Factors Influencing B2C E-Commerce Adoption in Organizations

linerdeliciousΑσφάλεια

5 Νοε 2013 (πριν από 3 χρόνια και 10 μήνες)

145 εμφανίσεις


IS 7890: IS Research Seminar


Spring 2006

1

Factors Influencing

B2C E
-
Commerce
Adoption

in Organizations

By: Thanaporn Sundaravej

College of Business Administration

University of Missouri at Saint Louis

Saint Louis, MO

63121
-
4400

1.

Introduction

A study on information systems (IS) innovation and its ad
option has a long history
o
n the IS
literature. Due to a rapid growth of the Internet and World Wide Web, many researchers

and
business
entrepreneurs have recently paid greater

attention to the adoption of the innovative
electronic market channel.

Unfortun
ately,
a review of prior research does not find
an exhaustive
view of factors in the electronic commerce (e
-
commerce) adoption in organizations that conduct
online transactions with customers.

Even though s
everal categories of factors were identified and
h
ave the potential to influence the business
-
to
-
customer (B2C) e
-
commerce adoption in
organizations
, qualitative and quantitative research
to strengthen knowledge i
n this domain has
been spare
.
This study attempts to gather information
underlying

factors in

the B2C

e
-
commerce
adoption in organizations on current literature in multiple disc
iplines, develop a research
framework
based on analyzed information and a studied theory, and produce useful guidelines
for sub
sequent researchers who are interested in
the

investigation of
IS adoption and

e
-
commerce
domains and
for
pr
actitioners who are considering

implement
ing

an innovative online transaction

channel

to their customers
.

1.1.

Theories of
Information Technology Adoption

and Innovations


The first comprehensive v
iew of diffusion of innovations has been proposed by Everett M.
Rogers (Raho et al., 1987).
Several studies in innovations
a
re exa
mined and categorized into

IS 7890: IS Research Seminar


Spring 2006

2

diverse

disciplines such as anthropology, social sciences, education, industrial, etc (Rogers,
1962
).
Rogers (1962) defined an innovation as an idea perceived as new by the individual.
Viewing an innovation as any new idea
assign
s a wide scope to this definition. To restrict the
definition of an innovation for the current study, an innovation is perc
eiv
ed as the B2C e
-
commerce
that

an organization
plan
s

to make an

effective use

of
.

Diffusion, according to Rogers
(1962), is defined as the process by which an innovation spreads. As such, the diffusion process
is the spread of a new idea from its source of
invention or creation to its ultimate users or
adopters.
In this context
,
the ultimate adopters are
defined
as organizations that currently do not
have but plan to adopt the B2C e
-
commerce to their organizations.
No matter
how

organizations

will accept or
reject

the technology of B2C e
-
commerce
, the diffusion process or the spread of a
new idea from sources to ultimate users
has existed.

Within

the IS literature, t
he diffusion of innovations theory has been embraced into IS
research in 1970s to determine th
e adoption of a diffused information technology innovation.

Several subsequent researchers put their efforts to develop and modify different models and
theories of information technology acceptance such as Theory of Reasoned Action (TRA) by
Fishbein and Aj
zen (1975), Technology Acceptance Model (TAM) by Davis (1989), Theory of
Planned Behavior (TPB) by Ajzen (1991), Model of PC Utilization (MPCU) by Thompson et al.
(1991), Motivational Model (MM) by Davis et al. (1992), Social Cognitive Theory in IS (SCT)
b
y Compeau and Higgins (1995), Combined TAM and TPB (C
-
TAM
-
TPB) by Taylor and Todd
(1995), Technology Acceptance Model 2 (TAM2) by Venkatesh and Davis (2000), and Unified
Theory of Acceptance and Use of Technology Model (UTAUT) by Venkatesh et al. (2003).
T
hese models or theories together provide overview picture of determinants to the adopted IS
usage and acceptance.


IS 7890: IS Research Seminar


Spring 2006

3

1.2.

Information Technology Adoption and Innovations in Organizations

The

number of
research studies o
n
IT

innovations

in organizations
, as well as

the attention
paid to these investigations,

has
been

increased in
the
last few decades.
D
iffusion of IT
innovation

theories
have been

applied to various technologies, for instance, administrative
Electronic Data Processing or EDP (Moch and Morse, 1977), c
omputer applications (Perry and
Danziger, 1980), modern

software practices (Zmud, 1982 and

1984),
Asynchronous Transfer
Mode

or ATM (Hannan and McDowell, 1984), new information technology (Huff and Munro,
1985), intelligent telephone (Manross and Rice, 198
6), database manag
eme
nt system (Ball et al.,
1988
), data administration (Hsieh, 1987), electron
ic scanners (Levin et al.
, 1987), expert system
(Leonard
-
Barton and Deschamps, 1988), software engineering technology (Bayer and Melone,
1989), spreadsheet softw
are (Brancheau and Wetherbe, 1990), general purpose individual
computing (Burkhardt and Brass, 1990), Material Requirements Planning or MRP (Cooper and
Zmud, 1990), database design tools and techniques (Nilakanta and Scamell, 1990), IS services
(Lind and Z
mud, 1991), personal work station (Moore and Benbasat, 1991),
Computer
-
Aided
Software E
ngineering

or CASE (Ramiller, 1991), business computing (Attewell, 1992),
information center (Full
er and Swanson, 1992a and

1992b), IT outsourcing (Loh and
Venkatraman,
1992), electronic scanners (Zmud and Apple, 1992). The list of these selected
empiri
cal research in IS innovations wa
s summarized by Swanson (1994).
Swanson (1994)
claimed

that IS innovation
s and their

diffu
sion at organizational level until that year had

been
relatively little studied by researchers.

However
,
recent IS literature
s show

that
a variety of IS innovations has been studied by
many researchers after
the study by Swanson (1994)
. Several

examples
consist of

Computer
-
Aided Software E
ngineering

or C
ASE (Orlikowski, 1993), Executive Information System or EIS

IS 7890: IS Research Seminar


Spring 2006

4

(Watson and Frolick, 1993), personal computer (Thompson and Higgins, 1994; Venkatesh and
Brown, 2001), Electronic Data Interchange or EDI (Iacovou et al., 1995; Wang and Seidmann,
1995), expert sy
stem (Gill, 1996), electronic mail (Gefen and Straub, 1997), electronic cash
(Szmigin and Bourne, 1999), group support systems (Dennis et al., 2001; Dennis and Garfield,
2003),
online banking (Bradley and Stewart, 2003),
Internet (Lyytinen and Rose, 2003;
Oh et al.,
2003; Forman, 2005; Hovav, 2005; Lymperopoulos and Chaniotakis, 2005), corporate portal
(Benbya et al., 2004), electronic brainstorming technology (Dennis and Reinicke, 2004),
Electronic Patient Record or EPR (Leonard, 2004), wireless technology

(Fang et al., 2005),
Information and Communication Technologies or ICT (Lapierre and Denier, 2005), Real
-
Time
Business Reporting Technology or RBRT (Li and Pinsker, 2005), and electronic p
ayment (He et
al., 2006). This incomplete

list of instances remarka
b
ly implies how
the research in IS
innovations

have

gain
ed

attention from researchers over the last five decades.

In co
nsidering

the study of aforementioned information technologies before and after the
study by Swanson (1994)
,
we can see that
the
research

trend

in IS innovation
s

recently
moves
from standalone applications to

electronic, Web
-
based, or wireless

network

technologies.

Thanks
to the
global,

rapid diffusion

of the Internet

since 1990s (Wolcott et al., 2001)
, many
organizations take
advantage
of
it
to
gain

or sustain competitive

profitability

over their
competitors

(GoldBerg and Sifonis, 1998)
.


1.3.

Electronic Commerce

and Its Types

In the broadest sense
, e
-
commerce refers to all online transactions. E
-
commerce is a

kind of
innovative techno
logies tha
t takes advantage of

the Internet growth
to allow organizations to
conduct business with improved efficiencies and productivity (Sharma and Gupta, 2003)
.
Additionally, e
-
commerce can enhance company image, enable access to new customers, and

IS 7890: IS Research Seminar


Spring 2006

5

generate new b
usiness opportunities (Chan, 2003).
Even with the

excessive optimism of e
-
commerce

in 1990s

and collapsed dot
-
com enterprises in 2001, e
-
commerce

continues to grow
today. E
-
commerce is differentiated into three types: business
-
to
-
business (B2B), business
-
t
o
-
customer (B2C), and customer
-
to
-
customer (C2C) e
-
commerce. This paper
discusses
the first
two types of e
-
commerce due to the
ir

richness of
literature
s
.

The
B2B e
-
commerce occurs when companies conduct an online transaction with other
businesses. The B2B

transactions are complex and require high security needs.

The B2B e
-
commerce is frequently utilized for automating workflows or supply
-
chain processes
, lowering
costs, and improving productivity

(Timmers, 1999).
In contrast, the B2C e
-
commerce applies to
any business or organization that sells its products or services to con
sumers ove
r the Internet for
the consumer
s


own use.
More specifically, B2C e
-
commerce includes the activity in which
consumers get in
formation and purchase products or
services using I
nternet technology (Pavlou
& Fygenson, 2006). As a result,
the definition of the B2C e
-
commerce could range from static
product catalogs on a Website to dynamic interaction between consumers and Web vendors.

One business may conduct both type
s

of e
-
commer
ce. For instance, Walmart uses electronic
data interchange (EDI) to
electronically
exchange business documents such as purchase orders or
invoices

with
its
suppliers
, while

Walmart

opens an alternative, online
channel to sell products to
its
customers.

As
more and more companies
and customers
get connected to the Internet, e
-
commerce is becoming increasingly important as an easy mechanism for companies

and
individuals

to buy, sell, and trade information, products, or services.

1.4.

Business
-
to
-
Customer Electroni
c Commerce Adoption in Organization Level

The adoption of e
-
commerce has been extensively studied in the IS literature. In an early age
of the e
-
commerce adoption, researchers put their concern
s

on the study of B2B e
-
commerce.

IS 7890: IS Research Seminar


Spring 2006

6

EDI was claimed as a key tech
nology in 1980s and 1990s (Swanson, 1994). Several evidences
can be found from the following articles. Hansen (1989) provided an overview of control
architectures and concerns associated with EDI. Ferguson et al. (1990) outlined the foundations
of EDI and
presented the survey result of the EDI use by U.S. firms in 1988. Iacovou et al.
(1995) identified critical factors in adopting and integrating EDI for small businesses.
Mukhopadhyay et al. (1995) examined the business value of EDI usage at the assembly ce
nters
of Chrysler Corporation. Wang and Seidmann (1995) studied positive and negative effects of
EDI on the trading partners and evaluated policy options for buyers. Massetti and Zmud (1996)
measured the EDI usage in seven organizations. Kaefer and Bendoly

(2000) developed a model
to identify the EDI cost effectiveness.

In the last decade, recent researc
hers have started paying more

attention to

the study of the
B2C e
-
commerce. Due to the increasing growth of estimated sales generated from the B2C e
-
commerc
e channel (U.S. Census Bureau, 2005), businesses are heavily investing in information
technology (IT) infr
astructures to conduct digital

transactions and to capture more market
segments, even though the effect of a high IT investment on the businesses’ per
formance has not
been proved (
Bharadwaj
, 2000). Non
-
profit organizations also use this innovative channel to
enhance their services to their c
lients
. Evidences to support the current trend of B2C e
-
commerce
study can be witnessed from severa
l articles stud
ied in the

following sections
.

Unfortunately, there is no comprehensive view of factors in the B2C e
-
commerce adoption in
organizations provided on the current IS literature.

The purpose of this study is to answer the
followin
g questions: (1) what factors

influencing the

adopt
ion of

the B2C e
-
commerce in an
organization appear on current literature
s
; and (2
) which factors have been studied

or still lack
attention

and need more exploration

from researchers. In order to solve the addressed problems,

IS 7890: IS Research Seminar


Spring 2006

7

this stu
dy attempts to gather, study, and analyze significant factors in
fluencing

the adoption of
the B2C e
-
commerce in the organizational level. An integrated framework is developed based on
prior research on
the B2C e
-
commerce adoption. The current

study can ben
efit subsequent
researchers when conducting experiments or case studies to confirm or reject the adoption
factors in order to obtain complemented and validated determinants of the B2C e
-
commerce

adoption

in organizations
. Additionally, the study is useful
for practitioners who are considering
a

novel, global, and digital business channel to gain awareness of the present e
-
commerce
phenomenon.

1.5.

Scope of the Study: Structurational Model of Technology

Organizations are complex social systems. Hence, organizati
on and management t
heorists
have developed
theo
ries
to explain phenomenon in organizations and to understand such
complicated systems.
Orlikowski (1992) develops

a theoretical model, called the Structurational
Model of Technology, to examine the interactio
n between technology and organizations. The
model

comprises the
three
main components: human agents, technology, and institutional
properties of organizations.
T
wo premises of the Structurational Model of Technology
,

which are
duality of techno
logy and int
erpretive

flexibility of

technology
, are elaborated
. The duality of
technology refers to the recursive notion of technology, which means that technology is crea
ted
and changed by human action,

and

in the meantime

it is also used by humans to accomplish
som
e action
s. The interpretive

flexibility

of technology

is a corollary of the first premise, which
refers to the interaction of technology and organization or a function of the different actors and
socio
-
historical contexts.
Based on these two promises, f
our

main concepts of the model are
classified

as follows
: (1) technology is the product of human action; (2) technology is the
medium of human action; (3) institutional conditions influence humans in their interaction with

IS 7890: IS Research Seminar


Spring 2006

8

technology; and (4) interaction with

technology influences the institutional properties of an
organization.

Figure 1 represents the relationship

among these concept
s, including their
definitions in Table 1.
Summarily, the three main components of the Structurational Model of
Technology, whic
h are human agents, technology, and institutional properties of organizations,

are not independent, but
cor
related to each other.

The scope of this study is bounded by the

Structurational Model of Technology
so as
to provide a comprehensive view of f
actors

in
fluencing the

B2
C e
-
commerce adoption in o
rganizations
.



Institutional Properties



d




c







Technology



a




b



Human Agents


Figure 1: Structurational Model of Technology


Arrow

Type of Influence

Nature of Influence

a

Technology as a Product of
Human Action

Technology is an outcome of such human
actions as design, development,
appropriation, and modification

b

Technology as a Medium of
Human Agents

Technology facilitates and constraints
human actions through the provision of
interpretive schemes, facilities, and norms

c

Institutional Conditions
of
Interaction with Technology

Institutional Properties influence humans in
their interaction with technology, for
example, intentions, professional norms,
state of the art in materials and knowledge,
design standards, and available resources
(time, money,

skills)

d

Institutional Consequences of
Interaction with Technology

Interaction with Technology influences the
institutional properties of an organization,

IS 7890: IS Research Seminar


Spring 2006

9

through reinforcing or transforming
structures of signification, domination, and
legitimation

Ta
ble 1: Type and Definition of Influence in Structurational Model of Technology


2.

Research Methodology

The research starts from gathering information from literatures in
IS and other

disciplines

that relate to the area of
the current
study
. Then, a research

framework is proposed based on the
findings in prior studies and the
adopted

theory. Factors i
nfluencing
the
B2
C e
-
commerce
adoption have been analyzed. Based on these analyzed factors, the framework

has been revised
until it explicitly explain
s the
facto
rs that drive the adoption of the B2C e
-
commerce in
organizations. Finally, a discussion of the
findings and contributions from

this study is provided

at the end of this
paper
.

2.1.

Research

Collection

The research collection within

this study comes from both

IS
and
business
journals such as
MIS

Quarterly,
Communications of AIS, Communications of ACM,
Electronic Markets,

Journal
of Marketing Management,

Information & Management,

Journal of Global Information
Management,

and
Journal of Small Business Management
.

Articles relating to the area of this
study have been searched and carefully reviewed to extract main factors influencing the B2C
adoption in organizations. Those studied factors are analyzed based on the scope of the

Structurational Model of Technology.

A new framework emerges from data gathered from prior
literature
s

and the applied model.

2.2.

Proposed Research Framework

To apply the theoretical model to the B2C e
-
commerce adoption in organizations, several
factors
influencing

the B2C e
-
commerce adoption

in

organizations, appearing on existing
literatures,

have been
determined

as the properties of the model elements. Figure 2 demonstrates

IS 7890: IS Research Seminar


Spring 2006

10

the Structurational Model of B2C E
-
Commerce Technology. Properties of each element in the
model are shown in Table 2.




Business Properties



d




c





B2C E
-
Commerce Technology



a




b



Decision Makers /


Consumers


Figure 2: Structurational Model of B2C E
-
Commerce Technology











IS 7890: IS Research Seminar


Spring 2006

11

Arrow

Type of Influence

Nature of Influence

Author

Publication

a

B2C E
-
Commerce
Technology as a
Product of Decision
Makers and
Consumer
s

Decision Makers
:

CEO’s Innovativeness

Chatterjee et al. (2002)

Al
-
Qirim (2005)

MIS Quarterly

Electronic Markets

Age, Education, and
Cosmopolitanism

Ching and Ellis (2004)

J. of Marketing Mgnt.

Managerial
Perceptions on
Productivity and

Strategic
Decision Aids

Grandon and Pearson (2004a)

Grandon and Pearson (2004b)

Information & Mgnt.

Communications of AIS

Consumers
:

Knowledge,
Familiarity
, and
Skills

Pavlou and Fygenson (2006)

MIS Quarterly

Trust

Gefen et al. (2003)

Pavlou and Fygenson (200
6)

MIS Quarterly

MIS Quarterly

Perceived Usefulness

Pavlou and Fygenson (2006)

MIS Quarterly

Perceived Ease of Use

Pavlou and Fygenson (2006)

MIS Quarterly

Time and Monetary
Resources

Pavlou and Fygenson (2006)

MIS Quarterly

b

B2C E
-
Commerce
Tech
nology as a
Medium of Decision
Makers and
Consumers

Download Delay

Pavlou and Fygenson (2006)

MIS Quarterly

Web Navigability

Pavlou and Fygenson (2006)

MIS Quarterly

Information Protection

Pavlou and Fygenson (2006)

MIS Quarterly

c

Business Conditio
ns of
Interaction with B2C
E
-
Commerce
Technology

External Properties:

Competition or Industry
Pressure

Ching and Ellis (2004)

Grandon and Pearson (2004b)

Al
-
Qirim (2005)

Looi (2005)

J. of Marketing Mgnt.

Communications of AIS

Electronic Markets

Communicati
ons of AIS

Government Support

Seyal et al. (2004)

Electronic Markets

Pressure from Customers

Ching and Ellis (2004)

J. of Marketing Mgnt.

Internal Properties:

Van Beveren and Thomson (2002)

J. of Small Business Mgnt.


IS 7890: IS Research Seminar


Spring 2006

12

Firm Size

MacGregor and Vrazalic (2005)

Al
-
Qirim (2005)

H
ong and Zhu (2006)

J. of Global Information Mgnt.

Electronic Markets

Information & Mgnt.

Industry Type

Chatterjee et al. (2002)

Hong and Zhu (2006)

MIS Quarterly

Information & Mgnt.

Web Experience

Chatterjee et al. (2002)

M
IS Quarterly

Organizational Age

Chatterjee et al. (2002)

MIS Quarterly

Organizational Culture

Chatterjee et al. (2002)

Seyal et al. (2004)

MIS Quarterly

Electronic Markets

Organizational Readiness

Chatterjee et al. (2002)

Grandon and Pearson (2004
b)

Hong and Zhu (2006)

MIS Quarterly

Communications of AIS

Information & Mgnt.

d

Business
Consequences of
Interaction with B2C
E
-
Commerce
Technology

Technology Integration

Shih et al. (2005)

Hong and Zhu (2006)

Communications of the ACM

Information & Mgnt
.

Compatibility

Ching and Ellis (2004)

Grandon and Pearson (2004b)

J. of Marketing
Mgnt.

Communications of AIS

Table 2: B2C Factors Based on Structurational Model of B2C E
-
Commerce Technology



IS 7890: IS Research Seminar


Spring 2006

13

According to the Structurational Model of Technology, thre
e

components
, which are
institutional

properties, human agents, and technology,

are equally crucial. When applied to

the
Structurational Model of B2C E
-
Commerce Te
chnology, all adoption factors

which are
properties of each component are critical
. Without o
ne of them, the B2C e
-
commerce adoption
rate is expected to be lower or the adoption may be prohibited. This study attempts to implement
a new completed paradigm of the B2C e
-
commerce adoption in IS research for subsequent
researchers. The study also attem
pts to benefit IS practitioners in learning which
areas they
should be

concern
ed about

before making a decision to launch an innovative business channel on
the Internet. Omitting one of these factors may cause a failure in the online business.

Each
compone
nt of the proposed model is explained as follows.

Arrow a: B2C E
-
Commerce Technology as a Product of Decision Makers and
Consumers

Orlikowski (1992) defined
human agents

as one
component

in her Structurational Model of
Technology. Technology is viewed as a
n outcome of human actions as design, development,
appropriation, and modification. Based on existing studies, decision makers and consumers
appear to be the human main factors of the B2C e
-
commerce adoption in organization. Even
though decision makers and

consumers are not technology designers or developers, we cannot
deny that they significantly influence the design, development, appropriation, and modification
of
the
technology in organizations.
Decision makers are defined here as a group of people or an

individual employed in the organization and making the decision to adopt or reject an
innovation.
Decision makers have powers to direct the organization

and use organizational
resources

in order
to serve consumers’ needs.
Customers in B2C transactions ref
er to existing or
prospective clients who purchase or plan to purchase products or services for personal, family, or

IS 7890: IS Research Seminar


Spring 2006

14

household purposes from a business seller or an organization.
As a result, decision makers and
consumers
are

accounted of human agents in t
he Structurational Model of B2C E
-
Commerce
Technology. Their actions are believed to have a great impact on the B2C e
-
commerce
technology adoption in an organization. Therefore, in the proposed model, B2C e
-
commerce
technology
is

viewed as a product of dec
ision makers and consumers. Several factors of decision
makers and consumers influencing the B2C e
-
commerce adoption in organizations are found on
existing studies. Examples of decision makers’ factors are CEO’s innovativeness, age, education,
cosmopolitan
ism, and managerial perceptions on productivity and strategic decision aids.
Examples of consumers’ factors are their knowledge, familiarity, skill, trust, perceived
usefulness, perceived ease of use, and time and monetary resources.

Decision Maker Factors

1.

Decision Makers' Attitude

In this context, the decision makers’ attitude refers to a feeling or emotion of managers
toward an introduction of new idea, method, or device to organizations. Al
-
Qirim (2005)
summarized a list of prior studies suggesting that
the CEO’s innovativeness, attitude towards
adoption, and knowledge are necessary factors influencing the extent of e
-
commerce adoption
into organizations. The results of the empirical study support the view that the greater the
manager’s (CEO) innovativene
ss, the more e
-
commerce technologies will be adopted.

Chatterjee et al. (2002) used the term top management championship to define managerial
beliefs about e
-
commerce initiatives in firms and participation in those initiatives. The definition
could be cou
nted on as an aspect of CEO’s attitude toward an adoption of B2C e
-
commerce. The
results of quantitative research by Chatterjee et al. (2005) prove that top management

IS 7890: IS Research Seminar


Spring 2006

15

championship positively influences extent of organizational assimilation of Web technolo
gies in
e
-
commerce strategies and activities.

2.

Age
, Education, and Cosmopolitanism

Ching and Ellis (2004) argued that several studies have found e
-
commerce adoption to be
correlated with the decision maker’s age, level of education, and degree of cosmopolit
anism.
Generally, research found that adopting decision makers tend to be young, educated, and
cosmopolitan. The study of Ching and Ellis (2004) to determine factors driving e
-
commerce
adoption was conducted at Hong Kong small and medium enterprises (SMEs)
. The findings
confirmed the similar results in prior studies.

3.

Managerial Perceptions on Productivity and Strategic Decision Aids

Managerial productivity and strategic decision aids are defined in the article of Grandon and
Pearson (2004a) as important fac
tors in e
-
commerce adoption in organizations. Managerial
productivity refers to managers’ perception that e
-
commerce provides better access to
information, helps in the management of time, improves communication among managers, etc.
The strategic decision
aids is defined as managers’ perceptions that e
-
commerce supports
strategic decisions. Grandon and Pearson (2004a) validated the managerial productivity and
strategic decision aids constructs in their study to determine that the perceptions of strategic
va
lue of e
-
commerce were associated with the decision to adopt e
-
commerce by managers or
owners of SMEs. This finding is consistent with the results of prior literatures that they studied.
Grandon and Pearson (2004b) also conducted a different study to deter
mine perceptions to adopt
e
-
commerce of managers or owners of SMEs in Chile. The findings confirm that managerial
productivity and strategic decision aids were found to be a good discriminator between e
-

IS 7890: IS Research Seminar


Spring 2006

16

commerce adopters and non
-
adopters. It implies that a
dopters perceive that e
-
commerce helps
their decision
-
making.

Consumer Factors

1.

Knowledge,

Familiarity
,

and Skills

Pavlou and Fygenson (2006) employed the Theory of Planned Behavior (TPB) and offered
numerous variables to explain and predict the process of
e
-
commerce adoption by consumers.
The empirical experiment in their study proves that consumers’ skills can be counted as
indicators influencing the e
-
commerce adoption. Consumer skills are defined as the knowledge
and expertise that a consumer has to unde
rtake a behavior. It is, therefore, a potential predictor of
whether a certain behavior can be accomplished. Applied to e
-
commerce, consumer skills refer
to the consumer’s knowledge and ability to purchase online products or services.

2.

Trust

Trust is one’s
expectation, assured reliance, dependence, or belief in another party. Gefen et
al. (2003) studied trust and the Technology Acceptance Model (TAM) in online shopping. The
results of the study show that consumer trust is an important element to online comme
rce,
especially in an interaction with an e
-
vendor. Trust results in an explanation of the consumer’s
intended behavior. Trust in the empirical study of Gefen et al. (2003) was proved to be a crucial
component to retrieve information and to purchase online

products or services by customers.
Pavlou and Fygenson (2006) also adopted trust into their study of the B2C e
-
commerce adoption
to predict consumer behaviors. The results of the study confirm that trust predicts B2C e
-
commerce adoption by customers.

3.

Perc
eived Usefulness


IS 7890: IS Research Seminar


Spring 2006

17

In addition to TPB, Pavlou and Fygenson (2006) applied the Technology Acceptance Model
(TAM) to determine factors of e
-
commerce adoption by consumers. Perceived usefulness is the
extent to which a person believes that using a system will i
mprove his performance. In the study,
perceived usefulness is shown to positively influence customers’ attitude toward getting product
information and product purchasing from a Web vendor.

4.

Perceived Ease of Use

Perceived ease of use is another TAM determin
ant used in the study by Pavlou and Fygenson
(2006). It is defined as the extent to which a person believes that using the system will be
effortless. Similarly to perceived usefulness, perceived ease of getting information and product
purchasing is shown t
o positively influence attitude toward getting product information and
product purchasing from a Web vendor.

5.

Time and Monetary Resources

Consumers’ time resources refer to the time needed to browse for production information,
while monetary resources are
identified as financial prerequisites to purchase products or
services from a Web vendor (Pavlou and Fygenson, 2006). Pavlou and Fygenson (2006)
employed these two constructs in their empirical experiment. The findings from the study
indicate that these re
sources are indicators to the intention and behavior to get information and to
purchase goods online by consumers.

Arrow b: B2C E
-
Commerce Technology as a Medium of Decision Makers and
Consumers

Besides an outcome of human actions
in the Orlikowski (1992)
Structurational Mode
l of
Technology, t
echnology is viewed as a medium of human agents that facilitates and constraints
human actions through the provision of interpretive schemes, facilities, and norms. In the

IS 7890: IS Research Seminar


Spring 2006

18

Structurational Model of B2C E
-
Commerce T
echno
logy, B2C e
-
commerce technology refers to
a computer programming system, application, or technology that creates a transaction on the
Internet. It can be

perceived as
a medium of
consumers that
could facilitate or constraint

their
purchasing

actions throug
h the provision of interpretive schemes, facilities, and norms.
Therefore,
properties of the technology influence in the B2C e
-
commerce adoption must either
facilitate or constraint the consumer’s purchasing actions.
Download delay, Web navigability,
and i
nformation protection are found on existing studies as the factors influencing an
organization to adopt the B2C e
-
commerce. Such factors can
be seen to
either
assist
or
impede
consumers’ purchasing
, depending on the design, development, appropriation, and
modification
of the B2C e
-
commerce technology in the organization.

B2C E
-
Commerce Technology Factors

1.

Download Delay

As mentioned earlier, Pavlou and Fygenson (2006) employed TPB to explain and to predict
the process of e
-
commerce adoption by consumers. Dow
nload delay is defined as one
technological characteristic to predict e
-
commerce adoption in organizations on their study. It
refers to the amount of time it takes for a Website to display a requested page from a Web server.
Based on previous research, dow
nload delay is expected to negatively impact attitude toward
getting online information. Pavlou and Fygenson (2006) claimed that download delay is a key e
-
commerce barrier. Thus, organizations planning to adopt e
-
commerce as a transaction channel
cannot av
oid the impact of download delay to their customers’ attitude. The findings of their
empirical study also support this argument.

2.

Website Navigability


IS 7890: IS Research Seminar


Spring 2006

19

Pavlou and Fygenson (2006) also defined Website navigability as a significant factor
influencing controlla
bility over getting product information from a Web vendor. Navigability in
the study by Pavlou and Fygenson (2006) refers to the natural sequencing of Web pages, well
-
organized layout, and consistency of navigation protocols, enabling consumers to find the

right
products and to compare among alternatives completely under the consumer’s control. Similar to
download delay, Website navigability is another critical factor that organizations must pay
attention in adopting e
-
commerce because it can either facilit
ate or impede the consumers’ online
purchase.

3.

Information Protection

Information security and privacy receive more attention in recent literature. Information
protection refers to an ability of Web technologies to fulfill security requirements of personal

information from unauthorized use or disclosure (Pavlou and Fygenson, 2006). Pavlou and
Fygenson (2006) proposed that when consumers feel comfortable with the way a Web vendor
protects their personal information, they are willing to purchase products or s
ervice form that
vendor. The findings of their study support this argument.

Arrow c: Business Conditions of Interaction with B2C E
-
Commerce Technology

Institutional
properties
are an
other

component of the Orlikowski’s (1992) Structurational
Model of Techno
logy. These
properties
influence human

agent
s in their interaction
s

with
technology. Examples of
the institutional conditions of interaction with technology
are
intentions, professional norms, state of the art in materials and knowledge, design standards,
and
available resources such as time, money, and skills. The current study applies this Orlikowski’s
(1992) influence into business conditions of interaction with B2C e
-
commerce technology.
Existing studies have extensively discussed this influence in seve
ral properties. These properties

IS 7890: IS Research Seminar


Spring 2006

20

can be classified into two main groups: external and internal components. External properties of
business conditions of interaction with B2C e
-
commerce
refer to social context, surroundings
outside the organization, or exte
rnal conditions that affect the B2C adoption in an organization.
Such properties in current studies are competition or industry pressure, government support, and
pressure from customers. On the other hand, internal business properties refer to organization
al
characteristics, structures, or arrangements that affect the B2C adoption in an organization.
Internal properties
found in existing studies
are firm size, industry type, Web experience, and
organizational age, culture, and readiness.

External Business P
roperty Factors

1.

Competition

and Industry Pressure

Based on the prior work of Davis (1989),
Grandon and Pearson

(2004b) defined the
definition of external pressure to an organization as direct or indirect pressure exerted by
competitors, social referents, o
ther firms, the government, and the industry to adopt an
innovation in an organization. By this

description, competition, industry pressure
(
Al
-
Qirim,
2005), competitive pressure
(Looi, 2005)
, and competitive intensity (Ching and Ellis
, 2004)
,
defined by d
ifferent researchers, are counted as the environment factor driving an organization to
adopt the B2C e
-
commerce. From the empirical study by
Grandon and Pearson

(2004b) on the e
-
commerce adoption in Chile SMEs, external pressure is found as a significant f
actor influencing
the e
-
commerce adoption.

Moreover, Al
-
Qirim (2005) summarized that most prior research found the high intensity of
competition as a significant factor to drive an e
-
commerce adoption. Partially consistent with
those prior studies, Al
-
Qiri
m’s (2005) empirical study represents mixed results of competition as

IS 7890: IS Research Seminar


Spring 2006

21

a factor of an e
-
commerce adoption in New Zealand SMEs. Competition is found significant
only in the case of extended adopters, neither starters nor innovators.

In contrast, the findings

from Ching and Ellis’ (2004) case studies identified the opposite
result from
Grandon and Pearson

(2004b) and Al
-
Qirum (2005). Ching and Ellis (2004) observed
no relationship between the e
-
commerce adoption and the intense competition within industries
or

inter
-
firm rivalry. Based on these different findings, more investigation in this factor is
crucially needed.

2.

Government Support

Unlike
Grandon and Pearson

(2004b), Seyal et al. (2004) differentiated government support
as a separated factor from the c
ompe
tition

and industry pressure. Their study proves that the
impact of governmental policies and initiatives is shown to have stimulation to the e
-
commerce
adoption in Pakistan SMEs. The greater government incentives are perceived by an organization,
the high
er is the likelihood of an organization to adopt e
-
commerce. Further studies that explain
the government support as an e
-
commerce driven factor in general contexts other than in
Pakistan are encouraged.

3.

Pressure from Customers

The pressure from customers s
eems to be neglected by most prior researchers. Not many
studies concern pressures from customers as a factor to adopt an e
-
commerce into a business.
Pressures from customers are found significant in Ching and Ellis’ (2004) qualitative research in
the inve
stigation of factors driving e
-
commerce adoption in Hong Kong SMEs. In their study,
existing customers appear to motivate the switch to the Internet for conducting business in
organizations. However, Ching and Ellis (2004) do not specify types of pressure
from customers

IS 7890: IS Research Seminar


Spring 2006

22

in further details. The consumer factors studied by Pavlou and Fygenson (2006) may explain the
pressure from customers defined by Ching and Ellis (2004).

Internal Business Property Factor

1.

Firm Siz
e

Van Beveren and Thomson (
2002
) conducted a
survey of manufacturers in Australia to
investigate if firm size could be a possible factor in determining whether businesses got involved
in e
-
commerce adoption. The study reveals that smaller firms are less likely to adopt e
-
commerce than larger firms. T
his outcome could be traced to a lack of the human resources
needed to manage Web
-
related tasks of small firms. However, there are few sample sizes in
some firm size categories and no case studies or empirical evidence to support the argument.

In contrast
,
MacGregor and Vrazalic

(2005) presented the opposite result from Beveren and
Thomson (
2002
). The findings from their study show that Swedish and Australian small
businesses, especially old small businesses, tend to implement e
-
commerce due to the
afforda
bility. Additionally, the findings from the study of Al
-
Qirim (2005) represent mixed
results, based on types of adopters. For starters, firm size appears insignificant in the e
-
commerce adoption in New Zealand SMEs. However, firm size plays a major role on

the
adoption of e
-
commerce technologies for innovators and extended innovators.

Hong and Zhu (2006) presented a different aspect of firm size as a control variable instead of
an independent variable as Al
-
Qirim (2005). They developed a framework based on
an earlier
theoretical model of technology adoption called

technology
-
organization
-
environment or TOE
framework to study the adoption of technology innovation proposed by Tornatzky and Fleisher
(1990). Three core aspects of a firm that influence it to adop
t an IT innovation are defined as
technological, organizational, and environmental contexts. Firm size is perceived as one factor in

IS 7890: IS Research Seminar


Spring 2006

23

the organizational context and believed to have some effects on the IT adoption. Hong and Zhu
(2006), however, do not apply

firm size (by total number of employees) as a predictor but control
variable. In their study, there is no explanation on what e
-
commerce type they intend to study.
Assumptions on the e
-
commerce type can be perceived from some defined factors used in the
s
tudy such as the EDI use and partner usage which are considered as factors of the B2B e
-
commerce and these are beyond the scope of the current study. Most importantly, the findings
from Hong and Zhu’ (2006) empirical study indicate that firm size is found
to be negatively
related to the e
-
commerce adoption. This can be interpreted to mean that both small and large
firms adopt e
-
commerce into their business. Nevertheless, it should be kept in mind that the
scope of Hong and Zhu’ (2006) study may cover both t
he B2B and/or B2C e
-
commerce. Further
investigation should be strictly to the effect of firm size on the adoption of the B2C e
-
commerce.

2.

Industry type

Industry type is used in empirical studies by Chatterjee et al. (2002) and Hong and Zhu
(2006) for e
-
comm
erce adoption in organizations as another control variable. The results of both
studies suggest that the differences among industries influence the e
-
commerce migration,
especially for firms in service industry, including marketing, sales, order processing
, delivery,
customer support services, and recruiting (Chatterjee et al., 2002).

3.

Web Experience

Web experience is identified by Chatterjee et al. (2002) as an extent of experience in using
the Web technology. It is used as a control variable in the experi
ment and Chatterjee et al. (2002)
concluded that the assimilation of Web technologies to e
-
commerce activities is influenced by
cumulative organizational learning and experience. Firms that have gained Web adoption for a

IS 7890: IS Research Seminar


Spring 2006

24

prolonged period of time have a gre
at likelihood of achieving a high level of maturity in e
-
commerce technology.

4.

Organizational Age

Organizational age is defined by Chatterjee et al. (2002) as another control variable in the
experiment. The results of the experiment demonstrate that organiz
ational age has slight
influence on Web assimilation. It was explained by Chatterjee et al. (2002) that older firms have
embedded structures of signification, legitimization, and domination. Thus, they are likely to
favor the structural inertia and have a
difficulty to adopt a new business structure.

5.

Organizational Culture

As mentioned earlier, Seyal et al. (2004) investigated factors predicting the e
-
commerce
adoption among SMEs in Pakistan. These factors are distinguished into

technological,
organization
al, and environmental types, similar to the categories proposed by Hong and Zhu
(2006). Seyal et al. (2004) claimed that organizational culture was one of the organizational
factors influencing the e
-
commerce adoption in Pakistan SMEs. Organizational cultu
re was
described as a coherent set of beliefs with a set of shared core values. Several prior studies were
summarized by Seyal et al. (2004) to presume that organization culture affected the e
-
commerce
adoption in Pakistan SMEs. The results of their empiri
cal study prove that organizational culture
is a significant factor in determining the e
-
commerce adoption. Again, an application of this
factor to different contexts should be undertaken.

Chatterjee et al. (2002) viewed the organizational culture in the a
spect of coordination within
an organization. It is believed that firms must shape consensus around applications or projects
that will focus Web deployments on e
-
commerce strategies and activities through the use of a
variety of coordination mechanisms. Th
e results of the study also prove such an assumption.


IS 7890: IS Research Seminar


Spring 2006

25

6.

Organizational Readiness

Organizational readiness was defined by Iacovou et al. (1995) and adapted to the e
-
commerce study of Grandon and Pearson (2004b) as availability of the financial and
technolog
ical resources to adopt e
-
commerce. Grandon and Pearson (2004b) summarized
different aspects of organizational readiness found in previous studies, for example,
organizational compatibility, technical compatibility, cost, etc. Their empirical study indicat
ed
that organizational readiness emerged as the best discriminator between organizational adopters
and non
-
adopters of e
-
commerce. This proves that technological and financial resources engage
in the adoption of this IT innovation.

In earlier years, Chatt
erjee et al. (2002) defined strategic investment rationale as value
propositions that guide the identification of promising organizational opportunities and
justification of resource commitments toward the implementation of e
-
commerce projects. The
results

of the study show that a well
-
developed explicit strategic investment rationale positively
influences extent of organizational assimilation of Web technologies in e
-
commerce strategies
and activities.

Additionally, Web spending was defined as a technology

factor driving e
-
commerce adoption
in the article by Hong and Zhu (2006). Web spending refers to the portion of financial resources
devoted to Web
-
based initiatives, including hardware, software, IT services, consulting, and
employee training. Findings fr
om the study confirm that Web spending is one of the factors
influencing e
-
commerce adoption. However, Web spending, defined by Hong and Zhu (2006)
should be considered as organizational readiness which is one element of organizational factors
driving e
-
co
mmerce adoption rather than technological factor, because Web spending can be

IS 7890: IS Research Seminar


Spring 2006

26

considered of financial and technological resources of an organization, determining e
-
commerce
adoption into an organization.

Arrow d: Business Consequences of Interaction with B
2C E
-
Commerce Technology

Finally, Orlikowski (1992) suggested institutional consequences of interaction with
technology in her Structurational Model of Technology. This interaction with technology
influences the institutional properties of an organization
through reinforcing or transforming
structures of signification, do
mination, and legitimation. The current

study applies this concept
as business consequences of interaction with B2C e
-
commerce. That means, the interaction with
B2C e
-
commerce influences th
e business properties of an organization through strengthening or
renovating structures of signification, domination, and legitimation. Examples of such
consequences are t
echnology integration and compa
tibility.

Summarily, based on existing studies and Orl
ikowski’s (1992) Structurational Model of
Technology, main
influence
s of the B2C e
-
commerce adoption can be distinguished into four
groups: business properties, decision makers, consumers, and B2C e
-
commerce tech
nology.
Business properties,
decision makers
, and technology

are perceived as the letter “B” or business
in B2C transactions. In contrast, consumers are perceived as the letter “C” or customer in B2C
transactions.
The interactions occur among four groups of influences as depicted in Figure 2.

B2C E
-
Commerce

T
echnology

Factors

1.

Technology Integration

Technology integration is defined in the Hong and Zhu (2006) article as the extent to which
various technologies and applications are represented on the Web platform. The study proves
that the more integra
ted these existing applications are with the Internet, the more capacity the
organization has to conduct its business over the Internet.


IS 7890: IS Research Seminar


Spring 2006

27

Shih et al. (2005) argued that transaction facilitators such as credit card or debit card payment
conducted electronic
ally for remote purchasing is a key determinant of e
-
commerce activities. In
some countries, the credit card usage is not widely available, resulting in less positive association
with the adoption of e
-
commerce technologies.

2.

Compatibility

Ching and Ellis
(
2004
) studied prior research and assumed that technology compatibility was
a propensity to adopt a technology innovation. This propensity is argued to reinforce the
innovation if the technology is compatible with the existing values, needs, and experience
s of the
potential adopters. The results of their study are found consistent with the results of prior studies,
which reveal that innovators were likely to adopt e
-
commerce that is compatible with their
existing business values and practices. This could su
pport the assumption that compatibility can
strongly affect the adoption of e
-
commerce in organizations.

Grandon and Pearson

(2004b) also summarized prior research on compatibility as a factor
determining e
-
commerce adoption. Compatibility defined in their

study is similar to Ching and
Ellis’ (
2004
) definition. It refers to consistency of e
-
commerce with the existing technology
infrastructure, culture, values, and preferred work practices of the firm. The results of the study
confirm that compatibility of t
he firm with e
-
commerce is a strong factor on e
-
commerce
adoption in Chile SMEs.

3.

Discussion

There is no comprehensive view of the
factors influencing the
B2C e
-
commerce adoption in
organizations. Some studies concentrate on a
single or
few particular facto
rs
.

Gefen et al. (2003)
studied trust as a main factor of online consumer’s intended behavior.
Pa
vlou and Fygensen
(2006) paid

their attention to the factors of consumers and
technology. Even though

these studies

IS 7890: IS Research Seminar


Spring 2006

28

provide

useful

quantitative research
to pro
ve th
eir assumptions, a complete analysis

on the
factors influencing the B2C e
-
commerce adoption in organizations

could produce
more valuable
outcomes from many separated studies
.

In many occasions
,
several

studies concentrate on a specific t
ype of organi
zations, especially
SMEs,

in particular countries and do not
explain the applicability

to organizations elsewhere.

For
instance,
Van Beveren and Thomson (2002) conducted a survey in Australia.
Ching and Ellis
(2004) conducted a study at Hong Kong SMEs.

Gra
ndon and Pearson (2004b) conducted a study
at Chile SMEs.

Seyal et al. (2004) studied the impact of government support
and organizational
culture
at Pakistan SMEs.
Al
-
Qirim (2005) presented a study at New Zealand SMEs.

It is
skeptical that the findings fro
m these studies are applicable to the B2C e
-
commerce adoption in
any organization.

Additionally, some studies offer conflict results.
Ching and Ellis

(2004) identified an
opposite result from Grandon and Pearson (2004b) and Al
-
Qirim
(2005) in terms of

comp
etition
and industry pressure

factors
.
MacGregor and Vrazalic (2005) presented the opposite result
concerning the firm size from Beveren and Thomson (2002)

and Al
-
Qirim (2005)
.
Hong and Zhu
(2006) presented a different aspect of firm size from Al
-
Qirim (20
05).
Hence, a research
should

be conducted to prove the validity of those result
s.

Lastly
,
there is no specification
of the type of e
-
commerce on most studies
. Some research
er
s
discuss either B2B or B2C e
-
commerce or

both

of them.
Hong and Zhu’ (2006) stu
dy includes
EDI use and partner usage as indicators for the e
-
commerce adoption

in organizations
.
As such,
i
t might be assumed that their study cover
s both the B2B and B2C
e
-
commerce.

As mentioned
earlier
, the B2B e
-
commerce is not in the scope of this stu
dy.

B2B factors, as a result, are not
counted as parts of the current analysis.


IS 7890: IS Research Seminar


Spring 2006

29

4.

Conclusions

Based on a founded theory and analysis on current works, this

study
shows that
the
factors
driving the B2C e
-
commerce adoption in organizations

can be viewed in
sev
eral
categories
:
decision makers,
consumers, technology, external business properties,
and internal business
properties
.

Each factor comprises

different properties. Some of these properties have been
theoretically or empirically proved as influences on the

B2C e
-
commerce adoption in
organizations. However, some properties need further experiment and investigation. In the
future, these

categories

may need to
be
redefine
d

and

examine
d

in further details
,

eventually

to
establish

a comprehensive understanding

a
nd validity
of factors influencing the B2C e
-
commerce adoption in organizations.

5.

Implications to Researchers and Practitioners

The current research proposes a new framework studying the adoption of B2C e
-
commerce
in the organizational level. The framework

introduces a comprehensive list of factors influencing
such adoption. The findings from the current study are encouraged to be further investigated so
as to confirm the previous results or to solve some contradicted outcomes. The current study
should be e
xtended into a qualitative or quantitative research to prove assumptions of each
component on the proposed framework and overall factors influencing the B2C e
-
commerce
adoption in organizations. The result of the future research is believed to offer a sign
ificant
progress in the IS discipline, especially in the area of IT adoption and its innovation and e
-
commerce.

Based on the findings from the current study, practitioners learn that several factors
influencing the B2C e
-
commerce adoption in organizations
can be seen in four different
components: decision makers, consumers, business properties, and technology itself. It is

IS 7890: IS Research Seminar


Spring 2006

30

believed that each of these factors plays an important role in the B2C e
-
commerce adoption in
organizations. Therefore, practitioners sh
ould pay their attention to every component if they
consider adopting the B2C e
-
commerce technology into their business.


IS 7890: IS Research Seminar


Spring 2006

31

Reference


Al
-
Qirim, Nabeel. “An Empirical Investigation of an E
-
Commerce Adoption


Capability Model
in Small Businesses in New Zeal
and,”
Electronic Markets
, 15 (2005): 418
-
437.


Ajzen, Icek. “The Theory of Planned Behavior,”
Organizational Behavior and Human Decision
Processes
, 50 (1991): 179
-
211.


Attewell, Paul. “Technology Diffusion and Organizational Learning: The Case of Business

Computing,”
A Journal of the Institute of Management Sciences
, 3 (1992): 1
-
19.


Ball, Leslie D., Dambolena Ismael G., Hennessey, Hubert D. “Identifying Early Adopters of
Large Software Systems,”
Data Base
, 19 (1988): 21
-
27.


Bayer, J., Melone N. “Adoption

of Software Engineering Innovations in Organizations,”
Software Engineering Institute, Carnegie Mellon University, Pittsburgh, PA, April 1989.


Benbya, Hind, Passiante, Giuseppina, Aissa, Nassim B. “Corporate Portal: A Tool for
Knowledge Management Synchr
onization,”
Internaltional Journal of Information
Management
, 24 (2004): 201
-
221.


Bharadwaj, Anandhi. “A Resource
-
Based Perspective on IT Capability and Firm Performance,”
MIS Quarterly
, 24 (2000): 169
-
190.


Bradley, Laura, Stewart, Kate. “The Diffusion o
f Online Banking,”
Journal of Marketing
Management
, 19 (2003): 1087
-
1109.


Brancheau, James C., Wetherbe, James C. “The Adoption of Spreadsheet Software: Testing
Innovation Diffusion Theory in the Context of End
-
User Computing,”
Information
Systems Researc
h
, 1 (1990): 115
-
143.


Burkhardt, Marlene E., Brass, Daniel J. “Changing Patterns or Patterns of Change: The Effects
of a Change in Technology on Social Network Structure and Power,”
Administrative
Science Quarterly
, 35 (1990): 104
-
127.


Chan, Pak Yuen P.
“E
-
Commerce Adoption in Small Firms: a Study of Online Share Trading,”
Managing E
-
Commerce and Mobile Computing Technologies
, PA: IRM Press, 2003.


Chatterjee, Debabroto, Grewal, Rajdeep, Sambamurthy V. “Shaping Up for E
-
Commerce:
Institutional Enablers of

the Organizational Assimilation of Web Technology,”
MIS
Quarterly
, 26 (2002): 65
-
89.


Ching
, Ha Lau
, Ellis, P
aul
. “Marketing in Cyberspace: What Factors Drive E
-
Commerce
Adoption?,”
Journal of Marketing Management
, 20 (2004): 409
-
429.



IS 7890: IS Research Seminar


Spring 2006

32

Compeau, Deborah R.
, Higgins, Christopher A. “Computer Self
-
Efficacy: Development of a
Measure and Initial Test,”
MIS Quarterly
, 19 (1995): 189
-
211.


Cooper, Randolph B., Zmud, Robert W. “Information Technology Implementation Research: A
Technological Diffusion Approach,”
Ma
nagement Science
, 36 (1990): 123
-
139.


Davis, Fred D. “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of
Information Technology,”
MIS Quarterly
, 13 (1989): 319
-
340.


Davis, Fred D., Bagozzi, R. P., Warshaw, P. R., “Extrinsic and Intrinsic

Motivation to Use
Computers in the Workplace,”
Journal of Applied Social Psychology
, 22 (1992): 1111
-
1132.


Dennis, Alan R., Garfield, Monica J. “The Adoption and Use of GSS in Project Teams: Toward
More Participative Processes and Outcomes,”
MIS
Quarterl
y
,
27

(2003): 289
-
323.


Dennis, Alan R., Reinicke, Bryan A. “Beta
versus

VHS and the Acceptance of Electronic
Brainstorming Technology,”
MIS Quarterly
, 28 (2004): 1
-
20.


Dennis, Alan R., Wixom, Barbara H., Vandenberg, Robert J. “Understanding Fit and
Appro
priation Effects in Group Support Systems via Meta
-
Analysis,”
MIS
Quarterly
, 25
(2001): 167
-
193.


Fang, Xiaowen, Chan, Susy, Brzezinski, Jacek, Xu, Shuang. “Moderating Effects of Task Type
on Wireless Technology Acceptance,”
Journal of Management Informati
on Systems
, 22
(2005): 123
-
157.


Ferguson, Darnel M., Hill, Ned C., Hansen, James V. “Electronic Data Interchange: Foundations
and Survey Evidence on Current Use,”
Journal of Information Systems
, 4 (1990): 81
-
91.


Fishbein, Martin, Ajzen, Icek.
Belief, Att
itude, Intention and Behavior: An Introduction to
Theory and Research
, MA: Addision
-
Wesley, 1975.


Forman, Chris. “The Corporate Digital Divide: Determinants of Internet Adoption,”
Management Science
, 51 (2005): 641
-
654.


Fuller, Mary

K., Swanson, E. B. “T
he Diffusion of Information Centers: Patterns of Innovation
Adoption by Professional Subunits,”
Proceedings of ACM SIGCPR Conference
,
Cincinnati, OH, April 5
-
7, 1992a, 370
-
387.


Fuller, Mary

K., Swanson E. B. “Information Centers as Organizational Innovati
on: Exploring
the Correlates of Implementation Success,”
Journal of Management Information Systems
,
9 (1992b): 47
-
67.


Gefen, David, Straub, Detmar W. “Gender Difference in the Perception and Use of E
-
Mail: An
Extension to the Technology Acceptance Model,”

MIS Quarterly
, 21 (1997):
389
-
400.


IS 7890: IS Research Seminar


Spring 2006

33


Gefe
n, David, Karahanna, Elena,
Straub, Detmar W. “Trust and TAM in Online Shopping: An
Integrated Model,”
MIS Quarterly
, 27 (2003), 51
-
90.


Gill, T.G. “Expert Systems Usage: Task Change and Intrinsic Motivation,”
MIS Q
uarterly
, 20
(1996): 301
-
329.


Goldberg, Beverly, Sifonis, John G. “Focusing Your E
-
Commerce Vision,”
Management
Review
, 87 (1998): 48
-
51.


Gr
andon, Elizabeth E.,
Pearson, J. Michael. “Electronic Commerce Adoption: An Empirical
Study of Small and Medium US

Businesses,”
Information & Management
, 42 (2004a):
197
-
216.


Grandon, Elizabeth E.,
Pearson, J. Michael. “E
-
Commerce Adoption: Perceptions of Managers/
Owners of Small and Medium Sized Firms in Chile,”
Communications of AIS
, 2004
(2004
b
): 81
-
102.


Hansen,

James V. “Control and Audit of Electronic Data Interchange,”
MIS
Quarterly
,
13

(1989): 403
-
413.


Hannan, Timothy H., McDowell, John M. “The Determinants of Technology Adoption: the Case
of the Banking Firm,”
RAND Journal of Economics
, 15 (1984): 328
-
335.


He, Qile, Duan, Yanqing, Fu, Zetian, Li, Daoliang. “An Innovation Adoption Study of Online E
-
Payment in Chinese Companies,”
Journal of Electronic Commerce in Organizations
, 4
(2006): 48
-
69.


Hong, Weiyin,
Zhu, Kevin. “Migrating to Internet
-
Based E
-
Commerc
e: Factors Affecting E
-
Commerce Adoption and Migration at the Firm Level,”
Information & Management
, 43
(2006): 204
-
221.


Hovav, Anat. “Global Diffusion of the Internet V


The Changing Dynamic of the Internet: Early
and Late Adoptors of the IPv6 Standard,

Communications of the AIS
, 2005 (2005): 242
-
262.


Hsieh, Shu
-
Chu. “An Integrated Model of the Adoption of Technical and Administrative
Innovations for Information Management,”
Information Systems Working Paper #2
-
88
,
Anderson Graduate School of Managemen
t, University of California, Los Angeles, July
1987.


Huff, Sid L., Munro, Malcolm C. “Information Technology Assessment and Adoption: A Field
Study,”
MIS Quarterly
, 9 (1985): 327
-
340.



IS 7890: IS Research Seminar


Spring 2006

34

Iacovou, Charalambos L., Benbasat, Izak, Dexter, Albert S. “Electronic

Data Interchange and
Small Organizations: Adoption and Impact of Technology,”
MIS Quarterly
, 19 (1995):
465
-
485.


Kaefer, Frederick, Bendoly, Elliot, “The Adoption of Electronic Data Interchange: A Model and
Practical Tool for Managers,”
Decision Support
Systems
, 30 (2000): 23
-
33.


Lapierre, Jozee, Denier, Arnaud. “ICT Adoption and Moderating Effects of Institutional Factors
on Salesperson’s Communication Effectiveness: A Contingency Study in High
-
Tech
Industries,”
Technovation
, 25 (2005): 909
-
927.


Leonar
d, Kevin. “The Role of Patients in Designing Health Information Systems: The Case of
Applying Simulation Techniques to Design an Electronic Patient Record (ERP)
Interface,”
Management Science
, 7 (2004): 275
-
284.


Leonard
-
Barton, Dorothy, Deschamps, Isabell
e. “Managerial Influence in Implementation of
New Technologies,”
Management Science
, 34 (1988): 1252
-
1265.


Levin, Sharon G., Levin Stanford L., Meisel, John B. “A Dynamic Analysis of the Adoption of a
New Technology: The Case of Optical Scanners,”
The Rev
iew of Economics and
Statistics
, 51 (1987): 12
-
17.


Li, Shaomin, Pinsker, Robert. “Modeling RBRT Adoption and Its Effects on Cost of Capital,”
International Journal of Accounting Information Systems
,” 6 (2005): 196
-
215.


Lind, Mary R., Zmud, Robert W. “The

Influence of a Convergence in Understanding between
Technology Providers and Users on Information Technology Innovativeness,”
Organization Science
, 2 (1991): 195
-
217.


Loh, Lawrence, Venkatraman, N. “Diffusion of Information Technology Outsourcing: Influe
nce
Sources and the Kodak Effect,”
Information Systems Research
, 3 (1992): 334
-
358.


Looi, Hong C. “E
-
Commerce Adoption in Brunei Darussalam: A Quantitative Analysis of
Factors Influencing Its Adoption,”
Communication of AIS
, 2005 (2005): 61
-
81.


Lymperopo
ulos, Constantine, Chaniotakis, Joannis E. “Factors Affecting Acceptance of the
Internet as a Marketing
-
Intelligence Tool among Employees of Greek Bank Branches,”
International Journal of Bank Marketing
, 23 (2005): 484
-
505.


Lyytinen, Kalle, Rose, Gregory
M. “The Disruptive Nature of Information Technology
Innovations: The Case of Internet Computing in Systems Development Organizations,”
MIS Quarterly
, 27 (2003):557
-
595.


MacGregor, Robert C.,
Vrazalic, Lejla. “The Effects of Strategic Alliance Membership o
n the
Disadvantages of Electronic
-
Commerce Adoption: A Comparative Study of Swedish and

IS 7890: IS Research Seminar


Spring 2006

35

Australian Regional Small Businesses,”
Journal of Global Information Management
, 13
(2005): 1
-
19.


Mahmood, M. A., Kohli, Rajiv, Devaraj, Sarv, Guest Editors. “Special
Section: Measuring
Business Value of Information Technology in E
-
Business Environments,”
Journal of
Management Information Systems
, 21 (2004): 11
-
16.


M
anross, George G., Rice, Ronald

E. “Don’t Hang Up: Organizational Diffusion of the
Intelligent Telephone
,”
Information and Management
, 10 (1986):

161
-
175.


Massetti, Brenda, Zmud, Robert W. “Measuring the Extent of EDI Usage in Complex
Organizations: Strategies and Illustrative Examples,”
MIS Quarterly
, 20 (1996):

331
-
345.


Moch, Michael K., Morse, Edward V.

“Size, Centralization, and Organizational Adoption of
Innovations,”
American Sociological Review
, 42 (1977): 716
-
725.


Moore, Gary C., Benbasat Izak. “Development of an Instrument to Measure the Perceived
Characteristics of Adopting an Information Technol
ogy Innovation,”
Information
Systems Research
, 2 (1991): 192
-
222.


Mukhopa
dhyay
, Tridas, Kekre, Sunder, Kalathur, Suresh. “Business Value of Information
Technology: A Study of Electronic Data Interchange,”
MIS Quarterly
, 19 (1995): 137
-
156.


Nilakanta, Sre
e, Scamell Richard W. “The Effect of Information Sources and Communication
Channels on the Diffusion of Innovation in a Data Base Development Environment,”
Management Science
, 36 (1990): 24
-
40.


Oh, Sangjo, Ahn, Joongho, Kim, Beomsoo. “Adoption of Broadban
d Internet in Korea: The Role
of Experience in Building Attitudes,”
Journal of Information Technology
, 18 (2003):
267
-
280.


Orlikowski, Wanda J. “The Duality of Technology: Rethinking the Concepts of Technology in
Organizations,”
Organization Science
, 3 (1
992): 398
-
427.


Orlikowski, Wanda J. “CASE Tools as Organizational Change: Investigating Incremental and
Radical Changes in Systems Development,”
MIS Quarterly
, 17 (2003): 309
-
340.


Pavlou, Paul A.,
Fygenson, Mendel. “Understanding and Predicting Electroni
c Commerce
Adoption: an Extension of the Theory of Planned Behavior,”
MIS Quarterly
,

30 (2006):
115
-
143.


Perry, James L., Danziger, James N. “The Adoptability of Innovations: An Empirical
Assessment of Computer Applications in Local Governments,”
Administ
ration and
Society
, 11 (1980): 461
-
492.



IS 7890: IS Research Seminar


Spring 2006

36

Raho, Louis E., Belohlav, James A., Fiedler, Kirk D. “
Assimilating New Technology into the
Organization: An Assessment of McFarlan and McKenney’s Model,”

MIS Quarterly
,
11
(1987): 46
-
57.


Ramiller, N
eil C
. “Perceive
d Compatibility of an Information Technology I
nnovation
among

Secondary Adopte
rs,”
presented at the Annual Meeting of the Academy of Management,
Las Vegas, NV, August 9
-
12, 1992.


Rogers, Everett M.
Diffusion of Innovations
, NY: Free Press, 1962.


Seyal, A
fzaal H., Awais
, Main M., Shamail, Shafay,
Abbas, Andleeb. “Determinants of
Electronic Commerce in Pakistan: Preliminary Evidence from Small and Medium
Enterprises,”
Electronic Markets
, 14 (2004): 372
-
387.


Sharma, Sushil K., Gupta, Jatinder N.D. “Adverse
Effects of E
-
Commerce,”
The Economics and
Social Impacts of E
-
Commerce
, PA: Idea Group Publishing, 2003.


Shih, Chuan
-
Fong, Dedrick, Jason, and Kraemer, Kenneth L. “Rule of Law and the International
Diffusion of E
-
Commerce,”
Communications of the ACM
, 48 (
2005): 57
-
62.


Swanson, B. E. “Information Systems Innovation
among

Organizations,”
Management Science
,
40 (1994): 1069
-
1092.


Szmigin, Isabelle T.D., Bourne, Humphrey. “Electronic Cash: A Qualitative Assessment of Its
Adoption,”
International Journal of B
ank Marketing
, 17 (1999): 192
-
203.


Taylor, Shirley, Todd, Peter A. “Assessing IT Usage: The Role of Prior Experience,”
MIS
Quarterly
, 19 (1995): 561
-
570.


Thompson, Ronald L., Higgins, Christopher A., Howell, Jane M. “Personal Computing: Toward
a Conceptu
al Model of Utilization,”
MIS Quarterly
, 15 (1991): 124
-
143.


Thompson, Ronald L., Higgins, Christopher A. “Influence of Experience on Personal Computer
Utilization: Testing a Conceptual Model,”
Journal of Management Information Systems
,
11 (1994): 167
-
188
.


Timmers, Paul.
Electronic Commerce: Strategies and Models for Business
-
to
-
Business Trading
,
NY: John Wiley & Sons, LTD, 1999.


Tornatzky, L
ouis

G., Fleisher, M
itchell
.

The Processes of Technology Innovation
, MA:
Lexington Books, 1990.


U.S. Census Burea
u. “Quarterly Retail E
-
Commerce Sales 4
th

Quarter 2005.”

Internet. (2006)
Available: http://www.census.gov/mrts/www/data/html/05Q4.html, March 2006.



IS 7890: IS Research Seminar


Spring 2006

37

Van Beveren, J.,
Thomson, H. “The Use of Electronic Commerce by SMEs in Victoria,
Australia,”
Journal of S
mall Business Management
, 40 (2002): 250
-
253.


Venkatesh, Viswanath, Brown, Susan A. “A Longitudinal Investigation of Personal Computers
in Homes: Adoption Determinants and Emerging Challenges,”
MIS
Quarterly
, 25 (2001):
71
-
102.


Venkatesh, Viswanath, Davi
d, Fred D., “A Theoretical Extension of the Technology Acceptance
Model: Four Longitudinal Field Studies,”
M
anagement Science
, 46 (2000): 186
-
204.


Venkatesh, Viswanath, Morris, Michael G., Davis, Gordon B., Davis, Fred D. “User Acceptance
of Information T
echnology: Toward a Unified View,”
MIS Quarterly
, 27 (2003): 425
-
478.


Wang, Eric T.G., Seidmann, Abraham. “Electronic Data Interchange: Competitive Externalities
and Strategic Implementation Policies,”
Management Science
, 41 (1995): 401
-
418.


Watson, Hugh

J., Frolick, Mark N. “Determining Information Requirements for an EIS,”
MIS
Quarterly
,
17 (1993): 255
-
269.


Wolcott, Peter, Press, Larry, McHenry, William, Goodman, Seymour, Foster, William, “A
Framework for Assessing the Global Diffusion of the Internet,

Journal of the
Association for Information Systems
, 2 (2001).


Zmud, Robert W. “Diffusion of Modern Software Practices: Influence of Centralization and
Formulation,”
Management Science
, 28

(1982): 1421
-
1431.


Zmud, Robert W. “An Examination of Push
-
Pull
Theory Applied to Process Innovation in
Knowledge Work,”
Management Science
, 30 (1984): 727
-
738.


Zmud, Robert W., Apple, L. E. “Measuring Technology Incorporation/ Infusion,”
Journal of
Product Innovation Management
, 9 (1992): 148
-
155.