The explosive growth of social media, particularly Social Networking Sites
(SNSs), has provided electronic commerce (e-commerce) with a new paradigm called
social commerce (s-commerce). s-commerce, a new business model based on e-commerce,
combines social media with e-commerce and enables the buying and selling of
a wide range of products and services over the Internet (Marsden,
2011). In other words, s-commerce makes use of social networks formed through
e-commerce transactions. s-commerce users collaborate with one another for their
online shopping activity by sharing product- and service-related information
and exchanging opinions, among others.
S-commerce has attracted increasing attention from vast numbers of online communities.
Furthermore, s-commerce has become one of the major forms of online commerce
and is an integral part of the social phenomenon involving social media. In
particular, s-commerce has enjoyed explosive growth in South Korea (hereinafter
Korea) because many consumers are interested in acquiring discount
coupons and sharing information on products and services by using social media
for their online buying and selling activities. Such characteristics of s-commerce
reflect collectivism. Pookulangara and Koesler (2011)
claimed that collectivism highlights a sense of interdependence; interactions
among individuals belonging to a collective group and the prioritization of
group goals. Thus, collectivism is often understood as a cultural phenomenon
reflecting individuals personal tendencies (Pookulangara
and Koesler, 2011). In addition, Brandtzaeg (2010)
claimed that cultural differences can influence the interaction between new
social media technologies (e.g., s-commerce) and users.
S-commerce suggests an interesting paradox for many researchers and practitioners
because it is an emerging e-commerce phenomenon. Although a number of studies
have examined diverse aspects of e-commerce and m-commerce, including their
adoption and diffusion, few have considered the nature of s-commerce to explain
consumers adoption of it because it is difficult to explain the adoption
of a new commerce mechanism (Kim, 2006; Kim
and Garrison, 2009). Therefore, there is a need for a better understanding
of consumers behavior toward s-commerce because s-commerce is a new phenomenon.
In addition, given the importance of s-commerce, there is an urgent need for
identifying the factors influencing consumers intention to adopt s-commerce
in the context of collectivism.
However, few studies have examined the effects of collectivism on consumers
behavior toward s-commerce. In this regard, the main purpose of this study is
to understand consumers acceptance of s-commerce by using the well-known
Technology Acceptance Model (TAM). This study provides an empirical analysis
and addresses the following research question: How does collectivism influence
the behavior of s-commerce users?
For this, this study employs the Technology Acceptance Model (TAM) as a theoretical
framework to suggest the research model because previous studies (Massimo
et al., 2002; Veiga et al., 2001)
have claimed that cultural characteristics, including individualism, collectivism,
uncertainty avoidance and power distance, can induce beliefs such as perceived
usefulness and perceived ease of use. The s-commerce users are likely to show
collectivism because s-commerce represents an online space in which product-
and service-related information is widely shared among users, which can encourage
them to develop favorable attitudes toward group purchases (or collectivism).
This indicates that collectivism, particularly with respect to the consumers
preferences, reliance, concern and norm acceptance, may influence s-commerce
Collectivism: Collectivism has been defined as an individuals
or a groups orientation toward relationships with other individuals or
groups. Individualists place greater emphasis on personal interests than on
group needs, looking after themselves and ignoring group interests when they
conflict with their personal desires. According to this commonly accepted view,
collectivism is the opposite of individualism (Hui, 1988;
Oyserman et al., 2002) claimed that collectivism
has the opposite of individualism. In fact, collectivism prioritizes group goals
over personal ones; stresses conformity and in-group harmony; and defines the
self in relation to the group (Triandis, 1989). Collectivists
place greater emphasis on group interests than on individual needs and desires
and tend to focus on the well-being of their group (Wagner
and Moch, 1986).
Hofstede (1980) suggested collectivism entails four major
cultural variables: power distance, uncertainly avoidance, individualism and
masculinity. In addition, Triandis et al. (1988,
1990) introduced several variables for the nature of
collectivism, including the concern for the group, interdependence, family integrity,
self-reliance and the distance from the group. Wagner and
Moch (1986) introduced three dimensions of collectivism: collective beliefs,
values and norms. In addition, Jackson et al. (2006)
examined the effects of various constructs (e.g., preference, reliance, concern
and goal priority) of collectivism on the performance of group members. These
characteristics of collectivism can play crucial roles in individuals
within-group behaviors, particularly in their technology adoption decisions
In-group goals take priority over personal goals for collectivists, whereas
the opposite tendencies are typically observed for individualists. For collectivists,
subjective boundaries of in-groups are clear in distinguishing between in-and
out-group members (Chen et al., 1997). Collectivists
are concerned about the importance of group harmony and stability (Triandis
et al., 1990). Similarly, collectivism reflects collectivistic cultures,
which are characterized by homogeneous, interdependent and long-term relationships
and common interests. The s-commerce is based mainly on social media, which
are online services, platforms or sites that focus on facilitating social networks
or relationships among users. This conclusion indicates that the nature of s-commerce
reflects the characteristics of collectivism.
s-commerce: s-commerce is a new e-commerce phenomenon and has grown more rapidly than any other form of online commerce. Few could have predicted how pervasive s-commerce would become not only in online environments but also in peoples daily lives. In fact, s-commerce itself is not new. However, what is new is its use of social media (e.g., SNSs) and innovative e-commerce technologies (e.g., social media stores and portable social graphs). This new phenomenon has introduced a wide range of new opportunities for the monetization of social media through e-commerce.
Because the use of social media in online commerce is a new phenomenon, few
studies have examined s-commerce adoption. In addition, most of the previous
s-commerce studies have provided descriptive analyses of various aspects of
s-commerce. For example, Marsden (2011) claimed that
s-commerce can deliver important business advantages such as the monetization
of social media, the optimization of e-commerce sales and the innovation of
business models. In addition, Stephen and Toubia (2010)
claimed that firms developing social strategies should take into account the
extent to which the socialness of such strategies may influence their business.
Some firms are hesitant to use Twitter or Facebook because of the possibility
of having to address negative comments or bad publicity. However, many have
recognized the benefits associated with forming relationships with their customers
through social networks (3dcart, 2010). For consumers,
s-commerce can enhance the purchase experience, offering trust, utility and
fun in key areas such as the discovery, selection and referral of products (Marsden,
2011). For example, Ticketmaster benefits from Facebooks focus on
friends because people tend to go to concerts with others.
Kim et al. (2011) investigated the effects of
various characteristics of s-commerce and s-commerce users that can induce trust
in s-commerce and found that variables such as reputation, economic feasibility,
information quality, transaction safety and interactions have positive effects
on trust and that consumers purchase experience and word-of-mouth communication
have considerable influence on trust in s-commerce, which in turn has a positive
effect on trust performance.
Technology acceptance model (TAM): Several studies have demonstrated
that the two beliefs of the TAM (perceived usefulness and perceived ease of
use) are significant predictors of an individuals acceptance in terms
of his or her use intentions and actual behaviors toward new technologies such
as websites (Fenech, 1998; Lee et
al., 2008), e-commerce (Khatibi et al., 2006;
Liu and Wei, 2003; Sek et al.,
2010; Yoon, 2009), online games (Hsu
and Lu, 2004; Wu et al., 2010) and SNSs (Pookulangara
and Koesler, 2011). However, these constructs do not fully reflect the specific
effects of usage-context factors that may influence an individuals technology
acceptance (Moon and Kim, 2001; Srivastava,
2012). Thus, it is difficult to conclude that these two variables can fully
explain consumers behavioral intentions and actual behaviors toward new
information systems, including social networking and s-commerce.
Based on these limitations of the TAM, previous studies have considered some
exogenous variables for national and individual cultures to extend the TAM (Srite
and Karahanna, 2006; McCoy et al., 2007).
Such exogenous variables (e.g., the national culture) can have considerable
influence on individuals acceptance of new technologies because their
adoption decisions depend mainly on these variables. In fact, many studies have
examined the effects of such usage-context variables within the TAM in various
technology adoption contexts. For example, Turel and Connelly
(2011) provided an empirical analysis of the relationship between perceived
usefulness and collectivism to examine individuals acceptance of e-collaboration
tools, focusing on collectivistic cultures. In addition, some studies have claimed
that a collectivistic culture is a typical type in culture in which individuals
follow group norms (Srite and Karahanna, 2006). In this
regard, the present study employs the TAM as a research framework to propose
a research model for investigating the effects of collectivism on perceived
usefulness and the relationships between the TAM variables in the context of
RESEARCH MODEL AND HYPOTHESES
Figure 1 shows the research model, which introduces the strategic rationale for including collectivism in the analysis of consumers intention to use s-commerce. Based on the TAM, the research model introduces four variables (the consumers preferences, reliance, concern and norm acceptance) to explain collectivism. These variables are expected to directly influence perceived usefulness. In addition, the research model includes the TAMs two beliefs to verify the relationships between the TAM variables in the context of s-commerce.
Hypothesis development: Previous studies (Srite
and Karahanna, 2006; McCoy et al., 2007)
have defined collectivism as a type of national or individual culture and claimed
that collectivism is a key determinant of IT adoption (Folorunso
et al., 2006; Veiga et al., 2001;
Zeng et al., 2009). Jackson
et al. (2006) considered many cultural variables and emphasized that
the variables such as consumers preferences, reliance, concern, norm acceptance
and goal priority are the key dimensions of collectivism in the context of group
|| The proposed research model and hypotheses
In addition, Turel and Connelly (2011) focused on psychological
collectivism (e.g., consumers preferences, reliance, concern and norm
acceptance) to explain the use of e-collaboration tools. Following previous
research, the present study proposes a research model and develops some theoretical
hypotheses about the four dimensions of collectivism and the perceived usefulness
The first antecedent factor of collectivism is the preference, which this study
defines as an individuals belief that collective efforts are superior
to individual efforts (Turel and Connelly, 2011). Because
s-commerce can provide consumers with social or collective shopping opportunities,
consumers who prefer to be part of a group tend to believe that such preferences
can strengthen the perceived usefulness of s-commerce. However, no study has
provided an empirical analysis of consumers preferences in the context
of their intention to adopt s-commerce. In this regard, the following hypothesis
||Hypothesis 1; H1: The consumers preference has
a positive effect on the perceived usefulness of s-commerce
The second variable in the proposed research model is reliance, which this
study defines as the extent to which a group member relies on other members.
Collectivists believe that they have some responsibility for the entire group
and this responsibility is shared among all group members. Thus, each group
member is comfortable relying on other members (Jackson
et al., 2006; Turel and Connelly, 2011). In
s-commerce, social groups have extensive relationships and individuals in collectivistic
cultures are more likely to show a high level of interdependence than those
in individualistic cultures, who tend to show a high level of self-reliance.
In this regard, Triandis (1989) strenuously insisted
that in collectivistic cultures, social relationships have the tendency to be
more persistent and spontaneous and tend to occur within larger groups.
One of the major concerns in individualistic cultures is self-reliance, whereas
it is conformity with others in public settings (e.g., s-commerce) (Triandis,
1989). Because consumers who rely on others in s-commerce tend to purchase
the same products at discounted prices, they try to acquire a price advantage
by relying on others. Such tendencies in s-commerce derive from the nature of
s-commerce, that is, collectivism, which can have positive effects on the perceived
usefulness of s-commerce. In this regard, hypothesis 2 is proposed:
||Hypothesis 2; H2: The consumers reliance on others
has a positive effect on the perceived usefulness of s-commerce
The third variable in the research model is concern defined as something that
interests individuals because of the size of the group they belong to. A group
members concern for the well-being of other members often motivates collectivists.
Self-interest is not the main motive in collectivistic cultures (Jackson
et al., 2006; Turel and Connelly, 2011). In
this regard, Triandis (1989) claimed that collectivists
tend to be concerned more about what happens to other group members than about
what happens to themselves. In addition to subordinating personal goals to collective
goals, collectivists tend to be concerned about the impact of their actions
on their in-group members and have interdependent relationships with their in-group
members (Hui and Triandis, 1986).
In general, interpersonal behavior naturally occurs within in-groups in s-commerce. In addition, s-commerce users are interested in the behavior of other users. This natural collectivistic behavior, particularly toward s-commerce users, may have positive effects on the perceived usefulness of s-commerce. However, no study has examined consumers concern as a dimension of collectivism in the context of their intention to adopt s-commerce. In this regard, the following hypothesis is proposed:
||Hypothesis 3; H3: The consumers concern has a
positive effect on the perceived usefulness of s-commerce
The fourth variable for collectivism is norm acceptance, which is defined as
the extent to which individuals are willing to accept a normal social behavior
as informal guidelines in a particular social group. Such normal social behaviors
reflect what is appropriate or inappropriate. Turel and Connelly
(2011) claimed that social norms form the basis for group members
collective expectation and play an important role in social control and order
by exerting pressure on others to conform.
In addition, collectivists obey social norms and rules of the in-group to build
solid harmony among group members (Jackson et al.,
2006; Turel and Connelly, 2011). If there is a conflict
between individual and group goals, then it is considered socially desirable
to prioritize collective goals over individual ones (Triandis
et al. 1990). In addition, social norms are related to transactions
in collectivistic cultures. For example, s-commerce is based on group purchase
deals, which require users to accept certain social norms. By accepting such
social norms, s-commerce users can derive many benefits in terms of prices and
service. For collectivists (s-commerce users), their perception of the usefulness
of s-commerce may be enhanced by accepting social norms. In this regard, the
following hypothesis is proposed:
||Hypothesis 4; H4: The consumers norm acceptance
has a positive effect on the perceived usefulness of s-commerce
Previous studies have employed the TAM to examine individuals behavioral
intentions and actual behaviors toward the use of new technologies (e.g., e-commerce,
m-commerce and SNSs). The TAM considers two major beliefs (perceived usefulness
and perceived ease of use) as the key determinants of technology adoption. Perceived
usefulness is defined as the extent to which individuals believe that a new
technology would improve job performance, whereas perceived ease of use is defined
as the extent to which individual believe that using a new technology would
require little effort (Davis, 1989).
Many studies based on the TAM have demonstrated that perceived usefulness is
a strong determinant of consumers acceptance, adoption and use behaviors
(e.g., Agrawal et al., 2000; Rigopoulos
et al., 2008). In addition, the relationships between the TAM variables
have been verified in various technology adoption contexts. Similarly, the present
study assumes that the ultimate reason why consumers exploit s-commerce is that
this technology can facilitate their online shopping and provide them with many
benefits, including efficient and effective online shopping. Because s-commerce
is a new e-commerce phenomenon, the TAM should be used for predicting consumers
intention to use s-commerce. The present study examines the effects of perceived
ease of use on perceived usefulness and on the intention to use s-commerce.
In this regard, the following hypothesis is proposed:
||Hypothesis 5; H5: Perceived usefulness has a positive
effect on the intention to use s-commerce
||Hypothesis 6a; H6a: Perceived ease of use has a positive effect
on perceived usefulness
||Hypothesis 6b; H6b: Perceived ease of use has a positive effect
on the intention to use s-commerce
Sample and the measurement: A survey was conducted to test the proposed model and hypotheses. A total of 375 responses was obtained by using various survey methods, including online, offline, on-site, telephone, email and fax solicitations but excluded 10 responses because of missing items. As shown in Table 1, the respondents reflected a demographically diverse group and their average age was 34.5. All the respondents were s-commerce users for various reasons (e.g., information sharing and purchasing discount coupons).
Items to measure each variable in the research model were mainly adopted from
previous studies (Kim, 2008; Oyserman
et al., 2002; Teoh and Cyril, 2008). However,
each item was modified to measure the respondents psychological feeling
with respect to his or her intention to use s-commerce. All items were measured
using a seven-point Likert-type scale ranging from strongly disagree
(1) to strongly agree (7).
RESULTS AND DISCUSSION
Analysis of the measurement model: Before testing the research model, a measurement model was created and tested through a Confirmatory Factor Analysis (CFA) with AMOS 7.0. To measure the fit of the measurement model, this study employed several fit indices, including the Normed Fit Index (NFI), the Goodness-of-fit Index (GFI), the Adjusted Goodness-of-fit Index (AGFI), the Comparative Fit Index (CFI), relative χ2 (χ2/df) and the Root Mean Square Error of Approximation (RMSEA).
A good fit is demonstrated if NFI, GFI and CFI values exceed 0.90 (Bentler,
1990), the AGFI exceeds 0.8 and the RMSEA is less than 0.05 (Browne
and Cudeck, 1993). In addition, the χ2/df value range from
less than 3 to as high as 5 (Goodhue, 1995). The results
for the measurement model with 23 items measuring the seven variables indicate
that the model provided a good fit to the data. Table 2 shows
|| Demographic characteristics
|| Fit indices for the measurement model
|| Results for reliability and construct validity
|| Results for discriminant validity
|Square root of the AVE is indicated along the bold diagonal
Reliability and construct validity: After purifying the overall fit
of the measurement model, construct validity was examined by testing item reliability,
internal consistency and discriminant validity. Individual item loadings for
item reliability were assessed. Satisfactory item reliability is generally demonstrated
if the loading for an item exceeds 0.7 for the proposed factor and is less than
0.4 for other factors (Chin, 1998). The results indicate
that all items exceeded the threshold, implying that the items were sufficient
for assessing each construct individually.
To test internal consistency, Cronbachs alpha, which is the most widely
used tool in social sciences, was considered. Teo et
al. (1999) suggested 0.7 as the minimum threshold for Cronbachs
alpha in an exploratory study. As shown in Table 3, Cronbachs
alpha ranged from 0.796 to 0.965, exceeding the threshold.
Discriminant validity was tested by considering the Average Variance Extracted
(AVE) and Pearsons correlation. For sufficient discriminant validity,
the square root of each latent variables AVE should exceed the vertical
and horizontal correlations between the variables (Fornell
and Larcker, 1981). The results indicate that the square root of each latent
variables AVE exceeded the correlation for each latent variable, demonstrating
sufficient discriminant validity. Table 4 presents the result
of discriminant validity.
Structural model assessment: The casual relationships between the variables were examined by using Structural Equation Modeling (SEM) approach with AMOS 7.0. The SEM approach provides two important pieces of information-the standardized path coefficient (β) and the squared multiple correlation (R2)-which are used as indicators of how well the structural model predicts hypothesized relationships. In particular, the standardized path coefficient shows the strength of the causal relationship between two variables. The results for all fit indices indicate that the structural model provided a good fit to the data (n = 375). The NFI (0.98), the GFI (0.95) and the CFI (0.97) all exceeded the required threshold (0.90) and the AGFT (0.92) exceeded the minimum threshold (0.80). The RMSEA (0.024) was less than 0.05 and the χ2/df value (1.57) was less than 3. Thus, each hypothesis was tested by using the standardized path coefficient. The results provide support for all hypotheses (Fig. 2).
Among the four antecedents of collectivism, consumers preferences were hypothesized to have a positive effect on perceived usefulness. Consumers preferences had a positive effect on perceived usefulness (β = 0.385, t = 5.204), providing support for H1; their reliance had a positive effect on perceived usefulness (β = 0.299, t = 4.340), providing support for H2; their concern had a positive effect on perceived usefulness (β = 0.382, t = 4.887), providing support for H3; and their norm acceptance had a positive effect on perceived usefulness (β = 0.537, t = 6.479), providing support for H4.
||The results of the structural model analysis. Regular numbers
are standard egress weight or factor loadings, Numbers with ( ) are t-value,
**p<0.01, ***p<0.001, R2 = Squared multiple correlations
Then, the hypotheses about the TAM variables were tested. Perceived usefulness had a significant positive effect on the intention to use s-commerce (β = 0.429, t = 6.151), providing support for H5 and perceived ease of use had a significant positive effect on both perceived usefulness and the intention to use s-commerce (β = 0.541, t = 7.518; β = 0.537, t = 8.859, respectively), providing support for H6a and H6b, respectively.
The second crucial SEM information is the squared multiple correlation (R2)
between exogenous and endogenous variables in the research model. The R2
value measures the percentage of the variance explained by each construct in
the model (Wixom and Watson, 2001). That is, the variance
of an exogenous variable can be explained by changes in each endogenous variable.
The results indicate that the four antecedents of collectivism and perceived
ease of use explained 65.7% of the variance in perceived usefulness. In addition,
perceived usefulness and perceived ease of use explained 72.1% of the variance
in the intention to use s-commerce. Figure 2 illustrates the
SEM test of the proposed model, including the standardized path coefficients
as well as their significance levels and variance explained.
This study proposes a research model theorizing consumers intention toward s-commerce adoption. The proposed research model was tested by using the SEM method. The results indicate the validity of the research model and provide support for all hypotheses. The results provide new insights into consumers intention to adopt s-commerce. The four antecedents (consumers preferences, reliance, concern and norm acceptance) of collectivism had significant effects on the perceived usefulness of s-commerce. In addition, the TAM variables were valid in the context of s-commerce. These variables, together with perceived ease of use, explained 65.7% of the variance in perceived usefulness. In addition, perceived usefulness and perceived ease of use explained 72.1% of the variance in the intention to use s-commerce.
The results have important implications for IS researchers and practitioners.
In terms of IS research, this study proposes a unique characteristic (collectivism)
of s-commerce to explain consumers intention to use the technology, providing
new insights into technology acceptance and use. In particular, no study has
conceptualized consumers psychological behaviors in terms of their preferences,
reliance, concern and norm acceptance to explain their intention to adopt s-commerce.
The results suggest that collectivism has considerable influence on online buyers
who prefer to be in-group members and prioritize in-group goals over personal
ones. Thus, s-commerce firms should formulate marketing strategies that focus
on such consumers.
This study develops and validates an instrument for measuring these new variables. The study contributes to the literature on general technology acceptance and provides additional insights into the effects of new technologies on consumers attitudes and behaviors. Finally, the study contributes to the literature by extending the well-established technology acceptance model and thus suggesting interesting avenues for future research on s-commerce.
For IS practitioners, the results provide some clues for successful s-commerce implementation, including new factors that may have considerable influence on consumers intention toward s-commerce. In addition, the results have important implications for researchers exploring other online topics, including ubiquity commerce (u-commerce). That is, this studys results for s-commerce are expected to facilitate future research on u-commerce and other types of online business models.
However, this study has some limitations. As in many studies employing survey methods, self-report bias is a source of concern. In addition, to make the research model parsimonious, this study focused only on the effects of collectivism, demonstrating that perceived usefulness is an important antecedent of collectivism. In this regard, future research should consider other factors that may explain consumers behaviors in the context of s-commerce.
This research was supported by Kyungpook National University Research Fund, 2010.