics and stakeholders in the fields of social media and mobile
payment.
In practice, the fast-increasing popularity of social media platforms,
such as Facebook, LinkedIn, Twitter and WeChat, has formed vast op­
portunities for new electronic commerce and business models (Liébana
Cabanillas et al., 2018). The rapidly increasing new mobile social apps
are providing a wide variety of functions to meet users’ multiple needs
(Hsiao et al., 2016). Given the continued growth of social media use,
Boyd and Ellison (2007) suggest that companies should align themselves
with users to fully benefit from the opportunities provided by new social
media. Both WeChat and Facebook have developed social commerce
platforms incorporating WeChat Pay or Facebook Pay which can exer­
cise market power (Pöyry et al., 2013). Milner (2003) proposes that the
adoption of novel social media in a country demonstrates market po­
tential and a stable model, and leads to its adoption in other countries.
Accordingly, it is of theoretical value to provide an understanding of
users’ continued usage intentions of WeChat Pay, a novel payment mode
incorporated into a popular social media platform in the Chinese mar­
ket, to bring insights into the development of MPS and develop new
* Corresponding author.
E-mail address: dengwhyi@mail.hzau.edu.cn (W. Deng).
https://doi.org/10.1016/j.elerap.2023.101275
Received 27 May 2022; Received in revised form 7 May 2023; Accepted 22 May 2023
Available online 25 May 2023
1567-4223/© 2023 Elsevier B.V. All rights reserved.
X. Li et al.
Electronic Commerce Research and Applications 60 (2023) 101275
business values in other regions.
There is a considerable amount of literature on the continuous use of
mobile payments (e.g., Chen and Li, 2017; Mensah, 2021; Mensah et al.,
2021). In contrast, among the relatively few studies that have addressed
usage behaviors in the context of WeChat Pay, Huang and Zhang’s
(2017) research concentrates on its initial adoption as well its influ­
encing factors of perceived relative technical advantages. To explore
factors affecting WeChat Pay’s continued use, the rest few studies
mainly focus on the perspective of functional value or technical ad­
vantages, including performance expectancy, perceived usefulness,
perceived ease of use, perceived service quality, as well as perceived
security and privacy issues (Mensah, 2021; Mensah et al., 2021; Mom­
beuil and Uhde, 2021; Mu and Lee, 2017). Users’ willingness to use or
re-use a technology is related to their perception of its value (functional
and or non-functional) (Sweeney and Soutar, 2001). Perceived value
(PV), which refers to a user’s overall evaluation of a service or product,
has been proven to be a significant determinant of repeat sales (Zei­
thaml, 1988). Although consumers’ behavioral intentions can be driven
by multiple values (Kim et al., 2012), the above mentioned existing
research on WeChat Pay mainly concentrates on its functional values to
explore factors influencing its continued use, and other dimensions of its
value, especially values about social gratification obtained from using
the social media platform of WeChat, have not yet been much explored.
Moreover, Mombeuil and Uhde’s (2021) research is based on a survey of
foreign users living in China, rather than a much larger population of
Chinese users in the home market and national cultural context.
Therefore, in order to gain a more systematic understanding about
the mechanism of Chinese users’ continued use of WeChat Pay in the
home culture, there is great value in empirically exploring factors from
multiple value dimensions in promoting continued intentions. There­
fore, from the main theoretical perspective of PV, this study proposes a
theoretical framework based on the stimulus-organism-response (S-O-R)
model to understand the factors which exert either positive or negative
influences on the continued usage intention (CUI) of WeChat Pay, a case
of the MPS integrated into a mobile social media platform. The empirical
data informing the framework consists of 568 questionnaires completed
by Chinese WeChat Pay users from different backgrounds and regional
areas. This data is complemented by thematic analysis of 30 interview
transcripts to understand WeChat Pay users’ feelings and perceptions
about their continuous use behaviors and the associated influencing
factors.
The paper is organized as follows. Section 2 introduces WeChat Pay
and its associated constructs, then reviews the influencing factors on
continued use of mobile payment from the main perspectives of PV.
Section 3 constructs the S-O-R model integrated with MPS and proposes
the hypotheses. Section 4 explains the research method, including the
research stages, data sampling strategy, data collection and descriptive
statistics. Section 5 presents the results of the data analysis and hy­
potheses testing. Section 6 discusses the underlying mechanisms of these
influencing elements, complemented by findings from thematic anal­
ysis. Section 7 outlines the theoretical contributions and practical im­
plications of this research.
payment and online payment). Mobile users can be liberated from the
temporal and spatial constraints of traditional payment modes and
conduct ubiquitous payments via mobile devices.
Users’ continuous usage is vital for the success of MPS (Ye et al.,
2019). Existing research has examined influencing factors upon MPS
users’ CUI (Chen and Li, 2017; Hwang et al., 2021; Jun et al., 2018). In
the above studies, the identified factors affecting post-adoption/postpurchase intensions of MPS are mainly investigated from the perspec­
tive of users’ cognition or psychology, including perceived usefulness
and perceived value (Chen and Li, 2017; Jun et al., 2018), function/
performance of the technical platform (Hwang et al., 2021; Morosan and
DeFranco, 2016) and the social context or environment, i.e., social in­
fluence (Bailey et al., 2017). Perceived value, including perceived use­
fulness and enjoyment, significantly affects adoption intention to MPS
(Jun et al., 2018). Function/performance of the technical platform,
including convenience, interoperability, platform security, system sta­
bility and visual attractiveness, has been proven to affect CUI of mobile
payment (Hwang et al., 2021; Morosan and DeFranco, 2016). The pos­
itive relationship between social influence and consumers’ continuous
adoption of MPS is empirically revealed by Bailey’s et al. (2017)
investigation. Besides these influencing factors, Chen and Li (2017) has
explored the psychological mechanism and revealed that perceived
usefulness can promote users’ satisfaction and further affect their will­
ingness to continuously use MPS.
As for the new mode of mobile payment, WeChat Pay, which is in­
tegrated into the mobile social app WeChat, is globally adopted by
consumers because of its relative convenience and better user experi­
ence compared with traditional payment methods (Mombeuil and Uhde,
2021). Most previous research focuses on functional performance fac­
tors influencing continued usage of WeChat Pay, including performance
expectancy, perceived usefulness, perceived ease of use, perceived ser­
vice quality, compatibility, complexity, as well as security and privacy
issues (Mensah, 2021; Mensah et al., 2021; Mombeuil and Uhde, 2021;
Mu and Lee, 2017). These factors mainly highlight the functional value
of WeChat Pay. Regarding users’ cognition or phycological factors,
many researchers have proven that trust and self-efficacy significantly
affect the continued use of WeChat Pay (Mensah, 2021; Mensah et al.,
2021). Mensah’s (2021) research found that social influence has a sig­
nificant impact on continued usage of WeChat Pay whereas Mu and Lee
(2017) suggest that it does not.
Considering the entertainment and social attributes of WeChat Pay
that contribute to its prevalence in China (Phua, 2021), it is necessary to
investigate the effect of non-functional value factors on users’ intention
for continuous usage. This paper considers the continuous use of WeChat
Pay as behavioral reactions and aims to analyze critical value factors
leading to re-usage intentions and psychological procedures forming this
influencing mechanism.
2.2. Perceived value
Although there is limited literature on the continuous usage of MPS,
the behavioral phenomenon of continuous use has received much
attention in the information system domains. The continuous usage of
information systems has been explored from different theoretical per­
spectives, especially the perceived value (PV) theory (Bhattacherjee,
2001). In particular, PV is multifaceted and complex, since it can be
defined from the perspectives of economics, social psychology, and
benefits. The economic perspective suggests that value can be created
when goods are purchased at a cheaper price (Hinterhuber, 2004). The
socio-psychological perspective emphasizes the creation of value from
the meaning of certain goods or services to the customer group (Howard
and Sheth, 1969). The benefit perspective stresses that PV is consumers’
holistic assessment of the utility of perceived benefits and perceived
costs (Zeithaml, 1988). Furthermore, several studies have demonstrated
that PV has produced various values, such as increasing user loyalty and
satisfaction, and forming a stronger behavioral intention to use a
2. Research background and theoretical basis
2.1. Continued usage intention of MPS and WeChat Pay
Mobile payment can be classified into remote payment and prox­
imity payment (Srivastava et al., 2010). Zhou (2013) states that remote
payment requires users to connect to remote payment servers to make
payment. It can be further classified into mobile internet payment ser­
vices and mobile banking. Proximity payment refers to payment via
users’ mobile phones on the spot, for instance, payment of public
transport tickets and bills payment, and so on (Giovanis et al., 2022).
According to Zhou (2013), the primary advantage of mobile payment is
its ubiquity, compared to traditional payment modes (i.e., offline
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Electronic Commerce Research and Applications 60 (2023) 101275
particular information system or technology (Lee et al., 2014; Li and Li,
2021).
In this paper, PV is selected as the inner state which drives users’
continuous usage. First, perceived value theory focuses on “perceived
performance” rather than on factors such as “expectations”. It can be
applied to interpreting the adoption of specific types of new product or
service, such as mobile instant messaging services (Basak and Calisir,
2015), and mobile social media applications (Ahmad and Sun, 2018).
Given that WeChat Pay is an MPS integrated in the social media platform
of WeChat, it makes PV a suitable theoretical basis for exploring this
novel mode of MPS. Second, since WeChat Pay is used for many reasons
(e.g., entertainment and socializing) beyond fulfilling specific payments,
PV can be employed as a multidimensional concept to explain its user
adoption. Venkatesh et al. (2008) also suggest that the concept of use
should be viewed as a multidimensional construct rather than a unidi­
mensional construct as its dimensions can be driven differently by in­
tentions, expectations, and facilitation conditions. Therefore, PV from
the use should also be multi-dimensional based on varying intentions
and expectations.
Sweeney and Soutar (2001) conceptualized value as a multidimen­
sional construct. There is no consensus on the classification of its di­
mensions (Lee et al., 2014). Several proposals about the elements
defining the concept of value in consumption values theories were
suggested. Sheth et al. (1991) proposed five dimensions of consumption
values in consumer choice: social, emotional, functional, epistemic and
conditional. Based on that, Sweeney and Soutar (2001) identified four
value dimensions in measuring consumption values driving purchase
attitude and behaviors in both pre-purchase and post-purchase situa­
tions: emotional, social, quality/performance, and price/value for
money. These four constructs consist of both utilitarian and hedonic
elements (Sweeney and Soutar, 2001). Accordingly, Pöyry et al. (2013)
proposed a more general way to divide it into utilitarian and hedonic
value. By incorporating the social factors, Kim et al. (2011) suggested
three dimensions of customer consumption value: functional, emotional,
and social. Functional value is the value created from the perceived
quality and expected performance of the product; emotional value is the
utility produced from the affective and emotional states generated by
the product; social value is the utility created from the product’s capa­
bility to promote social self-concept.
Most studies concur on the identification of functional and other
components (Lee et al., 2014). In other words, as stated by Fiol et al.
(2011), scholars generally agree that the underlying dimensionality
builds upon two factors: tangible (e.g., functional value) and intangible
(e.g., social and emotional value). Although this framework is usually
applied to analysis of the value of mobile services, there is no consensus
on the intangible factors related to mobile services (Hsu and Lin, 2015;
Pura, 2005). According to Zeithaml’s (1988) study on the multidimen­
sional concept of PV, “perceived performance” includes not only “fair
price” or “value for money” but also non-monetary issues. In other
words, PV theory can pay more attention to multidimensional
“perceived performance” in order to explore continued usage of WeChat
Pay.
identified as a medium’s innovative technical factors which can provide
more advantages compared to other MPS (Matemba and Li, 2018).
These external factors can be divided into people-related and
technology-related. In order to define the different impacts of two fac­
tors, this paper takes social influences and platform features as the
stimulus of PV, and satisfactory and CUI as their consequences. More­
over, to explore the integration of MPS and social media, media system
dependency theory will be used to investigate the moderating effect of
dependence on social media.
2.3. Social influences and platform feature
3.2. Hypothesis
Many other factors have been proposed as explanations for the
adoption of an information system, such as social influences, function­
ality, and compatibility (Kim et al., 2010; Yang et al., 2016). Social in­
fluence is defined by Rice and Aydin (1991) as the extent of influence on
interaction among individuals in the social network. It is also considered
by Venkatesh and Brown (2001) as the pressure from the social envi­
ronment to conduct specific behaviors. Hsieh (2021) has demonstrated
that social influence could explain the usage intention of MPS.
Meanwhile, Yang et al. (2016) have shown that platform features of
information systems are closely related to the intention and behavior of
initial and continuous usage of technology. Platform features can be
3.2.1. Organism: multidimensional construct of PV
In this SOR model, PV are considered as a core organism factor which
is a multidimensional construct that builds upon tangible (e.g., func­
tional value) and intangible (e.g., social and emotional value) value
dimension (Fiol et al., 2011). In the context of mobile payment, the
existing literature mainly focuses on functional dimension of PV (e.g.,
function/quality) as the influencing factors on CUI of mobile payment
(Zhou, 2013). For instance, Zhou (2013) identified three types of func­
tional value affecting continuous use of mobile payment: information
quality, system quality and service quality. However, as a mobile pay­
ment service integrated into a mobile social media app, perceived values
3. Research model and hypothesis development
3.1. Research framework of S-O-R
This study mainly explores the factors that influence continuous use
of the WeChat payment through inner procedure with a stimulusorganism-response (S-O-R) model integrated with MPS. Mehrabian
and Russell (1974) originally proposed the S-O-R paradigm, suggesting
that different environmental stimulus around individuals affect their
mental state and, consequently, affect their response behaviors. Stim­
ulus are those elements in the external environment that influence an
individual’s emotion or action (Sohaib and Kang, 2015). Organism is
personal inner state, which includes thoughts, emotions, and cognition
while response refers to the behavioral reactions that result from the
internal operations of organism (Li et al., 2021a,b).
The S-O-R model has been widely adopted for understanding human
behaviors, particularly for understanding consumers’ intention and be­
haviors (Chen et al., 2019; Kim and Park, 2019; Rao and Ko, 2021). Chen
et al. (2019) have studied the motives of consumers’ mobile payment
usage intention based on the S-O-R framework. Existing literature based
on the S-O-R model have confirmed that changes in human behavior are
associated with environmental elements (e.g., social presence, and sys­
tem and service quality) as well as inner state (e.g., perceived value and
satisfaction) (Chen et al., 2019; Kim and Park, 2019; Rao and Ko, 2021).
Therefore, it is considered appropriate to apply the S-O-R model to
explore the impact of payment technology on customers’ cognition and
CUI.
For the current study, it is hypothesized that stimulus affect users’
behaviors by influencing their inner state. Existing research has
considered perceived value as an inner state which affects CUI for mo­
bile services (Chen et al., 2019; Kim and Park, 2019; Rao and Ko, 2021).
Therefore, we particularly regard the PV as an organism and CUI as the
response. Meanwhile, since satisfaction has been regarded as a positive
emotion influencing usage intention (Chen et al., 2019) and perceived
risk has also been considered as an inner state affecting users’ satisfac­
tion (Mu and Lee, 2017), we consider satisfaction (SAT) and perceived
risk (PR) as the other elements of organisms. In line with previous
studies, which investigate social influence and platform features as the
external factors (Hsieh, 2021), we propose social influence (SI) and
platform features (PF) as the stimulus in this research. Based on this
model, we then propose the assumptions about the relationship between
these variables.
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Electronic Commerce Research and Applications 60 (2023) 101275
of WeChat Pay are bound to share features of customer value towards a
social media app, especially in terms of interactive value (i.e., main­
taining and expanding interpersonal relationships through social inter­
action) and social value (e.g., status seeking, social support, etc.). Hsiao
et al. (2016) identified three types of customer value influencing the CUI
of a social app: utilitarian motivation (i.e., perceived usefulness), he­
donic motivation (i.e., perceived enjoyment), and social influence (i.e.,
social ties). Values gained from using the mobile social apps of WeChat
mainly include hedonic gratification, emotional value, social gratifica­
tion, content gratification, information value, and social communication
value (Gan and Wang, 2015; Zhang et al., 2017). This indicates that
entertainment/hedonic, social and interactive gratifications play a
salient role in social media usage, and these are related to the intangible
factors in Fiol et al.’s (2011) PV framework. Consequently, in light of
Kim et al.’s (2011) dimension classification, by integrating the perceived
values of mobile social app and mobile payment, we propose that the PV
construct of WeChat Pay consists of four value dimensions: functional,
social, interactive and entertainment. Social value, interactive value and
entertainment value are seen as the intangible type while functional
value as tangible type, as suggested earlier.
Perceived Function Value (PFV) refers to the user’s overall percep­
tion of the utility or benefits obtained by using WeChat Pay in a specific
payment scenario and represents the tangible factors in the framework
set out by Fiol et al. (2011). In the context of WeChat Pay, functional
value can be interpreted as economic value and users’ judgments of
convenience and time savings (Cocosila and Igonor, 2015; Teo, 2001).
Perceived Social Value (PSV) refers to perceived usefulness in pursuing
social approval, status seeking and social support (Cocosila and Igonor,
2015; Park et al., 2009). Perceived Interactive Value (PIV) indicates the
perceived benefits for maintaining, improving and expanding interper­
sonal relationships through social interactions (Cocosila and Igonor,
2015; Katz et al., 1973; Lee et al., 2014). Perceived Entertainment Value
(PEV) emphasizes the user’s emotional experience of gaining the
happiness, excitement, and enjoyment of interacting with acquaintances
and attending entertaining activities provided by WeChat Pay (Cocosila
and Igonor, 2015; Zhang et al., 2017). As a multidimensional construct,
PV of WeChat Pay, a mobile payment service incorporated into a social
app, consists of tangible functional value from the payment service itself
and intangible values associated with the social media it is integrated
into, i.e., social value, interactive value and entertainment value.
Therefore, this study proposes the following research hypothesis:
H1: PV related to WeChat Pay consists of four dimensions: PSV, PIV, PEV
and PFV.
literature about adopting innovative IT products and services (Ven­
katesh et al., 2012). Shared usage experience of social apps is likely to
develop a common conversation basis for members in the same social
network (Hsiao et al., 2016). Group social ties create the opportunity for
online group members to recommend an innovative social media
product to peer members (Hsiao et al., 2016). Furthermore, social ties
among users can positively influence their intentions to continuously
use the social networking service provider and promote customer loy­
alty (Woisetschläger et al., 2011). Thus, it can indirectly promote users’
satisfaction towards the mobile payments in use. Moreover, PV is the
reflection of individuals’ subjective feelings, thus it can be influenced by
social influences of their social circumstances (Park et al., 2019). In
using WeChat Pay, the innovative information diffused via users’ social
network and others’ usage behaviors can shape users’ subjective per­
ceptions regarding product value. When more and more WeChat Pay
users in an individual’s social network use this new mode of mobile
payment, and send positive information about usage experience, the
individual will believe that it will bring similar values to themselves.
That is to say, the SI from WeChat Pay users’ social network can enhance
their perceptions of its value. Accordingly, the following hypothesis was
proposed:
H3: SI positively affects the PV related to WeChat Pay.
WeChat Pay’s platform features (PF) here can be explained as a series
of more innovative technical factors compared to other MPS. They
include a comparative advantage in being more convenient to use and to
interact with compared to traditional MPS (Mombeuil and Uhde, 2021;
Yang et al., 2016). The former comparative advantage is due to its
accessibility, time-saving, ubiquity, reliability, flexibility and wide
spread acceptance, and the latter is associated with its user-friendliness
(Mombeuil and Uhde, 2021; Yang et al., 2016). Innovative technical
factors are the overall evaluation of a user’s judgment on a service’s
superiority or excellence (Song et al., 2010). Kim et al. (2010) revealed
the impact of traditional mobile payment system characteristics upon
PV, that is, mobile compatibility, reachability, and ease of using mobile
payment for the first time across various mobile payment users. Besides
these traditional common platform features of mobile payment systems,
WeChat Pay’s more innovative technical features, which are greatly
related to its social app platform as described above, can bring more
positive emotional experiences to users such as convenience, joy and
social support, and, therefore, can enhance perceptions of its value.
Therefore, the following hypothesis was developed:
H4: PF positively affect the PV related to WeChat Pay.
3.2.4. Response: Continued usage intention
Bhattacherjee (2001) suggested that users’ perceived usefulness and
satisfaction together strongly affect CUI. Certain scholars have
confirmed that PV positively affects continuous usage behavioral
intention in using information systems (Yang et al., 2016). The greater
the perceived value generated in using WeChat Pay, the more likely
users are to increase their willingness of using it in a continuous way.
Therefore, PV of WeChat Pay, including its tangible value and intangible
value, gained by users from their usage experience can enhance their
CUI. Accordingly, the following hypothesis was proposed:
H5: PV related to WeChat Pay positively affects its users’ CUI.
Bhattacherjee (2001) suggested that higher levels of satisfaction can
generate stronger CUI in an online environment. Satisfaction (SAT) has
been proven to predict users continued use of mobile social media (Kuo
et al., 2009) and Internet banking services (Tsai et al., 2014). In online
payment activities using mobile service tools, satisfaction can also in­
crease users’ underlying and unconscious willingness to revisit or reuse
the platform service, which may result in long-term usage (Zhang et al.,
2017). In using WeChat Pay, more satisfaction in usage experience can
promote users’ reuse of this novel mode of MPS service in the long-term.
Therefore, the following hypothesis was developed:
H6: Users’ SAT with WeChat Pay positively affects their CUI.
3.2.2. Organism: Satisfaction
Certain scholars have proposed that satisfaction refers to the extent
to which a consumer perceives that the quality or performance of a
product (and/or service) has reached or exceeded desired outcomes
(Kim et al., 2007). It is the reflection of cumulative positive feelings
developed from multiple/continuous interactions with a service or
product (Oliver, 1980). Additionally, satisfaction is usually considered
as a unidimensional construct (Oliver, 1980). Unlike perceived value
which can emerge during all stages of the purchase process, even before
the usage experience, satisfaction is generated depending on use expe­
rience (Sweeney and Soutar, 2001). Li and Li (2021) revealed that
perceived value exerts positive effects on user satisfaction of third-party
mobile payments. Therefore, in the context of continuous usage of
WeChat Pay, users’ perceived value can also affect their satisfaction
towards this new mode of mobile payment. Users’ satisfaction with
WeChat Pay comes from the comfort, convenience, entertainment and
other social values associated with its use process. Therefore, the
following hypothesis was developed:
H2: PV related to WeChat Pay positively affects its users’ SAT.
3.2.3. Stimulus: Social influences and platform feature
Social influences (SI) have long featured in the information system
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Electronic Commerce Research and Applications 60 (2023) 101275
3.2.5. Other influencing factors: Perceived risk
Perceived risk (PR) is defined as subjective expectations of loss or
sacrifice in adopting a technology of risk (Sweeney and Soutar, 2001).
The negative impact of PR on mobile payment user satisfaction and
continuous usage has been demonstrated by many studies. For instance,
Daragmeh et al. (2021) indicated that perceived risk demotivates gen­
eration X to use mobile payment services. Thakur and Srivastava (2014)
found that PR in the form of perceived privacy risk, perceived security
risk and perceived monetary risk has a significant negative effect on
customers’ intention to use mobile payments. For WeChat Pay, users’
concerns about uncertainty and risks in making payment via this mobile
payment service could lower their satisfaction. Therefore, the following
hypothesis was developed:
H7: PR negatively affects WeChat Pay users’ SAT.
different usage levels vary in perceptions towards performance and risk,
which eventually influences their continued usage intention (Thakur
and Srivastava, 2014). Thakur and Srivastava (2014) found that usage
differences of mobile payment services can moderate the relationship
between perceived risk and usage intention. Ozdemir et al.’s (2008)
research on internet banking usage proves that there are perceptual
differences between heavy users who perceived the service as more
useful and less risky compared to non-adopters. When facing potential
risk caused by using WeChat payment, users with high-level MSD and
intensive usage would have fewer negative feelings and weaker risk
perceptions compared to users with low-level MSD. Thus, those with
high MSD may build a more negative relationship between PR and SAT.
For users with higher dependence on the social media platform WeChat,
the positive feedback from WeChat Pay service is stronger and more
frequent, and they perceive WeChat Pay to be more useful. Conse­
quently, their perceptions of value as well as satisfaction would bring in
more continued use behaviors. Thus, those with high MSD may build a
more positive relationship between SAT/PV and CUI.
Based on the above analysis, this research expects that media system
dependence on WeChat indirectly affects willingness to continue using
WeChat Pay by moderating the six hypothetical relationships proposed
earlier.
Hence, the following hypotheses were proposed:
H8a: MSD will positively moderate the relationship between PF and PV,
such that the positive effect is stronger when the MSD is strong.
H8b: MSD will positively moderate the relationship between SI and PV,
such that the positive effect is stronger when the MSD is strong.
H8c: MSD will positively moderate the relationship between PV and SAT,
such that the positive effect is stronger when the MSD is strong.
H8d: MSD will positively moderate the relationship between SAT and
CUI, such that the positive effect is stronger when the MSD is strong.
H8e: MSD will negatively moderate the relationship between PR and SAT,
such that the negative effect is weaker when the MSD is strong.
H8f: MSD will positively moderate the relationship between PV and CUI,
such that the positive effect is stronger when the MSD is strong.
Based on these hypotheses, an S-O-R model (as Fig. 1) was con­
structed to investigate how the social environment and platform factors
(i.e., stimulus) affect continuous use behavior of WeChat Pay service (i.
e., response) through the psychological procedure (i.e., organism). The
conceptual model provides a comprehensive framework for under­
standing users’ continuance intention with an MPS integrated in social
media (i.e., WeChat Pay). Two external factors, social influences (SI) and
platform features (PF), are the stimulus and reflect the situational
characteristics of WeChat Pay. PV, SAT, and PR are the organism. PV is a
multidimensional construct comprising four elements: perceived func­
tional value (PFV), perceived social value (PSV), perceived interactive
value (PIV) and perceived entertainment value (PEV). Satisfaction (SAT)
is proposed as the consequences of PV and can affect users’ continued
usage intention (CUI). Additionally, media system dependence (MSD) is
a moderating factor for the whole model.
3.2.6. Moderating factors: Social media dependence
Media system dependency (MSD) theory defines dependency as a
relationship between the goals of individuals and the extent to which
these goals are dependent upon the resources of media system for
creating, gathering, processing, and disseminating information (Zhang
and Zhong, 2020). Because dependency relations are goal oriented, the
goals’ scope and strength directly affect the strength of the dependency
between the user and the media (Zhang et al., 2021). Social media has
become an important way to obtain, disseminate and share information.
Thus, the phenomenon of social media dependence (which, in this
paper, concerns WeChat dependence) has been formed.
Research on IT dependence proves that MSD can indirectly affect
users’ rational use decisions by influencing their perception of tech­
nology. In exploring the impact of technology addiction on users’
behavior intentions, Turel et al. (2011) found that dependency
enhanced users’ perceived ease of use and perceived usefulness. Carillo
et al. (2017) identified the influence of MSD on users’ CUI for media
systems, finding that MSD could lead to individuals’ expectationconfirmation of the media system. Users with higher dependence on
media systems are more likely to perceive the value of payment tech­
nology on the effect of platform features and social environment, and
may obtain a stronger sense of satisfaction and willingness to continue
using it.
Users with high MSD usually rate their use experiences high and are
sensitive to the technical features improving the comfort of operation
(Ahuja and Thatcher, 2005). Part of the perceived value of WeChat Pay,
i.e., PFV, is generated from the evaluation of its functional features.
Thus, those WeChat Pay users with high MSD may build a more positive
relationship between PF and PV.
The users of online social platforms form a social network during
their communication, and their thoughts and behaviors are mutually
affected by each other in the network (Kim and Park, 2019). Users’
evaluation of the value of WeChat Pay can also be influenced by others
in their social network formed on the social media platform WeChat. For
WeChat Pay users with high MSD, the greater the influence of others
from their social network, the more likely they would be to make a
consistent evaluation of high value. Thus, those with high MSD may
build more a positive relationship between SI and PV.
The user’s satisfaction was affected by their value perception
(Cocosila and Igonor, 2015). MSD theory suggests that the dependency
relationship of individual-media is based on the perceived usefulness of
media to meet users’ specific goals (Ball-Rokeach, 1998). Accordingly,
users’ MSD on WeChat is formed and enhanced by its capacity to satisfy
specific needs to some extent. The greater the dependence on the social
media platform WeChat, the higher the expectations of satisfaction to­
wards its mobile payment service and perception of value would be. For
the WeChat Pay users with high-level MSD, their perceptions of value
could bring higher satisfaction expectations. Thus, those users with high
MSD may build a more positive relationship between PV and SAT.
The media impact on personal perceptions can be moderated by MSD
(Morton and Duck, 2001). New information technology users with
4. Methodology
4.1. The case of WeChat Pay: A novel MPS integrated in social media
WeChat Pay is a unique type of mobile payment, since it is integrated
in WeChat, China’s largest market-occupying social media app, and can
be used to complete payment quickly with smartphones. It is supported
by the third-party payment system of Tenpay and is a third-party plat­
form-led model, which is different from mobile operator-led, bank-led,
and hybrid models (Miao and Jayakar, 2016).
WeChat Pay has two distinct functions: multiple payment methods
and social payment functions. There are four payment methods: quick
payment (Fig. 2-a), QR code payment (Fig. 2-b), in-app web-based
payment (Fig. 2-c), and in-app payment (Fig. 2-d).
Fig. 2-a and 2-b show the offline scan payment function based on
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Electronic Commerce Research and Applications 60 (2023) 101275
H3
H7
H6
H2
H4
H5
H8a:MSD moderates PV->SAT
H8b:MSD moderates SI->PV
H8c:MSD moderates PF->SI
H8d:MSD moderates PV->CUI
H8e:MSD moderates SAT->CUI
H8f:MSD moderates PR->SAT
Fig. 1. The conceptual model of influencing mechanism of continued usage intention of WeChat Pay.
Fig. 2. Four payment methods and red envelope. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of
this article.)
two-dimensional code technology, which is widely used in traditional
small and high-frequency scenarios such as retail, catering, supermar­
kets and parking. Fig. 2-c shows in-app web-based payment: vendors
send product messages to the official accounts of their followers and
WeChat Pay enables the followers to buy items listed on the shopping
page. As shown by Fig. 2-d, WeChat Pay can be integrated in vendors’
apps. If the user makes a payment in another app, WeChat will be
authorized to process the payment.
Fig. 2-e shows the virtual Red Envelope (Hong bao红包) social pay­
ment function, named after the red envelopes containing money that are
sent as gifts during the Chinese New Year. It enables a certain amount of
money to be sent to contacts and groups as a gift. In the group red en­
velope, the money contained in red envelopes can be distributed
equally, or in random portions of different amounts. Red envelopes via
WeChat Pay have permeated every aspect of people’s lives, especially in
traditional festivals. It is estimated that more than eight billion red en­
velopes were sent to WeChat Pay users during the 2016 Chinese lunar
new year (Horwitz, 2016).
especially about the dimensions of users’ PV. A purposive sampling
strategy was used to select interviewees, who are WeChat users with
different ages, social backgrounds and regions, and different levels of
WeChat Pay usage. Thirty interviewees were recruited for face-to-face or
online interviews. They were from different age ranges (that is, under
30 years old, 30–40 years old, 40 years old and above) and different
regions of China (Central China, Eastern China, and Northern China),
and they had different jobs (including high school and college students,
white-collar workers, shop owners, coach drivers, etc.). The interview
usually lasted for 45–60 min and was recorded, and interview questions
were about users’ general demographic information, WeChat Pay usage
behaviors, continued use intentions, general comments about its PV, and
influencing factors upon continued use. A thematic analysis method was
used to code interview transcripts.
An initial questionnaire draft was designed, based on previous
studies and the interview results. Then, 50 WeChat Pay users were
invited to pilot test the questionnaire. The exploratory factor analysis
result based on these 50 collected questionnaires provided references for
the latter modification of question items in the questionnaires (and
following model verification). All ten constructs measured in this study
(PF, SI, PSV, PIV, PEV, PFV, SAT, CUI, PR, MSD) were measured using
multi-item scales adapted from prior studies with minor changes to fit
the specific research context (the measurement items are listed in Ap­
pendix 1 and 2). All of the adapted items from English literature were
4.2. Measurements
Both interview data and questionnaire data were collected in this
research. Semi-structured interviews were adopted to obtain an initial
understanding of users’ continuous usage behaviors of WeChat Pay,
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Electronic Commerce Research and Applications 60 (2023) 101275
translated into Chinese utilizing McGorry’s (2000) double-translation
methods to ensure the consistency of the Chinese-English question­
naire. PF, consisting of two items, was mainly operationalized from Kim
et al. (2010). SI, comprising four items, was mainly adapted and
modified from Venkatesh et al. (Venkatesh et al., 2003). The items used
to measure PIV, PSV, PEV and PFV, each having three items, were based
on the scale of Sheth et al. (1991), Sweeney and Soutar (2001), Teo
(2001), Park et al. (2009), Kim et al. (2010), Cocosila and Igonor (2015),
Lee et al. (2014) and Zhang et al. (2017), with appropriate modifications
pertinent to the continuous use of WeChat Pay. PR was measured by
three items adopted from Thakur and Srivastava (2014). SAT and CUI
were measured using the scale recommended by Bhattacherjee (2001).
MSD, with three items, was operationalized from Turel et al. (2011) and
Carillo et al. (2017). A five-point Likert scale, from strongly disagree to
strongly agree, was adopted to measure the ten constructs.
Table 2
Standardized item loadings, AVE, CR and Alpha values.
4.3. Survey data collection
In this research, an online survey was conducted. Both the conve­
nience sampling and snowball sampling techniques were adopted in
data collection by distributing the hyperlink of the created online
questionnaire on the WeChat platform. The online questionnaire used in
this research was designed on a survey website (i.e., Wenjuan.com).
Respondents were mainly accessed via social circles of research group
members, universities, companies and shops. The respondents were
usually invited to redistribute the hyperlink of questionnaire to their
contacts and groups on WeChat. In order to reach a large and repre­
sentative sample size, different types of rewards (e.g., small gifts, red
envelopes, and coupons) were offered to the respondents (Table 1).
In total, 809 completed questionnaires were collected. Of these, 241
responses were discarded due to questionnaires that fell far below the
mean value, or which had incomplete or invalid answers. Finally, 568
questionnaires were utilized for empirical analysis. The demographic
analysis of the samples was conducted via descriptive statistics and the
demographic profiles of the respondents are illustrated in Table 2. It
shows that most respondents were relatively young, which was in line
with the common characteristics of WeChat user groups (58.5% of users
are younger than 30) (Iqbal, 2022). Regarding the number of payments,
most respondents have some experience with WeChat payment (more
than 15 times). An attempt was made to ensure the respondents were
distributed in each main region of China rather than limited to
economically developed regions or economically backward areas, indi­
cating that the samples are considerably representative in terms of
regions.
Variables
items
λ
CR
AVE
Alpha
Platform features (PF)
PF1
PF2
0.664
0.756
0.671
0.506
0.666
Perceived interactive value (PIV)
PIV1
PIV2
0.789
0.797
0.772
0.629
0.772
Perceived social value (PSV)
PSV1
PSV2
PSV3
0.802
0.904
0.852
0.889
0.729
0.887
Perceived functional value (PFV)
PFV1
PFV2
PFV3
0.725
0.707
0.689
0.750
0.500
0.747
Perceived entertainment value
(PEV)
PEV1
PEV2
PEV3
0.772
0.739
0.777
0.807
0.582
0.806
Satisfactory (SAT)
SAT1
SAT2
SAT3
0.750
0.797
0.756
0.812
0.590
0.802
Continued usage intention (CUI)
CUI1
CUI2
0.850
0.853
0.841
0.725
0.840
Social influence (SI)
SI1
SI2
SI3
0.757
0.793
0.557
0.749
0.504
0.716
Perceived risk (PR)
PR1
PR2
PR3
0.696
0.901
0.735
0.824
0.612
0.819
three-step approach was conducted: a second-order confirmatory factor
analysis inspired by Marsh and Hocevar (1988), a structural equation
modeling (SEM) analysis, and a test of the moderating effect adopted
from Ping (1995).
5.1. Reliability and convergent validity analysis
Prior to the data analysis, the measurement instruments were eval­
uated for reliability. Reliability analysis aims to test the consistency,
stability, and dependability of data. Taking into account of the opera­
bility and efficiency of reliability, we analyzed only internal reliability.
As the Cronbach’s alpha (Alpha) values of all the constructs ranged from
0.666 to 0.887, exceeding the conventional cut-off level of 0.6 (Nunnally
5. Results
The research model was tested using AMOS 21 and SPSS 22, and a
Table 1
Descriptive statistics (N = 568).
Measure
Item
Percentage%
Measure
Item
Percentage%
Sex
Male
Female
<20
20–25
26–30
31–40
40–50
>50
35.4
64.6
10.7
20.8
11.9
24.6
23.9
8.1
Number of payments
<5
6–15
16–30
31
<100
101–500
501–999
>=1000
2.3
6.3
43.5
47.9
17.1
27.1
15.5
40.3
High school and below
16.5
Regions
College
Undergraduate
Master’s and above
19.9
44.4
19.2
Western area of China
Middle parts of China
Eastern area of China
Southern area of China
Northern area of China
13
37.1
14.8
9.9
25.2
Age
Education
Total amount paid
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Electronic Commerce Research and Applications 60 (2023) 101275
and Bernstein, 1978), the measurement instrument was proven to have a
sufficient internal consistency. Consequently, the data was found to be
appropriate for further analysis. The validity of data consists of
convergent validity and discriminant validity. As illustrated in Table 3,
all factor loading (λ) values in the confirmatory factor analysis of the
measurement model were greater than 0.6. Composite reliability (CR) of
constructs ranged from 0.671 to 0.889, and the values of the average
variance extracted (AVE) of every construct was over 0.5 and was sig­
nificant at the p < 0.001 level, so all values exceeded acceptable
thresholds (Bagozzi and Yi, 1988).
Discriminant validity refers to the extent to which a latent variable is
distinct from and uncorrelated with other latent variables. The
discriminant validity of the measurements is achieved when the square
root of AVE is larger than the correlation between that construct and all
other constructs (Bagozzi et al., 1981). Table 4 shows the correlation
matrix of the constructs and their square root of AVE value, which is
presented on the diagonal. The results indicate that every construct has
greater correlation with itself, showing satisfactory discriminant
validity.
Table 4
Testing of the PV’s multidimensional construct.
Hypotheses
Path
β
P
Results
H1a
H1b
H1c
H1d
PSV → PV
PIV → PV
PFV → PV
PEV → PV
0.739
0.779
0.743
0.887
***
***
***
***
Accepted
Accepted
Accepted
Accepted
1988), goodness-of-fit index (GFI) and adjusted goodness-of-fit index
(AGFI) should be 0.8 or above (Scott, 1995), and comparative fit index
(CFI) and increasing fitness index (IFI) should be 0.9 or above (Cheung
and Lee, 2009). Root mean square error of approximation (RMSEA) is
acceptable below 0.08 (McDonald and Ho, 2002). For our model, an
adequate fit (λ2/df = 2.461, GFI = 0.919, AGFI = 0.898, CFI = 0.946,
IFI = 0.947, and RMSEA = 0.051) was achieved for the measurement
model, which indicates that the model fits the empirical data
significantly.
Table 5 and Fig. 3 presents the results of path analysis for the hy­
pothesized model. All six hypotheses are validated and supported. SI (β
= 0.547, p < 0.001) and PF (β = 0.435, p < 0.001) has significant
positive associations with PV, which supports H3 and H4. SAT (β =
0.420, p < 0.001) and PV (β = 0.509, p < 0.001) is positively related to
CUI, supporting H5 and H6. Additionally, PV is significantly positively
associated with SAT (β = 0.796, p < 0.001), and PR is significantly
negatively associated with SAT (β = − 0.076, p < 0.05), which supports
H2 and H7.
The mediation effect of SAT can be identified in Fig. 3. The direct
effect between PV and CUI was 0.509 and the indirect effect of SAT was
0.334 (i.e., H2*H6). Thus, SAT has partial mediating effects between PV
and CUI. The results reveal that there are two paths between PV and CUI.
One is that PV directly affects CUI, and the other is that PV indirectly
affects CUI by stimulating satisfaction.
5.2. Hypothesis testing
5.2.1. Testing of the PV’s multidimensional construct
As stated in H1, this research conceptualizes PV as a second order
latent construct in the developed research model. To verify H1, a
second-order confirmatory factor analysis was conducted. This tech­
nique can be used to interpret scales as both multi-level and multidi­
mensional by bringing different dimensions under a common
overarching higher-level factor, and it involves two steps: first-order and
second-order (Marsh and Hocevar, 1988). The purpose of first-order
confirmatory factor analysis is to ensure a high correlation among
these factors. The results of the first-order confirmatory factor analysis
showed that the correlation coefficients of the covariate path between
PSV, PIV, PFV and PEV were all greater than 0.52, and closer to 0.6 (see
Appendix 3), which shows that a higher-order common factor can be
extracted from several factors (Bolton, 1980).
Based on first-order CFA, the second-order verification structure
model was established, taking PV as the second-order factor, including
PSV, PIV, PFV and PEV. The fit indices (λ2/df = 2.461, GFI = 0.919,
AGFI = 0.898, CFI = 0.946, IFI = 0.947, and RMSEA = 0.051) suggest
that the model with the four latent variables fit the data well. These
results clearly confirm hypothesis H1 that PV can be explained through
the four dimensions of value, namely, PSV (β = 0.739, P < 0.001), PIV (β
= 0.779, P < 0.001), PFV (β = 0.743, P < 0.001), and PEV (β = 0.887, P
< 0.001).
5.2.3. Exploring MSD’s moderating effect
In this research, WeChat Pay users were categorized into two types,
namely, higher MSD users and lower MSD users, based on their actual
responses to the MSD related questionnaire questions. According to their
responses, those who scored higher than the mean value of MSD (M =
3.86) were assigned to higher MSD users, while those who scored lower
than the mean value were grouped into lower MSD users. The results of
our WeChat Pay classifications showed that 394 respondents considered
themselves as higher MSD users, while 174 respondents identified
Table 5
Test results of the structural equation model.
5.2.2. Test results of the structural equation model
In the proposed model, there are six hypotheses about the relation­
ship of PV, SAT, CUI and other factors (e.g., H2, H3, H4, H5, H6, H7),
and the method of the SEM analysis was applied to test these hypotheses.
First, the overall goodness-of-fit of the measurement model can be
evaluated by a number of fit indices. It is suggested that χ2 relative to
degree of freedom (λ2/df) should range from 2.0 to 5.0 (Bagozzi and Yi,
Hypotheses
Path
β
P
Results
H2
H3
H4
H5
H6
H7
PV → SAT
SI → PV
PF → PV
PV → CUI
SAT → CUI
PR → SAT
0.796
0.547
0.435
0.509
0.420
− 0.076
***
***
***
***
***
*
Accepted
Accepted
Accepted
Accepted
Accepted
Accepted
Table 3
Discriminant validity result.
Construct
SI
CUI
SAT
PR
PEV
PFV
PSV
PIV
PF
SI
CUI
SAT
PR
PEV
PFV
PSV
PIV
PF
0.710
0.645
0.598
0.039
0.587
0.608
0.427
0.499
0.386
0.851
0.823
− 0.047
0.706
0.753
0.498
0.603
0.543
0.768
− 0.063
0.647
0.739
0.412
0.586
0.548
0.782
0.022
0.082
− 0.080
− 0.044
0.024
0.763
0.624
0.694
0.676
0.429
0.707
0.521
0.681
0.640
0.854
0.532
0.353
0.793
0.557
0.711
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Electronic Commerce Research and Applications 60 (2023) 101275
H3:
0.547***
H2:
0.796
***
H7:
-0.076*
H6:
0.42
***
H4:
0.435***
H5:
0.509***
Fig. 3. Analysis results of influencing mechanism of continued usage intention of WeChat Pay (N = 568).
themselves as lower MSD users. The path analysis results of WeChat Pay
user types are reported in Fig. 4 and Fig. 5, and the detailed test results
for the hypotheses are as follows. The path analysis results of WeChat
Pay user types are reported in Fig. 4 and Fig. 5, and the detailed test
results of the hypotheses are shown below.
First of all, since the perceived value was viewed as a second-order
construct consisting of four salient facets, the order of importance of
the key facets differs in two cases. In the case of higher MSD users (N =
394), the path coefficients of the four facets are arranged in descending
order as follows: PEV, PSV, PFV and PIV. On the contrary, in the case of
lower MSD users (N = 174), the order is PEV, PSV, PFV and PIV. Then, it
can be found that the path coefficients of H2-H7 in two cases are
absolutely different (see Fig. 4 and Fig. 5). In particular, the role of PV on
CUI (β = 0.384, p = 0.004 < 0.01) is less significant than that of the full
sample case (β = 0.509, p < 0.001).
Following that, a path-by-path comparison was conducted by eval­
uating a t-statistic of the absolute difference between the corresponding
path coefficients in the two cases (Ahuja and Thatcher, 2005).
with the sample of users with lower MSD (N = 174). Basically, there is
no statistically significant difference in the paths of “SI → PV”, “PF →
PV” and “PR → SAT”, which do not support H8a, H8b and H8e, and
other paths in the two cases all have a statistically significant difference
at 0.01 or 0.001 level. In particular, MSD positively moderates the effect
of PV on SAT (from 0.625 to 0.802) and CUI (from 0.384 to 0.529),
which supports H8c and H8f, and MSD negatively moderates the effect
of SAT on CUI (from 0.528 to 0.384), which supports H8d.
5.3. Interpretations of interview data
We have empirically tested the S-O-R model, as well as 13 hypoth­
eses. The interview analysis results, complement the findings drawn
from the questionnaire analysis and explained the reasons to some
extent, by providing WeChat Pay users’ perceptions, feelings and com­
ments about their WeChat Pay continued usage.
5.3.1. Verifiability of PV construct and the strongest role of PEV
This research finds that users’ PV of WeChat Pay is a multidimen­
sional construct that includes PFV, PSV, PEV, and PIV. The dimensional
analysis leads to four hypotheses, all of which were confirmed. This
empirical study confirms the existence of the four dimensions and their
effects on the overall concept of PV, which is consistent with the idea
that PV encompasses both tangible and intangible factors (Fiol et al.,
2011). Tangible value is related to the functional value, which refers to
the functional performance in certain conditions, including reduction of
time and cost (Teo, 2001). Intangible value, which is not related to
practical use, includes gratification factors of entertainment, status
seeking, social interactions, and so on. Given that WeChat Pay is inte­
grated into the social app WeChat, these intangible factors are relevant
to the social and psychological factors that motivate users to choose
particular media and content, as well as the associated attitudes and
behaviors (Cocosila and Igonor, 2015). In the existing literature, factors
(Path1 − Path2)
t=
[Spooled *sqrt(1/N1 + 1/N2)]
Where Path1 and Path2 represent the corresponding path co­
efficients in the two models.while N1 and N2 represent the sample sizes.
Spooled is the variance spooled estimator and was calculated using the
formula:
]
[
]
[
(N1 − 1)
(N2 − 1)
Spooled = sqrt{
* Se1 +
* Se2}
(N1 + N2 − 2)
(N1 + N2 − 2)
where Se1 and Se2 are viewed as the standard errors of the path co­
efficients in the two models.
Results presented in Table 6 depict a statistically significant differ­
ence between the model run with the full sample (N = 568) and that
H3:
0.533***
H2:
0.802
***
H7:
-0.08ns
H6:
0.384
**
H4:
0.432***
H5:
0.529***
Fig. 4. Analysis results of influencing mechanism of continued usage intention of WeChat Pay with high MSD (N = 394).
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Electronic Commerce Research and Applications 60 (2023) 101275
H3:
0.487***
H2:
0.665
***
H7:
-0.085ns
H6:
0.528
***
H4:
0.468***
H5:
0.384**
Fig. 5. Analysis results of influencing mechanism of continued usage intention of WeChat Pay with low MSD (N = 174).
Table 6
Model comparison between lower MSD users’ sample (174 respondents) and Higher MSD users’ sample (394 respondents).
Hypotheses
H1
H2
H3
H4
H5
H6
H7
PSV → PV
PFV → PV
PEV → PV
PIV → PV
PF → PV
SI → PV
PV → SAT
PV → CUI
SAT → CUI
PR → SAT
Lower MSD users’
sample (N = 174)
Higher MSD
users’ sample (N
= 394)
B
SE
B
SE
0.645
0.636
0.849
0.870
0.468
0.487
0.665
0.384
0.528
− 0.085
0.047
0.051
0.042
0.044
0.078
0.092
0.171
0.26
0.245
0.058
0.739
0.743
0.887
0.779
0.432
0.533
0.802
0.529
0.384
− 0.08
0.028
0.025
0.021
0.026
0.061
0.09
0.079
0.122
0.117
0.029
Spooled
t-statistics
Path coefficient Absolute difference
p-Value of the difference
Moderating results
0.197
0.193
0.176
0.189
0.258
0.302
0.328
0.406
0.396
0.195
5.912
5.066
1.248
− 11.091
− 1.534
1.676
4.591
3.925
− 3.997
0.282
0.106
0.089
0.02
0.191
0.036
0.046
0.137
0.145
0.144
0.005
***
***
0.213
***
0.125
0.094
***
***
***
0.778
Not support H8a
Not support H8b
Support H8c
Support H8f
Support H8d
Not support H8e
related to gratifications, including entertainment, information seeking,
socializing, and reputation/status attainment, are vital in using social
media to promote group discussions and social interaction (Zhang et al.,
2017).
Furthermore, a theoretically interesting finding is that PEV (β =
0.887) is the most significant element in influencing users’ PV of WeChat
Pay compared to other factors (e.g., PIV [β = 0.779], PSV [β = 0.739],
and PFV [β = 0.743]), as shown in Fig. 3. This finding is partially
different from classic Technology Acceptance Model (TAM) (Basak and
Calisir, 2015) and some other m-technology acceptance studies which
highlight perceived usefulness and perceived ease of use (Kim et al.,
2013). Eighmey and McCord (1998) define entertainment as the media
users’ feeling of being entertained and excited by using a particular
media. Papacharissi and Rubin (2000) further point out that users’
interaction with a particular media can generate entertainment that
meets their psychological needs for fun and pleasure.
The entertainment experience from WeChat Pay is mainly associated
with its Red Envelope function, which enables users to send cash
through electronic payments. Playing games of “grab red envelopes” via
WeChat Pay has swept China and frequently occurs in the interviewees’
family lives, social activities and work. The interview data reveals that
this is common in WeChat groups consisting of relatives, families,
friends, colleagues, and so on. For instance, one interviewee pointed out
the enjoyment gained from one red envelope grabbing game in their
WeChat classmate group:
As illustrated by the above interview transcript, the collective
entertainment experience of playing Red Envelope games can promote
socializing and integration, which means that the entertainment value
derived from Red Envelope games can further enhance respective PIV
and PSV. This shared entertainment value is one of the factors which
make WeChat Pay distinctive compared to other MPS. Furthermore, this
even works for the WeChat users with loose ties. Facilitation of social
interaction through such common entertainment experience is espe­
cially important for the WeChat group members with loose ties, that is,
people who do not communicate or socialize much, as reported by the
following interviewees:
“The WeChat group of our class is somewhat inactive. Once someone
sends a red envelope to our class group [for grabbing], the whole class will
be stirring. Even these lurkers join the game of red envelope grab. My
WeChat family group is also similar to that. The game of grab red enve­
lope will bring warmth (mutual feelings) to the family members who
seldom contact each other, create more interactions and
communications.”
Thus, entertainment value and socialization value are strongly
combined to enhance the social relationships in the Red Envelope
games. This aligns with Lee et al.’s (2012) proposition that maintaining
social relationships is an important motivator in using social networking
sites. In addition, according to Rubin (2008), a sense of belonging and
integration, which is vital for promoting socialization value, can be
achieved through mutual interactions such as those provided by the Red
Envelope function which provides shared entertainment value.
In addition, the social status of WeChat Pay users who actively send
red envelopes to chat groups and start this shared entertainment expe­
rience is promoted. In other words, the PEV of WeChat Pay can bring the
PSV (i.e., social status) to some users. Status attainment is a significant
motivator for users to participate in online activities (Lee and Ma, 2012).
“We all feel very happy when the game of grab red envelopes is played.
The rule of lucky draw set by the WeChat Red Envelope application
creates the luck king (e.g., the luckiest person who is assigned the biggest
amount of money). Then the chat groups will ask the luck king to send a
red envelope (for others to grab). There is another game of ‘tongue twister
red envelope’, which we are all interested in playing. These little games for
entertainment can create more interactions among us.”
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In the existing literature, there are two effective ways to promote social
status in online groups: 1). social media users interact with other group
members by participating in discussions that result in their status
establishment (Lee and Ma, 2012); 2). Sharing information and knowl­
edge enhances social status, recognition and popularity in online social
groups (Rafaeli and Ariel, 2008). This research finds that the altruistic
activity of sending red envelopes to WeChat groups is another way of
establishing status, as illustrated in the following interview data. This is
especially the case for those users with higher positions with respect to
gaining esteem and prestige from subordinates, as stated by an employee
working in a company.
confidence and develop habitual use behaviors with WeChat Pay. Prior
usage experience can strengthen the familiarity of online services and
result in habitual and ritualized usage behaviors (O’Brien, 2010). This
can be revealed by the following interview data.
“I use WeChat very frequently, and this leads me to use WeChat Pay a
lot.”
Prior usage experience of the Internet can help users perform various
tasks and reinforce their perceptions of self-efficacy (Hsu and Lin, 2015).
Similarly, the prior usage experience of WeChat Pay enables its users to
increase their perceived self-efficacy. Perceived self-efficacy is defined
as belief in one’s capabilities to organize and execute the course of ac­
tion required to produce given attainments” (Bandura et al., 1999). For
example, an elderly storekeeper stated:
“I think it is very easy to attract others’ attention by sending red envelopes
via WeChat Pay. One guy sends it, and all the group members grab for it.
At the lunar new year or other festivals, our managers or directors usually
send red envelopes to our colleagues’ WeChat group as consolation
money. Suddenly, I feel they grow in stature in my mind, especially when
their red envelopes contain a large amount of money, and we are driven to
work hard after grabbing them”.
“Nowadays everyone slowly turns to use WeChat Pay to pay and receive
money. Due to the influence of people around me and the development of
time, it is unavoidable to learn to use it…it becomes a fashion, and even
we elders can go with the tide.”
The above findings from interview data confirm the survey finding
that PEV is one of the most important influencing factors in continued
usage of WeChat Pay. In addition, the PEV promotes the PIV and PSV.
These three socializing gratification-related values are closely combined
and formulate the intangible value dimensions of PV embedded in the
use of WeChat Pay. Thus, enjoyment, close social relationships, the sense
of belonging as well as integration, and social status attainment from a
shared entertainment experience via the Red Envelope function, influ­
ence user satisfaction and promote the intangible values related to so­
cializing gratification rather than tangible value (e.g., PFV).
This interviewee believed that using WeChat Pay is a necessary skill
for running his business due to his customers’ payment habits. More
importantly, he considered that this is an important “new thing” that
requires him to keep in step with others and to remain up to date.
Therefore, the prior usage experience of WeChat Pay enables its users,
especially elderly users, to reinforce their beliefs that they can cope with
new developments and keep up with the times.
Long-term prior usage experience can reduce PR (β = − 0.08), as
shown in Fig. 4. Prior usage experience helps build trustworthy re­
lationships between the users and media use (Hsu and Lin, 2015).
Accordingly, long-term usage experience of WeChat Pay can offset PR.
Many interviewees expressed this:
5.3.2. The stronger effect of SI on PV
Although many studies assert that SI and PF are significant predictors
of people’s mobile payment usage intention (Yang et al., 2012), this
paper finds that SI (β = 0.547) has a stronger influence on PV than do PF
(β = 0.435), as shown in Fig. 3. This result is in line with the results of
Zhang et al.’s (2007) study that confirmed the effect of SI on PV related
to WeChat (Zhang et al., 2017). It is also strongly associated with the fact
that WeChat Pay is integrated in WeChat and is strongly influenced by it.
SI can be summarized as “network externalities”, which refers to “the
utility that a user derives from consumption of the good increases with
the number of other agents consuming the good” (Katz and Shapiro,
1985: 424). Previous studies modeled network size as a main component
of network externalities, which emphasizes that network externalities
arise depending on the total number of purchasers or users of the same
network product (e.g., Zhang et al., 2017). As the largest mobile social
media service provider in the Chinese market, WeChat has the largest
network size. As for WeChat Pay, existing users can build connections
with more potential participants, and thus access greater network utility
enabled by WeChat. According to the interview results, many users’
continuous use behavior is the result of influences from families and
market. For example, a coach operator reported:
“I use WeChat very frequently, and this leads to using WeChat Pay a lot.
At the beginning, I was a bit worried about the risk of using WeChat Pay.
Later, I used it lots of times, and nothing risky occurs, so I’m not con­
cerned about this anymore.”
As a result of MSD and continuous usage, the stickiness of users to­
ward WeChat Pay can be enhanced, and vice versa. Stickiness is defined
as the capability of attracting and retaining users and extending the
duration of their stay. Stickiness positively influences usage intentions
(Lin, 2007) and is created when WeChat users spend plenty of time
utilizing the service (Lien et al., 2017). Likewise, similar usage experi­
ence of WeChat Pay can also facilitate and strengthen stickiness. For
example,
“After using WeChat Pay for several years, I get used to make payments
via it when I buy vegetables in the markets, go shopping in the mall, and
buy bus tickets. It is quite habitual for me to use WeChat Pay and I no
longer bring any cash now.”
WeChat Pay users of different MSD levels also have varying attention
focus towards the internal construct of PV. For users of high-level MSD,
who frequently use WeChat Pay in their work and daily lives, their
concerns focus more on PFV, which can greatly reduce the cost of time
and efforts in their transactions, as revealed by the following two in­
terviewees (i.e., self-employed people and shop owner):
“My family all use WeChat. Many passengers also use WeChat to buy
tickets now, so I have to use WeChat Pay for sales.”
5.3.3. The significant moderating effect of MSD
As shown in Fig. 4 and Fig. 5, WeChat dependence exerts a signifi­
cant moderating effect in the whole model: the stronger the dependence
of users on the WeChat platform, the easier they accept the influence of
internal (e.g., PV) and external factors (e.g., PF and SI), and the more
they are willing to continue use it. This result can be better explained by
the WeChat users’ prior usage experience. Gratifying outcomes can
enhance media usage and promote users’ positive perception of their
prior experience, and in turn enhance their continued usage experience
(Ko et al., 2005).
Users with long-term usage experiences of WeChat can boost their
“It is very convenient to do business via WeChat Pay. I used to wait for
others to make payments [in person] before. Now they can directly
transfer the money to me on WeChat Pay without seeing each other. I can
immediately receive the money once they make the transfer. It saves lots
of time. You also don’t need to give change compared to cash payment.”
“I frequently use WeChat because I need to contact others in my business.
Communicating with customers and business partners on WeChat is very
important. I also frequently use WeChat Pay when the transaction
amount is below 20,000 yuan… It is very convenient to use it and all you
need is to input the password to make transfer of account.”
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What users of low-level MSD, who are light users of WeChat Pay, care
about most is the PIV. This is quite apparent for elderly users who use
WeChat Pay to send red envelopes and give money to their families to
maintain family relationships and promote communication with their
families, as revealed by the older interviewees:
This research identifies that both SI (social influences) and PF
(platform factors) can indirectly promote CUI through PV, which means
users’ CUI is affected by both people-related and technology-related
factors However, SI has a stronger influence on PV than PF do, due to
the influence of the social media platform of WeChat. PV consists of two
types of values: 1) tangible values (i.e., PFV), for instance, the reduction
of time and economic cost; 2) intangible values (i.e., PIV, PSV and PEV),
which are associated with the socializing gratification of social inter­
action, social status, and entertainment. Intangible values play a much
stronger role than tangible values (e.g., PFV) in positively influencing
SAT through the tight interrelations of the three social gratification
related values. Notably, the PEV emerging from common entertainment
experience of Red Envelope games is the strongest influencing factor of
PV, and it also directly promotes social interactions and associated social
integration (i.e., PIV), and social status attainment (i.e., PSV). SAT plays
a mediating role between PV and CUI, creating two paths between PV
and CUI. Some users choose to use WeChat Pay continuously after
perceiving its value while others choose to use it continuously after their
satisfaction is improved through perceived value.
MSD (i.e., WeChat dependence) has a significant moderating effect
on the relationship between the predictors and users’ CUI. Prior usage
experience of WeChat can develop into habitual use behaviors of
WeChat Pay, which can reinforce users’ perceptions of self-efficacy and
users’ stickiness, according to the interview data. WeChat Pay users with
high-level MSD value PFV more, while users with low-level MSD value
PIV. PR has a significant negative influence on SAT. The interview data
demonstrates that MSD can offset the negative influence of PR on SAT,
as well as users’ herd mentality, strong trust in mega-enterprise tech­
nology, low financial security awareness, and social influence (i.e., SI).
“I started to use WeChat Pay mainly because my family members all use
it. Later, I mainly use it to send red envelopes and make online transfers to
my family on their birthdays or festivals. We have more and more com­
munications by this. At normal times, I also send some red envelops to
make them to chat with me on WeChat. So, we can have more under­
standing between family members in the WeChat family group.”
5.3.4. Other PR offsetting factors
The interview data explains that WeChat Pay users’ herd mentality,
strong trust in mega-enterprise technology, users’ social circumstances
and low financial security awareness reduces or offsets PR on SAT, as
shown in Fig. 3.
“I feel that WeChat Pay is reliable. If not, there would not be so many
people using it so frequently. I think most people believe in the expertise
and technology of Tencent. So, ‘love me, love my dog’. People also believe
in WeChat Pay.”
“WeChat is not a specialized online payment app, but so many people are
using it now. This fully proves that we all trust WeChat Pay. After all,
Tencent is a large company… Sometimes even I know there may be some
technical bugs in using WeChat Pay. However, I do not worry about
personal information leakage when I really use it, because I feel the
probability of such things is pretty low.”
The above two interviewees’ belief in the safety of WeChat Pay were
all based on their confidence in the service provider’s mega-enterprise
nature and its huge user groups’ frequent usage. They all believe that
the big company’s financial technology and the huge customer base of
this product can fully ensure the reliability of WeChat Pay. Moreover,
the latter interviewee’s statement about personal information leakage
also reflects his/her low financial awareness, which can greatly reduce
their PR on SAT.
The SI from users’ social circumstances of popular use of WeChat Pay
can also reduce the concerns of risk (i.e., PR) in their continuous use. For
instance, one interviewee claimed that there should be no risk in using
WeChat Pay because no negative events have happened in his/her social
circle:
6.2. Theoretical implications
This research makes several significant theoretical contributions.
Firstly, it empirically explores users’ PV underpinning the S-O-R
framework to continue using WeChat Pay, a novel MPS hosted on the
popular social media app platform of WeChat, which contributes to the
existing literature of continuous use of mobile payments. This study
finds that PV, as an inner state, plays a key role in influencing user
satisfaction and their subsequent continuous usage. Thus, it also pro­
vides a theoretical lens from a value perspective for model construction
to understand how organism factors affect continuous usage. Moreover,
this research regards PF and SI as stimulus and reveals that, in the
context of WeChat Pay, social gratifications associated with SI play a
more important role than functional gratifications originating from PF.
Thus, this paper extends research on socializing-related influencing el­
ements in a social media context to the field of mobile payment research.
By doing so, the gap in the existing literature which separates MPS and
mobile social media can be partially filled.
Secondly, this study expands our knowledge about dimensions of the
construct of PV in the context of MPS by empirically identifying four
dimensions of PV of WeChat Pay, including the tangible functional value
of PFV and three intangible socializing gratification values of PEV (i.e.,
entertainment), PIV (i.e., social interaction), and PSV (i.e., social status
attainment). Prior studies exploring the continuous usage behaviors or
intentions of MPS mainly focused on the role of tangible PV while few
have paid attention to the intangible PV (Hsu and Lin, 2015; Pura,
2005). It empirically identifies the multiple dimensions of PV of WeChat
Pay, which make the value of this novel MP distinct from that of other
traditional MP services. Thus, it further extends the existing research on
the content of PV (Fiol et al., 2011; Sweeney and Soutar, 2001) in the
context of MPS. Moreover, in contrast to prior researches on traditional
MPS, which stress the importance of tangible functional values, the
findings empirically identify the stronger roles of intangible values
(PEV, PIV and PSV) over tangible values in WeChat Pay. Among the
three types of intangible values, the PEV is identified as the strongest
influencing factor of PV in this research. This confirms the idea that
“There are many people using WeChat Pay around me, and I never hear
anything goes wrong. Since nothing bad happened to us after using it for
many years, there certainly should be no risk or very little risk, in my
opinion.”
6. Discussion and conclusion
6.1. Key findings
By building the S-O-R model and clarifying the factors influencing its
users’ continuous usage, this research empirically explores the reasons
for the continued use of a new model of mobile payment services inte­
grated in a mobile social media app, i.e., WeChat Pay. From the users’
perceived value perspective, this research explains the mechanism of its
continuous usage, by identifying the more important role of intangible
value dimension, the strongest value factor of PEV, and the social
gratifications from strong interrelations among three intangible values
of WeChat Pay. This research also identifies multiple factors which can
offset the negative influences of PR, including MSD, social influence,
users’ herd mentality, strong trust in mega-enterprise technology, low
financial security awareness. The above findings of this research pave a
solid basis for building a model to explain, in-depth, the reasons behind
the continued usage of WeChat Pay, as a novel type of MPS.
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Electronic Commerce Research and Applications 60 (2023) 101275
hedonic value has a strong effect on commitment (Karjaluoto et al.,
2019) in the context of WeChat Pay. Therefore, by highlighting intan­
gible socializing gratification values, our findings empirically prove the
distinctiveness of WeChat Pay from other MPS in its dimensions of PIV,
PSV, and PEV, which contribute a comprehensive understanding of the
role of non-functional values in promoting continued use intentions of
MPS integrated into social media.
Thirdly, this research extends the understandings of the relationships
between value dimensions and associated effects on gratification of
continued usage in the context of MPS. In line with prior research that
the hedonic and utilitarian elements of consumer perceived value are
related (Sweeney and Soutar, 2001), this study empirically reveals that
the tight combination of the three intangible types of PV (i.e., PEV, PIV
and PSV) can greatly facilitate the socializing gratifications of continued
usage of WeChat Pay. WeChat provides its users with both social grati­
fications such as social interaction and hedonic gratification such as
entertainment (Gan and Wang, 2015). Thus, it can be inferred that such
interrelations and consequent socializing gratifications are mainly
attributed to WeChat and associated MSD, which further makes WeChat
Pay distinct from other mobile payment modes. This provides a theo­
retical lens for other studies exploring influences of social gratifications
upon continued use behaviors of MPS, especially those integrated into
social commerce platforms or social media.
6.4. Limitations and future research
This study has a few limitations that indicate possible directions for
future research. First, the generalizability of the present research is
limited by the Chinese cultural and geographic scope of the sample. One
of the distinct cultural characteristics of China is a high degree of power
distance, featured by concentrated authority, hierarchical structure, and
social position acceptance. Thus, it has a strong connection with the
value of social status attainment, i.e., PSV, identified in this research.
Since national culture has specific moderating effects on IS adoption,
when future studies research continuous use of WeChat Pay in a
different cultural population with a low degree of power distance, which
avoids authority concentration and is decentralized, it can be inferred
that the PSV’s moderating effects could be greatly reduced or nonexistent in the new model.
Secondly, there are some omissions in selecting influencing factors,
such as user self-efficacy and perceived behavior control. Future
research could include these characteristics as antecedents or modera­
tors to study their impact on the continued use of WeChat Pay. In
addition, to determine whether the four dimensions of PV found in our
study are different from those found in other countries, studies should
explore the PV of social media in other cultural contexts.
CRediT authorship contribution statement
6.3. Practical implications
Xuguang Li: Conceptualization, Writing – original draft, Writing –
review & editing, Methodology, Formal analysis. Xuekun Zhu: Formal
analysis, Visualization, Writing – review & editing. Yingying Lu:
Methodology, Investigation, Writing – original draft. Dingyu Shi:
Visualization, Data curation. Weihua Deng: Conceptualization, Meth­
odology, Investigation, Formal analysis, Supervision.
The present study helps us understand the critical determinants of
users’ continuous use of MPS integrated in social media, which is rele­
vant for providers and developers of MPS.
For providers of social media services who wish to move into the
MPS market, understanding the influence of PV upon continued usage of
WeChat Pay has important implications. First, the huge number of
existing users and frequent prior use experience are significant advan­
tages for social media providers entering the mobile payment market.
Second, to attract and retain users of an integrated MPS, social media
platform designers can incorporate functions associated with socializing
gratification, as well as features related both to external factors (e.g.,
ease of use, friendly user interface) and to internal factors (e.g., enter­
tainment, social status, and social interaction).
For the providers of mobile payment apps, they can focus more on
incorporating collective entertainment functions into the MPS to attract
users and promote their continued usage. The intrinsic rewards (such as
self-efficacy, social status, and reputation) from the collective enter­
tainment experiences should be considered in designing its interactive
entertainment function. Furthermore, elements relating to national or
popular culture, such as Red Envelope, can be absorbed into its design to
promote users’ stickiness in different national regions.
Declaration of Competing Interest
The authors declare the following financial interests/personal re­
lationships which may be considered as potential competing interests:
Weihua Deng reports financial support was provided by National Social
Science Foundation of China (grant number 18BTQ086). Xuguang Li
reports a relationship with National Social Science Foundation of China
(18BTQ086) that includes: funding grants.
Data availability
Data will be made available on request.
Acknowledgements & Funding statement
This work was supported by The National Social Science Fund of
China [Grant number 18BTQ086].
Appendix 1. Measurement items and associated definitions
Variables
Names
definitions
CUI
PV
PFV
PSV
PIV
PEV
SI
PF
MSD
PR
Continued Usage Intention
Perceived Value
Perceived Function Value
Perceived Social Value
Perceived Interactive Value
Perceived Entertainment Value
Social Influences
Platform Feature
Media System Dependency
Perceived Risk
Willingness and motivation to use a product for a long time
The user’s overall evaluation of a service or product
The user’s overall perception of the utility or benefits obtained by using WeChat Pay
Perceived usefulness in pursuing social approval, status seeking and social support
Perceived benefits for maintaining, improving and expanding interpersonal relationships through social interactions
The user’s emotional experience of gaining happiness, excitement, and enjoyment
The extent of influence on interactions among individuals in the social network
A series of more innovative technical factors of WeChat Pay compared to other MPS
The dependency to media system
Subjective expectations of loss or sacrifice in adopting a technology of risk
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Appendix 2. Measurement items and their sources
Construct
items
Source
PF
PF1
PF2
WeChat Pay can provide many receiving and payment function.
WeChat Pay is compatible with its own functional blocks.
(Kim et al., 2010; Sweeney and Soutar, 2001)
PIV
PIV1
PIV2
Using WeChat Pay is conducive for me to maintain interpersonal relationships.
Using WeChat Pay is conducive to keeping in touch with friends.
(Cocosila and Igonor, 2015; Katz et al., 1973; Lee et al., 2014)
PSV
PSV1
PSV2
PSV3
Using WeChat Pay will make it easier for me to be accepted.
Using WeChat Pay will let me make a good impression on others.
Using WeChat Pay will make me more confident in interpersonal
communication.
(Cocosila and Igonor, 2015; Park et al., 2009; Sheth et al., 1991; Sweeney and
Soutar, 2001)
PFV
PFV1
PFV2
PFV3
WeChat Pay can make small change and non-cash payments more often.
WeChat Pay can save more time when paid by acquaintances.
WeChat Pay can make transactions more convenient under certain
circumstances.
(Cocosila and Igonor, 2015; Kim et al., 2010; Sheth et al., 1991)
PEV
PEV1
WeChat Pay brings me more pleasure in communicating and interacting with
friends.
Some functions of WeChat Pay are more interesting to use.
Using WeChat Pay can add some life happiness.
(Cocosila and Igonor, 2015; Lee et al., 2014; Sweeney and Soutar, 2001)
PEV2
PEV3
PR
PR1
PR2
PR3
I am worried that the technology of WeChat Pay system is not mature enough.
I am worried about property damage due to operational errors.
I am worried about the leakage of personal information or transaction
information.
(Thakur and Srivastava, 2014)
SI
SI1
SI2
SI3
I feel that more and more people are using and accepting WeChat Pay.
All my relatives and friends are using WeChat Pay.
The people who have an important influence on me prompted me to use
WeChat Pay.
WeChat friends often send me Red envelops or transfer money to attract me to
participate.
(Venkatesh et al., 2003)
SI4
MSD
MSD1
MSD2
MSD3
I often get and share information through WeChat moments.
WeChat is an important way for me to keep in touch with my friends.
WeChat brings me a lot of convenience and fun, and it is very meaningful to my
life.
(Carillo et al., 2017; Turel et al., 2011)
SAT
SAT1
SAT2
SAT3
The services provided by WeChat Pay can meet my needs.
After using WeChat Pay, I don’t think my choice to use it is wrong.
In general, the process of using WeChat Pay is very smooth.
(Bhattacherjee, 2001)
CUI
CUI1
CUI2
I will use WeChat Pay more frequently in the future.
I would like to recommend WeChat Pay to my friends and colleagues.
(Bhattacherjee, 2001)
Appendix 3. Results of the first-order confirmatory analysis
Covariate path coefficient
β
PSV ←→PFV
PFV ←→PEV
PFV ←→PEV
PSV ←→PIV
PFV ←→PIV
PEV ←→PIV
0.590
0.679
0.684
0.568
0.713
0.687
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Appendix 4:. Ping’s (1995) schematic diagram of research methods
References
Cocosila, M., Igonor, A., 2015. How important is the “social” in social networking? A
perceived value empirical investigation. Inf. Technol. People 28, 366–382. https://
doi.org/10.1108/ITP-03-2014-0055.
Dahlberg, T., Mallat, N., Ondrus, J., Zmijewska, A., 2008. Past, present and future of
mobile payments research: A literature review. Electron. Commer. Res. Appl. 7,
165–181. https://doi.org/10.1016/j.elerap.2007.02.001.
Daragmeh, A., Lentner, C., Sagi, J., 2021. FinTech payments in the era of COVID-19:
Factors influencing behavioral intentions of “Generation X”in Hungary to use mobile
payment. J. Behav. Exp. Finan. 32, 1–13. https://doi.org/10.1016/j.
jbef.2021.100574.
Eighmey, J., McCord, L., 1998. Adding value in the information age: Uses and
gratifications of sites on the World Wide Web. J. Bus. Res. 41, 187–194. https://doi.
org/10.1016/S0148-2963(97)00061-1.
Fiol, L.J.C., Tena, M.A.M., García, J.S., 2011. Multidimensional perspective of perceived
value in industrial clusters. J. Bus. Ind. Mark. 26, 132–145. https://doi.org/
10.1108/08858621111112302.
Gan, C., Wang, W., 2015. Uses and gratifications of social media: a comparison of
microblog and WeChat. J. Syst. Inf. Technol. 17, 351–368. https://doi.org/10.1108/
jsit-06-2015-0052.
Giovanis, A., Rizomyliotis, I., Konstantoulaki, K., Magrizos, S., 2022. Mining the hidden
seam of proximity m-payment adoption: A hybrid PLS-artificial neural network
analytical approach. Eur. Manag. J. 40 (4), 618–631.
Hinterhuber, A., 2004. Towards value-based pricing—An integrative framework for
decision making. Ind. Mark. Manag. 33, 765–778. https://doi.org/10.1016/j.
indmarman.2003.10.006.
Horwitz, J., 2016. Over 8 billion ‘red envelopes’ were sent over WeChat during Chinese
New Year. https://qz.com/613384/over-8-billion-red-envelopes-were-sent-over-we
chat-during-chinese-new-year/.
Howard, J.A., Sheth, J.N., 1969. The Theory of Buyer Behavior.
Hsiao, C.H., Chang, J.J., Tang, K.Y., 2016. Exploring the influential factors in
continuance usage of mobile social Apps: Satisfaction, habit, and customer value
perspectives. Telematics Inform. 33, 342–355. https://doi.org/10.1016/j.
tele.2015.08.014.
Hsieh, P.J., 2021. Understanding medical consumers’ intentions to switch from cash
payment to medical mobile payment: A perspective of technology migration.
Technol. Forecast. Soc. Chang. 173, 1–14. https://doi.org/10.1016/j.
techfore.2021.121074.
Hsu, C.L., Lin, J.C.C., 2015. What drives purchase intention for paid mobile apps?–An
expectation confirmation model with perceived value. Electron. Commer. Res. Appl.
14, 46–57. https://doi.org/10.1016/j.elerap.2014.11.003.
Huang, H., Zhang, X., 2017. The adoption and use of WeChat among middle-aged
residents in urban China. Chinese J. Commun. 10, 134–156. https://doi.org/
10.1080/17544750.2016.1211545.
Ahmad, W., Sun, J., 2018. Antecedents of SMMA continuance intention in two culturally
diverse countries: An empirical examination. J. Glob. Inf. Technol. Manag. 21,
45–68. https://doi.org/10.1080/1097198X.2018.1423840.
Ahuja, M.K., Thatcher, J.B., 2005. Moving beyond intentions and toward the theory of
trying: Effects of work environment and gender on post-adoption information
technology use. MIS Q. 29, 427–459. https://doi.org/10.2307/25148691.
Bagozzi, R.P., Yi, Y., 1988. On the evaluation of structural equation models. J. Acad.
Mark. Sci. 16, 74–94. https://doi.org/10.1007/BF02723327.
Bagozzi, R.P., Fornell, C., Larcker, D.F., 1981. Canonical correlation analysis as a special
case of a structural relations model. Multivariate Behav. Res. 16, 437–454. https://
doi.org/10.1207/s15327906mbr1604_2.
Bailey, A.A., Pentina, I., Mishra, A.S., Mimoun, M.S.B., 2017. Mobile payments adoption
by US consumers: an extended TAM. Int. J. Retail Distrib. Manag. 45, 626–640.
https://doi.org/10.1108/IJRDM-08-2016-0144.
Ball-Rokeach, S.J., 1998. A Theory of media power and a theory of media use: different
stories, questions, and ways of thinking. Mass Commun. Soc. 1 (1-2), 5–40.
Bandura, A., Freeman, W.H., Lightsey, R., 1999. Self-efficacy: The exercise of control.
J Cogn Psychother 13 (2), 158–166.
Basak, E., Calisir, F., 2015. An empirical study on factors affecting continuance intention
of using Facebook. Comput. Hum. Behav. 48, 181–189. https://doi.org/10.17559/
TV-20180413122553.
Bhattacherjee, A., 2001. Understanding information systems continuance: An
expectation-confirmation model. MIS Q. 25, 351–370. https://doi.org/10.2307/
3250921.
Bolton, B., 1980. Second-order dimensions of the Work Values Inventory (WVI). J. Vocat.
Behav. 17, 33–40. https://doi.org/10.1016/0001-8791(80)90012-3.
Boyd, D.M., Ellison, N.B., 2007. Social network sites: Definition, history, and scholarship.
J. Comput.-Mediat. Commun. 13, 210–230. https://doi.org/10.1111/j.10836101.2007.00393.x.
Carillo, K., Scornavacca, E., Za, S., 2017. The role of media dependency in predicting
continuance intention to use ubiquitous media systems. Inf. Manag. 54, 317–335.
https://doi.org/10.1016/j.im.2016.09.002.
Chen, X., Li, S., 2017. Understanding continuance intention of mobile payment services:
an empirical study. J. Comput. Inf. Syst. 57, 287–298. https://doi.org/10.1080/
08874417.2016.1180649.
Chen, S.C., Chung, K.C., Tsai, M.Y., 2019. How to achieve sustainable development of
mobile payment through customer satisfaction—the SOR model. Sustainability 11,
6314. https://doi.org/10.3390/su11226314.
Cheung, C.M., Lee, M.K., 2009. Understanding the sustainability of a virtual community:
model development and empirical test. J. Inf. Sci. 35, 279–298. https://doi.org/
10.1177/0165551508099088.
15
X. Li et al.
Electronic Commerce Research and Applications 60 (2023) 101275
Miao, M., Jayakar, K., 2016. Mobile payments in Japan, South Korea and China: Crossborder convergence or divergence of business models? Telecommun. Policy 40,
182–196. https://doi.org/10.1016/j.telpol.2015.11.011.
Milner, H.V., 2003. The global spread of the Internet: The role of international diffusion
pressures in technology adoption. In: 2nd Conference on Interdependence, Diffusion,
and Sovereignty, UCLA, California.
Mombeuil, C., Uhde, H., 2021. Relative convenience, relative advantage, perceived
security, perceived privacy, and continuous use intention of China’s WeChat Pay: A
mixed-method two-phase design study. J. Retail. Consum. Serv. 59, 1–21. https://
doi.org/10.1016/j.jretconser.2020.102384.
Morosan, C., DeFranco, A., 2016. It’s about time: Revisiting UTAUT2 to examine
consumers’ intentions to use NFC mobile payments in hotels. Int. J. Hosp. Manag.
53, 17–29. https://doi.org/10.1016/j.ijhm.2015.11.003.
Morton, T.A., Duck, J.M., 2001. Communication and health beliefs: Mass and
interpersonal influences on perceptions of risk to self and others. Commun. Res. 28,
602–626. https://doi.org/10.1177/009365001028005002.
Mu, H.-L., Lee, Y.-C., 2017. Examining the influencing factors of third-party mobile
payment adoption: a comparative study of Alipay and WeChat Pay. J. Inf. Syst. 26,
247–284. https://doi.org/10.5859/KAIS.2017.26.4.247.
Munger, 2018 Berkshire Hathaway 2018 Annual shareholders meeting. https://www.
brownadvisory.com/us/theadvisory/2018-berkshire-hathaway-annual-shareholdermeeting.
Nunnally, J.C., Bernstein, I., 1978. Psychometric Theory, 2nd edition. (McGraw-Hill
Psychology Ser.) McGraw-Hill Companies.
Oliver, R.L., 1980. A cognitive model of the antecedents and consequences of satisfaction
decisions. J. Mark. Res. 17, 460–469. https://doi.org/10.2307/3150499.
Ozdemir, S., Trott, P., Hoecht, A., 2008. Segmenting internet banking adopter and nonadopters in the Turkish retail banking sector. Int. J. Bank Mark. 26 (4), 212–236.
O’Brien, H.L., 2010. The influence of hedonic and utilitarian motivations on user
engagement: The case of online shopping experiences. Interact. Comput. 22,
344–352. https://doi.org/10.1016/j.intcom.2010.04.001.
Papacharissi, Z., Rubin, A.M., 2000. Predictors of Internet use. J. Broadcast. Electron.
Media 44, 175–196. https://doi.org/10.1207/s15506878jobem4402_2.
Park, N., Kee, K.F., Valenzuela, S., 2009. Being immersed in social networking
environment: Facebook groups, uses and gratifications, and social outcomes.
Cyberpsychology & behavior 12, 729–733. https://doi.org/10.1089/cpb.2009.0003.
Park, J., Ahn, J., Thavisay, T., Ren, T., 2019. Examining the role of anxiety and social
influence in multi-benefits of mobile payment service. J. Retail.Consum. Serv. 47,
140–149. https://doi.org/10.1016/j.jretconser.2018.11.015.
Phua, K., 2021. Telling the fortune of digital payments in 2021. https://www.ejinsight.
com/eji/article/id/2721065/20210226-Telling-the-fortune-of-digital-paymentsin-2021.
Ping Jr, R.A., 1995. A parsimonious estimating technique for interaction and quadratic
latent variables. J. Mark. Res. 32, 336–347. https://doi.org/10.1177/
002224379503200308.
Pöyry, E., Parvinen, P., Malmivaara, T., 2013. Can we get from liking to buying?
Behavioral differences in hedonic and utilitarian Facebook usage. Electron. Commer.
Res. Appl. 12, 224–235. https://doi.org/10.1016/j.elerap.2013.01.003.
Pura, M., 2005. Linking perceived value and loyalty in location-based mobile services.
J. Serv. Theory Pract. 15 (6), 509–538. https://doi.org/10.1108/
09604520510634005.
Rafaeli, S., Ariel, Y., 2008. Online motivational factors: Incentives for participation and
contribution in Wikipedia. In: Barak, A. (Ed.), Psychological Aspects of Cyberspace:
Theory, Research, Applications. Cambridge University Press, pp. 243–267.
Rao, Q., Ko, E., 2021. Impulsive purchasing and luxury brand loyalty in WeChat Mini
Program. Asia Pac. J. Mark. Logist. 33, 2054–2071. https://doi.org/10.1108/
APJML-08-2020-0621.
Rice, R.E., Aydin, C., 1991. Attitudes toward new organizational technology: Network
proximity as a mechanism for social information processing. Adm. Sci. Q. 36,
219–244. https://doi.org/10.2307/2393354.
Rubin, A.M., 2008. Uses-and-Gratifications Perspective on Media Effects.
Scott, J.E., 1995. The measurement of information systems effectiveness: evaluating a
measuring instrument. ACM SIGMIS Database: the DATABASE for Advances in
Information Systems 26, 43-61. https://doi.org/10.1145/206476.206484.
Sheth, J.N., Newman, B.I., Gross, B.L., 1991. Why we buy what we buy: A theory of
consumption values. J. Bus. Res. 22, 159–170. https://doi.org/10.1016/0148-2963
(91)90050-8.
Sohaib, O., Kang, K., 2015. Individual level culture influence on online consumer iTrust
aspects towards purchase intention across cultures: A SOR model. Int. J. Electron.
Bus. 12, 142–161. https://doi.org/10.1504/IJEB.2015.069104.
Song, P., Zhang, C., Xu, Y.C., Huang, L., 2010. Brand extension of online technology
products: Evidence from search engine to virtual communities and online news.
Decis. Support Syst. 49, 91–99. https://doi.org/10.1016/j.dss.2010.01.005.
Srivastava, S.C., Chandra, S., Theng, Y.L., 2010. Evaluating the role of trust in consumer
adoption of mobile payment systems: An empirical analysis. Commun. Assoc. Inf.
Syst. 27, 561–588. https://doi.org/10.17705/1CAIS.02729.
Sweeney, J.C., Soutar, G.N., 2001. Consumer perceived value: The development of a
multiple item scale. J. Retail. 77, 203-220. https://doi.org/.
Teo, T.S., 2001. Demographic and motivation variables associated with Internet usage
activities. Internet Res. 11, 125–137. https://doi.org/10.1108/
10662240110695089.
Thakur, R., Srivastava, M., 2014. Adoption readiness, personal innovativeness, perceived
risk and usage intention across customer groups for mobile payment services in
India. Internet Res. 24, 369–392. https://doi.org/10.1108/IntR-12-2012-0244.
Tsai, H.T., Chien, J.L., Tsai, M.T., 2014. The influences of system usability and user
satisfaction on continued Internet banking services usage intention: empirical
Hwang, Y., Park, S., Shin, N., 2021. Sustainable development of a mobile payment
security environment using Fintech solutions. Sustainability 13, 1–21. https://doi.
org/10.3390/su13158375.
Iqbal, M., 2022. WeChat Revenue and Usage Statistics (2022). https://www.business
ofapps.com/data/wechat-statistics/.
IResearch, 2020. 2020 China’s Third-party Payment Industry Report. http://www.ir
esearchchina.com/content/details8_62751.html.
Jun, J., Cho, I., Park, H., 2018. Factors influencing continued use of mobile easy payment
service: an empirical investigation. Total Qual. Manag. Bus. Excell. 29, 1043–1057.
https://doi.org/10.1080/14783363.2018.1486550.
Karjaluoto, H., Shaikh, A.A., Saarijärvi, H., Saraniemi, S., 2019. How perceived value
drives the use of mobile financial services apps. Int. J. Inf. Manag. 47, 252–261.
https://doi.org/10.1016/j.ijinfomgt.2018.08.014.
Katz, M.L., Shapiro, C., 1985. Network externalities, competition, and compatibility. Am.
Econ. Rev. 75, 424–440. https://doi.org/10.1016/j.mathsocsci.2020.12.003.
Katz, E., Haas, H., Gurevitch, M., 1973. On the use of the mass media for important
things. Am. Sociol. Rev. 38, 164–181. https://doi.org/10.2307/2094393.
Kim, J.H., Park, J.W., 2019. The effect of airport self-service characteristics on
passengers’ perceived value, satisfaction, and behavioral intention: based on the
SOR model. Sustainability 11, 1–11. https://doi.org/10.3390/su11195352.
Kim, H.W., Chan, H.C., Gupta, S., 2007. Value-based adoption of mobile internet: an
empirical investigation. Decis. Support Syst. 43, 111–126. https://doi.org/10.1016/
j.dss.2005.05.009.
Kim, C., Mirusmonov, M., Lee, I., 2010. An empirical examination of factors influencing
the intention to use mobile payment. Comput. Hum. Behav. 26, 310–322. https://
doi.org/10.1016/j.chb.2009.10.013.
Kim, H.W., Gupta, S., Koh, J., 2011. Investigating the intention to purchase digital items
in social networking communities: A customer value perspective. Inf. Manag. 48,
228–234. https://doi.org/10.1016/j.im.2011.05.004.
Kim, C., Galliers, R.D., Shin, N., Ryoo, J.-H., Kim, J., 2012. Factors influencing Internet
shopping value and customer repurchase intention. Electron. Commer. Res. Appl. 11,
374–387. https://doi.org/10.1016/j.elerap.2012.04.002.
Kim, Y.H., Kim, D.J., Wachter, K., 2013. A study of mobile user engagement (MoEN):
Engagement motivations, perceived value, satisfaction, and continued engagement
intention. Decis. Support Syst. 56, 361–370. https://doi.org/10.1016/j.
dss.2013.07.002.
Ko, H., Cho, C.H., Roberts, M.S., 2005. Internet uses and gratifications: A structural
equation model of interactive advertising. J. Advert. 34, 57–70. https://doi.org/
10.1080/00913367.2005.10639191.
Kuo, Y.F., Wu, C.M., Deng, W.J., 2009. The relationships among service quality,
perceived value, customer satisfaction, and post-purchase intention in mobile valueadded services. Comput. Hum. Behav. 25, 887–896. https://doi.org/10.1016/j.
chb.2009.03.003.
Lee, C.S., Ma, L., 2012. News sharing in social media: The effect of gratifications and
prior experience. Comput. Hum. Behav. 28, 331–339. https://doi.org/10.1016/j.
chb.2011.10.002.
Lee, M.R., Yen, D.C., Hsiao, C., 2014. Understanding the perceived community value of
Facebook users. Comput. Hum. Behav. 35, 350–358. https://doi.org/10.1016/j.
chb.2014.03.018.
Li, C.Y., Li, Y., 2021. Research on user satisfaction of third-party mobile payment under
the IoT environment-based on the structural equation mode. J. Intell. Fuzzy Syst. 40,
5853–5861. https://doi.org/10.3233/jifs-189425.
Li, C., Li, Y., Satapathy, S.C., Agrawal, R., García Díaz, V., 2021a. Research on user
satisfaction of third-party mobile payment under the IoT environment-based on the
structural equation mode. J. Intell. Fuzzy Syst. 40 (4), 5853–5861. https://doi.org/
10.3233/jifs-189425.
Li, X., Zhou, Y., Wong, Y.D., Wang, X., Yuen, K.F., 2021b. What influences panic buying
behaviour? A model based on dual-system theory and stimulus-organism-response
framework. Int. J. Disaster Risk Reduct. 64, 1–10. https://doi.org/10.1016/j.
ijdrr.2021.102484.
Lien, C.H., Cao, Y., Zhou, X., 2017. Service quality, satisfaction, stickiness, and usage
intentions: An exploratory evaluation in the context of WeChat services. Comput.
Hum. Behav. 68, 403–410. https://doi.org/10.1016/j.chb.2016.11.061.
Lin, J.C.C., 2007. Online stickiness: its antecedents and effect on purchasing intention.
Behav. Inform. Technol. 26, 507–516. https://doi.org/10.1109/IC4E.2010.42.
Liébana Cabanillas, F., Muñoz Leiva, F., Sánchez Fernández, J., 2018. A global approach
to the analysis of user behavior in mobile payment systems in the new electronic
environment. Serv. Bus. 12, 25–64. https://doi.org/10.1007/s11628-017-0336-7.
Marsh, H.W., Hocevar, D., 1988. A new, more powerful approach to multitraitmultimethod analyses: Application of second-order confirmatory factor analysis.
J. Appl. Psychol. 73, 107–117. https://doi.org/10.1037/0021-9010.73.1.107.
Matemba, E.D., Li, G., 2018. Consumers’ willingness to adopt and use WeChat wallet: An
empirical study in South Africa. Technol. Soc. 53, 55–68. https://doi.org/10.1016/j.
techsoc.2017.12.001.
McDonald, R.P., Ho, M.-H.-R., 2002. Principles and practice in reporting structural
equation analyses. Psychol. Methods 7, 64. https://doi.org/10.1037/1082989X.7.1.64.
Mehrabian, A., Russell, J.A., 1974. An Approach to Environmental Psychology. the MIT
Press.
Mensah, I.K., Liu, Y., Luo, C., 2021. Factors influencing the continued acceptance of
Wechat mobile payments by chinese vendors. Inf. Resour. Manage. J. (IRMJ) 34,
28–47. https://doi.org/10.4018/IRMJ.2021100102.
Mensah, I.K., 2021. Predictors of the Continued Adoption of WECHAT Mobile Payment.
15, 1-23. https://doi.org/10.4018/IJEBR.2019100101.
16
X. Li et al.
Electronic Commerce Research and Applications 60 (2023) 101275
and personal traits. Comput. Hum. Behav. 28, 129–142. https://doi.org/10.1016/j.
chb.2011.08.019.
Yang, H., Yu, J., Zo, H., Choi, M., 2016. User acceptance of wearable devices: An
extended perspective of perceived value. Telematics Inform. 33, 256–269. https://
doi.org/10.1016/j.tele.2015.08.007.
Ye, Q., Luo, Y., Chen, G., Guo, X., Wei, Q., Tan, S., 2019. Users intention for continuous
usage of mobile news apps: the roles of quality, switching costs, and personalization.
J. Syst. Sci. Syst. Eng. 28, 91–109. https://doi.org/10.1007/s11518-019-5405-0.
Zeithaml, V.A., 1988. Consumer perceptions of price, quality, and value: a means-end
model and synthesis of evidence. J. Mark. 52, 2–22. https://doi.org/10.2307/
1251446.
Zhang, X.Z., Zhong, Z.J., 2020. Extending media system dependency theory to
informational media use and environmentalism: A cross-national study. Telematics
Inform. 50, 1–15. https://doi.org/10.1016/j.tele.2020.101378.
Zhang, C.B., Li, Y.N., Wu, B., Li, D.J., 2017. How WeChat can retain users: Roles of
network externalities, social interaction ties, and perceived values in building
continuance intention. Comput. Hum. Behav. 69, 284–293. https://doi.org/
10.1016/j.chb.2016.11.069.
Zhang, J., Li, F., Zhang, Z., Xu, G., Wang, Y., Wang, X., Zhang, Y., 2021. Integrate syntax
information for target-oriented opinion words extraction with target-specific graph
convolutional network. Neurocomputing 440, 321–335. https://doi.org/10.1016/j.
neucom.2020.07.152.
Zhou, T., 2013. An empirical examination of continuance intention of mobile payment
services. Decis. Support Syst. 54, 1085–1091. https://doi.org/10.1016/j.
dss.2012.10.034.
evidence from Taiwan. Electron. Commer. Res. 14, 137–169. https://doi.org/
10.1007/s10660-014-9136-5.
Turel, O., Serenko, A., Giles, P., 2011. Integrating technology addiction and use: An
empirical investigation of online auction users. MIS Q. 35, 1043–1061. https://doi.
org/10.2307/41409972.
Venkatesh, V., Brown, S.A., 2001. A longitudinal investigation of personal computers in
homes: Adoption determinants and emerging challenges. MIS. Q. 25, 71–102.
https://doi.org/10.2307/3250959.
Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D., 2003. User acceptance of
information technology: Toward a unified view. MIS Q. 27, 425–478. https://doi.
org/10.2307/30036540.
Venkatesh, V., Brown, S.A., Maruping, L.M., Bala, H., 2008. Predicting different
conceptualizations of system use: The competing roles of behavioral intention,
facilitating conditions, and behavioral expectation. MIS Q. 32, 483–502. https://doi.
org/10.2307/25148853.
Venkatesh, V., Thong, J.Y., Xu, X., 2012. Consumer acceptance and use of information
technology: extending the unified theory of acceptance and use of technology. MIS
Q. 36, 157–178. https://doi.org/10.2307/41410412.
WATCH, C.I., 2021. Mobile reach in 2021: Tencent, Alibaba, Baidu, ByteDance,
Kuaishou. https://www.chinainternetwatch.com/30684/batt/#:~:text=Tencent%
20has%20the%20highest%20reach%20of%2096.3%25%20of,ByteDance%20inc
reased%2.
Woisetschläger, D.M., Lentz, P., Evanschitzky, H., 2011. How habits, social ties, and
economic switching barriers affect customer loyalty in contractual service settings.
J. Bus. Res. 64, 800–808. https://doi.org/10.1016/j.jbusres.2010.10.007.
Yang, S., Lu, Y., Gupta, S., Cao, Y., Zhang, R., 2012. Mobile payment services adoption
across time: An empirical study of the effects of behavioral beliefs, social influences,
17