Consumer behavior in social commerce: A literature review

Consumer behavior in social commerce: A literature review
Kem Z.K. Zhang a,b,⁎, Morad Benyoucef b
a School of Management, University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, China
b Telfer School of Management, University of Ottawa, 55 Laurier East, Ottawa, ON, Canada K1N 6N5
a b s t r a c ta r t i c l e i n f o
Article history:
Received 7 August 2015
Received in revised form 26 January 2016
Accepted 1 April 2016
Available online 7 April 2016
The emergence of social commerce has brought substantial changes to both businesses and consumers. Hence,
understanding consumer behavior in the context of social commerce has become critical for companies that
aim to better influence consumers and harness the power of their social ties. Given that research on this issue
is new and largely fragmented, it will be theoretically important to evaluate what has been studied and derive
meaningful insights through a structured review of the literature. In this study, we conduct a systematic review
of social commerce studies to explicate how consumers behave on social networking sites. We classify these
studies, discuss noteworthy theories, and identify important research methods. More importantly, we draw
upon the stimulus–organism–response model and the five-stage consumer decision-making process to propose
an integrative framework for understanding consumer behavior in this context. We believe that this framework
can provide a useful basis for future social commerce research.
© 2016 Elsevier B.V. All rights reserved.
Keywords:
Literature review
Social commerce
Social networking sites
Consumer behavior
Decision-making process
Stimulus–organism–response model
1. Introduction
The concept of social commerce emerged in 2005 amid the growing
commercial use of social networking sites and many other social
media websites [15]. It ushers a new form of electronic commerce (e-
commerce) [97]. Unlike traditional e-commerce where consumers
usually interact with online shopping sites separately, social commerce
involves online communities that support user interactions and user-
generated content [55]. A recent survey points out that social commerce
in the U.S. has already generated 5 billion dollars in sales, with 9 billion
expected in 2014 and 15 billion in 2015 [71].
The significance of social commerce has made it the subject of
various studies. For instance, prior research posits that online reviews
in social media are an important source of information that assists
consumers' decision-making [1,32]. Liang et al. [65] showed that social
support from online friends is critical in driving consumers to adopt
social commerce. Edelman [22] advocated that social media enables
consumers to engage with brands in profoundly new ways; hence, com-
panies should shift marketing strategies from attracting consumers'
awareness (pre-purchase stage) to bonding with consumers after
their purchases (post-purchase stage).
To harness the power of social commerce, it is important to study the
process and uniqueness of how consumers behave in this setting [38].
Although we are witnessing an increase in the literature on this emerg-
ing issue, current research is rather fragmented, which makes it difficult
to derive meaningful and conclusive implications from it. To this end,
the purpose of this study is to conduct an extensive review of the liter-
ature on consumer behavior in social commerce. We first address im-
portant aspects such as research contexts, theories, and methods in
this area. We then draw upon the stimulus–organism–response model
[69] and the five-stage consumer decision-making process [23] to de-
velop an integrative framework for better understanding consumer be-
havior in the context of social commerce. We argue that this framework
can provide a useful foundation for future social commerce research.
The paper is organized as follows. First, we discuss the definition and
scope of social commerce in the present research. Second, we explain
our review method of studies on consumer behavior in social
commerce. Third, we review these studies and summarize findings in
several aspects. Fourth, we propose a theoretical framework to under-
stand consumer behavior in social commerce. Finally, we discuss our
implications, opportunities for future research, as well as the limitations
of our work.
2. What is social commerce?
Social commerce is often considered as a subset of e-commerce
[16,67]. Prior research has broadly characterized it with two essential
elements: social media and commercial activities [65,104]. However,
a closer look at its definitions in the literature reveals that the social
commerce concept is associated with many inconsistencies. For
instance, Stephen and Toubia [92] defined social commerce as a form
of Internet-based social media which enables individuals to engage in
Decision Support Systems 86 (2016) 95–108
⁎ Corresponding author at: School of Management, University of Science and
Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, China. Tel.: + 86 551
63600195.
E-mail addresses: [e-mail] (K.Z.K. Zhang),
[e-mail] (M. Benyoucef).
http://dx.doi.org/10.1016/j.dss.2016.04.001
0167-9236/© 2016 Elsevier B.V. All rights reserved.
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the selling and marketing of products and services in online communi-
ties and marketplaces. Such definition limits sellers to individuals,
excluding companies. Dennison et al. [21] adopted a definition provided
by IBM and explained it as the marriage of e-commerce and electronic
word-of-mouth (eWOM). Marsden and Chaney [68] conceptualized
social commerce as the selling with social media websites, such as
Facebook, Twitter, LinkedIn, Pinterest, and YouTube (the “Big Five”),
which support user-generated content and social interaction.
The conceptual confusion in defining social commerce, to some
extent, brings about different understandings of what social commerce
websites are. Recent research identified two major types of social
commerce: (1) social networking sites that incorporate commercial
features to allow transactions and advertisements; and (2) traditional
e-commerce websites that add social tools to facilitate social interaction
and sharing [43,67]. The first social commerce type is the focus of a
majority of previous studies (e.g., [7,8,26]). In contrast, Amblee and
Bui [2] considered Amazon, a traditional e-commerce website, as
practicing a form of social commerce because it contains a large amount
of online consumer reviews. Group shopping websites were also
recognized as a form of social commerce in which people form groups
to purchase products with price advantages [54]. Indvik [45] summa-
rized seven categories of social commerce websites, including social
network-driven sales platforms (e.g., Facebook), peer recommendation
websites (e.g., Amazon), group buying websites (e.g., Groupon), peer-
to-peer sales platforms (e.g., eBay), user-curated shopping websites
(e.g., Lyst), social shopping websites (e.g., Motilo), and participatory
commerce websites (e.g., Kickstarter).
A recent study by Yadav et al. [104] defines social commerce as the
“exchange-related activities that occur in, or are influenced by, an
individual's social network in computer-mediated social environments,
where the activities correspond to the need recognition, pre-purchase,
purchase, and post-purchase stages of a focal exchange” (p. 312). This
definition explicates two building blocks of the concept: (1) exchange-
related activities, which include various stages of consumers' decision-
making; and (2) computer-mediated social environments, where
meaningful personal connections and sustained social interactions
exist among network members. This definition clearly rules out
websites such as Amazon and Groupon, which have no explicit social
networks among their users.
In this study, we adopt Yadav et al.'s definition of social commerce,
and we further restrict our discussion to social networking sites to better
highlight the “social” nature of social commerce. Moreover, to obtain a
holistic view of consumer behavior, we consider various stages in
the decision-making process, instead of narrowly emphasizing the
transaction stage.
3. Literature identification and collection
We employ a systematic approach to identify relevant articles for
our literature review. We use two methods to collect academic and
peer-reviewed journal articles in this process. First, we select a number
of academic databases, including Web of Science, Business Source
Premier, Science Direct, ABI/INFORM Global (ProQuest), Emerald, and
Wiley Online Library. We search these databases using keywords like
social commerce, Facebook commerce, social shopping, and social
media marketing. Second, we check important journals to ensure that
we do not miss relevant articles. This method is consistent with Cheung
and Thadani's [10] work on reviewing the literature of eWOM commu-
nication. We conduct a similar keyword search on information systems
(IS) and e-commerce journals, such as MIS Quarterly, Information
Systems Research, Journal of Management Information Systems, Decision
Support Systems, Information & Management, and International Journal
of Electronic Commerce; as well as marketing journals like Journal of
Marketing, Journal of Marketing Research, and Journal of Consumer
Research.
We follow the conventional literature review approach to cross-
check and validate the relevance of the initial set of articles [100]. To
select relevant articles, we examine the title, abstract, or the content
of the articles manually by referring to three criteria: (1) empirical
research, (2) focusing on consumer behavior, and (3) examining the
context of social networking sites. This literature selection process allows
us to reflect on significant peer-reviewed journal articles with empirical
evidence regarding consumer behavior on social networking sites.
Finally, a total of 77 articles are collected for our literature review. As
shown in Fig. 1, the number of articles about consumer behavior on
social networking sites has increased each year since 2010. The increase
suggests that this is a new research area that is increasingly attracting
the interest of academics. Note that six articles have already been
published in early 2015, and we expect that more studies are likely to
appear in the upcoming years.
Table 1 shows a list of 19 journals with more than one article, sug-
gesting that they have an interest in publishing in such area. Computers
in Human Behavior (n = 6) and Journal of Interactive Marketing (n = 5)
are the two journals with the highest numbers of published articles. In
addition, we observe that some articles appeared in social commerce-
related special issues of a few journals. These special issues include
(1) Decision Support Systems, Volume 65, September 2014, pages
59–68: “Crowdsourcing and Social Networks Analysis”; (2) Electronic
Commerce Research and Applications, Volume 12, Issue 4, July–August
2013, pages 224–235: “Social Commerce”; (3) Information Systems
Research, Volume 24, Issue 1, March 2013: “Social Media and Business
Transformation”; and (4) International Journal of Electronic Commerce,
Volume 16, Issue 2, 2011: “Social Commerce”. This is perhaps an indica-
tion that these journals are pioneers in showing an interest in social
commerce research. Note that not all articles in the special issues were
part of our studied sample. As mentioned earlier, we only selected
those that focus on consumer behavior on social networking sites using
empirical methods.
4. Review of the studies
To guide our review of the studies, we consider four major ques-
tions: (1) what research contexts were studied? (2) What theories
were adopted? (3) What research methods were used? And (4) what
important factors were studied to understand consumer behavior in
social commerce? These questions are consistent with previous
literature review studies [39,91] and can help us synthesize the research
findings of various articles. We discuss the first three questions in this
section. The fourth question is addressed in the next section with the
discussion of an integrative framework.
4.1. Research contexts
While all the social commerce studies in our sample emphasize
social networking sites, a further examination reveals two different38 920316051015202530352010 2011 2012 2013 2014 2015
Fig. 1. Publication timeline of the literature.
96 K.Z.K. Zhang, M. Benyoucef / Decision Support Systems 86 (2016) 95–108

streams of studies with regards to their research contexts: focusing on
social networking sites in general (n = 37) vs. brand pages on social
networking sites (n = 40). Fig. 2 depicts the publication timeline of
the two research streams. We can see that both streams have an
increasing publication trend, with relatively more recent interest in
the second stream.
Studies in the first research stream examine consumer behavior by
considering the context of social networking sites in general. Moreover,
a majority of these studies examine consumer behavior by shedding
light on information (especially eWOM) seeking [4,5,12], purchase
attitude [63,99], and purchase intention [53,75,98]. This shows that
pre-purchase and purchase behaviors are often the focus, which reflects
the view that social networking sites can function as tools that stimulate
consumers to purchase. Further, consumers' perceptions and feelings
toward the websites [65], other consumers [99], and content created
by other consumers [32] are deemed to be important aspects in
influencing consumer behavior.
The second research stream pays particular attention to brand pages
on social networking sites. Such brand pages are usually created by
companies with the purposes of disseminating information, promoting
brands/products, and interacting with consumers [109]. In this setting,
it becomes important to consider factors associated with companies,
their brands, and brand pages in understanding consumer behavior.
For instance, Pentina et al. [81] examined the influence of consumers'
perceived relationships with brands on Facebook and Twitter. de Vries
et al. [19] investigated the effects of posted messages on brand pages,
which include vividness, interactivity, informational content, entertaining
content, position of the messages, and valence of comments. Labrecque
[58] considered whether the perceived interactivity, openness, and
parasocial interaction of brands can entice consumers to provide informa-
tion and develop loyalty toward the brands. Overall, this research stream
mainly focuses on consumer participation [81,109], purchase intention [3,
70], eWOM spreading intention [6,61], and brand loyalty [24,59,110].
Thus, compared to the first stream, the second stream of studies has
placed more emphasis on purchase and especially post-purchase behav-
iors. This reflects the view that social networking sites can be helpful for
branding strategies after the purchase [22]. In sum, the second research
stream is likely to provide more specific insights for companies to under-
stand the influence of their brand pages on consumer behavior.
4.2. Theories
To understand consumer behavior, prior social commerce studies
have adopted a number of theories. Table 2 depicts the theoretical
foundations for these studies. The table shows that motivation theory,
technology acceptance model, theories of reasoned action and planned
behavior, and culture-related theoretical perspectives are mostly
adopted in the literature (at least five articles for each theoretical
perspective).
Upon further review, we note that the selected studies have put
several theoretical emphases in addressing consumer behavior in social
commerce. These emphases are detailed below.
First, there is an interest in investigating what consumers' motives,
benefits, and values are in this setting, and theories such as consumer
value theory, uses and gratifications theory, and motivation theory are
used to explain these issues. Consumer value theory states that
consumers may be able to identify functional value, emotional value,
self-oriented value, social value, and relational value while interacting
with brand pages on social networking sites [18]. Uses and gratifications
theory is adopted to explain that consumers tend to seek entertainment,
information, and remuneration on brand pages [17]. Likewise, motiva-
tion theory suggests that a consumer's intention to shop and intention
to spread eWOM in the context of social commerce may be determined
by utilitarian (e.g., perceived effectiveness of using a social commerce
website) and hedonic (e.g., perceived enjoyment of using the website)
motivations [70].
Second, behavioral theories such as the theory of reasoned action
(TRA), the theory of planned behavior (TPB), and the technology
acceptance model (TAM) were also applied in a number of the studies.
Table 1
List of journals with more than one article.
Journal Studies Number
Computers in Human Behavior [60,61,63,64,82,109] 6
Decision Support Systems [36,103] 2
Electronic Commerce Research and Applications [83,87,98] 3
Global Economic Review [53,78] 2
Information & Management [52,75,108] 3
Information Systems Research [26,85] 2
International Journal of Advertising [8,13] 2
International Journal of Electronic Commerce [65,81] 2
International Journal of Hospitality Management [49,62] 2
International Journal of Information Management [29,32,59] 3
International Journal of Market Research [5,31,33] 3
Journal of Business Research [7,50,107] 3
Journal of Consumer Behaviour [35,37,47] 3
Journal of Global Marketing [12,93] 2
Journal of Interactive Marketing [19,41,58,90,99] 5
Journal of Marketing Communications [27,95] 2
Journal of Retailing and Consumer Services [3,18] 2
Technological Forecasting and Social Change [30,102] 2
Tourism Management [44,73] 2
Fig. 2. Publication timeline of the literature: in general vs. brand page.
Table 2
Theoretical foundations in the literature.
Theory Studies Number
Brand relationship theory [81,82] 2
Communication privacy management
theory
[87] 1
Consumer decision process theory [47,48] 2
Consumer socialization theory [99] 1
Consumer value theory [3,18,20,52] 4
Contagion theory [84] 1
Culture-related theoretical perspectives [12,27,63,75,82,95,102,105] 8
Elaboration likelihood model [7] 1
Information processing theory [98] 1
Motivation theory [37,42,70,73,83,93,95] 7
Parasocial interaction theory [58] 1
Self-congruence theory [109] 1
Social capital theory [53,105,106] 3
Social cognitive theory [61] 1
Social exchange theory [110] 1
Social influence theory [57,103] 2
Social response theory [64] 1
Social support theory [30,31,65] 3
Stimulus–organism–response model [78,98,108] 3
Technology acceptance model [9,35,57,62,88] 5
Theories of reasoned action and planned
behavior
[57,88,102,105,106] 5
Trust transference theory [75] 1
Uses and gratifications theory [17,20] 2
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TAM highlights the important roles of perceived usefulness and
perceived ease of use, whereas TRA and TPB provide a belief-attitude-
intention framework to understand individuals' behavior. Such theories
have been widely tested in the IS literature for understanding the
adoption of information technology (IT), as well as online shopping
behavior (e.g., [25,80]). Thus, there were attempts to empirically
examine whether these theories can also be applicable in the emerging
social commerce context. For instance, Chen et al. [9] found that per-
ceived usefulness and perceived ease of use of brand pages on Facebook
can entice consumers to spread eWOM. Shin [88] adapted TAM and TPB
to investigate the behavioral antecedents of using social commerce
websites.
Third, the inherent social nature of social commerce entices
researchers to derive theoretical insights from social-related theories.
As shown in Table 2, these theories include social capital theory, social
cognitive theory, social exchange theory, social influence theory, social
response theory, and social support theory. The social capital theory
indicates that consumers may invest and utilize social capital to
facilitate their social shopping behavior [53]. The social cognitive theory
explains that consumers' eWOM behavior on social networking sites
may be a function of their cognitive judgment and social outcome
expectation [61]. According to the social exchange theory, consumers
are found to evaluate the benefits and costs to decide whether or not
to participate in brand pages [110]. The social influence theory high-
lights the influence of social others. It is found that the frequency of
interaction with online friends and their reviews of a product can be
good measures to reflect the social influence in a consumer's product
purchase decision [103]. Meanwhile, the social response theory views
a social networking site as an independent social actor in which
consumers can establish social relationships and apply social rules
[64]. The social support theory characterizes social support from online
friends with several dimensions (e.g., emotional support and informa-
tion support). Further, social support is found to be an important deter-
minant of consumers' social commerce intention [65].
Finally, our literature review shows that culture-related issues in
social commerce have attracted considerable attention. Research
shows that the levels of usage, participation, trust, and eWOM behavior
on social networking sites are likely to differ across cultures [12,27,102].
Culture is also found to have moderating effects on consumers' purchase
decision [75,82]. Overall, we identify several culture-related theoretical
perspectives in these studies. For instance, Hofstede's five cultural
dimensions [40], namely, individualism/collectivism, uncertainty
avoidance, masculinity/femininity, power distance, and long-/short-
term orientation, were adopted to explain cultural differences [27]. Ng
[75] contended that the individualism/collectivism and uncertainty
avoidance are the most relevant dimensions to compare behavioral dif-
ferences between East Asians (high individualism and low uncertainty
avoidance) and Latin Americans (high collectivism and high uncertainty
avoidance) on Facebook. According to Triandis [94], the individualism/
collectivism dimension can be further divided into horizontal individu-
alism, vertical individualism, horizontal collectivism, and vertical collec-
tivism. This more sophisticated classification was helpful in addressing
the differences in participation behavior [95] and eWOM communica-
tion [12] in social commerce. Xu-Priour et al. [102] considered the
dimension of polychronic/monochronic time orientation besides the
individualism/collectivism dimension. They found that consumers
from a polychronic culture (e.g., France) are more likely to enjoy
multitasking and social interactions than those from a monochronic
culture (e.g., China), thus, are more prone to use social commerce
websites. Lastly, Li [63] adopted the culture learning model to
explain social networking sites as cultural products, which enable
newcomers (e.g., international students and immigrants) in a host
society to shape new cultural orientations. They showed that new-
comers' attitude and purchase intention toward products with cultural
symbols are associated with their usage intensity of social networking
sites.
4.3. Research methods
Previous studies have employed a number of research methods to
provide empirical evidence with regards to consumer behavior in social
commerce. According to Hoehle et al. [39], empirical research methods
are classified as qualitative (e.g., netnographic approach and focus group
interview) if they emphasize descriptive data collection and the under-
standing of contextual and environmental research phenomena. In
contrast, the quantitative methods (e.g., survey and experiment) focus
on observable and numerical data collection and the analysis of
relationships among factors in the phenomena. As shown in Fig. 3,
both qualitative and quantitative methods have been adopted in the
studies we collected. Further, over 70% (n = 54) of the studies adopted
the quantitative survey method. This indicates that the survey method
dominates empirical research in social commerce studies.
Since social commerce is still a new research area, only few studies
apply qualitative methods such as narrative analysis, netnographic
approach, and focus group interview to attain exploratory understand-
ings of the phenomenon. For instance, using the narrative analysis
method, Heinonen [37] asked consumer respondents to keep a diary
to report their thoughts and information about social networking site
usage. She was able to identify 15 types of activities regarding
consumers' participation, consumption, and production behaviors. The
Fig. 3. Research methods in the literature.
98 K.Z.K. Zhang, M. Benyoucef / Decision Support Systems 86 (2016) 95–108