Embed Size (px)
DESCRIPTION
Citation preview
1
A study of Influecing Factors for Purchase Intentions in Social
Commerce
Jeong Woong Sohn and Jin Ki Kim
Department of Business Administration, Korea Aerospace University
100 Hanggongdae gil, Hwanjeon-Dong, Deogyang-gu, Goyang City, Gyeongg- Do 412-791, Korea
Tel: +82-2-300-0353 E-mail: [email protected]
Department of Business Administration, Korea Aerospace University
100 Hanggongdae gil, Hwanjeon-Dong, Deogyang-gu, Goyang City, Gyeongg- Do 412-791, Korea
Tel: +82-2-300-0353 E-mail: [email protected]
Abstract
Recently, Social commerce expands real time by combining itself with social network services.
The business model of social commerce is simple, it has great potential to create big sales.
Due to this, the social commerce market is increasing sharply.
At the aspect that how consumer as a new innovation service different from existing business
transaction adapts the social commerce will determined the growth potentiality of future
social commerce, we need to check what type of attributes social commerce has.
The purpose of this study is to make the social commerce to check the attirbutes and purchase
intentions as the users increase, and suggesting a marketing and strategy to the company
which are trying to sell via social commerce providers and social commerce.
This study finds the following: First, factor analysis reveals five attributes that can be used to
classify Social commerce – these are Economy, Necessity, Reliability, Interaction, Sales
Promotion; and second, As a result of carrying out the Multiple Regession Analysis by
making Purchase intention to be Dependent variable, Economy, Necessity, Reliability, Sales
Promotion are shown to affect the Purchase Intentions.
Through this research, entrepreneurs in social-commerce business can attract far more
customers by figuring out the reasons for purchase and needs of them. And this research also
can help to organize the strategy that can effectively manage the things explained above.
Keywords: Social Network Service(SNS), Social commerce, Purchase Intentions
2
1. Introduction
SNSes are well-known as web-based services that help users to build a public or
semi-public profile over the internet. Users can share human connections with other users
while exchanging their lists of connections with each other within the same system (Boyd &
Ellison, 2007). From recent research, it has been found that the use of SNSs in the world has
been rapidly increasing. The number of users that uses the service increased by 87% in 2009
from 2003 and the time they spend increased by 833% (Global trends in online shopping,
2010).
As Social Network Service (SNS) gets boosted, based on this, Social Commerce
service has been growing internationally. Social Commerce makes business transaction by
connecting producers and consumers through Facebook, Twitter, etc. of a typical SNS, and
was born in the United States in the middle of 2000. As Groupon succeeded in the United
States in 2008, Social Commerce services have grown significantly.
Furthermore, the popularization of such internet social communities and users’ desire
to participate in such communities became important factors to increase social commerce.
More general research in the USA (Forrester Research, 2007) than those about online
commerce reported that consumers are now starting to have more confidence in product
popularity or recommendations for products from other users than from one-way
communication tools such as advertisements or other information provided by product
marketing companies.
Yahoo introduced terminology of social commerce for the first time in 2005. At the
beginning, users use this terminology meaning services including sharing shopping list or
evaluation on products. If commercial transaction is made in social media or there is any
social factor in commercial transaction service, it can be considered as social commerce. Also,
3
it is not selling products, but can generate word of mouth though SNSs(Strabase, 2001).
It has been developed in the form of social shopping or Social Commerce which is a
new shopping approach combined with online shopping mall SNS. In other words, it is a new
form of shopping mall which did not exist previously, and combined with SNS, it functions
the new media beyond "Shopping”.
Social Commerce created a new form of promotion that consumers determine a
product by themselves and also contribute to the sales (Strabase 2007). In addition,
consumers are able to see and share other consumer’s opinions or interests for a product
through a variety of the path such as Product Review, Blog, SNS, etc. Thus, consumer's
characteristics of a member to participate in the process of commerce can be more important
than in any other form of commerce.
The largest providers of the Web Service Industry who have paid keen attention to
the rapid growth of the Groupon, the representative social commerce company in the United
States, showed interest directly or indirectly since late last year in entering into the social
commerce market. Facebook has over 600 million subscribers throughout the world
announced in November 2010 that they launched their “Facebook Deals”. Google, the leader
of the U.S. web service market focusing on search services made an unconventional offer last
year to take over Groupon at 6 billion dollars, but their offer was declined (Lee, 2011).
Amazon, the representative leader of e-Commerce in United States announced that, after the
fact was known by the public that Google was trying to take over Groupon, they invested 175
million dollars in Living Social, the second largest company in the social commerce industry,
and agreed mutually to carry out the business collaboratively (Strabase, 2011; Lee, 2011).
Table1. Recent Moves of Google, Amazon and Facebook related to the latest Social Commerce.
4
Company Contents
Groupon
• Through the participation in 35 countries including United States, Canada, Brazil,
Germany, Greece, France, Britain, Israel, Italy, Portugal, Spain, Japan, Poland,
Turkey, Mexico, Peru, Chile, Colombia, etc., about 5,000 registered users have
been obtained.
• Considering the importance of locality due to the nature of Social Commerce
business, entry to the world market has been made by acquiring the local
companies.
• Instant sales system has been introduced through the installation of Kiosk.
• Made an unconventional offer late last year to take over Groupon at 6 billion
dollars, but offer was declined by Groupon.
•‘Google Offers’ services began in June.
Amazon
• Today daily deal site Groupon, Amazon invest 175 million dollars in Living
Social, the second largest social commerce company in the America., and agreed
mutually to execute the business partner.
Source: (Strabase, 2011; DMC, 2011).
Despite such aggressive moves by the large providers, Groupon still remains firmly
as the leader of the social commerce market in the United States. Groupen successfully
secured more than 60 million subscribers within two years after starting its service and
attracted more than one billion dollars of investment in the form of venture capital. Groupon
is still growing, marking annual sales equivalent to 760 million dollars through the services
provided from over 500 markets in 44 countries around the world (Strabase, 2011).
The biggest change brought by social commerce is the change in the relationship
between companies and consumers. In the social commerce market, consumers not only
purchase products, but also spread their experiences by word of mouth. That is, consumers
produce information and spread it by themselves. This has a great impact on the sales of
goods and services. Through the information spread real time on the social network,
companies can have the advantage of maximizing the effect of verbal advertizing without
large costs. The objective of this study is to identify factors which affect users to use social
commerce, as the social commerce market grows.
5
The reasons Social Commerce comes into the spotlight are 1) less marketing costs
enable sales promotion, so it can be used for a small company's new marketing channels, 2)
you can afford to enjoy a product at a reasonable price, 3) Due to recommendations by
acquaintances, the confidence of the product is formed prior to purchasing, there is high
possibility of purchasing, 4) thanks to the growth of mobile devices such as smart phones and
SNS, there is high possibility of the market growth (DMC, 2011).
Leitner & Grechenig (2007) claimed that SNS has also changed online market
through continued participation of the users. Social Commerce has delivered shopping culture
to consumers in a new way over the entire generation, created trends and has reflected the
diverse needs of consumers.
With the advent of a smart phone recently, consumers are made possible to obtain
real-time information through SNS by connecting to internet anytime, anywhere. As various
smart phone applications combining and providing information of current Social Commerce
sites began to be created, consumers are able to come across the information of Social
Commerce anytime, anywhere through the applications of a smart phone. If Social
Commerce can better satisfy information acquisition motive of consumers as more reliable
information, Social Commerce will become a channel of new shopping information.
Unlike the existing business transaction, Social Commerce, as innovative services, is
required that its property shall be identified in because how to accept Social Commerce
determines the growth potential of Social Commerce in future. In addition, despite the
innovative distribution structure of Social Commerce becomes a worldwide sensation and is
rapidly growing, this study includes only a meaning as the basic data of Social Commerce
research due to the lack of advanced research.
Thus, the purpose of this study, as the users of Social Commerce increase, is to
6
investigate the properties that Social Commerce has and is to propose marketing and strategic
direction of the companies that intend to sell using Social Commerce providers and Social
Commerce. In particular, at the present time we meditate the true meaning of Social
Commerce, we will be able to reconsider the implications of this study in that a variety of
issues shall be diagnosed and examined.
2. Social Commerce Business Model
Social Commerce is a wider concept including the ones that individuals sell stuff
through the SNS as well as electronic commerce based on a specific site. In other words,
Social Commerce is a new concept that was born by combining the effects of traditional
online shopping and word of mouth marketing (Tedeschi, 2006; Chevalier & Mayzin, 2006;
Liu, 2006; Godes & Mayzlin, 2004).
The biggest difference between Social Commerce and the existing electronic
commerce is that consumers play the natural role of the sellers through ongoing
communication between sellers and consumers as a new network way. Communal purchase
Social Commerce has a certain volume sold within the specified time and only if the sales
volume is met, large scale of discount will be applied. Thus, in order to receive great
discounts, consumers shall bring friends, acquaintances or a third party through the SNS.
As one of Social Commerce features, a purchase is made within a specified time.
Kruglanski (1989) argued that when consumers are pressured by the time or the quantity of a
product, there will be Need for Closure that they intend to make a decision based on
information search. Need for Closure is the answer as opposed to the confusion and
ambiguity, and it is the desire to get definitive answers about some issues.
7
Social commerce is new business of e-commerce model. So many companies that
want to prove new products (Silverton, 2010). Levi’s, which is famous for its blue jeans,
opened its ‘Friend Store’ on its website in April, 2010. People could use a ‘Like’ button as
well as easily take advantage of a Facebook Connect function through a link with Facebook.
In this way, consumers can easily recognize in which clothes their friends as well as other
people are interested. After only one week of launching the store, it recorded over 4,000
‘Likes’. Also, over 60,000 products have had at least one ‘Like’ until now. In addition to this,
they found that an increasing number of people like Levi’s in Facebook (Kmobile, 2011).
A new type of social commerce is to directly place a store and sell goods on an SNS.
While Joint buying is an indirect utilization of SNSs and Link-to-Web direct utilization, this
new type is to add a shopping mall in the SNS as a form of a tap or an application. Recently,
an increasing number of companies are opening shopping malls on Facebook by using
shopping mall builders like Pavement, Alvenda and so on. By using these builders, you can
use additional functions such as joint buying and events as well as product registration,
shopping carts, reviews, etc. Disney sold thickets for their famous animation movie ‘Toy
Story 3’ on Facebook and Delta Airlines started an advance selling service of their tickets
(DMC, 2011; Social commerce today, 2011; Kim, 2011).
2.1 Social Commerce Four Types
• Social Link
This is to place a button on the commerce site linking to an SNS. If you click the button,
you can automatically go into the posts writing window on your social network site through a
web-link or you can copy the web documents into a posting on your SNS(Bloter, 2011; DMC,
2011).
8
• Joint Buying
In this type, a joint buying site is combined with a social network. The price of goods
would be discounted if the selling quantity per item reaches a certain number. This will
encourage the consumers to invite their friends to the joint buying through social networks.
They sometimes have an incentive program to reserve cash or points for the consumers
whose friends become members of the site or goods are bought when new consumers are
introduced. The source of profit is an advertisement fee or a sales commission. Groupon and
Wipon are typical examples(Bloter, 2011; DMC, 2011).
• Offline Connection
This is a type that links off-line places to a social network through terminals capable of
networking. By utilizing location based services like Posqure, Gowala or Runpipe, consumers
spread their experiences at off-line stores to social networks through mobile terminals(Bloter,
2011; DMC, 2011).
• Social Web
It is a type that aggressively combines commerce with social networks, making it
possible to use social network functions on a commerce site. Such consumer activities as
purchasing, evaluations, reviews and so on are automatically reflected to the social network
and shared with friends. Consumers may see what their friends in the same social network do
at the commerce site (Bloter, 2011; DMC, 2011).
9
3. Theoretical Background
3.1 Social Network Service (SNS)
In traditional social network theory, a social network is defined as a set of social
entities that includes people and organizations which are connected by a set of socially
meaningful relationships and who interact with each other in sharing values (Kwon & Wen
2010).
The definition of an SNS in Boyd & Ellison's theory is the most commonly used.
Social networking service is web-based services and can connection by others within the
system. The nature and nomenclature of these connections may vary from site to site (Boyd
& Ellison 2007). Scholars have studied such social areas as privacy, social capital, youth
culture, and education so far. In particular, Facebook is increasingly becoming the object of
scholarly research (Ellison et al. 2007; Ahn et al. 2007; Boyd et al. 2006; Haythornthwaite
2005). There have been few attempts in the past to define and classify business models in the
SNS industry. O’Murchu et al. (2004) presented a review of the classification of various
SNSs.
SNSs earn money through various ways. For example, people are paying for various
sites. in particular, dating related site. However, revenue is typically gained in the
autonomous business model via advertisements in the SNS industry (Lee, 2008). There are
websites categorized differently such as movie, clothing and online business websites being
studied to assess reliability, trust and web credibility. Social networking sites share online
interaction and communication with specific goals and patterns across different services. The
structures and characteristics of online social networking services and functionalities may
vary significantly (Ahn et al. 2007; Bulter, 2001; Hu & Kettinger 2008; Alexander Richter &
Koch 2008).
10
Previous research has analyzed several open and closed SNSs to identify their
common functionalities and characteristics. Alexander & Michael (2008) and Ko, Hwang & Ji
(2010) define the function of SNS by analyzing several websites of SNSes. Also, the
common functions were defined in Table 2 resulting from a study of the relevant papers.
Table 2. Functions of SNS
Alexander &
Michael (2008) Ko et al. (2010) Functions of SNS
Expert finding Expert search Function that enables you to search for those who
have expertise or things of interest, etc.
Network
awareness Identity
Function that enables you to express your status,
mood or feeling, etc.
Exchange Communication Function that enables you to share your messages or
conversations with others
Contact
management Connection
Function that enables you to establish, communicate
and manage a relationship with others
Alexander & Michael (2008) suggests the functions of SNSes could be categorized
as Identity management (access rights can be direct or role based) and Context awareness (the
awareness of a common context with other people). Ko et al. (2010) presents that SNSes also
provide the function of Content sharing (the function that enables sharing and distribution of
personal audio and video content).
3.2 Online Shopping Mall
Internet shopping mall is the Electronic retail market that supports the electronic
transaction between enterprises & consumers, which is in contrast with modern shopping
mall concept. And It's been used in various terms, including Internet Shopping Mall,
Electronic Shopping Mall,Virtual Storefront, Online Storefront, Internet Mall, Electronic Mal
l, etc. (Zimmerman, 1994).
A sharp increase in on-line shopping business can be attributed to time and spatial
convenience and advantages in price comparison based on the characteristics of the internet.
11
As the number of internet users and internet usage increase, the way consumers use and will
use this interactive tool in or as part of their shopping decisions and practices continues to
attract the attention of researchers and practitioners (Rohm & Swaminathan 2004; Brengman
et al. 2005).
One way to think of these applications is that they merge online shopping and social
networking (Tedeschi, 2006). Chevalier & Mayzlin (2006) and Godes & Mayzlin (2004)
studied the effect of word of mouth and revenue on consumer. Watts & Dodds (2007) studies
part of social phenomena by connecting with marketing-related fulfillment from social
network perspective to.
With the advent of E-Commerce, the need for personalized services has been
emphasized. Business researchers have advocated the need for one-to-one marketing
(Resnick et al. 1994). One-to-one marketing attempts to improve the nature of marketing by
using technology to assist businesses in treating each customer individually. To be successful
in an increasingly competitive internet marketplace, researchers have stressed the need for
capturing customer loyalty (Reichheld et al. 1990). Schafer et al. (1999) has confirmed the
examples of recommender systems inside E-commerce and the function of one-to-one match
making, and customer’s royalty.
To implement e-commerce solutions, it is necessary to have supporting information,
and organizational infrastructure and systems. The benefits of e-commerce are not only for
large firms; small and medium sized enterprises can also benefit from e-commerce. In
addition, it can ‘‘level the playing field’’ with big business, provide location and time
independence, and ease communication (Chong, 2000; Iacovou et al. 1995; Longenecker et al.
1997; Purao & Campbell 1998 ).
The capabilities and opportunities afforded by an internet-based electronic
12
marketplace significantly improve the productivity and competitiveness of participating
organizations (Gunasekaran et al. 2002; Wilson & Abel 2002; DeCovny, 1998). E-
commerce-based organizations tend to have higher annual revenues in comparison to other
organizations (Neese, 1999; Lancioni et al. 2003; Gunasekaran et al. 2002).
Previous research has identified four determinants of consumer acceptance with
respect to online shopping, namely consumer characteristics, personal perceived values,
website design and the product itself. Many researchers have insisted on the importance of
product differences in online marketing. Spiller and Lohse (1998) proposed to divide 35
properties of 137 internet retailers by strategies sought by web-based marketing. The online
features are the quality measures of Web system or services provided by the Web system. As
an internet shopping mall provides its major services via a web environment, the IS oriented
view of the internet shopping mall suggests that the drivers for consumer acceptance are
based on the system features such as design, functionality, security, and information quality
(Palmer, 2002 & Ranganathan et al. 2002) and services features, supported by the web
system, such as reliability, responsiveness, and empathy (Pitt et al. 1995).
Van Slyke et al. (2002) point out gender differences in other online shopping
characteristics such as compatibility, complexity, result demonstrability, and relative
advantage. Huff et al. (2000) emphasize nine critical success factors (CFS) for EC firms: First,
add value in terms of convenience, information value, disintermediation, reinter mediation,
price, and choice; second, to focus on a niche market and then expand; third, maintain
flexibility; fourth, segment geographically; Fifth, get the technology right; sixth, manage
critical perceptions; seventh, provide exceptional customer services; eighth, create effective
connectedness; and ninth, understand the Internet culture.
13
Plant (1999) studies the success factors associated with over 40 organizations in the
US and Europe and identifies the following seven CSFs: financial impact, competitive
leadership, brand, service, market, technology, and site metrics. Riggins (1999) presents a
framework that identifies 15 key ways to add value to an organization’s e-commerce strategy.
The extent to which each of these is utilized represents critical success factors. Similarly,
Eight key drivers for EC operational success: system integration, customer orientation of IT,
supply orientation of IT, international operation of IT, customer-related processes, supplier-
related processes, customer e-business readiness, and supplier e-business readiness (Barua,
Konana, Whinston & Yin, 2000).
Chun & Choi(2004) confirmed the importance of the reliability, the economics of
price and cost, customer service and convenience in the Factor Analysis for Online Purchase
Decision Attribute, and Lee(2000)presented convenience, cheap price, etc on the reasons to
purchase goods through the online in the Study on User’s Purchase Pattern.
Kim & Kim(2004) argued the needs for the strategies to lower prices or reduce costs
incurred in the purchase step and to meet the requirements of users in order to attract users to
online purchases, and Ward(2000) explained the factors that influence the choice of the user's
online marketplace in terms of transaction costs and explained the main factors for that by the
minimization of transaction costs.
Monroe (1990) claims that the perception of the product value is formed by the
product quality and price comparison. Thus, in light of the claims of Parasuraman, Zeithaml
& Berry (1994) that perceived quality and perceived price were the antecedents of the
accumulated customer satisfaction. the product value perceived by product quality and
product value will affect customers’ loyalty for a specific store( Parasuraman, Zeithaml &
Berry, 1994).
14
Lynch, Kent & Srinivasan (2001) claimed that the factors affecting the purchase
through the online purchase are Trust, quality and emotion, and as a result of analysis on
impact to purchase intention, the Trust factor influences the most (Tan & Thoen , 2001)
presented that Trust played an important role in performing Loyalty of customer, Immersion
and Purchase Intention, and Trust was found to have the main relationship with Purchase
Intention.
Donny & Cannon (1997) defined the perception for credit and patronizing of the
Trust target, and according to Lewicki & McAllister (1998), high Trust showed the features
of belief, confidence, assurance, sincerity and etc.
Kotler (1997) presented two criteria of consumer characteristics and consumer
reaction. Consumer characteristics include geographic, demographic and psychological
variables, and consumer reaction includes Usage Situation and Usage Brand.
Yoo (2010) explained that the attributes of the Internet shopping mall website had a
major impact on customer satisfaction, and information and system website attributes
influenced customer satisfaction. Shopping mall features were claimed to be web design,
order processing and stability, and marketing attributes of shopping mall to be
communications, merchandising and sales promotion.
Eighmey & McCord (1998) suggested entertainment, information, structure and
design of the sites as the attributes that users think are important. According to Hyon (2007),
what makes web sites distinctive and competitive are information, entertainment, structure,
cognition, interaction, search and connection. Choi (2009), the purchasing motivation of
consumers is derived from the perceived image, shopping mall design, convenience of
shopping, quality of information, security and product price. Yoo (2010) classified the
15
marketing attributes of web sites as communication, commercialization and promotion and
studied the impacts of web site attributes on repurchase.
3.3 Purchase Intentions
Purchase Intention means the anticipated or planned future behavior of individuals,
and it is the probability that beliefs and attitudes can be moved to act (Engel & Blackwell
1982).
Planned Behavior is the main concern of marketing researchers because a lot of
decisions of companies are made from the prediction of consumer behavior. In order to
predict such consumer behaviors, the studies regarding the relationship of attitudes and
behaviors have been made, and in the most studies, attitude changes have been identified as a
predisposing factor of behavioral changes.
Fishbein and Ajzen (1975) proposed the theory of reasoned action and mentioned
that reasoned action had the correlation of behavioral intention and actual behavior. In other
words, the theory of reasoned action means that when humans determine whether to execute
any action or not, what results they would think rationally will be caused by the outcome of
executing behavior, and the more positive consequences the results lead to, the more its
behavior is likely to actually be executed.
Looking at existing research about Purchase Intention, Hoffman & Novak (1996)
argued that Flow should be facilitated in order to visit the website repeatedly and increase
Purchase Intention on the internet. In order words, if you feel the joy during the visit to the
website, you will visit the site repeatedly and it could increase Purchase Intention on the
internet.
16
The factors that affect consumer's purchase intention can be divided by product
perception, shopping experience, customer service, consumer’s risk by purchasing, etc.
(Javenpaa & Todd, 1997). The product recognition in shopping behavior of consumers are
important criteria, on which shopping mall consumers will select, and the most important
factors are Price, Product Quality, Product Variety and etc. And the factor that affects
consumer's purchase intention in the existing shopping is the shopping experience and the
shopping is very important socially and personally for many people, and shopping experience
is also an important element in determining consumers' purchase behavior (Holt, 1995).
Social commerce marketplaces have four defining characteristics: 1) sellers (or
shopkeepers) are individuals instead of firms, 2) sellers create product assortments organized
as personalized online shops, 3) sellers can create hyperlinks between their personalized
shops, and 4) sellers’ incentives are based on being paid commissions on sales made by their
shops (Tedeschi, 2006).
In order to draw users attributes of social commerce marketplaces from the precedent
documentary research, the functions and attributes of SNSes, four type of social commerce,
internet attribute, E-commerce success factors, website & homepage attributes, shopping mall
attributes are summarized in Table 3 below.
17
Table 3. Four Type of Social Commerce, Functions and attributes of SNSes, Internet
Attributes, E-commerce Success Factors, Website & Homepage Attributes, Shopping Mall
Attributes.
Functions & Attributes Reference
Four Type of
Social
Commerce
Group Buying, Offline Connection, Social Link, Social
Web DMC (2011)
SNS
Functions
Identity management, Expert search, Context awareness,
Network awareness, Exchange, Contact management
Alexander & Michael
(2008)
Expert search, Communication, Connection, Content
Sharing, Identity Ko, Hwang & Ji(2010)
Internet
Attributes
Interaction, Internationalization, Communication,
Connection, Expense, Fun, Accord of time Jang(1998)
E-commerce
Success
Factors
Information Value, Disintermediation, Reintermediation,
Price, Maintain flexibility, Segment geographically, Get the
technology right, Manage critical perceptions, provide
Huff et al. (2000)
Financial impact, Competitive leadership, Brand, Service,
Market, Technology, Site metrics Plant(1999)
Website &
Homepage
Attributes
Entertainment, Information, Structure, Design, Interaction,
Perception, Search, Connection Eighmey &
McCord(1998)
Web design , Production , Sales Promotion Madlberger(2004)
Information, Fun, Recognition, Interaction, Searching,
Connection, Perceived Usefulness Hyun(2007)
Ease of use, Product information, Entertainment, Trust,
Customer support, Currency Elliott & Speck(2005)
Entertainment, Information, Homepage Construction Chen & Wells(1999)
Convenience, Interaction, Private Preferences, Interaction Ghosh(1998)
Information, Entertainment, Interaction Kim(2005)
Shopping
Mall
Attributes
Trust, Quality, Emotion Lynch, Kent &
Srinivasan (2001)
Trust, Economy, Customer Service, Convenience Chun & Choi(2004)
Comparison of Product Quality and Product Price Monroe(1990)
Geographical, Population Statistics, Psychological variable,
Pursuit Benefit, Use Conditions, Use Brand Kotler(1997)
Web design, Order Management, Safety Yoo(2010)
Convenience, InformationUsefulness, Security, Payment
System, Communication, Customer Satisfaction Chung & Ko(2007)
Web design Liu&Arnett(1999)
18
4. Social Commerce Model
It is essential to examine the intrinsic functions and related users attributes of Social
commerce marketplaces to draw attributes from it. Upon examination of precedent research
on functions of SNSes and four type of social commerce, internet attributes, E-commerce
success factors, website & homepage attributes, shopping mall attributes, four attributes of
social commerce marketplaces are identified. Figure 1 shows these four attributes of social
commerce marketplaces. As a result we propose a list of basic attributes of social commerce
marketplaces.
Figure 1. Social Commerce Attributes Model
There are not much academic studies related to the new type of online social
commerce which is based on SNS. Also, social commerce is not a new service, and it is the
result of development by adding the original online shopping mall with SNS. Therefore, the
social commmerce's attributes are Internet Attributes, E-commerce success factors, Internet
& Homepage attributes, Shopping Mall attributes based on the social commerce
functions and 4 types of social commerce.
As Four Type of Social Commerce, SNS Functionalities, E-commerce Success
19
Factors and Website Characteristics Shopping Mall Characteristics, 5 attributes of Social
Commerce are derived as shown below. Mapped social commerce attributes shown Table4.
20
Table 4. Mapped Social Commerce Attributes
SocialCommerce
Attributes
Four Type
of Social
Commerce
SNS Functions
Attributes & Factors
Internet
Attributes
E-commerce Success
Factors
Website & Homepage
Attributes
Shopping Mall
Attributes
Economy Group
Buying -
Price
(Huff, et.al.2000)
Expanse
(Jang, 1998)
Information
(Eighmey&Mccord,1998)
Economy of price
(Chun & Choi,2004)
Low price
(Lee, 2004),
Economy of price
(Chun & Choi,
2004)
Necessity Offiline
Connection - -
Segment Geographically
(Huff, et al.2000)
Private preference
(Ghosh,1998)
Geographical,
Use situation
(Kotler 1997)
Reliablity
Group
Buying
Social Link
Social Web
Exchange
(Alexander &
Michael 2008)
Content Sharing(Ko,
et.al 2010)
Interaction
(Jang, 1998)
Brand
(Plant, 1999)
Information
(Eighmey&Mccord,19
98)
Trust
(Elliott&Speck,2005)
Reliability
(Chun &
Choi,2004;
Lynch, et.al 2001)
Interaction Social Link
Social Web
Network awareness
(Alexander &
Michael 2008)
Communication
(Ko, et.al 2010)
Interaction
(Jang, 1998) -
Interaction
(Eighmey&Mccord,19
98) -
Sales
Promotion
Social Link
Social Web - - -
Sales Promotion
(Madlberger,2004) -
21
4.1 Social Commerce Attributes
• Economy
Kim& Kim (2004) argued the needs for the strategies to lower prices or reduce costs
incurred in the purchase step and to meet the requirements of users in order to attract users to
online purchases, and Ward (2000) explained the factors that influence the choice of the
user's online marketplace in terms of transaction costs and explained the main factors for that
by the minimization of transaction costs.
The factor for online purchase decision attributes of Chun & Choi (2004) is
identified to be the economy for the reliability, prices and costs that is important.
Berkowitz & Walton (1980) demonstrated that if clues about the price discount were
provided, it could induce the consumer's favorable response. As one of the main attraction of
Social Commerce, consumers could receive a large discount through the group buying. The
price plays a role in improving consumer’s perception and facilitating the buying behavior
(Kukar-Kinney et al. 2011).
Of Social Commerce Group business model, the form of group buying, when the
minimum purchase quantity is achieved, takes a business model that is applied to half price.
The price perceived by the consumer can change Purchasing Behavior of the consumer and it
is expected to have different behavior from conventional Internet shopping mall. Therefore,
based on the above leading papers and Group Buying Strategies of Social Commerce
business models, the economy attributes of the Social Commerce are derived.
• Necessity
When there are Wants for any goods or services, a consumer will look for it.
Marketing is the work to meet Needs and Wants through the medium of the product. Thus, to
22
understand the Wants of consumers is the starting point to understand consumer behavior.
Belk (1979) said that consumers in the shopping process experience utilitarian shopping
value and hedonic shopping value at the same time. The utilitarian value has been treated as
an important factor to influence purchase intention in an Internet shopping mall related study
(Bloch & Bruce 1984).
The study of Szymanski & Hise (2000) confirmed that the utilitarian value of
Internet shopping mall was the determinant for shopping satisfaction, and according to a
study of Park(2001) the utilitarian value significantly influenced the frequency on a site visit,
which showed to play an important role in purchase intention again.
Kotler (1997) proposed two criteria of consumer characteristics and consumer
reaction, but consumer characteristics included geographical, demographic and psychological
variables, and consumer reaction included usage situation or usage brand.
Social Commerce is strengthening partnership with convenience stores and café
living shops as a specific location (off-line stores) customers purchase utilizing location-
based services (LBS) in each area.
In addition, social networks (SNS) as a link to the offline area (Offline area) because
it can extend existing Internet shopping malls and other big ripple effect can be. Therefore,
the above papers and the leading Social Commerce strategy, business model from the need
for Offline Connection (Necessity) properties were obtained.
• Reliability
The concept of trust is importantly recognized in exchange relationships and forms
the basis of strategic partnerships to improve the quality appearing in the interaction with
trading partners and improve level of cooperation to increase the involvement of relationship
23
between trading partners (Speckman, 1998).
Javenpaa (1999) defined Trust in Internet shopping mall for the first time, and
highlighted the cognitive aspects of Trust and considered Trust to be reasonable selection
process by defining Trust as the intention of the consumer that rely on a seller and leave a
seller in a vulnerable state.
Hoffman & Novak (1999) claimed that the reason for consumers not to purchase
products through online was the lack of Trust between the Internet shopping malls and
consumers. Suh & Han (2003) and Morgan & Hunt (1994) argued that Trust was the most
critical element to understand the successes and failures.
When consumers make purchasing decisions, they often rely on Word-of-Mouth (WOM),
recommendations, observational knowledge (a point of view knowledge) about other
consumers (Dichter, 1966).
Recommendations will have a positive impact on a purchase decision or will not
have effect anymore. The previous study said that when new products are launched,
consumers can generate customer referrals in a variety of situations and spread the products
through word of mouth, and when consumers making purchasing decisions, they often
referred to the opinion of others (Mahajan, Muller & Bass 1995).
Park & Park (2002) presented the study that the interaction between businesses and
consumers got more active, consumer confidence increased more.
Kim & Eune (2011) proposed that SNS acquaintance-based product recommendation
system gave larger confidence and preference than the one selected by the general public did.
Social Commerce can recommend products to acquaintances by e-mail, instant messaging,
social media message exchange and sharing functions and consumers can have confidence
before they view the products.
24
• Interaction
The definition for the interactivity has been proposed by many scholars, but has not
shown nearly uniform opinion. The interactivity of is complex process and is defined as the
degree that two or more communication parties may affect with each other, communication
media and messages, and such impacts occur simultaneously (Liu & Shrum, 2002; Hoffman
& Novak, 1996).
Alba et al. (1997) defined the interactivity as never-ending two-way
communicational characteristics between two parties, buyer and seller, and according to
Berthon, Pitt & Watson (1996) study, Consumers gave more positive assessments and made
more favorable decisions for the sites perceived by high interactivity than for the sites
perceived by lower sites.
Cho & Leckenby (1999), Hwang & McMillan(2002), Wu(1999), Yoo & Stout(2001)
argued that interactivity have a positive impact on receptive attitude toward the website in an
online environment.
Thorbiornsen (2002) claimed that the more active the interaction got, the more the
relationship between brands and customers was shown to be enhanced, as a result of the
analysis on the impact of interactive communication to the marketing effect.
Social Commerce can be shared easily with other people via the SNSs or general
commerce site, provide product information to acquaintances via Email/Messenger and
exchange comments by utilizing bulletin boards. Thus, based on the interactive attributes of
above previous studies and SNS Function Social Commerce Social Link and Social web
strategy, the interactive attributes were derived.
25
• Sales Promotion
Kotler (2001) defined that sales promotion was designed to stimulate faster or
massive purchase for a particular product on a short term basis to a consumer or a
intermediate in order to encourage the sales and purchase of products or services, and defined
sales promotion as all marketing activities to stimulate the purchase of customers or the
efficiency of distributors, except for personal selling, advertising, public relations, etc.
It can be defined as marketing activities providing additional incentive such as online
coupons, sweepstakes offers, discounts, rebates, etc. in the short term in order to induce an
immediate response of customers.
There is also the view of Value Shopping that the price is equal to the value, which
means shopping, looking for discounts and a bargain on sale (Arnold & Reynolds 2003).
Consumers may have playful benefit by obtaining a bargain that increases sensory
involvement (participation) and interest (Babin et al. 1994).
Value Shopping may also have something to do with Selection Optimization defined
by Westbrook and Black (1985) because discounts or bargains can elicit satisfaction from
personal achievement.
Lichtenstein, Netemeyer & Burton (1995) classified as price-oriented promotions
including coupons, sale, etc. lowering the purchase price, and non-price-oriented sales
promotion including sweepstakes, giveaways, etc. Unlike advertising, it refers to encouraging
or stimulating means in the short term to induce immediate action of other consumers.
Social Commerce has come up with strategies that coupons are issued for goods as a
means of promoting the sale targeted for consumers, and based on the above papers and
26
Social Link and Social Web's business model, the attributes for sales promotion were derived.
5. Research Methodology
5.1 Data Collection
An online & offline survey was conducted to collect data. The sample was selected
from among individuals who are using social commerce services in Korea Aerospace
University.
Initially, A pre-test, a pilot test and a main test have been conducted. Through the pre-test this
study refines a measurement instrument made by reviewing the previously available literature.
Based on the results of the pre-test, this study further develops an instrument to measure the
major constructs and then conducted a pilot test. In terms of methodology, this study carries
out a factor analysis through 3 times (a pre-test, a pilot test, and a main test) surveys data and
then finalized the constructs regarding measurement reliability and validity to verify a causal
relationship model.
This study selected 144 usable survey responses out of 160 for 10 days (from March
22 to April 3, 2012) through an online & offline survey. The sample consisted of 57.6% male
and 42.3% female participants ranging from 20 to 49 years old, the majority of which were in
their twenties and thirties (77.7% and 14.5%, respectively). Respondents mainly used
TicketMonster (40.9%), Coupang (34%).
The category mainly used in Social Commerce is food (43.7%), fashion (13.8%),
performance (12.5%), and the purchase number through Social Commerce within the last six
months is 2 times to 41.6% .
The number of access to Social Commerce is as follows: 1) Whenever thinking of
Social Commerce (52%), 2) One or more times per week (20%), 3) Once a month (18%).
27
Recommended approach is as follows: 1) Word of mouth (story) (59%), 2) Instant messaging
(24.3 %).
Product satisfaction is followed in the order by satisfaction (56.9%), average (31.9%),
very satisfied (7.6%), and overall satisfaction comes to 64.5%, so future repurchase of social
commerce and the growth will be bright.
In addition, the availability of the SNS is followed by Facebook (60.4%), Cyworld
(10.4%), Twitter (10.4%) and 86.2% of SNS users uses Social Commerce.
Those who have never purchased through Social Commerce are 16 out of 160 people
to 10%. And in the survey asking non-purchasers why they have not used Social Commerce,
80% of respondents have had insufficient awareness of Social Commerce. However, 14
people were responded to have an intention of purchases. This seems to be absolute to
promote Social Commerce and grow the market size of the future.
Social Commerce is the service of combined form by SNS and Internet shopping, so
it can reduce uncertainty that can occur in the purchase behavior through SNS and psychical
and temporal (time) costs required to obtain information. In this respect, it can be considered
that the respondents with experience in using Social Commerce might think easier to use
Social Commerce and might think positive effects about the intention of using Social
Commerce.
Most of the respondents have used social network services heavily: 55% of the
respondents use at least one of the services for more than one hour per day. Hence, the
respondents seem to be qualified to analyze attributes of social network services. The
demographics of the respondents are shown in Table 5.
28
Items to measure constructs in the model were mainly adopted from prior research.
Some minor wording changes were made for the SNS context. New constructs in the model,
however, had to be constructed.
All items were measured on a 5-point Likert scale, where 1 is disagree strongly and 5
is agree strongly. SPSS18 was used as a statistical package for testing. All items are shown in
Appendix A.
Table 5. Attributes of respondents (n= 144)
Items Number Percentage (%)
Gender Male 83 57.6
Female 61 42.3
Age
Under 20 0 0
21-30 112 77.7
31-40 32 14.5
41-50 11 7.6
Over51 0 0
Education
High school or below 0 0
College 0 0
Undergraduate 35 24.3
Graduate 109 75.6
Occupation
Student 77 53.4
Manager 20 13.8
Specialized job 8 5.5
Service industry 29 20.1
Technical post 3 2.08
Housewife 5 3.43
Etc. 2 1.3
Mainly using Social
commerce
Ticket monster 59 40.9
WemakePrice 9 6.25
Coupang 49 34
NowShop 11 7.6
Groupon 4 2.7
Daum Social Shopping 4 2.7
Etc. 8 5.5
Mainly using
Category
Food 63 43.7
Performance 18 12.5
Beauty 14 9.7
Leisure 8 5.5
Travel 4 2.7
Industrial 9 6.2
Fashion 20 13.8
Etc. 8 5.5
29
Recently 6 Monthly
number of purchase
1 over 57 39.5
2 over 60 41.6
5 over 20 13.8
10 over 7 4.86
Frequency of access
One or more times per day 14 9.72
One or more times per week 29 20
Once a month 26 18
Whenever thinking of Social
Commerce 75 52
Recommend method
Email 4 2.7
Talk 85 59.0
Messenger 35 24.3
general site 15 10.4
Etc. 5 3.4
Product satisfaction
Very Satisfaction 11 7.6
Satisfaction 82 56.9
Normal 46 31.9
dissatisfaction 4 2.7
Very dissatisfaction 1 0.6
SNS use
Facebook 87 60.4
Twitter 15 10.4
Me2day 2 1.3
Cyworld 15 10.4
Etc 5 3.4
No Account 20 13.8
6. Results
Before running an exploratory factor analysis and reliability check, we checked
where the data satisfied the assumptions for factor analysis. The following three checks were
performed (the correlation coefficient among question items, Bartlett’s test of sphericity, and
the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy (MSA)).
Validity is the extent to which a measure diverges from other similar measures.
Testing for validity involves checking whether the items measure the construct in question or
other constructs. With the exception of a strong correlation between some constructs (e.g.,
Economy, Necessity, Reliability, Interaction, Sale Promotion), correlations were moderate,
weak, or nonexistent (Table 5).
30
Reliability is the most common index of the validity of measures. It is used to check
whether the scale items measure the construct in question or other (related) constructs; a
value of .70 or above is deemed acceptable (Fornell & Larcker, 1981). Cronbach’s coefficient
alpha was used to test the inter-item reliability of the scales used in this study. Cronbach’s
alpha assesses how well the items in a set are positively correlated with one another. In
general, reliability of less than .60 is considered poor, reliability in the .70 range is considered
acceptable, and reliability greater than .8 is considered good (Sekaran, 2003). As shown in
Table 6, all of the alpha values were greater than the recommended level and showed good
reliability with Cronbach’s alpha (>.70) in each construct.
Factor analysis was done using the data collected from the first version of the survey.
The cut-off criteria had a factor loading of 0.60. The analysis was done using a stepwise
approach. The question item which had the lowest maximum factor loading was removed. If
the lowest maximum factor loading was less than 0.60, factor analysis was repeated until the
lowest maximum factor loading was greater than 0.60. Three items were finally omitted.
Values of 0.50 and above are recommended for factor analysis (Fornell & Larcker, 1981). In
addition, factor analysis was used to examine construct validity. The Kaiser–Meyer–Olkin
test and Bartlett’s test of sphericity were first used to assess the appropriateness of the
correlation matrices for factor analysis (Hair, Anderson, Tatham, & Lack, 1998).
Thus we can conclude that the data satisfies the assumption for the factor analysis.
The result of Bartlett's test of sphericity in this study shows that Sig (P) = 0.000 < α(=0.05) (χ
2=1887.242, df = 190). The result implies that there is no evidence that the correlation matrix
is an identity matrix. All seven factors showed a number of strong loadings, and all variables
loaded substantially on only one factor. The results of this analysis provided evidence of
construct validity (Table 7).
31
Table 6. Principal component analysis with varimax rotation and reliability check
Component 1 2 3 4 5 Number
of items
Cronbach’s
alpha
Reliability8 .859 .116 .199 .064 -.037
5 .931
Reliability12 .855 -.044 .184 .013 .163
Reliability9 .840 .203 .022 .103 .113
Reliability10 .837 .127 .149 -.069 .099
Reliability11 .796 .118 .118 .025 .351
Reliability7 .776 .330 .221 .126 .085
Economy2 .157 .885 .097 .071 .093
4 .891 Economy1 .077 .881 .108 .037 .108
Economy4 .148 .803 .031 .167 .128
Economy5 .247 .741 .040 .314 .183
Interaction1 .182 .056 .862 .004 .080
4 .865 Interaction2 .242 .115 .838 .036 .046
Interaction3 .083 .021 .805 .048 .157
Interaction6 .138 .074 .762 -.044 .169
Sales
Promotion7 .100 .162 -.065 .871 .127
3 .819 Sales
Promotion11 .098 .291 -.049 .852 .053
Sales
Promotion3 -.043 .012 .132 .803 -.113
Necessity1 .092 .101 .193 .099 .835
3 .795 Necessity4 .196 .089 .272 .053 .793
Necessity2 .202 .288 .007 -.109 .742
Eigen-value 6.880 2.910 2.165 1.801 1.422
% of variance 34.398 14.552 10.823 9.003 7.108
KMO. 839
Note. Numbers in bold shows loading coefficients for items in each construct
The results of examining the relationship between attributes of Social Commerce and
variables of purchase decision are shown in Table7. Overall, the directions between the
variables presented in model and research hypothesis were mostly consistent.
32
Table 7. Correlation matrix
Purchase
Intentions Economy Necessity Reliability Interaction
Sales
Promotion
Purchase
Intentions 1
Economy .571***
1
Necessity .458***
.367***
1
Reliability .602***
.403***
.396***
1
Interaction .258***
.208***
.363***
.370***
1
Sales
Promotion .495
*** .343
*** .090 .109
* .062 1
AVG 3.43 3.88 2.90 2.9 2.8 3.47
S.D .73 .68 .72 .66 .78 .94
***p < 0.01 , **p<0.05 , *p<0.1
Multiple regression analysis was carried out by making 5 attributes of Social
Commerce including Economy, Necessity, Reliability, Interaction and Sales Promotion as
independent variables and making purchase decision of Social Commerce as the dependent
variable. The results conducted are shown in Table 8 conducted.
As a result of analysis, only 4 different attributes including Economy (β = .233, p
<0.01), Necessity (β = .199, p <0.01), Reliability (β = .452, p <0.01), Sales Promotion (β
= .280, p <0.01) on purchase intention for Social Commerce have shown to have a significant
at p<0.01 level, but Interaction has shown not to have a significant impact.
In particular, Sales Promotion has showed the highest level at .280, which was the
most influential to the purchase intention of Social Commerce users. Regression model has
showed 46.960 at F value p=.000, and the explanatory power for Regression Model showed
the Adjusted R2=.616 at F value p=.000 to 61.6%.
33
Table 8. Economy& Necessity& Reliability & Interaction& Sales Promotion Multiple
Regression
Unstandardized Coefficients Standardized
Coefficients T P
β Standard
error beta
(Constant) -.248 .261
-.952 .343
Economy .233 .067 .217 3.507 .001***
Necessity .199 .061 .195 3.254 .001***
Reliability .452 .067 .410 6.705 .000***
Interaction -.030 .055 -.032 -0.552 -.582
Sales
Promotion .280 .043 .360 6.518 .000
***
R2 = .630, Adjusted R
2= .616, F=46.960 (p=.000)
***p < 0.01 , **p<0.05 , *p<0.1
7. Conclusions
7.1 Implications
Through the results of this research, we have identified the attributes of Economy,
Necessity, Reliability, Interaction, Sales Promotion that consumers have thought about Social
Commerce emerging as a new distribution channel, and have studied what impact the
attributes have given to purchase decision.
The results of this study can be summarized as follows.
First, respondents mainly used TicketMonster (40.9%), Coupang (34%). The category mainly
used for Social Commerce was followed by food (43.75%), fashion (13.8%). The purchase
through Social Commerce 1-2 times or more within the last six months was 81%.
Second, the number of access to Social Commerce was followed by whenever
thinking about Social Commerce (52%), one or more times per week (20%), once a month
(18%), and product satisfaction was followed by satisfaction (56.9 %), average (31.9%), very
34
satisfied (7.6%), overall satisfaction (64.5%). In this respect, repurchase decision through
Social Commerce and growth in future will be bright.
Third, those who have never purchased through Social Commerce are 16 out of 160
respondents, showing 10%. And in the survey asking non-purchasers why they have not used
Social Commerce, 80% of respondents have had insufficient awareness of Social Commerce.
However, 14 people were responded to have an intention of purchases. This seems to be
absolute to promote Social Commerce and grow the market size of the future.
Fourth, the attributes affecting purchase decision of Social Commerce among 5
attributes of Social Commerce Economy, Necessity, Reliability, Interaction and Sales
Promotion have been found to be Economy, Necessity, Interaction and Sales Promotion.
The results of this study performed for the purpose of identifying overall effects of
Social Commerce attribute to purchase intention have significance in terms of academic and
application perspectives.
In the academic perspective, Social Commerce concept has been recently formed and
gained interest, so the relevant study is at entry-level.
Therefore, it can be the basis of relevant papers regarding Social Commerce in future.
In addition, there is significance in showing a possibility of configuring the general theory by
generalizing Social Commerce features.
In the practical perspective (application perspective), it provides strategic elements to
the operators of Social Commerce or the merchants to sell goods through Social Commerce.
In other words, according to the results of this study, the operators of Social Commerce and
the intermediary of Social Commerce should identify impacts on the purchase decision by the
attributes of Social Commerce.
35
According to these analyzes, Social Commerce providers will be able to induce more
customers by satisfying purchasing factors of Social Commerce and further prepare
satisfactory information and provide information to effectively manage them by looking at
the user's needs or motives carefully, and it will be helpful to organize the strategies to derive
the best business performance.
Moreover, empirical studies for Social Commerce have been insufficient. Therefore,
through this study, the attributes of Social Commerce only conceptually explained have been
proved, so it will helpful to other follow-up studies.
7.2 Limitations and Future research
This is the paper conducted in order to achieve the performance of management
strategy by deriving the influence of Social Commerce attributes to user’s purchase intention
based on existing literatures. This study, however, had several limitations which must be note.
First, Application form, application motivation and satisfaction level considering the
characteristics of SNS users have not been measured and not been applied to this study.
However, in previous studies, the study regarding application motivation and satisfaction
level of each SNS for each study has not been materialized.
Second, the survey has been targeted at customers having used Social Commerce
located in Seoul and Gyeonggi Province, but sex ratio and age composition ratio of actual
customers using social shopping do not fit, so there are limitations to expand the results
obtained in this study to the data of the customers using nationwide social commerce.
In future research, it is necessary to consider regional expansion for a survey, sex ratio and
age composition ratio of customers who have actually purchased through Social Commerce.
Third, there are limitations in that pilot survey and main survey have been conducted
by targeting at 20’s to 30’s college students. It overlooked each age group may have different
36
motivations. In addition, depending on the type of product used primarily, the attribute that
consumers know may be different, so degree of diversity of these products will need to be
considered in future.
Economy in Social Commerce may have a positive effect on purchase frequency of
consumers for price discounts that Social Commerce companies claim. The marketing that
lures customers with special offer such as half price has been shown to stimulate customers to
open their wallets.
For the continued growth of Social Commerce in future, it is essential to manage the
consumer’s satisfaction so that the action for repetitive repurchase can take place. Thus, it
may be a problem that consumers using Social Commerce for fun and convenience do not
feel satisfaction in real purchase experience.
For the reasons that consumers expecting Social Commerce as a means of excitement
and convenience are not satisfied after the actual experience of use, we will need to make in-
depth study in future on whether to be simply 'unsatisfactory quality of the product or service'
or whether levels of consumer expectations are not high' or whether another factors exist.
As it is a social network-based e-commerce form, the relations that the influence of
SNS or the effect of Word-of-Mouth (WOM) in Social Commerce affects will need to be
studied.
In order for Social Commerce market to continue to grow in the future, the study on
the motivation and impact factors of non-purchased consumers will be needed, despite great
discounts benefit, convenience and interesting elements of Social Commerce.
37
Appendix 1. Questionnaire Items
The following is a summation of the question items used in the study.
All items solicited responses on a five-point Likert scale with 1 = strongly disagree, 2 = disagree, 3 =
neutral, 4 = agree, and 5 = strongly agree.
Economy (Arnold & Reynolds 2003; Caruana & Ewing 2010)
1. You can buy product at a discounted price through social commerce sites.
2. Prices are economical in social commerce sites.
3. Values are higher than prices in social commerce sites.
4. Prices are comparatively lower in social commerce sites than in other sites.
5. In terms of prices, social commerce products are economical.
6. You can save shopping expenses in social commerce sites.
Necessity (Balasubramanian, Raghunathan, & Mahajan 2005; Peterson& Merino 2003)
1. You can purchase what you want in social commerce sites.
2. In social commerce sites, you can purchase products (coupons) suitable for an area that you want.
3. In social commerce sites, you can see products by area.
4. Social commerce provides location-based services (LBS).
5. If you see products in the place of social commerce (home, company and so on), you become
interested in them.
6. In social commerce sites, you can get information on products available in a specific place (home,
company and so on).
7. In social commerce sites, you can purchase products after getting coupons without any problem.
Social commerce seems helpful to your life in purchasing products.
Reliability (Koufaris & Hampton-Sosa, 2004)
1. Social commerce sites are more reliable than other Internet shopping sites.
2. I rely on social commerce information providers.
3. I think purchasing processes through social commerce sites are reliable.
4. I think that products and services I purchase through social commerce sites are reliable.
5. I think I will not make mistakes when I purchase through social commerce sites.
6. In general I reply on social commerce.
7. Social commerce businesses are reliable.
8. I rely on business information provided to me by social commerce businesses.
9. In general, I rely on social commerce businesses.
10. I rely on the product information provided by social commerce I use.
11. I think that the social commerce products I purchase are reliable.
12. I rely on the information provided by social commerce sites.
Interaction (Deuze 2001; Chen & Wells 1999; Ghosh 1998)
1. People can interactively communicate with each other through social commerce.
2. People can smoothly communicate with social commerce businesses.
3. Social commerce promptly responds to customers’ opinions and inquiries.
4. Social commerce actively accepts customers’ proposals and opinions.
5. There are a lot of other users’ questions and answers found in social commerce sites.
38
6. Social commerce is interactive.
Sales Promotion (Kotler, 1997)
1. I purchase social commerce products when they sell at a discounted price or are on sale.
2. I check if social commerce sells products at a discounted price before purchasing.
3. I have experience in purchasing products because of their discount rates even though I have never
thought of buying them.
4. Social commerce has a variety of discount coupon systems.
5. The sales promotion of social commerce gives me values.
6. Social commerce provides a lot of premiums and giveaways.
7. I feel like buying when I see the discounted prices of social commerce.
8. I think that social commerce offers big discounts.
9. Social commerce sells products in a certain period.
10. Social commerce has a variety of products.
11. I feel like buying when I see the discounted prices of social commerce.
12. I think positively about the reduction in price of social commerce.
13. I will connect to social commerce in order to buy required products.
14. I will connect to half-price social commerce in order to buy required products.
15. I will visit social commerce sites to enjoy window-shopping.
Purchase Intentions (Hong & Na, 2008)
1. I will keep using social commerce.
2. I will speak positively about social commerce to people around me. .
3. I will recommend people around me to use social commerce.
4. I am interested in social commerce products.
5. I connect to social commerce sites even though I do not buy anything from them.
6. I am planning to buy products from social commerce if I find them interesting.
39
References
Ahn, Y. Y., Seung, Y. H., Kwak, H. W., Moon, S., & Jeong , H. W. (2007). Analysis of Topological
Characteristics of Huge Online Social Networking Services. Proceedings of the 16th
international conference on the World Wide Web, pp.835.
Alba, J., John Lynch, Barton Weitz, Chris Janiszewski, Richard Lutz, Alan Sawyer , Stacy Wood
(1997). Interactive Home Shopping: Consumer, Retailer, and Manufacturer Incentives to
Participate in Electronic Marketplaces. Journal of Marketing, 61, pp.38-53.
Alexander, R., & Michael, K. (2008). Functions of Social Networking Services. Paper presented
at the COOP08.
Arnold, M. J., & Reynolds, K. E. (2003). Hedonic shopping motivations. Journal of Retailing, 79,
pp.77-95.
Babin, B. J., Darben, W. R., & Griffin, M. (1994). Work and/or fun: Measuring hedonic and
utilitarian shopping value. Journal of Consumer Research, 20 (1), pp.644-656.
Balasubramanian, S., Raghunathan, R., & Mahajan, V. (2005). Consumers In A Multichannel
Environment : Product Utility, Proces Utility, and Channel Chioce. Journal of Interactive
Marketing, 19(2), pp.12-30.
Belk, R. W. (1979). Gift-Giving Behavior. Research in Marketing, 2, ed. Jagdish N. Sheth,
Greenwich, Connecticut: JAI Press, pp.95-126.
Berkowitz, E. N., & Walton, J. R. (1980). Contextual Influences on Consumer Price Responses: An
Experimental Analysis. Journal of Marketing Research, pp.349-350.
Berthon, P., Pitt, L., & Watson, R. T. (1996). The World Wide Web as an Advertising Medium:
Toward as Understanding on Conversion Efficiency. Journal of Advertising Research, 36(1),
pp. 43-54.
Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship.
Journal of Computer-Mediated Communication, 13(1).
40
Braua, A., Konana, P., Whinston, A. B., & Yin, F. (2000). Making e-business pay:eight key drivers
for operational success. IT Pro, pp.2-10.
Brengman, M., Geunens, M., Weijters, B., Smith, S. M., & Swinyard, W. R. (2005). Segmenting
Internet shoppers based on the web-usage-related lifestyle: a cross cultural validation. Journal
of Business Research 58, pp.79-88.
Butler, B. (2001). Membership Size, Communication Activity, and Sustainability: A Resource-Based
Model of Online Social Structures. Information Systems Research, pp. 346-362.
Caruana, A., & Ewing, M. T. (2010). How corporate reputation, quality, and value influence online
loyalty. Journal of Business Research, 63(9), pp. 1103 - 1110.
Chen, Q., & Wells, W. D. (1999). Attitude toward the Site. Journal of Advertising Research, 39,
pp.27-37.
Chevalier, A. J., & Mayzlin, D. (2006). The Effect of Word of Mouth on Sales: Online Book
Reviews. Journal of Marketing Research, 43(3), pp.345-354.
Cho, C. H., & Leckenby, D. (1999). Interactivity as a Measure of Advertising Effectiveness.
proceeding in Annual Conference of the American Academy of Advertising in Albuquerque.
Choi, J. Y. (2009). A study on the trust and satisfaction of the purchasing motivation by internet
shopping mall users - focused on the online specialty malls. Korea Distribution Association,
16.
Chong, S. (2000). Model of Factors on EC Adoption & Diffusion in SMEs. Proceedings of the 1st
We-B Conference,Working for E-Business: Challenges of the New e-Conomy.
Chun, C. S., & Choi, J. S. (2004). A Study on the Factors Affecting Customer`s Repurchase Intention
of Online Travel Products. Korean Academic Society of Hospitality, 13(2), pp.239-255.
Chung, K. H., & Ko, Y. D. (2007). A Study on the Relationship between the Characteristics
Affecting Customer Satisfaction and Customer Loyalty in B2C Online Shopping Internet.
Korea Internet e-Commerce Association, 7(4).
41
DeCovny, S. (1998). Electronic commerce comes to age. Journal of Business Strategy, 19(16).
Deuze, M. (2001). Online journalism : Modelling the first generation of new media on the world wide
web. First Monday, 6(10).
Dichter, E. (1966). How Word-of-Mouth Advertising Works. Harvard Business Review 44 pp.147-
166.
DMC (2011a). Social commerce awareness & use survey. DMC MEDIA.
DMC (2011b). Social commerce Market future & view. DMC MEDIA.
Doney, P. M., & Cannon, J. P. (1997). An Examination of the Nature of Trust in Buyer-Seller
Relationships. Journal of Marketing, 61 (4), pp.35-51.
Eighmey, J., & McCord, L. (1998). Adding Value in the Information Age: Uses and Gratifications of
Sites on the World Wide Web. Journal of Business Research, 41 pp.187-194.
Ellison, N., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook "friends": Exploring the
relationship between college students' use of online social networks and social capital.
Journal of Computer-Mediated Communication, 12 (3), article 1. Retrieved July 30, 2007
from <http://jcmc.indiana.edu/vol2012/issue2004/ellison.html/>.
Engel, J. F., & Blakewell, R. D. (1982). Consumer Behavior. 4th ed., Hinsdale, Ⅲ. : Dryden Press.
Fishbein, M., & Ajzen, I. (1975). Belidf, Attitude, Intention and Behavior : An Introduction to
Theory and Research. Reading, Mass : Addision-Wesley.
Forrester (2007). Retrieved March 27, 2011 from <http://www.forrester.com/rb/research>.
Ghosh, S. (1998). Making business sense of the Internet. Harvard Business Review Harvard Business
Review, pp.126-135.
Godes, D., & Mayzlin, D. (2004). Using Online Conversations to Study Word-of-Mouth
Communication. Marketing Science, 23 (4), pp.545-560.
42
Gunasekaran, A., Marri, H. B., McGaughey, R. E., & Nebhwani, M. D. (2002). E-commerce and its
impact on operations management. International Journal of Production Economics, 75, pp.
185-197.
Haubl, G., & Trifts, V. (2000). Consumer Decision Making in Online Shopping Environments; The
Effects of Interactive Decision Aids. Marketing Science, 9(1), pp.1-20.
Haythornthwaite, C. (2005). Social networks and Internet connectivity effects. Information,
Communication, & Society, 8(2), pp.125-147.
Hoffman, D. L., & Novak, T. P. (1996). Marketing in Hypermedia Computer Mediated Environment:
Conceptual Foundations. Journal of Marketing, 60, pp.50-58.
Holt, D. B. (1995). How consumers consume : A Typology of consumption practices. Journal of
consumer research, 22, pp.1-16.
Hong, B. S., & Na, Y. K. (2008). The Effect of the Perceived Hedonic Value, Usefulness and Ease of
use on Attitude toward using in Internet Shopping Mall and purchase Intention of the Fashion
Merchandise. Journal of the Korean Society of clothing and Textiles, 32(1), pp.147-156.
Hu, T., & Kettinger, W. J. (2008). Why People Continue to Use Social Networking Services:
Developing a Comprehensive Model. International Conference on Information Systems.
Huff, S., Wade, M., Parent, M., Schneberger, S. C., & Newson, P. (2000). Cases in Electronic
Commerce. Irwin/McGraw-Hill, Columbus, OH.
Hyun, M. S. (2007). The Effects of tourism information web site factors on usefulness, web site
attitude and behavior. Sejeong university.
Iacovou, A. L., Benbasat, I., & Dexter, A. (1995). Electronic data interchange and small
organizations: adoption and impact of technology. MIS Quarterly, pp.465-485.
Jarvenpaa, S. L., & Todd, P. A. (1997). Consumer reactions to electronic shopping on the World
Wide Web. Journal of Electronic Commerce, 1(2), pp.59-88.
Javenpaa, L. (1999). Consumer Trust in an Internet Store: A Cross-cultural validation. Journal of
computer-mediated communication, 5(2).
43
Kim, C. H. (2010). Bloter, Retrieved March 27, 2011 from <http://www.bloter.net/archives/31355/>.
Kim, D. H., & Kim, H. J. (2004). The Comparison of Online and Offline Purchases: A Transaction
Cost Perspective. Korea Distribution Association pp.19-45.
Kim, H. S., & Eune, J. H. (2011). Preferences of product recommendation based on SNS friends in
online shopping mall. Korean Society of Basic Design & Art, 12(1), pp.137-145.
Kmobile (2011). Retrieved February 27, 2011 from
<http://www.kmobile.co.kr/k_mnews/news/news_view.asp?tableid=IT&idx=328944/>.
Ko, S. M., Hwang, B. W., & Ji, Y. G. (2010). A Study on Social Network Service and Online Social
Capital：Focusing on a Korean and Chinese Case. Society for e-business Studies, pp.
103~118.
Kotler, P. (1997). Marketing management: Analysis, planning, implementation, and control. Prentice
Hall (Upper Saddle River, NJ).
Koufaris, M., & Hampton-Sosa, W. (2004). The development of initial trust in an online company by
new customers. Information and Management, 41(1), pp.377-397.
Kruglanski, A. W. (1989). Lay epistemics and human knowledge: Cognitive and motivational basis.
New York: Plenum Press.
Kukar-Kinney., Monika., Ridgway, N. M., & Monroe, K. B. (2011). The Role of Price in the
Behavior and Purchase Decisions of Compulsive Buyers. Journal of Retailing, pp.1-9.
Kwon, O., & Wen, Y. (2010). An empirical study of the factors affecting social network service use.
Computers in Human Behavior, 26(2), pp.254-263.
Lancioni, R., Schau, H., & Smith, M. (2003). Internet impacts on supply chain management.
Industrial Marketing Management, 32(3), pp.173-175.
Lee, D. H. (2000). Future of E-commerce for Korea Consumer. Korean Society of consumer studies.
Lee, E. M. (2011). Social Commerce global business view. KISDI, 23(3), pp. 36-44.
44
Lee, H. J. (2008). The evolution of business model of social networking services: A comparative
study of cyworld and facebook. Management of Technology, Pohang university.
Leitner, P., & Grechenig, T. (2007). Next generation shopping : Case study Research on future E-
commerce Models. Procedding of IADIS International conference e-commerce 2007,
pp.312~316.
Lewicki, R. J., & McAllister, D. J. (1998). Confident Expectations and Reasonable Doubts: The
Social Dynamics of Ambivalence in Interpersonal Relationships. Academy of Management
National Meetings.
Li, H., Juo, C., & Russell, M. G. (1999). The impact of perceived channel utilizes, shopping
orientations, and demographics on the consumer’s online buying behavior. Journal of
computer-mediated communication, 5(2), pp. 1-20.
Lichtenstein, D. R., Netemeyer, R. G., & Burton, S. (1995). Assessing the domain specificity of deal
proneness: A field study. Journal of Consumer Research, 22, pp.314-326.
Liu, C., & Arnett, K. (1999). Assessing the Customer Behavioural Intentions on the Web: A
Research Model. Proceedings of the 5th Americas Conference on Information Systems
Association for Information Systems, pp. 307-309.
Liu, Y. (2006). Word of Mouth for Movies: Its Dynamics and Impact on Box Office Revenue.
Journal of Marketing, 70(3), pp. 74-89.
Liu, Y., & Shrum, L. J. (2002). What is Interactivity and is it Always Such a Good Thing?
Implications of Definition, Person, and Situation for the Influence of Interactivity on
Advertising Effectiveness. Journal of Advertising, 31 (4), pp. 53-64.
Lynch, P. D., Kent, R. J., & Srinivasan, S. S. (2001). The global Internet shopper: evidence from
shopping tasks in twelve countries. Journal of advertising Research pp.15-23.
Mackenzie, S. B., Lutz, R. J., & Belch, G. E. (1986). The role of attitude toward the ad as a mediator
of advertising effectiveness: A test of competing explanations. Journal of Marketing
Research, 23, pp.130-143.
45
Madlberger, M. (2004). Strategies and Business Models in Electronic Retailing: Indicators From the
U.S and the UK. New York: ACM Press, pp.296-303.
Mahajan, Vijay, Eitan Muller, & Bass., F. M. (1995). Diffusion of New Products: Empirical
Generalizations and Managerial Uses. Marketing Science, 14(3), pp.78-88.
Monroe (1990). Pricing: Making profitable decisions. McGraw-Hill.
Morgan, R. M., & Hunt, S. D. (1994). The Commitment-Trust Theory of Relationship Marketing.
Journal of Marketing, pp.20-38.
Neese, T. (1999). Small business joining e-commerce bandwagon. Long Island Business News,
46(37).
Nielsen (2010). Global trends in online shopping, Retrieved March 27, 2011 from
<http://hk.nielsen.com/documents/Q12010OnlineShoppingTrendsReport.pdf/>.
O’Murchu, I., Breslin, J. G., & Decker, S. (2004). Online Social and Business Networking
Communities. DERI Technical Report.
Palmer, J. W. (2002). Web site usability design and performance metrics. Information Systems
Research, 13(2), pp.151- 167.
Parasuraman, A., Valarie, A., Zeithmal., & Berry, L. L. (1998). ServQual. A Multiple item Scale For
Measuring Consumer Perception of service Quality. Journal of Retailing.
Parasuraman, A., Zeithaml V. A., & Berry L. L. (1994). Servqual: Alternative scales for measuring
servicec quality? A comparative assessment based on psychometric and diagnostic criteria.
Journal of Retailing, 70(1), pp. 193-199.
Park, C. (2001). A Classification of Online Consumer Group by the Web Navigation Value. Korean
Society of Consumer Studies, 12(1), pp.32-51.
Park, G. S., & Park, J. S. (2002). An Empirical Study on the Influencing Factors of Trust in the
Internet Shopping. Journal of marketing management 7(2), pp.135-163.
46
Park, J. C., & Yoon, B. H. (2002). Factors Affecting on Internet Shopping Mall Members`
Relationship Quality. Asia Pacific Journal of Information Systems, 12(3).
Peter H. Bloch, & Bruce, G. D. (1984). PRODUCT INVOLVEMENT AS LEISURE BEHAVIOR.
Association for Consumer Research, 11, pp.197-202.
Peterson, R. A., & Merino, M. C. (2003). Consumer Information Search Behavior and the Internet.
Psychology & Marketing, 20(2), pp.99-121.
Pitt, L. F., Watson, R. T., & Kavan, C. B. (1995). Service quality: a measure of information systems
effectiveness. MIS Quarterly, 19 (2), pp.173-187.
Plant, R. (1999). eCommerce: Formulation of Strategy, Prentice-Hall. Upper Saddle River.
Purao, S., & Campbell, S. (1998). Critical concerns for small business electronic commerce: some
reflections based on interviews of small business owners. Proceedings of the AIS Conference.
Ranganathan, C., & Ganapathy, S. (2002). Key dimensions of business-to-consumer Web sites.
Information and Management, 38, pp.457-465.
Reichheld, F. R., & Sasser, J. W. (1990). Zero Defections: Quality Comes to Services. Harvard
Business School Review, 5, pp.105-111.
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., & Riedl, J. (1994). GroupLens: An Open
Architecture for Collaborative Filtering of Netnews. In Proceedings of CSCW '94.
Riggins, F. J. (1999). A framework for identifying web-based electronic commerce opportunities.
Journal of Organizational Computing and Electronic Commerce, pp.297-310.
Rohm, A. J., & Swaminathan, V. (2004). A typology of online shoppers based on shopping motives.
Journal of Business Research, 57, pp.748-757.
Schafer, J. B., Konstan, J., & Riedl, J. (1999). Recommender Systems in E-Commerce. In
Proceedings of ACM E-Commerce 1999 conference.
Silverton, E. (2010). blog.9thsphere . Retrieved March 27, 2011 from
<http://blog.9thsphere.com/blog/social-commerce/>.
47
Socialcommercetoday (2011). Retrieved February 27, 2011 from
<http://socialcommercetoday.com/clever-facebook-sponsored-stories-from-actions-to-ads-
video-examples/>.
Speckmam, R. E. (1998). Strategic supplier selection : understanding long-term buyer relationships.
pp.75-81.
Spiller, P., & Lohse, G. L. (1998). A classification of Internet retail stores. International Journal of
Electronic Commerce, 22.
Strabase (2011). America social commerce business. STRABASE.
Suh., & Han. (2003). The Impact of Consumer Trust and Perception of Security control on the
Acceptance of Electronic commerce. International Journal of Electronic Commerce, 7(3),
pp.135-162.
Szymanski, D., & Hise, R. (2000). e-Satisfaction: An Initial Examination. In Journal of Retailing,
3(76), pp. 309-322.
Tan, Y. H., & Thoen, W. (2001). Formal Aspects of a Generic Model of Trust for Electronic
Commerce. Erasmus University Research Institute for Decision and Information Systems
Tedeschi, B. (2006). Like Shopping? Social Networking? Try Social Shopping. New York Times.
Thorbjornsen, H., Supphellen, M., Nysveen, H., & Pedersen, P. E. (2002). Building Brand
Relationships Online: A Comparison of Two Interactive Applications. Journal of Interactive
Marketing, 16(3), pp.17-34.
Van Slyke, C., Comunale, C., & Belanger, F. (2002). Gender differences in perceptions of Web-
based shopping. Communications of the ACM, 45(7), pp.82-86.
Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender,
social influence, and their role in technology acceptance and usage behavior. MIS Quarterly,
24(1), pp.115-139.
Ward, M. R. (2000). Will Online Shopping Compete more with Traditional Retailing of catalog
Shopping?”, Wore Paper. Univ. of Illinois, Urban_Champaign.
48
Watts, D. J., & Dodds, P. S. (2007). Influentials, Networks, and Public Opinion Formation. Journal
of Consumer Research, 34, pp.441-458.
Westbrook, R. A., & Black, W. C. (1985). A Motivation-Based Shopper Typology. Journal of
Retailing, 61(1), pp.78-103.
Wilson, S., & Abel, I. (2002). So You Want to Get Involved in E-commerce. Industrial Marketing
Management, 31, pp. 85-94.
Wu, g. (1999). Perceived Interactivity and Attitude toward Website. Proceeding in Annual
Conference of the American of Advertising in Albuerque.
Yoo, C. Y., & Stout, P. A. (2001). Factors Affecting Users' Interativity with the Web Site and the
Consquences of Users' Interactivity. American Academy of Advertising, pp.53-61.
Yoo, S. K. (2010). The effect of the website attributes on repurchase intention in online shopping
mall -Focusing on online market in china. Business Aministration, Konkuk universiry.
You, J. W. (2011). Social commerce, customer business. LG Economic research.
Zeithaml, V. A. (1998). Consumer Perceptions of Price, Quality, and Value: A Means-End Model and
Synthesis of Evidence. The Journal of Marketing, 52, pp.2-22.
Zimmerman, B. J. (1994). Dimensions of academic self-regulation: A conceptual framework for
education. In D. H. Schunk & B. J. Zimmerman (Eds.). Self-regulation of learning and
performance: Issues and educational applications, pp. 3-21.
