E-Business (Module) Essay: Changing Trading Patterns & Market Models

This essay delves into the transformation of trading patterns and market models driven by e-business, examining how e-commerce has reshaped business operations, consumer shopping trends, and the competitive landscape. It begins by defining e-business and contrasting it with traditional business approaches, then proceeds to analyze the evolving trading patterns of both consumers and businesses, with a specific focus on industry structure, industry dynamics, value chains (both industry and firm-level), and the influence of these changes. The essay also critically evaluates the Technology Acceptance Model (TAM) and explores the evolving social shopping patterns among consumers, providing a comprehensive understanding of the key forces shaping the e-business environment. The analysis incorporates insights from the provided research papers on social commerce, social media marketing, and customer participation to offer a holistic view of the subject.

International Journal of Information Management35 (2015) 183–191
Contentslists available at ScienceDirect
International Journal of Information Management
j o ur n a lh om e p a g e :w w w . e l s e v i e r . c o m / l o c a t e / i j i n f o m g t
Social commerceconstructsand consumer’sintention to buy
Nick Hajli ∗
NewcastleUniversityBusinessSchool,UnitedKingdom
a r t i c l e i n f o
Articlehistory:
Available online 3 January 2015
Keywords:
Social commerce
Social commerceconstruct
Social media
Social networking site
Trust
PLS-SEM
a b s t r a c t
Social commerceis a new developmentin e-commercegeneratedby the use of social media to empower
customers to interact on the Internet. The recent advancementsin ICTs and the emergenceof Web 2.0
technologiesalong with the popularity of social media and social networking sites haveseenthe develop-
ment of new social platforms.Theseplatforms facilitatethe use of social commerce.Drawing on literature
from marketing and information systems (IS) the author proposes a new model to develop our under-
standingof social commerceusing a PLS-SEM methodologyto test the model. Resultsshow that Web 2.0
applications are attractingindividuals to have interactions as well as generatecontent on the Internet.
Consumersuse social commerce constructsfor these activities,which in turn increasethe level of trust
and intention to buy. Implications, limitations, discussion,and future researchdirections are discussed
at the end of the paper.
© 2014 Elsevier Ltd. All rights reserved.
1. Introduction
Recentadvancementsin information and communication tech-
nologies (ICTs) and the emergenceof Web 2.0 technologies have
brought new developmentsto e-commerce.The popularity of social
technologies and platforms such as social networking sites (SNSs)
is one of the main reasons for advancement in this area (Liang
& Turban, 2011). These developments attract individuals to come
online and have interactions with their friends on social platforms
such as online communities. The social connections and interac-
tions of people on the internet, especially in social networking
sites, the main focus of SNSs (Fue, Li, & Wenyu, 2009), have devel-
oped e-commerceto social commerce.These advancementsshape
a postmodern view of consumers (Füller, Mühlbacher, Matzler,
& Jawecki, 2009), where they communicate, rate other products,
review others’ opinions, participate in forums, share their experi-
encesand recommend products and services.They co-createvalue
with firm (Wang & Hajli, 2014). This is an advantage of social
commerce era, where consumers interact and their social inter-
action influence other consumers (Hajli, Lin, Featherman,& Wang,
2014). Social commerce is mediated by social media (Hajli, 2014a;
Jeppesen& Molin, 2003; Shin, 2013) and is mostly related to online
communities and SNSs, which have grown rapidly (Lu & Hsiao,
2010). These social platforms give opportunities to consumers to
∗ Tel.: [phone].
E-mail address:[e-mail]
support each other with information exchangeand with the con-
tent they generatethere (Hajli, 2013).
Trust is a challengingissue of e-commercefor consumers(Gefen
& Straub,2000).Trust can now be supported by social commerceas
social commerce includes social interactions of consumers,which
increasethe level of trust (Hajli et al., 2014).Distrust fails to shapea
good relationship between consumers and firms (Jones & Leonard,
2008). Therefore, trust is a critical point in an online context.
Considering trust as a critical aspect of e-commerce,this research
is being directed to investigatethe role of social interactions of con-
sumers through social commerce constructs in order to establish
trust in e-commerce platforms.
The present study tries to develop social commerce constructs
and investigateon the role of theseconstructson trust and intention
to buy. SCCsare forums and communities, ratings and reviews and
referrals and recommendations. Therefore, this study recognizes
social commerce constructs and tries to answer these questions:
(1) Do social commerce constructs influence consumers’trust and
their purchasedecisions? (2) Does trust influence social commerce
intention?
2. Literature review and theoretical framework
2.1. Socialcommerce
Social commerce is a new stream and subset of e-commerce
(Hajli, 2014b; Kim & Park, 2013),which enablesconsumersto gen-
erate content. Social commerce enables vendors to reach different
http://dx.doi.org/10.1016/j.ijinfomgt.2014.12.005
0268-4012/©2014 Elsevier Ltd. All rights reserved.

184 N. Hajli / InternationalJournal of InformationManagement35 (2015)183–191
markets by integrating social interactions of consumers(Hargadon
& Bechky, 2006). Social commerce is a new development in e-
commercewith the popularity of social networking sites and social
media that enable consumers to be active content creators on the
Internet. A powerful tool for this is social media, which differenti-
ates e-commerce from social commerce. Social commerce is the
use of Web 2.0 applications to support interaction of people in
an online context where the contribution of users can help in the
acquisition of services and products (Liang & Turban, 2011). The
popularity of social media sites is the main element for develop-
ment in this area, introducing new business models as a result
(Leitner & Grechenig, 2007; Liang & Turban, 2011). Social media
technologies have become social tools and online platforms are
now places where users share information and use opinions and
experiences of others in music, photographs, insight and knowl-
edge (Lai & Turban, 2008). In this era, SNSs and the attraction
of its applications play an important role in the development of
social media (Johann, Bartl, Ernst, & Hans, 2006; Liang & Turban,
2011). The mission of SNSs is to create online communities where
members can share and seek common interests, activities, expe-
riences and information (Shin, 2010). Social commerce statistics
show that this is a promising phenomenon. Social commerce is
introducing new business models based on online communities
where the objective is to bring features of Web 2.0 technologies
to e-commercein order to design customer-oriented business.The
businessescan develop an online community and encouragetheir
consumers to share their knowledge, experiences,and informa-
tion about their products or services,which forms social commerce
strategy for them. Alternatively, the firms may join popular SNSs
such as Facebook and sell their product through this channel or
ask their consumers to like their page or product to benefit from
social commerce. Many companies have their Facebook page and
ask their consumersto share their commentsabout the products or
the serviceson thesesocial platform, which help them to introduce
their products or services.Channel,H&M, Selfridge,Dell and many
other shops are examplesof brands that use social commercein this
context.
2.2. Socialcommerceconstructs
The experienceof consumersin an online environment enabled
by social media is different to that offline, as the customers have
social interactions with other individuals (Do-Hyung, Jumin, &
Ingoo, 2007). Today researchersclaim that through social media
and the emergenceof social platforms such as forums and com-
munities, ratings and reviews, and referrals and recommendations,
consumers do have sociability. In addition, relationships between
e-vendor and consumers are in fact personal. These social plat-
forms are social commerce constructs, which this research will
investigate. SCCs are social platforms which have emerged from
Web 2.0 and empowered consumersto generatecontent and share
their experiences.They also use others’ information, offer advice
and share experiences in these platforms providing a source for
online social support. Although, SCCs have the same functions to
facilitate the sharing of information and establishing social sup-
port platforms for consumers,they are different in their technical
capabilities.
Ratings and reviews are one of the constructs that shape social
commerce.Individuals can easily post their product reviews online
(Chen,Xu, & Whinston, 2011) and rate products.Thesereviews and
ratings give comprehensive information about products for the
benefit of other potential customers. Researchshows that a pop-
ular product review by a third party is growing (Yubo & Jinhong,
2005). It is argued that reviews generatedby a third party reduce
customers’ need for advertising information (Yubo & Jinhong,
2005). Therefore, reviews and ratings seem to generate effective
information for customers. Additionally, the engagement of
consumers in co-creation and content generation empowers
them (Füller et al., 2009), where they are able to learn about
others’ experiencesabout a product, for instance. Consumers are
increasinglyco-creatingvalue with firms (Prahalad & Ramaswamy,
2004).Empowerment refers to the capability of social technologies
to enable people to have social interaction and collaborate on
the Internet (Füller et al., 2009). Research shows that customer
feedbacksand ratings promote a higher level of trust (Ba & Pavlou,
2002; Ono et al., 2003). However, information related to the iden-
tity of reviewers has an effecton community members’perceptions
(Chris, Anindya, & Batia,2008).This issue has beenraised as a result
of fake ratings and reviews produced by third parties. E-vendors
now have to consider whether to take actions to persuadereview-
ers to give more information about their identity (Chris et al., 2008)
to assureconsumersabout the authenticity of ratings and reviews.
Recommendations and referrals, the other construct of SCCs,
are likely to play an important role on social commerce intention.
Researchshows, in an online context, as customers cannot expe-
rience the products or services, consumers should rely more on
other consumers’experiencessuch as their product recommenda-
tions (Senecal & Nantel, 2004). In a high street shop, customers
spend their time in store and interact with the staff whereas in an
online shop it is a major challenge to create an online store which
is socially rich (Kumar, Novak, & Tomkins, 2010).
The third construct of social commerce is forums and com-
munities. Online communities and Internet forums are social
environment that facilitate social interaction of individuals. Mem-
bers of online communities participate in different group activities
and support other members through their social interactions and
communications in the provided platform (Bagozzi & Dholakia,
2002). They use social technologies, such as social media, online
communities and other Web 2.0 applications, to support other
membersby their experienceand information sharing.Thesecom-
munities allow people to obtain information for products and
services and to support each other (Y. Lu, Zhao, & Wang, 2010).
This type of information, which is createdby other consumers,is a
new kind of word-of-mouth recommendationas used in traditional
markets (Do-Hyung et al., 2007).
2.3. Trust
Trust is a central issue in most economic and social transac-
tions, especially in an online context where there may be lots of
uncertainty (Pavlou, 2003).Trust is more important when risks are
perceived to be high, as in the case of e-commerce (Mutz, 2005).
This area has been widely studied by researchers (Gefen, 2002;
Gefen, Karahanna, & Straub, 2003; Kim, 2012; Morid & Shajari,
2012; Mutz, 2005; Pavlou, 2003).It is mostly becausetrust plays an
important role in the e-commerce adoption process (Aljifri, Pons,
& Collins, 2003) and it has a significant role in online commerce
(Gefen,2002).
With the increase of social technologies and interconnectivity
of people on the Internet, there is a need for some sort of trust
and security that will allow two parties to reduce their perceived
risk in transactions (Hajli & Lin, 2014). Researchshows that peo-
ple like to reduce their social uncertainty (Gefen & Straub, 2004).
It is also argued that if an e-commerce website describes prod-
ucts or servicesaccurately,consumers will trust the website more
(Ming-Hsien, Chandlrees,Binshan, & Hung-Yi, 2009). This can be
facilitated by social technologies such as customer reviews, infor-
mation and experiencesof others in forums and communities. For
instance,when a reputable member of an online forum or commu-
nity makesa recommendationto a vendor by giving good feedback,
the other members are likely to have a high level of trust in the
process (Lu et al., 2010).

N. Hajli / InternationalJournal of InformationManagement35 (2015)183–191 185
Social
Commerce
Constructs
Trust
Intention to Buy
Recommendatio
ns & Referrals
Ratings &
Reviews
Forums &
Communities
H 1
H 2 H 3
Fig. 1. Social commerceadoption model.
There are differencesin the definition of trust, dependingon the
different dimensions involved. In e-commerce literature, benevo-
lence and credibility are seen as two distinct types of trust (Ba &
Pavlou, 2002). Credibility based trust, which usually is impersonal
and relies on reputation information, refers to the belief that the
other party in a transaction is reliable and honest (Ba & Pavlou,
2002). Benevolence,however, refers to repeatedseller-buyer rela-
tionships (Ba & Pavlou, 2002). There is also a three dimensional
definition of trust (Gefen,2002)namely integrity,ability and benev-
olence. Ability refers to the skills of the trusted party, integrity
refers to honesty and keeping promises of the e-vendor and finally
benevolenceis the intention of the trusted party to do well for their
consumers (Gefen,2002; Gefen & Straub,2004).
In the present environment where social interactions of people
on the Internet shape new forms of interconnectivity and relation-
ships between people, the study of trust might be influenced by
social relationships of people and the platforms on which they
interact. Social trust is important becauseit reduces “transaction
cost” in business interactions (Mutz, 2005). It reduces the ten-
dency to monitor other parties’ activities and is an element in
sanctioning systems as reliable (Mutz, 2005). In fact, the infor-
mation from a commercial website is different from information
provided by other customers.The information that consumerspro-
vide by their reviews is seen to be more trustworthy (Do-Hyung
et al., 2007).
To endorse trust in an online environment, it is important to
have some mechanisms to provide credible signals to distinguish
among sellers (Ba & Pavlou, 2002). For this purpose, SCCs provide
recommendations,referrals and ratings.Theseconstructsgive sell-
ers reasons to be trustworthy. Social interactions of customers on
social platforms and social commerce constructs seem to have an
impact on users’behaviour.Researchersagreethat social activities
in SNSs will increaseintention to buy (Han & Windsor, 2011). This
researchconsiderstwo dimensional trusts, benevolenceand credi-
bility. Benevolencerefers to goodwill trust while credibility covers
reliability, integrity and honesty (Pavlou, 2003). The present study
defines trust in SNSs as the degree to which the SNS is willing to
put into operation its commitment and promises. Therefore,trust
is a vital component in the operation of SNSs.
2.4. Intentionto buy
Intention to buy is a construct of technology acceptancemodel
(TAM), one of the most successful theories in predicting an indi-
vidual’s intention to use a system (Pavlou, 2003). There are two
core theories to test and predict an individual’s intention to uti-
lize information systems(Mathieson, 1991).Thesetwo theories are
TAM and the theory of planned behaviour by Ajzen (1989). Inten-
tion to buy in the present study is defined as a customer’sintention
to engagein online buying in social networking sites. TAM is a core
theory in e-commerce studies (Martins, Oliveira, & Popoviˇc, 2014;
Park, Roman,Lee,& Chung,2009) and many authors developedthis
model (Hsiao & Yang, 2011).
3. Research model and development of hypotheses
In this research a social commerce adoption model has been
developed in order to increase our understanding of social com-
merce and emerging social relationships of individual on the
Internet. Specifically,this researchinvestigatesthe role of SCCs to
discover the role of theseconstructson a social commerceenviron-
ment.Along with SCCs,recommendationsand referrals,forums and
communities and rating and reviews, the researcher added trust
and intention to buy as on-going issues in e-commerce.These are
included in the model as shown in Fig. 1.
3.1. Socialcommerceconstructs
The emergenceof Web 2.0 applications and the ability of users
to co-create on the internet has supported consumers in solving
tasks while giving them feelings of empowerment and enjoyment
(Füller et al., 2009). Researchshows that social activities on these
platforms have economic implications in the form of product sales
(Chris et al., 2008).
The impact of social media in the market can be seen from how
e-vendors provide more opportunities than before to interact with
consumers (Amblee & Bui, 2011). Social commerce,with the aid of
Web 2.0 and social media technology,facilitate consumers’ratings
and reviews, and recommendations and referrals. Ratings and

186 N. Hajli / InternationalJournal of InformationManagement35 (2015)183–191
reviews, which enablecustomersto have a look at friends’ reviews,
help them in the decision-making process of buying. Brand repu-
tation can also be affected by feedbackfrom reviews (Davidson &
Copulsky,2006).The consumercan turn to online recommendation
systems,which seem to have a significant influence on the buyer.
However, such systems are often biased according to findings in
different markets (Riemer & Lehrke,2009; Senecal& Nantel, 2004).
Research also shows that reviews by a third party has a sig-
nificant effect on the purchasing decision of consumers (Yubo &
Jinhong, 2005). In fact, one of the main reasons that customer
reviews have such influence on salesis related to the value of infor-
mation and the experiencea customer has for a product or service
(Chris et al., 2008). This can be shared with consumers who have
not had the experience. Research shows that a recommendation
as a source of information strongly influences customer behaviour
(Senecal & Nantel, 2004). It is also noted that online recommen-
dations strongly influence the online choice of product (Senecal
& Nantel, 2004). Participation of people in online communities,
with information exchange,is the main reason for joining virtual
communities. This has a direct influence on customer behaviour
(Ridings & Gefen,2004).Consequently,this study can hypothesize:
H1. Socialcommerceconstructshavea positive effecton the user’s
intention to buy.
SCCsalso have influence on trust. Researchshows customer rat-
ings has influence on the level of trust, which consequentlyleads to
more saleson that platform (Swamynathan,Wilson, Boe,Almeroth,
& Zhao,2008).Ratingswill also increaseuser satisfactionwhen they
undertake a transaction (Swamynathan et al., 2008). In fact, posi-
tive ratings have a strong influence on trust formation (Ba & Pavlou,
2002).This researchalso shows that social context is the other fac-
tor that influences trust (Weisberg, Te’eni,& Arman, 2011). When
an e-commerceplatform has social presence(Weisberg et al.,2011)
and social application, consumers feel more secure and conse-
quently they have more intention to buy. Previous researchshows
that social presence increases the level of trust (Gefen & Straub,
2004) and that social presence can be achieved by SCCs. In fact,
social interactions of consumerscreatesocial word of mouth which
positively affectstrust (Kim & Park, 2013).Therefore,the following
researchhypothesis is hypothesized:
H2. Socialcommerceconstructshavea positive effecton the user’s
trust.
3.2. Trust
Trust is an important aspect in e-commerce (Gefen & Straub,
2004; Mutz, 2005; Pavlou, 2003) and when rules are not adequate,
consumers try to reduce social uncertainty by relying on trust and
familiarities (Gefen & Straub, 2004). When people participate in
forums and communities or read others’ reviews and ratings of a
product or service,their level of familiarity to a website or SNSs is
likely to increase.This brings trust to the transaction.
Trust has the ability to decreasebehaviouralhesitation to intend
to buy in e-vendor websites(Pavlou,2003).It givespower of control
over the transactionto consumers(Pavlou,2003).This power helps
customers to interact with the website as they deliberate their
intention to buy. It is likely that trust in online communities sup-
port customers in their shopping behaviour. Researchshows that
trust positively influences a consumer’sintention to buy (Gefen &
Straub,2004; Pavlou, 2003). Trust has the mediating position in an
electronic market (Ba & Pavlou, 2002) and in the proposed model
has the mediating role. It is mainly due to the fact that trust has
a key influence on the successof e-commerce (Ming-Hsien et al.,
2009) and it should have the same influence in social commerce.
In addition, it has been confirmed that trust has a significant
role in enhancing intention to buy (Lu et al., 2010; Shin, 2010).
Having confidence and less perceived risk are important factors
when searchingfor new items or servicesin an online environment
(Hassanein & Head, 2007; Shin, 2010). Hence, it is important to
investigate the role of trust on social commerce adoption. In the
study of concerns and risks about e-commerce, researchersstate
that there is a significant relationship between trust and online
commerce behaviour (Ba & Pavlou, 2002; Gefen,2002).
H3. Trust of users in SNSshas a positive effect on intention to buy.
4. Research methodology
An empirical study was conducted to test the relationship
between the constructsand a questionnairewas developedfor this
purpose.The researchconducteda surveyto collect the data,which
is described below.
4.1. Instrumentdevelopment
The research has four constructs: intention to buy, social com-
merce constructs, perceived usefulness and trust. To measure the
constructsa questionnairewas developed.The researchused a five
point Likert-scale from 1, strongly disagree to 5, strongly agree.
Social commerce constructs include three dimensions: forums
and communities, ratings and reviews, referrals and recommen-
dations. The measurementsof SCCs are based on participation of
individuals in these social platforms. The measurement assessed
participation of consumers to generatecontent, rate, review, rec-
ommend and refer products or services. Trust was measured by
benevolence and credibility in SNSs. The dependent variable of
this research is intention to buy. Intention to buy measures the
user’swillingness to pay on SNSsand their intention to buy through
SNSs.
4.2. Data collection
The data was collected through a survey conducted in the UK
in March 2012. We targeted students, mainly in the UK as they
are using social networking sites. Before the main survey, a pilot
study with 15 students was used to make sure the questions and
wordings were clearly understood by respondents. In total 1000
students were identified from various sources for the main sur-
vey. The questionnaire was by paper and in an electronic version
to maximize the number of participants. The questionnaire,which
was sent by email, requested people to participate in the survey.
For this researchwe targetedstudent union mailing shots and also
posted ads in Facebook,asking friends to share the questionnaire.
200 questionnaireswere distributed in two universities in London.
A total of 280 responseswere received.Some of the questionnaires
were dropped as they were incomplete.The total valid respondents
included 113 males and 130 females.The responserange was from
18 to 45 years, with 16%of eighteen to twenty-two years and 84%
of twenty-three to forty-five years.The researchused a total of 243
usable responses.
4.3. Data analysisand findings
The present study applies Structural Equation Modelling (SEM).
SEM as recommended has many advantagesover other methods
(Gefen, Rigdon, & Straub, 2011; Ringle, Sarstedt,& Straub, 2012).
SEM is also good in terms of path and factor analysis, especially
when we are looking for reliability and validity of a research out-
come from different angles.This is availablethrough this approach.
The research chose Partial Least Squares (PLS) method to test the

N. Hajli / InternationalJournal of InformationManagement35 (2015)183–191 187
hypotheses.PLS simultaneously assessesthe validity and reliabil-
ity of constructs(McLure Wasko & Faraj, 2005).PLS has advantages
compared to other methods such as LISREL. Sample size is an
important issue in SEM and PLS can handle a small sample size
(Chin, 1998; Ringle et al., 2012). In addition, PLS is also good for
exploratory research (Chin, 1998; Gefen & Straub, 2004), which is
the nature of this research.This method is also suitable for testing
a new model and theory as it can be good for confirmatory and
exploratory research(Gefen et al., 2011).
The researchuses the re-sampling method of SmartPLSfor sig-
nificance testing. In the present study the bootstrapping of 200
re-samples and 250 cases per sample was carried out in order to
assess the path significance. The estimate of bootstrap provides
the basis for confidence intervals allowing an estimation of factor
stability (Ringle et al., 2012).
4.4. Measurementmodel
4.4.1. Reliability
Reliability in a survey is the stability of the measures it uses
(Sapsford,2006).Eachsurveyconstructshavedifferent items which
assessinternal consistency (McLure Wasko & Faraj, 2005; Straub,
Boudreau,& Gefen,2004). There are different methods available to
test the internal consistency.In PLS it is advisable to calculate the
composite reliability, where the acceptedvalue should exceed0.70
and should be interpreted by Cronbach’salpha (McLure Wasko &
Faraj, 2005). The results of the composite reliability as shown in
Table 1 indicate an acceptablerate and show the research has an
internal consistency.To measurereliability, the researchalso tested
the internal consistency, which can be calculated by Cronbach’s
alpha, as seen in Table 1. All constructs have a value more than
0.70, an acceptablevalue for this test. Moreover, to improve the
reliability of the test, the author amended the questionnaire after
the pilot study, as the check for reliability of the researchdepends
on piloting of the instrument and question wording (Bell, 2010).
These two types of reliability tests ensure we can analyze the data
accuratelyfor the survey.
4.4.2. Validity
To have a high content validity, the author undertook a sub-
stantial literature review in the area of e-commerce and social
commerce and piloted it with 15 students. The face validity was
the other object of this test (Gefen, 2002). Each of the students
was asked to check if the scale items were appropriate and unam-
biguous. Moreover, some of the constructs – trust and intention to
buy – are taken from existing literature and have been frequently
shown to demonstrate evidence of strong content validity (Gefen
et al., 2003; Pavlou, 2003).The literature source for each construct,
which has beenused in the literature review, is indicated in Table 1.
Noticeably, constructs drew their items from different validated
sources,which improved the validity of this researchwith regards
to the measurementof the constructs.
Constructvalidity can be checkedby discriminantand convergent
validity (Chin, Gopal, & Salisbury, 1997). The results of convergent
Table 1
Sourcesof constructs,reliability and validity.
Codes Scales Factor loadings CR AVE Cronbach’salpha
Trust
Adaptedfrom D. Gefenand D.W. Straub;HAN, BO and WINDSOR,JOHN
0.874 0.536 0.828
T1 Promises made by SNSs are likely to be reliable 0.791
T2 I do not doubt the honesty of SNSs 0.732
T3 I expectthat the advice given by SNSs is their best judgement 0.737
T4 I believe SNSs have my information safetyin minds 0.706
T5 SNSs give me an impression that they keep my privacy information
safe
0.709
T6 SNSs (such as Facebook,MySpace) are trustworthy 0.763
Intention to Buy
Adaptedfrom HAN, BO and WINDSOR,JOHN; Lu and Hsiao; D. Gefenand
D.W. Straub
0.801 0.510 0.711
IB1 I am likely to pay for fees to have speeddating on SNSs 0.722
IB2 I am likely to pay for the membershipif SNSs start chargingfees 0.703
IB3 I am very likely to buy books from SNSs 0.824
IB4 I would use my credit card to purchasefrom SNSs 0.838
Recommendation and referrals
Adaptedfrom HAN, BO and WINDSOR,JOHN
0.879 0.656 0.813
RE1 I feel my friends’ recommendationsare generallyfrank 0.845
RE2 I feel my friends’ recommendationsare generallyreliable 0.839
RE3 Overall, my friends’ recommendationsare trustworthy 0.851
RE4 I trust my friends on SNSs and share my status,pictures with them 0.805
Forums and communities
Adaptedfrom HAN, BO and WINDSOR,JOHN
0.871 0.630 0.802
FC1 I feel my friends on forums and communities are generallyfrank 0.801
FC2 I feel my friends on forums and communities reliable 0.700
FC3 Overall, my friends on forums and communities are trustworthy 0.882
FC4 I trust my friends on forums and communities and share my status,
pictures with them
0.782
Rating and reviews
Adaptedfrom HAN, BO and WINDSOR,JOHN
0.904 0.702 0.858
RT1 I feel my friends rating and reviews are generallyfrank 0.823
RT2 I feel my friends rating and reviews reliable 0.849
RT3 Overall, my friends rating and reviews are trustworthy 0.885
RT4 I trust my friends on rating and reviews and share my status,pictures
with them
0.793
Notes:CR, composite reliability; AVE, averagevariance extracted;T, trust; IB, intention to buy; RE, recommendationsand referrals; RT, ratings and reviews; FC, forums and
communities.

188 N. Hajli / InternationalJournal of InformationManagement35 (2015)183–191
Table 2
Squareof correlation between constructs.
Forums and communities Intention to buy Rating and reviews Recommendationand referrals Trust
Forums and communities 0.80
Intention to buy 0.388744 0.72
Rating and reviews 0.51316 0.36317 0.84
Recommendationand referrals 0.509202 0.327371 0.620878 0.81
Trust 0.39646 0.47034 0.360911 0.384942 0.74
Notes:Numbers on the diagonal (in boldface)are the averagevarianceextracted.Other numbers are the square of correlation.
test are shown in Table 1, where AVE in all constructs is more than
0.5 indicating that this researchachievedthese criteria.
Further assessmentwas madeto test the validity of the research,
discriminant validity, to gaugethe extentto which a given construct
of the research model is different from others (McLure Wasko &
Faraj, 2005). As it is shown in Table 2, all AVEs are greater and
demonstratediscriminant validity.
Another way to assessdiscriminant and convergent validity of
the research is by examining the factor loadings of each indicator
(McLure Wasko & Faraj, 2005). Table 3 shows the factor loadings
for each construct and confirms that the observed indicators has
enough convergent and discriminant validity. The author needs
to mention that two items, intention to buy and trust, have been
dropped due to low factor loading.Theseitems are shown in Table1.
This helps to get better results from PLS. The overall results and
scale have been checked to make sure the dropped items do not
affect the model.
4.5. Structuralmodel
The estimation results from SmartPLS software are shown in
Fig. 2. According to the results, all the paths among constructs
are positive and significant at the 0.05 level. The model validity
is assessedby R square value and the structural paths (Chwelos,
Benbasat,& Dexter,2001). The results of the R square indicate that
almost 30%of the variance in the intention to buy was accounted
for by social commerce constructs and trust. It means intention
to buy was, as hypothesized, affected by SCCs and trust. The R
square for trust means that 28%of the variance in this construct
was accounted for by SCCs. Hence, the result of R square shows
a satisfactory level of explanation. In the following section, the
relationships among these constructs are explained and inter-
preted.In addition, directed effects of social commerce constructs,
trust and perceivedusefulnessare examined.
The research empirically tested social commerce constructs
throughout the survery. To do this, the research performed boot-
strapping to test the statistical significance of construct path
coefficient by means of t-tests.The path coefficient and t-value has
been shown in Fig. 2. The bootstrappingof 200 re-samples and 240
cases per sample shows social commerce constructs has a signif-
icant effect on intention to buy. Therefore, H1 is supported. The
effect of SCCson trust is also strongly supported.Hence,H2 is sup-
ported. Trust also positively affectsintetion to buy, which supports
H3.
According to the path coefficients, the direct effect of SCCs on
trust (0.407) is stronger than that of intention to buy (0.233).This
indicates that SCCs have more influence on trust than intention
to buy. In fact, SCCs have influence on intention to buy directly
and indirectly through trust. The path coefficient of trust in inten-
tion to buy (0.378) shows that direct effect of trust on intention to
buy is stronger than SCCs.This indicates trust is more important
than SCCsin intention to buy. Finally, the results of constructspath
coefficient indicate that trust is the most important factor in deter-
mining user’sintention to buy, followed by SCCswith a strong path
coefficient.
5. Discussion
A social commerceadoption model has been developedin order
to study consumer’sbehaviour in social commerce era. The results
of this study show that consumers are increasingly using SNSs
to share their knowledge, information, and experiences about a
Table 3
Cross loadings.
Forums and communities Intention to buy Recommendationand referrals Rating and reviews Trust
FC1 0.800471 0.329931 0.688005 0.62159 0.286632
FC2 0.699037 0.352371 0.497193 0.508466 0.332643
FC3 0.881783 0.254574 0.71932 0.715373 0.317193
FC4 0.781804 0.31647 0.641389 0.71424 0.330931
IB1 0.153339 0.721622 0.148738 0.177938 0.258653
IB2 0.248987 0.702764 0.173106 0.178739 0.228793
IB3 0.306287 0.823762 0.253246 0.274998 0.40408
IB4 0.362728 0.837106 0.319263 0.359776 0.407054
RE1 0.633081 0.245338 0.844159 0.601222 0.291806
RE2 0.619011 0.304563 0.838275 0.639425 0.306974
RE3 0.684005 0.346784 0.850499 0.777026 0.37117
RE4 0.661377 0.135628 0.804364 0.602325 0.255844
RT1 0.587304 0.352256 0.654269 0.822756 0.268831
RT2 0.611567 0.311534 0.65492 0.848529 0.248898
RT3 0.755221 0.259022 0.752753 0.884673 0.320616
RT4 0.756814 0.301757 0.681416 0.792566 0.365455
T1 0.365039 0.49106 0.237294 0.21509 0.790414
T2 0.220782 0.331588 0.187766 0.20093 0.731702
T3 0.354482 0.327859 0.384519 0.413889 0.736214
T4 0.159287 0.333245 0.165205 0.149576 0.705097
T5 0.214142 0.222775 0.287018 0.202757 0.708546
T6 0.353499 0.309483 0.394662 0.350998 0.762858
Notes:Numbers on the diagonal (in boldface)are the factor loading of each item.

N. Hajli / InternationalJournal of InformationManagement35 (2015)183–191 189
***p <0.001
Social
Commerce
Constructs
Trust
R2 0.28
Intention to Buy
R2 0.30
Recommendatio
ns & Referrals
Ratings &
Reviews
Forums &
Communities
Path Coefficient 0.375***
Path Coefficient 0.233***
Path Coefficient 0.407***
94.02***
93.19***
Fig. 2. Resultsof the PLS analysis,***p<0.001.
product or a service with their peers. They use social commerce
constructs to have social interaction with their peers.Initially, the
model emphasized the role of social relationships of individuals
on the Internet and the paradigm change of transferring passive
consumersof information to active content generators.Individuals
are being rapidly attracted to SNSs,online communities and other
social platforms and enjoy participation in creating content. The
empowerment earned by consumers through social media makes
them active users and encourages them to have social interac-
tions with other consumers.These social relationships drive value
for both businesses and consumers. Businessesare happy seeing
consumers provide information for other consumers by their con-
tent generation. E-vendors also develop closer relationships with
their customers, giving rise to better customer relationship man-
agement.Social commerceconstructsare facilitated by thesesocial
interactions through the development of Web 2.0 technologies.In
these platforms, consumers feel closer to each other and encour-
age each other to have more participation. This supportive climate
helps to alleviate some big issues,such as trust, in the e-commerce
market. Empirical tests significantly support the assertion that
social commerce constructs will increase trust. Therefore, these
platforms help to increasetrust and intention to buy in consumers.
In fact, SCCson the Internet have developed e-commerce to social
commerceby theseadvantages.Overall,this researchindicatesthat
social commerce constructs are more likely to attract individuals,
increasetrust and influence consumers’intention to buy.
5.1. Theoreticaland practicalcontributionof this research
The present research highlights the role of social commerce
constructs and how they shape social commerce and increase the
level of trust and intention to buy. The practical contribution of
this researchis that the results emphasizethe importance of social
platforms provided by Web 2.0 technologies in social commerce
era. As indicated in previous research(Yubo & Jinhong, 2005), it is
important for firms to make a plan for reviews and to managesocial
platforms effectively as it has a significant impact on purchasing
decisions of consumers.
The results give some practical instructions to e-vendors as
to how social commerce constructs can be used as trust building
mechanismsto influence consumerbehaviour and intention to buy
in SNSs.Social platforms such as forums and communities, recom-
mendations and referrals, and ratings and reviews are the main
element in social commerceto build that trust. Therefore,the firms
may engage with their consumers in these platforms to develop
trust.
In terms of theoreticalimplication, this researchproposesa new
model given the new concepts in social commerce. This research
develops the literature of social commerce by introducing social
commerce constructs through an empirical study. This research
also discusseshow these constructs can influence trust and inten-
tion to buy in a social commerce era.
5.2. Limitationsand futureresearch
The researchis not without limitations. One of the researchlim-
itations is that the study used a five-point Likert-scale. The future
research should test the scales using a seven-point Likert-scale to
get better results.It may be valid to carry out similar researchusing
LISREL,as most of the constructshave beentestedin previous stud-
ies.
6. Conclusion
This researchinvestigatesthe new streamin e-commerce;social
commerceto offer better understandingof social commerce.In the

190 N. Hajli / InternationalJournal of InformationManagement35 (2015)183–191
present study, the author borrowed some constructs from tech-
nology acceptancemodel to explain social commerce constructs
and its influence on intention to buy and trust. Social commerce
constructs,namely, forums and communities, ratings and reviews
and recommendationsand referrals are the main constructs of the
social commerceadoption model. A researchmodel with four con-
structs investigated the role of SCCs on intention to buy. It also
validated the role and importance of trust. The findings of the
research show that social commerce constructs are measured by
forums and communities, ratings and reviews and recommenda-
tions and referrals and have been justified by?? (Is this correct?).
The results of empirical testing, using PLS-SEM indicate the direct
and significant effect of SCCson intention to buy. The findings also
show trust has a positive effect on intention to buy, consistentwith
many other TAM researches.Finally, the positive and significant
effect of SCCs on trust is the other valuable result of the research.
These findings give some highlights into the study of social com-
merce.
The main contribution of this researchis that when empirically
tested, social commerce constructs showed that social relation-
ships and interactions of individuals in theseplatforms, which have
emerged by Web 2.0 applications, influence consumer behaviour.
The results also show that social commerce constructs give the
opportunities for co-creation, participation, sharing information
and collaboration between users, thus generating a value. These
activities also have positive influence on intention to buy. The find-
ings suggestto e-vendors that it is important to bring togetherand
meet consumers by forming online communities. This enhances
communication channels with customers and creates opportuni-
ties for marketing strategies that can benefit both vendors and
consumers.
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Nick Hajli is the degreeprogramme director for the BSc in Marketing programme
and a Lecturerin Marketing in NewcastleUniversity BusinessSchool.He also serves
as the guest editor for the International Journal of Information Management and
the TechnologicalForecastingand Social ChangeJournal. His active researchareas
are consumer decision making in a social commerce context, co-creation of value
with consumers,and healthcaredevelopmentin current digital era.His researchhas
appearedin the top 20 Journals used in BusinessSchool ResearchRankingssuch as
Journal of BusinessEthics. He has also published on refereedjournals such as Tech-
nological Forecastingand Social Change,International Journal of Market Research,
International Journal of Information Management, and other quality journals as
well as in severalinternational Conferences.His recent paper was among the final-
ists from the nominations for an outstanding paper award in the 20th Americas
Conferenceon Information Systems(AMCIS 2014).