Journal of Retailing and Consumer Services 51 (2019) 320–330

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Journal of Retailing and Consumer Services

journal homepage: www.elsevier.com/locate/jretconser

Exploring purchase intention in cross-border E-commerce: A three stage T

model
Wenlong Zhua, Jian Moub,c,*, Morad Benyoucefc
a
Business School, Qingdao University of Technology, China
b
School of Economics and Management, Xidian University, Xi'an, Shaanxi, China
c
Telfer School of Management, University of Ottawa, Canada

A R T I C LE I N FO A B S T R A C T

Keywords: Cross-border e-commerce (CBEC) has been thriving in recent years, generating economic benefits for sellers and
Cross-border e-commerce consumers. To keep up with this trend, sellers need to improve product cognition in order to improve consumers’
Three-stage theoretical model interest and behavior. Little research has focused on the influence of product cognition on purchase intention in
Hierarchy-of-effects model CBEC. This study employs the hierarchy-of-effects model and the commitment-involvement theory to develop a
Purchase intention
three-stage model to evaluate the impact of product cognition on purchase intention in CBEC. Data was collected
Commitment-involvement theory
on a popular Chinese CBEC platform. The analysis shows that product description and product awareness have a
positive effect on trust beliefs, and both platform enduring involvement and platform situational involvement
positively affect trust. Purchase intention is subject to the positive impact of platform situational involvement
and trust beliefs in addition to platform enduring involvement. Finally, perceived trust plays a full mediation
effect in the three-stage model, which indicates that, on CBEC platforms, consumers’ processing and response is a
sequence from product cognition to platform emotion and from platform emotion to behavior intention. The
theoretical contribution of this study is a three-stage model involving two types of platform involvement in CBEC
settings. Such model allows CBEC platform providers to increase consumers’ purchase intentions by improving
product description, product awareness and platform involvement.

1. Introduction habits (Kim et al., 2017), consumers usually reveal different levels of
attention to products, online stores, and advertisements on CBEC plat-
Compared to domestic e-commerce, the increasing interest in cross- forms (Porter, 2008; Mou and Shin, 2018). In such circumstances, at-
border e-commerce (CBEC) is relatively recent. CBEC is becoming an tracting consumers’ attention to notice the products and induce their
important channel for promoting international trade (Mou et al., 2017) purchase intention becomes an important issue for sellers (Kim, 2018).
as it provides huge business opportunities for all countries and regions In other words, sellers need to increase consumers’ cognition of their
to reap benefits from global transactions. At present, Europe is the products (Lee et al., 2011). If consumers do not have an awareness of a
world’s largest CBEC market, and the CBEC market in North America is product, they will not show any interest in it or desire towards it; hence
at a high-speed development stage (ICIECC, 2018). In 2018, global no purchase will take place. Furthermore, in the long run, sellers will
business-to-consumer (B2C) CBEC transactions reached US$ 676 bil- not be successful in CBEC because they are unable to attract more
lion, which increased by 27.5% over the previous year. It is estimated buyers and increase their market share (Mou et al., 2017).
that this number will exceed US$ 1 trillion in 2020 (ICIECC, 2018). In In view of the abovementioned considerations, this study analyzes
addition, Forrester (2018) predicts that CBEC will grow faster than the role of product cognition on consumers’ purchase intention on CBEC
domestic e-commerce in the next four years. By 2022, global CBEC sales platforms. So far, academic research on CBEC has mainly focused on the
will account for 20% of all e-commerce. Moreover, driven by China, the fields of logistics (Hsiao et al., 2017), behavior (Cui et al., 2019), as well
Asia-Pacific region will become the largest CBEC market. as effects (Wang and Lee, 2017). Little has been done to address the
CBEC brings various benefits to sellers and buyers, but it also in- influence of product cognition on purchase intention in CBEC settings.
tensifies market competition (Cui et al., 2019; Mou et al., 2019). In a Taking into account the sequential process of consumers’ response to
CBEC setting, due to differences in language, culture, history, and product information in the hierarchy-of-effects (HOE) model, we

*
Corresponding author. School of Economics and Management, Xidian University, 266 Xinglong Section of Xifeng Road, Xi'an, Shaanxi, 710126 , China.
E-mail address: jian.mou@xidian.edu.cn (J. Mou).

https://doi.org/10.1016/j.jretconser.2019.07.004
Received 18 May 2019; Received in revised form 20 June 2019; Accepted 6 July 2019
0969-6989/ © 2019 Elsevier Ltd. All rights reserved.
W. Zhu, et al. Journal of Retailing and Consumer Services 51 (2019) 320–330

consider the effect of product cognition on purchase intention as a se- process of consumers’ response to information, and systematically il-
quential process. In this study, we propose a three-stage model to detect lustrates the transformation process from consumers’ ignorance of a
the influence of product cognition on purchase intention in CBEC based product to the actual purchase behavior (Smith et al., 2008). It is a
on the HOE model and the commitment-involvement theory (Helgeson sequential process consisting of three stages: cognition, affect and
et al., 2002). Our three-stage theoretical model can identify several key conation. In the cognition stage, consumers know or perceive product
factors responsible for systematically predicting consumers’ purchase information and identify with products or services. This stage includes
intention in CBEC. Moreover, it can reflect the consumers’ entire pro- the perception of product, the awareness and understanding of product
cessing and response process on CBEC platforms. attributes, characteristics and advantages (Barry and Howard, 1990). In
There have been studies on purchase intention in CBEC, however the affect stage, consumers’ attitudes and affects towards products and
most of them focused on exploring and analyzing the motivation and platforms are gradually cultivated, and consumers form a good im-
risk perspectives (Mou et al., 2017; Lee et al., 2015). We believe there is pression and a certain degree of preference for them. This stage can
a lack of research on the impact of product cognition on purchase in- reflect the consumers’ strong preference, such as the desire, conviction,
tention. This study will therefore analyze the entire processing and and so forth (Barry and Howard, 1990). In the action stage, consumers’
response process from consumers’ product cognition to their purchase purchase desire is stimulated, and their strong preference leads them to
intention on CBEC platforms, and investigate the key factors and their take actions on the products. At that time, they will try, buy and use
influencing mechanism at each stage of the process. products and services (Barry and Howard, 1990).
The potential contribution of this study will enable sellers to im- Taking into account the various decision-making situations of con-
prove consumers’ product cognition in order to attract more buyers and sumers in CBEC, we adopt the operationalization of a sequential process
generate more profits on CBEC platforms. Moreover, it will help aca- consisting of cognition, affect and conation. This sequence is consistent
demics and practitioners understand the situation and dynamics of with the processing and response of consumers in the context of CBEC.
consumers at each stage by analyzing their entire processing and re- Initially, something attracts the attention of a consumer on a CBEC
sponse process on CBEC platforms. platform (cognition). Then, the consumer forms an interest and desire
The remainder of this paper is organized as follows. First, the the- in something (affect). Lastly, the consumer takes action on the CBEC
oretical background for this study is reviewed. Second, we propose a platform (conation). In this study, cognition is viewed as a mental ac-
research model and develop hypotheses based on the theoretical tivity that is reflected in consumers’ thoughts, beliefs or knowledge of
foundations gathered from the literature. Third, our research metho- some products on CBEC platforms (Barry and Howard, 1990), and we
dology is detailed. Finally, the data analysis results, implications and call this stage product cognition. Furthermore, affect is treated as the
further research directions are presented. degree of feelings and emotions which can be attributed to the CBEC
platform (Wijaya, 2015). In this study, we refer to this stage as platform
2. Theoretical background emotion. Finally, conation reflects the intension to perform a behavior
(e.g., purchase) or the behavior itself on CBEC platforms (Egan, 2007).
2.1. Purchase intention in CBEC We refer to this stage as behavior intention.
In the product cognition stage, consumers begin with no awareness
In view of its fast paced development, CBEC has naturally been the of the product. In this situation, a specific description of the product
subject of academic research. Table 1 gives an overview of the major may arouse consumers’ interest, so as to maintain their attention long
studies in this domain. From Table 1, we can see that existing research enough to establish a mental connection between product description
involved a wide range of issues and employed diverse research and product cognition (Smith et al., 2008). Once this connection is
methods. It should be noted that prior work on CBEC can provide a established, consumers will be aware of the product and consider it as a
great research basis for subsequent studies on this topic. factor during their decision-making (Smith and Swinyard, 1988). Thus,
Scholars have also considered consumer purchase intention in the we choose product description and product awareness as analytical
CBEC context. For instance, Yoon and Zhang (2018) validated the key variables during this stage. Product description is a synthesis of all
factors affecting the cross-border adoption of feedback posted on social elements related to the description of a product, and may produce an
media. An experimental study confirmed that the adoption of opinions emotional response when purchasing products online (Park et al.,
about Korean cultural products indeed influenced Chinese consumers’ 2005). On the other hand, product awareness refers to the degree to
intention to purchase cultural products made in Korea. Furthermore, which consumers may become familiar with the products sold through
Han and Kim (2019) tested a research model to analyze the influence product presentation or product description (Collins, 2007).
mechanism of purchase intentions in CBEC, and found that consumer Previous studies in consumer research have shown several different
informedness positively affected purchase intentions. In addition, Mou conceptualizations and operationalizations of involvement (Drossos
et al. (2017) drew on the valence framework to develop and test a re- et al., 2014). The degree of involvement is positively correlated with
search model of buyer repeat purchase intentions in CBEC. The results individuals’ cognitive participation (Petty et al., 1983). In the platform
revealed that positive valences exerted the strongest effects on repeat emotion stage, with the gradual increase of consumers’ understanding
purchase intention, and that negative valences were significant. Lee of product description and product awareness, consumers are increas-
et al. (2015) identified factors that influenced fashion consumers’ ingly involved in the platform that displays these products (Celsi and
purchase intentions in cross-border online shopping. The results Olson, 1988). They will pay more attention to their feelings and in-
showed that three motivations (utilitarian, social, and hedonic) had terests and therefore spend more time processing and responding on
positive effects on cross-border online shopping purchase intentions, this platform. During the involvement process, consumers can con-
but perceived risk did not negatively influence purchase intentions. tinuously enhance the level of trust towards the product providers.
From our review of the literature on purchase intention in CBEC, we Thus, during this stage we choose platform involvement and perceived
found that existing research mainly investigated the factors influencing trust as analytical variables. In this study, platform involvement refers
purchase intention, while our study classifies the factors into different to the perceived relevance of CBEC platforms based on consumers’
decision-making stages. We therefore expect our study to reach a more values, interests and needs (Jiang et al., 2010). Additionally, perceived
profound and comprehensive conclusion. trust is regarded as consumers’ confidence in product providers on
CBEC platforms (Wang and Hazen, 2016).
2.2. Hierarchy-of-effects (HOE) model In the behavior intention stage, consumers see a CBEC platform as a
preference (Smith et al., 2008). On this preferred platform, products
The HOE model is a response hierarchy model that describes the displayed will create potential behaviors from consumers (Peng et al.,

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Table 1
Summary of studies on CBEC.
Topic Major contents Methods Major results References

Logistics Analyzed the relationships between the feelings of customers and service Partial least squares and text In addition to conventional customer surveys, user generated online content Hsiao et al. (2017)
elements of cross-border logistics service. mining techniques analysis should be an effective way of catching customer-oriented design
elements.
Reviewed scientific publications in the field of logistics underlying CBEC in Systematic review CBEC in China was gaining increasing interest, as shown by the rising amount Giuffrida et al.
China. of publications from 2013 onwards. However, studies investigating the (2017)
relation between logistics and CBEC seemed to be lacking.
Analyzed the mode of Chinese CBEC logistics. Systematic review Summarized the ten major logistics modes for export trade and import trade. Jiao (2016)
Drives and barriers How to Explore the potential for CBEC transactions between Canada and the Systematic review Constructed two distribution network models to analyze the process and Gessner and
United States. program participation of Canadian or American enterprises. Snodgrass (2015)
Proposed and validated that CBEC as enterprise innovation should include Hierarchical regression Business model innovation played a full mediating role in the relationship Chen and Yang
business model innovation, not just institutional innovation or technological between government pro-innovation policy and firm performance, while (2017)
innovation. technological innovation had a partial mediating effect.
Explored whether distance was still important for online trade in physical Mathematical Modeling Distance-related trade costs were greatly reduced compared to offline trade in Gomez-Herrera et al.
goods. the same goods. (2014)
Effects Explored the impact of CBEC on international trade in the context of China by Mathematical Modeling CBEC had a positive role in promoting international trade only when the Wang and Lee (2017)
analyzing information cost, negotiation cost, transportation cost, tariffs and negative impact caused by tariffs cost and transportation cost was offset. In
middlemen cost separately. addition, CBEC had a positive effect on the growth of Chinese international

322
trade each year.
Examined distance effects on CBEC and in particular the importance of Correlation test and Express delivery reduced distance for cross-border demand. Furthermore, the Kim et al. (2017)
express delivery in reducing the time dimension of distance. mathematical modeling adoption of express delivery was positively associated with e-loyalty in terms
of repurchase rates.
Consumers’ Explored the determinants of the individual’s decision to perform CBEC. Logistic regression Being a male was positively related to the probability of practicing CBEC. Valarezo et al. (2018)
behavior Education was positively and significantly related to the probability of being
involved in CBEC within European Union countries. Computer and Internet
Skills were significant and positive factors in practicing CBEC.
Examined service justice as the antecedent factor of dysfunctional customer Structural equation modeling Service justice had a negative significant correlation with negative emotion, Lin et al. (2018)
behavior (DCB) and how it interacted with negative emotion and service (SEM) and negative emotion significantly induced service dissatisfaction. In
dissatisfaction, which in turn, affected DCB. addition, both negative emotion and service dissatisfaction were positively
correlated with DCB.
Sellers’ behavior Examined both the antecedents and the impacts of sellers’ trust on buyers and SEM Sellers’ trust in buyers had a negative impact on perceived risk of chargeback Guo et al. (2017)
their perceived risk of chargeback fraud on sellers’ intention to trade with fraud, and had a positive impact on sellers’ intention to trade.
buyers in CBEC.
Identified sellers’ behaviors and their decisions on which platforms to Sequential multi-method More than 67% of sellers were interested in participating in cross-border Cui et al. (2019)
participate. platforms, where trust and perceived benefits were both important to the
decision-making process.
Culture Explored 100 German companies’ domestic, U.S., U.K. and Latin American Analysis of variance (ANOVA) Cultural value depiction was not very strong in the relevant markets, thus a Sinkovics et al.
websites and employed a cultural value analysis. certain degree of ‘cultural alienation’ took place. (2007)
Journal of Retailing and Consumer Services 51 (2019) 320–330
W. Zhu, et al. Journal of Retailing and Consumer Services 51 (2019) 320–330

2019). During this stage, we choose purchase intention as the analytical 3. Research hypotheses
variable. This variable measures the consumers’ intention to purchase a
product. 3.1. Impacts of product cognition on platform emotion

3.1.1. Product description

2.3. The commitment-involvement theory Uncertainty reduction theory suggests that in initial interactions,
the length and depth of communication can reduce uncertainty and
The commitment-involvement theory is the combination of the in- enhance the trust between the communicating parties (Sunnafrank,
volvement theory and commitment. The involvement theory is used to 1986). In the case of product description, information quality can in-
predict people’s attitudes, and posits that when people are stimulated or fluence the consumers’ perception and understanding of the informa-
in a certain situation, they feel a degree of relationship between the tion’s credibility and accuracy (Kim et al., 2008). Moreover, it is im-
stimulation or situation and themselves, which leads to interest (Sherif portant for consumers to obtain and process high quality product
and Cantril, 1947). Commitment can be regarded as “a variable which description (Miranda and Saunders, 2003). The extent of quality
encompasses the ranges of allegiance an individual may be said to have available in a product description on a platform helps consumers assess
for the social system of which he is member” (Hornback, 1971, pp. 65). the attributes of the product and reduces uncertainty about the product
Presently, many studies regard commitment-involvement as a different (Racherla et al., 2012), thereby enhancing their perceived trust in the
view of solving the relationship between consumers’ behaviors and product and its provider. In addition, signal theory is used in situations
attitudes (Kahle and Homer, 1988). According to the commitment-in- of uncertainty and explains environments with incomplete information
volvement theory, when an individual had a strong commitment to an (Landgrebe, 2005). It can be used to explain the relationship between
activity or behavior, she/he is unlikely to take the initiative to termi- signals and trust. Consumers perceive high quality product description
nate this activity or behavior (Helgeson et al., 2002). Recently, the as a credible commitment of a high-quality product provider
commitment-involvement theory has been extended to explain con- (Mavlanova and Benbunan-Fich, 2010). So consumers believe that
sumers’ behavior in fields such as tourism (Ferns and Walls, 2012) and these providers are reliable to a certain extent, and therefore consider
social psychological activities (Havitz and Mannell, 2005). them trustworthy. We hence hypothesize:
In this study, according to the commitment-involvement theory,
H1. High quality product description has a significant positive impact
platform involvement is divided into platform enduring involvement
on perceived trust.
and platform situational involvement. Platform enduring involvement
reflects a sustained level of concern with the platform. It can be stable
for a long time (Albaum et al., 1998). This involvement is related to the 3.1.2. Product awareness
consumers’ experience with the platform (Hong, 2015), and reflects Yoon (2002) suggested that awareness is significantly related to
their long-term interest in it. Consumers with high levels of enduring online trust. Trust is a consumer’s psychological state of confidence and
involvement, to a large extent, perceive the platform as highly im- positive expectations, and it plays a role when the consumer has high
portant and relevant (Im and Ha, 2011). In contrast to platform en- product awareness (Yoon, 2002). According to Cheskin (2000), a seller
during involvement, platform situational involvement reflects tem- needs to be recognized as trustworthy in order to become an effective
porary feelings for the platform in terms of consumers’ desires, interests product provider. High product awareness enhances perceived trust in
and convictions. It can be influenced by a special situation on the the sense that product awareness is a prerequisite to trust formation and
platform. Consumers’ perceived relevance and importance for the it is necessary for trust to rise (Cheskin, 2000). Moreover, awareness
platform is a state that occurs in some circumstances (Havitz and can have an important impact on the creation of online trust. Greenfield
Mannell, 2005). Platform situational involvement increases if the con- Online (1998) found that surveyed customers (whether they purchased
sumers can foresee negative consequences on the platform, in which a product on the platform or not) believed that product awareness
case they are more cautious about something (e.g., product) on the played a role in the constitution of their perceived trust. Thus, product
platform. awareness can be regarded as an important factor for gaining perceived
trust in online product providers. We therefore hypothesize:
H2. High product awareness has a significant positive impact on
2.4. Perceived trust
perceived trust.
In the online shopping process, consumers usually face a variety of
uncertainties which can be alleviated through perceived trust. In CBEC 3.2. Impacts among internal variables of platform emotion
settings, when consumers engage in online transactions, perceived trust
plays an important role in eliminating uncertainty and uncontroll- 3.2.1. Platform involvement
ability. Considering the credibility of information provided by online Social judgment theory suggests that individuals with higher in-
merchants (Lemire et al., 2008), we choose the product provider’s volvement can evaluate more results than other individuals, thus they
ability, benevolence, and integrity as measurements for perceived trust, may be difficult to persuade (Sherif et al., 1965; Hong, 2015). In other
which may influence consumers’ behavior intentions toward the pro- words, the higher consumers’ involvement in a platform is, the less
duct. If consumers perceive the ability, benevolence and integrity of a likely they are to be persuaded by other platforms and the greater their
product provider, they will increase perceived trust toward the provider trust in this platform and its product providers is. Also, involvement
and engage in purchase behavior with the provider on a CBEC platform. may have various influences on consumer psychology (Eslami and
Exploring perceived trust on CBEC platforms and the model devel- Ghasemaghaei, 2018; Teichert and Rost, 2003). Symbolic and hedonic
oped in this study, ability refers to the group of skills, competencies, values may establish a psychological tie between consumers and pro-
and characteristics that enable a seller to influence the process of pro- duct providers (Beatty et al., 1988). Thus, consumers with platform
viding products (Mayer et al., 1995). Benevolence is the extent to which involvement are aware of the importance of product and purchase
a seller is believed to want to do good to consumers, aside from an (Hong, 2015), which fosters the creation process of perceived trust.
egocentric profit motive (Mayer et al., 1995). Integrity involves the With regards to the two types of platform involvement in this study,
consumers’ perception that the seller adheres to a set of principles that platform enduring involvement reflects consumers’ long-term interest
consumers find acceptable (Mayer et al., 1995). in CBEC platforms, while platform situational involvement represents
consumers’ temporary interest in CBEC platforms (Park et al., 2007).

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Whether it is a long-term or temporary interest, consumers always need 3.4. Mediation effects in the three-stage model
to make the right decision in the process of shopping. For this, con-
sumers need to enhance the level of perceived trust in product providers Our proposed three-stage model assumes that the consumer re-
and obtain sufficient information to comprehensively evaluate products sponse process is ordered as follows: product cognition-platform emotion-
and make good decisions (Hong, 2015). This indicates a positive re- behavior intention (see Fig. 1). This means that the influence of the early
lationship between platform enduring involvement or platform situa- variables (product description and product awareness) on the later
tional involvement and perceived trust on CBEC platforms. We there- variable (purchase intention) is fully mediated. In view of this, the
fore hypothesize: three-stage model will not show the direct effects of product cognition
on behavior intention through other paths. Therefore, in order to test
H3a. Platform enduring involvement has a significant positive impact
whether perceived trust in the model has mediation effects, we iden-
on perceived trust.
tified the significant paths in the model. We examined the full media-
H3b. Platform situational involvement has a significant positive impact tion effects of perceived trust to test whether our three-stage model can
on perceived trust. show the sequence of consumers’ processing and response on CBEC
platforms.
3.3. Impacts of platform emotion on behavior intention
4. Methodology
3.3.1. Platform involvement
For this research, we collaborated with DHGate.com, a well-known
Previous research demonstrated that involvement affected con-
Chinese CBEC platform. DHGate.com was established in 2004 as the
sumers’ attitudes and behaviors on a website (Eroglu et al., 2003; Kim
first online platform to provide business-to-business (B2B) cross-border
et al., 2007). An involved consumer needs to evaluate more informa-
transactions for small and medium-sized enterprises (SMEs) in China.
tion, and spends more time and effort to make decisions and take ac-
Our collaboration with DHGate.com stems from the following three
tions (Jiang et al., 2010; Bian and Moutinho, 2008). High involvement
reasons. (1) DHGate.com is a global online trade website, which meets
indicates that consumers actively acquire and process as much in-
the basic requirements of CBEC platforms. (2) DHGate.com has been
formation as possible on a platform (Schlosser, 2003). Therefore, the
conducting global online trade for over 14 years and has 2 million
more consumers are involved with a website, the more they purchase
Chinese online suppliers and 22 million kinds of commodities, which
on that website (Richard, 2005).
enables us to test our research hypotheses reasonably. (3) DHGate.com
In this study, as far as the two types of platform involvement are
has 19 million registered buyers from 222 countries and regions around
concerned, enduring involvement with products on the platform may
the world. This gives us access to an appropriate population to survey
have a positive influence on purchase intention (Peter and Olson, 1996)
for our research.
because it is easier for consumers to make decisions in the light of
product information. Furthermore, purchase experience on a platform
4.1. Scale design
can increase enduring involvement and further improve purchase in-
tention (Laaksonen, 1994). On the other hand, situational involvement
We designed 30 items related to the 8 variables of the theoretical
is usually caused by the shopping environment (Im and Ha, 2011).
model, and used a 5-point Likert scale. Respondents were asked to rate
Enhanced situational involvement can eliminate consumers’ un-
items from 1 (“completely disagree”) to 5 (“completely agree”). All the
certainties to some extent and reduce their costs and social risks in the
measurement items were adapted from prior validated measures. All
shopping process. Thus, consumers will spend more time on a platform,
measurement items are presented in Appendix A.
which will produce higher purchase intentions on this platform. So we
attempt to test the following hypotheses:
4.2. Data collection
H4a. Platform enduring involvement has a significant positive impact
on purchase intention. We first conducted a pilot test to assess the comprehensibility of the
scale, the clarity of the measurement items, and the appropriateness of
H4b. Platform situational involvement has a significant positive impact
the survey questions in the CBEC context. As for the recruitment of
on purchase intention.
participants in our survey, we selected buyers who use the DHGate.com
platform. Participation was entirely voluntary. Participants were pro-
3.3.2. Perceived trust vided with three options: “participate now”, “maybe next time”, or “do
Online shopping requires consumers to evaluate sellers’ social not ask again”. Obviously, no matter which one of the three options
connections to help them make a better decision (Gefen et al., 2003). they chose, participants would not lose anything or be negatively af-
Perceived trust can determine consumers’ reliance on the information fected in any way. The sample selected for this study consisted of
and behaviors of product providers (Hajli et al., 2017). Mayer et al. consumers with shopping experience on CBEC platforms, which al-
(1995) studied three characteristics (ability, benevolence, and in- lowed us to effectively analyze the influence of product cognition on
tegrity) of the parties that influence trust. These three characteristics behavior intention. During the survey, we did not record the personal
can enhance consumers’ reliance on the product provider, reduce information of respondents in order to ensure their anonymity. The
transaction uncertainty, and extend the relationship with product pro- survey was compiled in English, and was conducted from January 22,
viders (Suh and Han, 2003). In other words, perceived trust can reduce 2019 to February 28, 2019. In total, 515 respondents participated in
consumers’ risk perception while shopping on a platform, thereby en- our survey and 473 responses were deemed usable. Detailed descriptive
hancing their participation in “trust-related behaviors”, such as making statistics are shown in Table 2.
purchases. In addition, several prior studies have shown a direct effect
between trust and purchase intention (Pappas, 2016; Lu et al., 2010, 4.3. Descriptive statistics
2016). Accordingly, we expect that perceived trust will also positively
influence purchase intention. We hypothesize: The descriptive statistics of all measurement items are shown in
Table 3. We conducted Kolmogorov-Smirnov tests to examine the
H5. Perceived trust has a significant positive impact on purchase
normality in all items by using SPSS 17.0 software. In Table 3, the K-S Z
intention.
scores indicate that there is a significant difference between the dis-
The research model of this study is shown in Fig. 1. tribution of every item and the normal distribution.

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Fig. 1. Research model.

Table 2 Table 3
Descriptive statistics of the respondents’ characteristics. Descriptive statistics of all measurement items.
Demographics Category Frequency Percentage Variables Items Mean Standard Skewness Kurtosis K-S Z p
deviation score
Gender Male 252 53.3
Female 221 46.7 PD PD1 3.96 1.08 −0.87 −0.02 5.99 < 0.01
Age ≤20 40 8.4 PD2 3.96 1.04 −0.84 0.03 5.20 < 0.01
21–30 132 27.9 PD3 3.76 1.44 0.22 −1.32 5.75 < 0.01
31–40 94 19.9 PA PA1 4.10 1.06 −1.07 0.45 4.87 < 0.01
41–50 103 21.8 PA2 4.02 1.05 −0.95 0.30 4.75 < 0.01
51–60 61 12.9 PA3 4.13 1.02 −1.18 0.96 3.98 < 0.01
≥61 43 9.1 EI EI1 4.04 1.12 −1.12 0.58 5.59 < 0.01
Experience in CBEC Less than one month 38 8.0 EI2 3.61 1.28 −0.60 −0.68 4.16 < 0.01
One to three months 67 14.2 EI3 3.90 1.12 −0.87 0.11 4.88 < 0.01
Three to twelve months 118 24.9 EI4 3.92 1.12 −0.89 0.11 4.83 < 0.01
More than one year 250 52.9 EI5 3.92 1.15 −0.89 0.01 5.25 < 0.01
SI SI1 4.01 1.15 −1.12 0.50 5.42 < 0.01
SI2 4.02 1.12 −1.16 0.77 5.17 < 0.01
SI3 3.85 1.14 −0.87 0.12 4.78 < 0.01
5. Data analysis and results
SI4 3.38 1.36 −0.39 −0.97 4.54 < 0.01
SI5 3.86 1.28 −0.92 −0.24 5.32 < 0.01
5.1. Reliability and validity test PT PTB PTB1 4.14 1.05 −1.31 1.28 5.73 < 0.01
PTB2 4.06 1.09 −1.14 0.72 5.53 < 0.01
SPSS 17.0 software was used to conduct an exploratory factor PTB3 4.12 1.01 −1.15 0.98 5.59 < 0.01
PTI PTI1 3.97 1.08 −0.89 0.18 5.13 < 0.01
analysis. The analytical results show a KMO value of 0.95 and an ap-
PTI2 3.94 1.11 −0.89 0.17 5.09 < 0.01
proximate chi-square value of 14543.579 (p < 0.001), which indicates PTI3 3.94 1.12 −0.90 0.12 5.02 < 0.01
that the data can be analyzed using the exploratory factor analysis PTI4 3.93 1.09 −0.88 0.15 4.84 < 0.01
(Williams et al., 2010). In this analysis, we used the principal compo- PTA PTA1 3.89 1.10 −0.81 0.02 4.72 < 0.01
PTA2 3.97 1.07 −0.95 0.44 4.91 < 0.01
nent extraction technique and the varimax rotation method. As a result,
PTA3 3.99 1.08 −1.05 0.58 4.92 < 0.01
8 factors were extracted, which explains 77.13 percent of variance to- PTA4 3.95 1.12 −0.99 0.34 4.79 < 0.01
tally. Notably, the factor loadings of EI2 and SI5 were both less than PI PI1 4.28 1.13 −1.70 2.05 7.46 < 0.01
0.7, which means that the correlations between these two items and PI2 4.27 1.12 −1.65 1.99 7.28 < 0.01
loaded factors were not strong on this scale. Thus, we deleted the two PI3 3.97 1.32 −1.16 0.16 6.54 < 0.01

items (EI2 and SI5). Other factor loading results are shown in Table 4.
We tested the reliability of the scale using SPSS 17.0 software and
discriminant validity respectively. The analytical results of convergent
Lisrel 8.1 software. The analytical results are shown in Table 4. We can
validity are also shown in Table 4. We can see that all average variance
see that the values of Composite Factor Reliability (CFR) and Cronbach
extracted (AVE) values are greater than 0.5, which confirms the con-
α are greater than 0.7, indicating that this scale is indeed reliable
vergent validity of the scale (Muhammad et al., 2011). The analytical
(Royal and Hecker, 2016).
results of discriminant validity are shown in Table 5 where the square
In the validity test, we tested the convergent validity and
root (diagonal values) of all AVE values exceed the correlation

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Table 4 perceived trust (β = 0.12, p < 0.05). So H1 was supported. Moreover,

Statistical results of some indicators. a significant positive effect of product awareness on perceived trust was
Factors Items Loadings AVE CFR Cronbach α found (β = 0.15, p < 0.01). Therefore, H2 was supported. Ad-
ditionally, the other two variables that influence perceived trust were
PD PD1 0.74 0.55 0.79 0.84 found to be significant: enduring involvement (β = 0.16, p < 0.01)
PD2 0.74
and situational involvement (β = 0.32, p < 0.001). So H3a and H4a
PD3 0.75
PA PA1 0.80 0.63 0.84 0.90
were both supported. Lastly, situational involvement (β = 0.71,
PA2 0.80 p < 0.001) and perceived trust (β = 0.09, p < 0.05) both produced
PA3 0.78 significant positive impacts on purchase intention. However, enduring
EI EI1 0.71 0.62 0.87 0.94 involvement did not significantly influence purchase intention
EI3 0.82
(β = 0.03, p > 0.05). So H4b and H5 were both supported, but H3b
EI4 0.79
EI5 0.82 was not supported. In the hypothesis test, the direct and indirect effects
SI SI1 0.76 0.55 0.83 0.87 of the research model are displayed in Table 7. Table 8 shows the total
SI2 0.74 effects and the coefficient of determination (R2) in our model.
SI3 0.74
SI4 0.72
PT PTB PTB1 0.76 0.64 0.84 0.94
5.4. Mediation effect test
PTB2 0.82
PTB3 0.81 According to the theoretical model and statistical analysis results,
PTI PTI1 0.84 0.74 0.92 0.95 the path coefficients of product description (β = 0.12, p < 0.05) and
PTI2 0.86
product awareness (β = 0.15, p < 0.01) to perceived trust were sig-
PTI3 0.87
PTI4 0.86 nificant respectively, and the path coefficient of perceived trust to
PTA PTA1 0.81 0.66 0.88 0.94 purchase intention was significant (β = 0.09, p < 0.05), which means
PTA2 0.82 that perceived trust played a full mediation role in our model. To test
PTA3 0.82 the full mediation effect, following (Wen and Ye, 2014), we used the
PTA4 0.79
PI PI1 0.79 0.60 0.82 0.86
Mplus 7.0 software’s Bootstrap method to test the above mediation
PI2 0.81 effects. After setting up the repeated 2000 Bootstrap samples and 95
PI3 0.73 percent bias-corrected confidence intervals, the confidence intervals of
the mediation effects of perceived trust were found to be [0.047, 0.106]
and [0.022, 0.068] respectively. The zero point was not included in
Table 5 these two confidence intervals. This verifies the full mediation effect of
Statistical results of discriminant validity. perceived trust. Therefore, in our three-stage model, there was no al-
Factors PD PA EI SI PTB PTI PTA PI ternative path representing direct effects from product cognition to
behavior intention. In other words, consumers’ processing and response
PD 0.74
on CBEC platforms is a sequential activity.
PA 0.56 0.79
EI 0.52 0.56 0.79
SI 0.58 0.56 0.69 0.74 6. Findings and conclusion
PTB 0.48 0.50 0.57 0.64 0.80
PTI 0.49 0.47 0.57 0.68 0.67 0.86 This study developed a three-stage model in order to assess the in-
PTA 0.51 0.52 0.62 0.67 0.68 0.68 0.81
PI 0.52 0.55 0.58 0.68 0.52 0.56 0.57 0.77
fluence of product cognition on behavior intention in a CBEC setting
based on the HOE model and the commitment-involvement theory, as
well as the possible mediation effects of perceived trust. Our model
coefficients between two factors, which means that the discriminant enabled us to identify the following interesting insights.
validity of the scale is acceptable. First, a high quality product description has a significant positive
impact on perceived trust on CBEC platforms. This is consistent with the
findings of previous studies in traditional e-commerce settings (e.g., Ha
5.2. Common method biases test and multiple collinearity test
(2004) and Lee et al. (2011)). In CBEC settings, there are various bar-
riers between consumers and sellers, such as language, culture, etc., but
Using Harman’s single factor test, we analyzed the common method
a high quality product description still plays an important role in the
biases. The results of the principal component analysis indicate that the
formation of perceived trust. A high quality product description can
factor with the largest proportion of variance explains 29.93 percent of
alleviate foreign customers’ uncertainty about products and reduce
the total variance. Therefore, there are no common method biases in
their perceived risk to some extent. Our results also show that a high
our study (Podsakoff and Organ, 1986). Furthermore, as can be seen in
quality product description can enhance consumers’ trust beliefs to-
Table 5, the correlation coefficients between any two factors are less
wards product providers.
than 0.7, which means there is no serious multiple collinearity in our
Second, high product awareness has a significant positive influence
study.
on perceived trust on CBEC platforms. Previous research has shown
that, on traditional e-commerce platforms, high product awareness has
5.3. Hypothesis test a significant positive influence on trust (Smith and Wheeler, 2002;
Komiak and Benbasat, 2004). On CBEC platforms, consumers see a
We conducted the hypothesis test using structural equation mod- variety of foreign online products, and they usually need to spend more
eling in Lisrel 8.7 software. The main fitting indices and evaluation mental effort and dedicate more cognitive capacity to identify such
criteria are shown in Table 6. Comparing the main fitting indices with products than they would for domestic online products. If a product can
the evaluation criteria values, we found all the main fitting indices attract consumers’ awareness in a more appealing way, such as using
values in our model to be acceptable, which indicates that the data and colorful and moving pictures, interesting animations, videos, etc., then
model fitted well. consumers will be more impressed by the product. This will increase
Fig. 2 shows the values of normalized path coefficients in our model. their positive feelings and emotions towards the product and the pro-
There was a significantly positive effect of product description on duct provider. The results of this study prove that such feelings and

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Table 6
Fitting indices and evaluation criteria of research model.
Fitting indices Absolutely indices Parsimony indices Incremental indices

GFI AGFI RMSEA PNFI PGFI CFI NFI IFI

Values of fitting indices 2.93 0.91 0.88 0.07 0.81 0.68 0.99 0.98 0.99
Evaluation criteria values (Ullman and Bentler, 2012) <3 > 0.9 > 0.8 < 0.08 > 0.5 > 0.5 > 0.9 > 0.9 > 0.9

emotions are reflected in consumers’ perceived trust in product provi- Table 7

ders. Direct effects and indirect effects of research model.
Third, platform involvement has a significant positive effect on Factors Direct effects Indirect effects
perceived trust in CBEC settings. More specifically, both platform en-
during involvement and platform situational involvement have a sig- PD PA EI SI PT PD PA EI SI
nificant effect on perceived trust. This conclusion is consistent with
PT 0.12 0.15 0.16 0.32 – – – – –
those obtained in traditional e-commerce environments (Hong, 2015). PI – – 0.03 0.71 0.09 0.01 0.01 0.02 0.03
In CBEC, a platform brings consumers into contact with providers, fa-
cilitating value exchange between them. Once consumers have a high
involvement on a platform, they will spend more time and effort en- Table 8
gaging in some activities on this platform. With the increase of in- Total effects and coefficient of determination (R2) in research model.
volvement, consumers will gradually show trust and commitment to-
Factors Total effects R2
wards this platform. Our results show that whether platform
involvement is enduring or situational, it will eventually influence the PD PA EI SI PT
level of consumers’ trust in product providers.
PT 0.12 0.15 0.16 0.32 – 0.40
Fourth, platform situational involvement has a significant positive
PI 0.01 0.01 0.05 0.74 0.09 0.62
effect on purchase intention, but this effect is not significant in the
relationship between platform enduring involvement and purchase in-
tention. This conclusion is different from the results obtained in tradi- psychological activities and behavioral motivations in the enduring
tional e-commerce settings (Jiang et al., 2010; Huang et al., 2010). On a involvement of the platform are more complicated than those in the
CBEC platform, in theory, consumers with higher platform involvement platform’s situational involvement, which eventually leads to a non-
may make purchase decisions when facing products and product pro- significant purchase intention.
viders (Richard, 2005). However, previous research indicates that Fifth, perceived trust has a significant positive impact on purchase
consumers do not have significant purchase intention under the en- intention in CBEC settings. This finding is also true for traditional e-
during involvement of such platform, which shows that consumers’ commerce (e.g., Lu et al., 2016; Lu et al., 2010). CBEC is a transaction

Fig. 2. Hypothesis testing results.

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between buyers and sellers in different countries, but its essence is still and stimulate consumers’ attention in various ways, for instance by
e-commerce. Therefore, as one of the critical factors of influencing using videos, pictures, etc. In this case, consumers’ perceived trust can
decision-making in e-commerce, perceived trust still plays a large role be increased, which will increase purchase intention and purchase be-
in the whole transaction process. This conclusion shows that perceived havior. On the other hand, in light of the functions and characteristics
trust also influences consumers’ purchase intention in CBEC settings. of CBEC platforms, after they succeed in understanding the shopping
Finally, perceived trust plays a full mediation role between product habits of consumers in different countries/regions, product providers
description and purchase intention as well as between product aware- should create a shopping environment conducive to consumers’ pro-
ness and purchase intention on CBEC platforms. In other words, ac- cessing and response to information, and try to make consumers spend
cording to our model, platform emotion plays a full mediation role as much time as possible on CBEC platforms, even for the purpose of
between product cognition and behavior intention. Although this study browsing. If necessary, product providers can also increase commu-
does not analyze the direct effect between product cognition and be- nication with consumers on how to browse and find products on their
havior intention, our research suggests that product cognition can affect CBEC platform, how to effectively use the functions of the platform, and
behavior intention through platform emotion. This conclusion reflects a how to conveniently purchase products. This will potentially increase
dynamic path for consumers to engage in a series of sequential activities consumers’ involvement on such platforms, which can stimulate con-
on CBEC platforms. This path embodies the dynamic process from sumers’ purchase activities.
cognition to emotion and from emotion to intention.
8. Limitations and future research
7. Implications
The main limitation of this study is that data collection was carried
7.1. Theoretical implications out on a single CBEC platform in China. Future studies could expand the
data collection process using multiple channels. This will be beneficial
The main theoretical contribution of this study is that we developed to obtain more comprehensive and profound conclusions. In addition,
a three-stage model in CBEC settings based on the HOE model. This this research only analyzed one of the dynamic response paths that
model describes the three stages that consumers go through when they influenced consumers’ purchase intentions on CBEC platforms based on
establish or form the purchase intention on CBEC platforms. Our em- the HOE model. Consumers’ purchase intention can be analyzed from
pirical results support the validity of our model. From the model we multiple perspectives and within multiple disciplines. Therefore, future
learned that consumers on CBEC platforms move over time through the research can be carried out based on this consideration.
successive steps of product awareness, product description (product
cognition), platform involvement, perceived trust (platform emotion), Acknowledgements
and purchase intention (behavior intention). In the traditional e-com-
merce environment, product cognition is not a main factor influencing This study was partially supported by the Fundamental Research
behavior intention. But in the CBEC environment, since consumers ty- Funds for the Central Universities of No. 20103176477, the Shandong
pically have different language and cultural backgrounds, the influence Social Science Planning Program (Grant NO. 16DGLJ04), Natural
of product description and product awareness on consumers cannot be Sciences and Engineering Research Council of Canada [grant number:
ignored. Furthermore, product cognition needs to go through a process 2018-05241], and QUT Undergraduate Teaching Construction and
to influence behavior intention. Hence we believe that researchers Reform Fund Program (Grant NO. F2018-088).
should consider the effects of product description or product awareness
and analyze such effects on other factors and the whole influencing Appendix A
process in the context of CBEC. In addition, according to the commit-
ment-involvement theory, our research focused on the important im- Measurement Items.
pact of two types of platform involvements (enduring involvement and Product description (PD) Smith et al. (2008).
situational involvement) on perceived trust and purchase intention re-
spectively. Our empirical analysis showed that both types of platform PD1: The products’ descriptions were easy to understand.
involvement can significantly influence perceived trust, but only si- PD2: I was able to comprehend the descriptions made about the
tuational platform involvement can significantly affect purchase in- products.
tention. It suggested that platform involvement can affect purchase PD3: The products’ descriptions were hard to understand.
intention either alone or through perceived trust. Our analysis makes
up for the lack of studies related to CBEC, and can provide a basis for Product awareness (PA) Smith et al. (2008).
exploring consumers’ behavior intentions from the perspective of in-
volvement. Our findings suggest that research should focus on the PA1: I am aware of the products on this platform.
products, services and functionalities of CBEC platforms in order to PA2: I can recall the products on this platform.
explore their potential impacts on consumers’ purchase intention from PA3: I can recognize the products on this platform.
the perspective of involvement. Unlike traditional e-commerce, CBEC
consumers, merchants, platforms providers, and third parties are all Enduring involvement (EI) Ferns and Walls (2012).
novel. Thus the adoption of involvement theory can help researchers
identify novel insights and implications. EI1: The pleasure of shopping on this platform is important.
EI2: The pleasure of shopping on this platform is of great concern.
7.2. Practical implications EI3: The pleasure of shopping on this platform means a lot.
EI4: The pleasure of shopping on this platform is significant.
Additionally, our conclusions suggest a number of practical im- EI5: The pleasure of shopping on this platform matters a lot.
plications for product providers implementing marketing plans on
CBEC platforms. On the one hand, product providers should improve Situational involvement (SI) Havitz and Mannell (2005).
the description and awareness of the products sold on their CBEC
platforms through marketing methods that enhance consumers’ cogni- SI1: The shopping activity on this platform interests me a lot.
tive levels regarding these products. For consumers around the world, SI2: I am really enjoying buying products on this platform.
sellers should make product information clear and easy to understand, SI3: I am confident that shopping on this platform is the right

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activity right now. paper. URL: http://www.199it.com/archives/746009.html.

SI4: Shopping on this platform gives a glimpse of the type of person I Gefen, D., Karahanna, E., Straub, D.W., 2003. Trust and TAM in online shopping: An
integrated model. MIS Q. 27 (1), 51–90.
really am. Gessner, G.H., Snodgrass, C.R., 2015. Designing E-commerce cross-border distribution
SI5: I will be annoyed if shopping on this platform proves to be a networks for small and medium-size enterprises incorporating Canadian and US trade
poor activity. incentive programs. Research in Transportation Business & Management 16, 84–94.
Giuffrida, M., Mangiaracina, R., Perego, A., Tumino, A., 2017. Cross-border B2C E-
commerce to greater China and the role of logistics: A literature review. Int. J. Phys.
Perceived trust (PT) Mou et al. (2016). Distrib. Logist. Manag. 47 (9), 772–795.
Gomez-Herrera, E., Martens, B., Turlea, G., 2014. The drivers and impediments for cross-
border E-commerce in the EU. Inf. Econ. Policy 28, 83–96.
PTB1: (Benevolence) I expect this platform’s product provider has Greenfield Online, 1998. Cybershoppers research report. URL: http://greenfieldcentral.
good intentions toward me. com/newsroom.html.
PTB2: (Benevolence) I expect this platform’s product provider is Guo, Y., Bao, Y., Stuart, B.J., Le-Nguyen, K., 2017. To sell or not to sell: Exploring sellers’
trust and risk of chargeback fraud in cross-border electronic commerce. Inf. Syst. J.
acting in my best interest.
28 (2), 359–383.
PTB3: (Benevolence) I expect this platform’s product provider Ha, H., 2004. Factors influencing consumer perceptions of brand trust online. J. Prod.
means well. Brand Manag. 13 (5), 329–342.
PTI1: (Integrity) This platform’s product provider is truthful. Hajli, N., Sims, J., Zadeh, A.H., Richard, M.O., 2017. A social commerce investigation of
the role of trust in a social networking site on purchase intentions. J. Bus. Res. (71),
PTI2: (Integrity) I would characterize this platform’s product pro- 133–141.
vider as honest. Han, J.H., Kim, H.M., 2019. The role of information technology use for increasing con-
PTI3: (Integrity) This platform’s product provider would keep its sumer informedness in cross-border electronic commerce: An empirical study.
Electron. Commer. Res. Appl. (34), 100826.
commitments to deliver quality products. Havitz, M.E., Mannell, R.C., 2005. Enduring involvement, situational involvement, and
PTI4: (Integrity) This platform’s product provider is sincere and flow in leisure and non-leisure activities. J. Leis. Res. 37 (2), 152–177.
genuine. Helgeson, J.G., Voss, K.E., Terpening, W.D., 2002. Determinants of mail-survey response:
Survey design factors and respondent factors. Psychol. Market. 19 (3), 303–328.
PTA1: (Ability) I believe this platform’s product provider is effective Hong, I.B., 2015. Understanding the consumer's online merchant selection process: The
in assisting me to search for products. roles of product involvement, perceived risk, and trust expectation. Int. J. Inf. Manag.
PTA2: (Ability) This platform performs its role of product provider 35 (3), 322–336.
Hornback, K.E., 1971. Toward a theory of involvement propensity for collective behavior.
very well. Socio. Focus 4 (4), 61–77.
PTA3: (Ability) Overall, this platform is a capable and proficient Hsiao, Y.H., Chen, M.C., Liao, W.C., 2017. Logistics service design for cross-border E-
provider of products. commerce using kansei engineering with text-mining-based online content analysis.
Telematics Inf. 34 (4), 284–302.
PTA4: (Ability) In general, this platform is a very knowledgeable
Hsu, C.J., Yen, J.R., Chang, Y.C., Woon, H.K., 2016. How do the services of low cost
provider of products. carriers affect passengers’ behavioral intentions to revisit a destination? J. Air Transp.
Manag. (52), 111–116.
Purchase intention (PI) Hsu et al. (2016). Huang, C.Y., Chou, C.J., Lin, P.C., 2010. Involvement theory in constructing bloggers'
intention to purchase travel products. Tourism Manag. 31 (4), 513–526.
ICIECC, 2018. ICIECC Releases 2017 World Electronic Commerce Report: Online
PI1: I intend to purchase products on this platform in the future. Shopping in the Asia-Pacific Region Will Account for Half of the World in 2018. .
PI2: I would purchase products on this platform in the future. URL:http://www.ec.com.cn/article/zhlt/swblh/201804/27259_1.html?from=
singlemessage.
PI3: I am inclined to purchase products on this platform in the fu- Im, H., Ha, Y., 2011. The effect of perceptual fluency and enduring involvement on si-
ture. tuational involvement in an online apparel shopping context. J. Fash. Mark. Manag.
15 (3), 345–362.
Jiang, Z., Chan, J., Tan, B.C.Y., Chua, W.S., 2010. Effects of interactivity on website in-
References volvement and purchase intention. J. Assoc. Inf. Syst. 11 (1), 34–59.
Jiao, Z.L., 2016. Modes and development characteristics of China’s cross-border E-com-
Albaum, G., Evangelista, F., Medina, N., 1998. Role of response behavior theory in survey merce logistics. In: Contemporary Logistics in China. Springer, Berlin, pp. 211–232.
research: A cross-national study. J. Bus. Res. 42 (2), 115–125. Kahle, S.E.B.L.R., Homer, P., 1988. The involvement-commitment model: Theory and
Barry, T.E., Howard, D.J., 1990. A review and critique of the hierarchy of effects in ad- implications. J. Bus. Res. 16 (2), 149–167.
vertising. Int. J. Advert. 9 (2), 121–135. Kim, M., 2018. Digital product presentation, information processing, need for cognition
Beatty, S., Kahle, L., Homer, P., 1988. The involvement-commitment model: Theory and and behavioral intent in digital commerce. J. Retail. Consum. Serv (in press).
implications. J. Bus. Res. 16 (2), 146–167. Kim, J., Fiore, A.M., Lee, H.H., 2007. Influences of online store perception, shopping
Bian, X., Moutinho, L., 2008. The role of product involvement, knowledge, and percep- enjoyment, and shopping involvement on consumer patronage behavior towards an
tions in explaining consumer purchase behaviour of counterfeits: Direct and indirect online retailer. J. Retail. Consum. Serv. 14 (2), 95–107.
effects. Research Memorandum (77), 1–34. Kim, T.Y., Dekker, R., Heij, C., 2017. Cross-border electronic commerce: Distance effects
Celsi, R.L., Olson, J.C., 1988. The role of involvement in attention and comprehension and express delivery in European Union markets. Int. J. Electron. Commer. 21 (2),
processes. J. Consum. Res. 15 (2), 210–224. 184–218.
Chen, N., Yang, J., 2017. Mechanism of government policies in cross-border E-commerce Komiak, S.X., Benbasat, I., 2004. Understanding customer trust in agent-mediated elec-
on firm performance and implications on M-commerce. Int. J. Mob. Commun. 15 (1), tronic commerce, web-mediated electronic commerce, and traditional commerce. Inf.
69–84. Technol. Manag. 5 (1/2), 181–207.
Cheskin Research Group, 2000. Trust in the wired americas. URL: http://www.cheskin. Laaksonen, P., 1994. Consumer Involvement: Concepts and Research. Routledge, London.
com/think/studies/trust2.html. Landgrebe, D.A., 2005. Signal Theory Methods in Multispectral Remote Sensing. John
Collins, C.J., 2007. The interactive effects of recruitment practices and product awareness Wiley & Sons, New York.
on job seekers' employer knowledge and application behaviors. J. Appl. Psychol. 92 Lee, S., Ha, S., Widdows, R., 2011a. Consumer responses to high-technology products:
(1), 180–190. Product attributes, cognition, and emotions. J. Bus. Res. 64 (11), 1195–1200.
Cui, Y., Mou, J., Cohen, J., Liu, Y., 2019. Understanding Information System Success Lee, C., Kim, J., Chan-Olmsted, S.M., 2011b. Branded product information search on the
Model and Valence Framework in Sellers’ Acceptance of Cross-Border E-Commerce: A web: The role of brand trust and credibility of online information sources. J. Mark.
Sequential Multi-Method Approach. Electron. Commer. Res. (1), 1–30. Commun. 17 (5), 355–374.
Drossos, D.A., Kokkinaki, F., Giaglis, G.M., Fouskas, K.G., 2014. The effects of product Lee, J.Y., Choo, H.J., Lee, H., 2015. Fashion consumers’ purchase intention on cross-
involvement and impulse buying on purchase intentions in mobile text advertising. border online shopping. Fashion & Textile Research Journal 17 (5), 741–753.
Electron. Commer. Res. Appl. 13 (6), 423–430. Lemire, M., Paré, G., Sicotte, C., Harvey, C., 2008. Determinants of internet use as a
Egan, J., 2007. Marketing Communications. Thomson Learning, US. preferred source of information on personal health. Int. J. Med. Inform. 77 (11),
Eroglu, S.A., Machleit, K.A., Davis, L.M., 2003. Empirical testing of a model of online 723–734.
store atmospherics and shopper responses. Psychol. Market. 20 (2), 139–150. Lin, A.J., Li, E.Y., Lee, S.Y., 2018. Dysfunctional customer behavior in cross-border E-
Eslami, S.P., Ghasemaghaei, M., 2018. Effects of online review positiveness and review commerce: A justice-affect-behavior model. J. Electron. Commer. Res. 19 (1), 36–54.
score inconsistency on sales: A comparison by product involvement. J. Retail. Lu, Y., Zhao, L., Wang, B., 2010. From virtual community members to C2C E-commerce
Consum. Serv. (45), 74–80. buyers: Trust in virtual communities and its effect on consumers’ purchase intention.
Ferns, B.H., Walls, A., 2012. Enduring travel involvement, destination brand equity, and Electron. Commer. Res. Appl. 9 (4), 346–360.
travelers’ visit intentions: A structural model analysis. Journal of Destination Lu, B., Fan, W., Zhou, M., 2016. Social presence, trust, and social commerce purchase
Marketing & Management 1 (1–2), 27–35. intention: An empirical research. Comput. Hum. Behav. (56), 225–237.
Forrester, and Facebook, 2018. 2018 global cross-border E-commerce marketing white Mavlanova, T., Benbunan-Fich, R., 2010. Counterfeit products on the internet: The role of

329
W. Zhu, et al. Journal of Retailing and Consumer Services 51 (2019) 320–330

seller-level and product-level information. Int. J. Electron. Commer. 15 (2), 79–104. educators. J. Vet. Med. Educ. 43 (1), 1–4.
Mayer, R.C., Davis, J.H., Schoorman, F.D., 1995. An integrative model of organizational Schlosser, A.E., 2003. Experiencing products in the virtual world: The role of goal and
trust. Acad. Manag. Rev. 20 (3), 709–734. imagery in influencing attitudes versus purchase intentions. J. Consum. Res. 30 (2),
Miranda, S.M., Saunders, C.S., 2003. The social construction of meaning: An alternative 184–198.
perspective on information sharing. Inf. Syst. Res. 14 (1), 87–106. Sherif, M., Cantril, H., 1947. The Psychology of Ego-Involvements: Social Attitudes and
Mou, J., Shin, D., 2018. Effects of social popularity and time scarcity on online consumer Identifications. John Wiley & Sons, US.
behaviour regarding smart healthcare products: An eye-tracking approach. Comput. Sherif, C.W., Sherif, M.S., Nebergall, R.E., 1965. Attitude and Attitude Change:The Social
Hum. Behav. 78, 74–89. Judement-Involvement Approach. Saunders, Philadelphia.
Mou, J., Shin, D.H., Cohen, J., 2016. Health beliefs and the valence framework in health Sinkovics, R.R., Yamin, M., Hossinger, M., 2007. Cultural adaptation in cross border E-
information seeking behaviors. Inf. Technol. People 29 (4), 876–900. commerce: A study of German companies. J. Electron. Commer. Res. 8 (4), 221–235.
Mou, J., Cohen, J., Dou, Y., Zhang, B., 2017. Predicting buyers’ repurchase intentions in Smith, R.E., Swinyard, W.R., 1988. Cognitive response to advertising and trial: Belief
cross-border E-commerce: Avalence framework perspective. In: Proceedings of the strength, belief confidence and product curiosity. J. Advert. 17 (3), 3–14.
25th European Conference on Information Systems (ECIS), pp. 2382–2394. Smith, S., Wheeler, J., 2002. Managing the Customer Experience: Turning Customers into
Mou, J., Ren, G., Qin, C., Kurcz, K., 2019. Understanding the topics of export cross-border Advocates. Pearson Education, London.
E-commerce consumers feedback: An LDA approach. Electron. Commer. Res. 1–29. Smith, R.E., Chen, J., Yang, X., 2008. The impact of advertising creativity on the hier-
Muhammad, M.Z., Leng, G.S., Lada, S., Ibrahim, A.A.H.A., 2011. An exploration of social archy of effects. J. Advert. 37 (4), 47–62.
networking sites (SNS) adoption in Malaysia using technology acceptance model Suh, B., Han, I., 2003. The impact of customer trust and perception of security control on
(TAM), theory of planned behavior (TPB) and intrinsic motivation. J. Internet Bank. the acceptance of electronic commerce. Int. J. Electron. Commer. 7 (3), 135–161.
Commer. 16 (2), 1–27. Sunnafrank, M., 1986. Predicted outcome value during initial interactions: A re-
Pappas, N., 2016. Marketing strategies, perceived risks, and consumer trust in online formulation of uncertainty reduction theory. Hum. Commun. Res. 13 (1), 3–33.
buying behavior. J. Retail. Consum. Serv. 29, 92–103. Teichert, T., Rost, K., 2003. Trust, involvement profile and customer retention-modelling,
Park, J., Lennon, S.J., Stoel, L., 2005. On-line product presentation: Effects on mood, effects and implications. Int. J. Technol. Manag. 26 (5/6), 621–639.
perceived risk, and purchase intention. Psychol. Market. 22 (9), 695–719. Ullman, J.B., Bentler, P.M., 2012. Structural equation modelling. In: Weiner, I.V. (Ed.),
Park, D.H., Lee, J., Han, I., 2007. The effect of on-line consumer reviews on consumer Handbook of Psychology, second ed. John Wiley & Sons, New York.
purchasing intention: The moderating role of involvement. Int. J. Electron. Commer. Valarezo, Á., Pérez-Amaral, T., Garín-Muñoz, T., Herguera García, I., López, R., 2018.
11 (4), 125–148. Drivers and barriers to cross-border E-commerce: Evidence from Spanish individual
Peng, L., Zhang, W., Wang, X., Liang, S., 2019. Moderating effects of time pressure on the behavior. Telecommun. Pol. 42 (6), 464–473.
relationship between perceived value and purchase intention in social E-commerce Wang, Y., Hazen, B.T., 2016. Consumer product knowledge and intention to purchase
sales promotion: Considering the impact of product involvement. Inf. Manag. 56 (2), remanufactured products. Int. J. Prod. Econ. 181, 460–469.
317–328. Wang, Y., Lee, S., 2017. The effect of cross-border E-commerce on China’s international
Peter, J.P., Olson, J.C., 1996. Consumer Behavior and Marketing Strategy, fourth ed. trade: An empirical study based on transaction cost analysis. Sustainability 9 (11),
Irwin, Chicago. 2028.
Petty, R.E., Cacioppo, J.T., Schumann, D., 1983. Central and peripheral routes to ad- Wen, Z.L., Ye, B.J., 2014. Analysis of mediating effects: The development of methods and
vertising effectiveness: The moderating role of involvement. J. Consum. Res. 10 (2), models. Adv. Psychol. Sci. 22 (5), 731–745.
135–146. Wijaya, B.S., 2015. The development of hierarchy of effects model in advertising. Int. Res.
Podsakoff, P.M., Organ, D.W., 1986. Self-reports in organizational research: Problems and J. Biol. Sci. 5 (1), 73–85.
prospects. J. Manag. 12 (4), 531–544. Williams, B., Brown, T., Onsman, A., 2010. Exploratory factor Analysis: A five-step guide
Porter, M.E., 2008. The five competitive forces that shape strategy. Harv. Bus. Rev. 86 (1), for novices. Journal of Emergency Primary Health Care 8 (3), 1–13.
25–40. Yoon, S.J., 2002. The antecedents and consequences of trust in online-purchase decisions.
Racherla, P., Mandviwalla, M., Connolly, D.J., 2012. Factors affecting consumers' trust in J. Interact. Mark. 16 (2), 47–63.
online product reviews. J. Consum. Behav. 11 (2), 94–104. Yoon, S., Zhang, D., 2018. Social media, information presentation, consumer involve-
Richard, M.O., 2005. Modeling the impact of internet atmospherics on surfer behavior. J. ment, and cross-border adoption of pop culture products. Electron. Commer. Res.
Bus. Res. 58 (12), 1632–1642. Appl. 27, 129–138.
Royal, K.D., Hecker, K.G., 2016. Understanding reliability: A review for veterinary

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