Understanding and Predicting Electronic Commerce Adoption: An Extension of the Theory of Planned Behavior Author(s): Paul A. Pavlou and Mendel Fygenson Source: MIS Quarterly, Vol. 30, No. 1 (Mar., 2006), pp. 115-143 Published by: Management Information Systems Research Center, University of Minnesota Stable URL: http://www.jstor.org/stable/25148720 Accessed: 05-03-2015 21:08 UTC
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Pavlou & Fygenson/ExtendingtheTPB
Qjarteny and Predicting Understanding Electronic An Extension of Commerce Adoption: the Theory of Planned Behavior1 Paul A. Pavlou Anderson Graduate
By:
elicit
School
of
Management
stress the Our findings by self-efficacy and controllability. variables of trust and technology adoption (perceived e and ease of use) as salient usefulness beliefs for predicting commerce
the integration adoption, justifying of trust and tech In addition, variables within the TPB nology adoption framework. characteristics Website technological (downloaddelay, navigability, and
U.S.A.
The process
subjective
's (1991)
behavior theory of planned (TPB) the process of e-commerce by adoption is captured through two online consumer
of planned
Theory
Keywords: extends Ajzen and predict
time and monetary
control,
behavior,
behavioral
perceived
tech technology adoption, controllability, consumer commerce, trust, electronic
self-efficacy,
model,
acceptance nology behavior
a product information and (2) purchasing we association model the First, simultaneously
(1) getting
a Web
theory
skills,
and (product diagnosticity and predictive power product value) add to the explanatory of our model. Implications for Information Systems, e-commerce, TPB, and the study of trust are discussed.
Abstract
following
consumer information protection), and product characteristics
resources,
[email protected]
intentions
each
importance
Mendel Fygenson Marshall School of Business University of Southern California Los Angeles, CA 90089
from between
beliefs for
formed
[email protected]
behaviors:
of salient
the proposed supports longitudinal study with online consumers e-commerce the model, adoption validating predictive power ofTPB a higher-order factor and theproposed conceptualization ofPBCas
U.S.A.
to explain consumers.
set
comprehensive
A
University of California, Riverside Riverside, CA 92521
This paper
test a
and
behavior.
vendor.
these two contingent online behaviors and their respective to consumer behavior theories and the by appealing
of TPB,
implementation we derive for
norm, and perceived
intentions, each
behavior
behavioral
Second, respectively. its intention, attitude,
control
(PBC).
Third, we
Introduction^ Business-to-consumer consumers
e-commerce
(B2C)
information
get
and purchase
i
is the activity products
in which
using
Internet
technology (Olson and Olson 2000). The potentialbenefitsof e commerce
have
consumers
materialize, getting websites.
MIS
been
for these
However, the accepting senior editor for this paper. Elena !Ritu Agarwal was Karahanna was the associate editor. D. Harrison McKnight, Jonathan Palmer, and David Gefen served as reviewers.
^
information B2C
touted (e.g., Gefen widely information technology-enabled must and
e-commerce
Quarterly
first adopt
online
et al.
2003). to benefits
activities,
such as
from commercial products consumer's engagement adoption?the
purchasing
Vol. 30 No.
1, pp.
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115-143/March
2006
115
theTPB Pavlou & Fygenson/Extending
vendors?goes beyond relationships with Web and itmust thus be understood of traditional marketing, are simultaneously IT that online consumers from the viewpoint in online
exchange
1.
e-commerce
of B2C
Adoption
as a monolithic
is not viewed
the realm
andgetting behavior,but is ratherproposed ofhoXh.purchasing
users (Koufaris2002). According toTaylor and Todd (1995b), IT
predict related behaviors, by modeling these two online
usage
not only use of hardware and software, but also that that surround the IT and the people and procedures
support its use. B2C to examine a user's
thus presents a unique opportunity a complex IT system.
e-commerce
2.
interaction with
PBC To
E-commerce
IS researchers
among
e-commerce
the B2C
toward
3.
of this study is to theoretically purpose a set of factors that integrate test and propose empirically to variables and with economic marketing technology adoption our understanding
enhance B2C
e-commerce
traditional
consumer
and Web
5.
Second,
2002).
information
personal
can be easily
IT use when
consumers
Third,
interacting with
the store itself (Koufaris of the open reliability
confidence,
a barrier
creating traditional
TPB
the
vendors
over
effortlessness
Therefore,
adoption. perceived
online
summary, validation
116
to be IT-related shown (e.g., empirically or within the of use, information protection),
ease
IS domain (e.g., trust,navigability),highlightingthekey role
of IT in online
consumer
behavior.
The
paper
proceeds
as follows:
behavioral
role
in B2C
model
e-commerce.
that has
to predict it is model,
shown
been
online Web by
behaviors: vendors.
examining
in a comprehensive,
getting This
study the major
yet parsimonious
the TPB
are consistent with important factors that the derived model structure. Moreover, explains
in e-commerce portion of the variance this study provides clarity conceptual on the following issues:
The
behaviors.
describes
behaviors,
the next
section
the TPB
framework
discusses
the two
section proposes
following
and the nature
and describes
the elicited
externalbeliefs and justifieshow they linktoTPB. The next two sections
final
The and results. the research methodology the contribution, study's findings,
present
section
discusses
and
implications.
activities,
to compared control (PBC),
model thatatteststo the influentialrole of PBC, while identifying nomological substantial
are
factors
Most
and role of PBC, and linksTPB perceptionswith intentionsand
about
constructsof TPB (attitudeand PBC) and theirmost important
and validating
and
has become
to predict two prevalent of TPB productsfrom information and purchasing to predict these two behaviors aims results
of both attitude and PBC,
which
As a general a variety of settings. across it to explain most human behaviors 1991). Hence, (Ajzen designed could effectively model to expect that a TPB-based is reasonable We thus create an extended online consumer behavior. explain
This
control
website,
behavior
antecedents.
of external
a vendor's
behavior,
version
as an antecedent
is viewed
Trust
examination
detailed
e-commerce
and
is a well-researched
a more
in extensive
as described in thetheoryofplanned behavior (TPB) (Ajzen 1991), is likely to play
formed by two
construct
engage
Fourth, there are concerns 2002). that Web Internet infrastructure
a critical
of or
actively
to e-commerce
consumer
set
advanced
must
et al. 1999). These to interface with consumers (Rose employ and of the online environment stress the uncertainty differences of consumer trust the and of the significance importance emphasize IT adoption. More perception importantly, they reduce consumers' of control,
as a two-dimensional
is viewed
PBC
a
has
theoretically
collected,
processed, and exploited bymultiple parties not directly linked to the transaction.
examined.
usefulness,
selleropportunismdue toproduct and identity uncertainty(Ba and Pavlou
empirically
nor
2002),
(e.g., George ever been
of PBC
within theproposed TPB model. therebyintegrated
to compared the spatial and temporal increases fears of vendors
First,
4.
behavior.
differences
notable
behavior. consumers
between
separation
some
has
consumer
of online
for PBC
antecedents
allowing beliefs.
The
behavior.
extend TPB.
theoretically
underlying dimensions {self-efficacyand controllability),
phenomenon,
there is only a limitedand fragmentedunderstandingof online
consumer
to simultaneously
used
is a key determinant of both focal e-commerce behaviors. most e-commerce the best of our knowledge, studies do not
account and use within is an instance of IT acceptance adoption a setting with that combines marketing adoption technology elements, and it thus requires distinct theorization within the infor interest mation systems literature. However, despite an emerging
we
behaviors,
encompasses
the services
has not been
TPB
Since
information.
a
In adoption. and empirical
Electronic Commerce Adoption Description of Online Consumer Behaviors as the commerce described is broadly adoption in online exchange relationships with Web engagement From a consumer behavior vendors. standpoint, getting product information and purchasing (among products are generally viewed
Electronic
consumer's
other activities) and
Straub
as the two key online consumer behaviors e-commerce most studies have While
(Gefen
largely behavior is not on product purchasing, online consumer in getting product first engage since consumers must monolithic 2000).
focused
information beforepurchasing. Choudhury et al. (2001) argue that
consumers consider
do not make two distinct
a single, stages:
inclusive
decision,
getting product
but they rather and then
information
purchasing theproduct. Gefen and Straub (2000) also distinguish between
the two behaviors
by arguing
that getting
information
is an
activity intrinsicto the IT since theWeb system itselfpresents the
2006 MIS QuarterlyVol. 30 No. 1/March
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theTPB Pavlou & Fygenson/Extending
information.
product
Product
purchasing,
on
the other hand,
is a
Web systemprimarilyprovides the taskextrinsicto the IT since the
means
to achieve
the purchase.
TPB
Getting informationinvolves the transferof informationfromthe Web
to the consumer
vendor
information
Getting
the vendor's website. through browsing or window referred to as browsing
has been
searchhas shopping(Gefen2002). The value of online information beenwidely acknowledged (Bellman et al. 1999) since it is critical for learning
and potential alternatives, specifications tomake and gaining sufficient knowledge et al. 2001). Product pur (Choudhury
about product
determining requirements, well-informed decisions refers
chasing
to the procurement
information
monetary
in exchange
information,
monetary
consumer
providing
a product by providing In addition to for the focal good. of
purchasing
product
(e.g., address
information
usually
involves
information,
product
preferences).2
constitute
the major
et al.
Engel
(1973)
getting information and product purchasing, part of long-held consumer behavior models. a five-stage describe buyer decision-making
behavior.
includes information search, problem recognition, and post-purchase of alternatives, decision, purchase to getting information and Information search corresponds
purchase
decision
evaluation
to product
(1984) propose thecustomerresource lifecycle (CRLF) with three stages:
prepurchase, is a information
Getting
purchasing corresponds Kalakota and Whinston model
activity,
to predict
shown
a wide
of three phases:
prepurchase
interaction,
interactions.
Prepurchase
interaction
search, while
transaction
stages:
requirements service. and after-sales
comparison-shopping
purchase, to requirements sum, we
product
determination,
corresponds
vendor
selection,
information corresponds Getting to purchase. and determination, product purchasing focus on two behaviors?getting information and
purchasing?that
largely determine
range of behaviors
et al.
(Sheppard
1988). to TRA,
According behavioral and
the proximal
norm
subjective
by attitude
(A) a person's overall refers to the person's
Attitude
captures
the behavior;
SN
(SN).
is a
of a behavior
determinant
in turn, is determined
intention, which,
evaluation
of performing
perception
of the expectations of important others about the specific the of attitude and SN are a set of antecedents Finally,
behavior.
underlyingattitudinal(b{) and normativebeliefs (n{), respectively. Attitudinal beliefs are assessments about the likelihood of the normative
consequences;
are assessments
beliefs
about
what important othersmight thinkof thebehavior. Attitudeand SN are described
via an expectancy-value
formula:
(1)
Aoclb.-e, SN
Where:
is
ej
e-commerce
the
rrii (2)
oc^n;
person's
desirability
Similarly, mercantile
to getting information.Choudhury et al. (2001) describe four
In
been
post-purchase. while product
to during purchase activities. introduce the consumer
and post-purchase
purchase, consists of product
purchase,
and
(1997)
that consists
(CMM)
during
prepurchase
action
and Learmonth
Ives
purchasing.
of the theory of reasoned
(TRA) (Ajzen and Fishbein 1980). TPB has been one of themost influentialtheoriesinexplainingand predictingbehavior,and ithas
that
process
key
1) is an extension
(Figure
behavior's
two behaviors,
These
The Theory of Planned Behavior
is the person's
mj
evaluation
subjective
of the outcome,
to comply with
motivation
of
the
and
important
others.
that most
Recognizing
human
behaviors
are
subject
to obstacles,
Ajzen (1991) introducedTPB, which generalizesTRA by adding a third perception:
perceived
expectancy-value
formula:
behavioral
control
A
(PBC).
set of
controlbeliefs (c;) and theirperceived power (p;) (to facilitateor inhibittheperformanceof a behavior) determinePBC throughan
adoption.3
PBC
oc?c,.
p.
(3)
Behavioral Intentions and Actual Behavior The purchasing process may be supplemented by automatic information extraction through cookies and data mining tools. However, it is beyond the scope of this study to account for this type of information sharing, which is
not related to consumer behavior.
recognize the existence of other e-commerce activities, such as fulfillment and repeat buying. Yet, fulfillment is a vendor's behavior (Kalakota andWhinston 1997). Even ifpost-purchase experience influences future behaviors, for predicting a specific behavior, the proposed TPB
We
are supposed to take into account all previous experiences (Ajzen 1991). Most important, consumer post-purchase behavior is contingent upon fulfillment,which cannot be predicted before purchase.
variables
Behavioral
intentions are motivational
factors that capture how hard
people arewilling to trytoperforma behavior (Ajzen 1991). TPB suggeststhatbehavioral intentionis themost influential predictorof behavior;
after all, a person of 87 studies,
analysis
does what
an average
she intends to do.
correlation
of
In a meta
.53 was
reported
between intentionsand behavior (Sheppard et al. 1988). Following TPB,
we
expect
behaviors?getting
a
positive
information
relationship
for
and purchasing?and
our
two
focal
their respec
tive intentions.
MIS QuarterlyVol. 30 No. 1/March 2006
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117
Pavlou
the TPB
& Fygenson/Extending
Attitudinal
kr
Beliefs
/r
Normative
I
_
__j^
I_!^I___I
I
Beliefs
f
\.
_| Subjective
1-'
psychology using the TPB
behaviors modeled
of Planned
Behavior
j
(Adapted
model
related
are always framework, but these behaviors without any attempt to capture the extent of raises
important
simultaneously
within theTPB framework? If so, how? Through which TPB two related behaviors
should
at one level of specificity. only applies a crucial to another remains behavior open I. Ajzen
with
communication
explain draw upon
(2003)
to reduce
the two focal
behaviors,
we
behavior.
getting facilitates
argue
influences
a
assume
which
information
purchases. that consumers engage
in getting
of product purchasing. This is captured purchasing.
Third,
getting in the theory of
exposure
from a vendor's website information product a that from influences product purchasing positively Web vendor. Getting
intentions
link behavioral
we
(implementation)
118
MIS
website.4
textbook
from Amazon
information consumers particular facilitate (goal)
Quarterly
between
refer
intentions
that help
Vol. 30 No.
about
a student that intends to buy a example, to get price ismost likely to visit Amazon In terms of the temporal order, the textbook. For
a product to fulfill a to purchase intentions to then the and form need, they implementation the the need. Therefore, product purchasing fulfilling first form the intention
intention precedes
and drives
the getting product
information
realize
to purchase
intentions preceding H2:
arguments
relate
to intention
to get
information.
The
suggest
a product vendor to purchase from a Web Intentions about influence intentions to get information positively the product website. from the vendor's
and
information
information and getting to Gollwitzer's (1999) theory of product purchasing, are self-regulatory that which intentions, strategies implementation to the theory, a behavior. aim to drive a goal-oriented According activates a set of goal-enabling behavior automatically goal-driven
To
vendor's
Second, Kim
holds that the frequency of 1968), which (Zajonc et studies al. facilitates a behavior. exposure (Choudhury Empirical between correlation 2001; Gefen getting 2002) report a positive information and purchasing. Therefore, we suggest
HI:
activates
the goal behavior intention). (implementation a product from aWeb a goal intention to purchase vendor an intention to get information about that product from the
sequential
and purchasing. For example,
the uncertainty
information mere
1997),
to achieve
Therefore,
(implementation) intentions. Salisbury et al. (2001) show that
of consumer
and Whinston between
Benbasat
(personal
means
(Ives and Learmonth 1984), and theCMM
al. 1973), theCRLF
relationship getting information
question
one
First, aspects This is contingent upon getting information. in the buyer's decision making model (Engel et
product purchasing notion is captured (Kalakota
to relate
How
2003). between
the relationship three different
To
In principle,
be connected?
TPB
1991)
a specific product from a view purchasing 1999). We as vendor while Web the behavior, goal getting particular as a vendor is viewed information about the product from theWeb
researchers
literature, many
from Ajzen
and Orbell
independently, et al. 2000). This their relationship (e.g., Povey two be modeled related behaviors Can questions: constructs
Behavior
_^
Jh-J^T-7^-1
Control
I
Connecting Getting Information and Product Purchasing In the social
Intention
Perceived I Behavioral \ ^~~ ^~~~~~~*
Control - I
1. The Theory
Figure
\
Beliefs
In
Vl
v Attitude
_^
the behavior
(Sheeran
Attitude Attitude
has
long been
shown
to influence
behavioral
intentions
(Ajzen and Fishbein 1980). This relationshiphas received sub atti support. With regard to the focal behaviors, empirical is defined tude toward getting information and product purchasing as the consumer's of using a website of the desirability evaluation to get information from a Web and purchase vendor, products a deductive logic, favorable attitude is likely to Using respectively. stantial
Gollwitzer's (1999) theory suggests that a goal behavior can trigger several implementation intentions. Intention to purchase a product from a specific Web vendor triggers intentions to get product information, not only from the specific vendor, but also from other sources. Both implementation intentions
are potential consequences of the goal behavioral intention, but the intention to get information about a specific product from a specific Web vendor is more likely to occur, and it is thus examined.
1/March 2006
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theTPB Pavlou & Fygenson/Extending
encourage a vendor.
consumers
to get information
and purchase
vendor.
Underlying Dimensions
Subjective Norm is instigated by one's desire to act as to the important referent others act or think one should act. Applied two focal behaviors, SN reflects consumer perceptions of whether
SN
that behavior
suggests
these two behaviors the consumer's
are accepted, and implemented by encouraged, circle of influence. The literature suggests a positive
relationshipbetween SN and intendedbehavior,and empiricalwork has
shown
that SN
influences
behavioral
intentions
toward
system
use
et al. 1999). A positive between SN (Karahanna relationship and intentions to get information and purchase products from aWeb
vendor
behavior toward product purchasing from theWeb
from
products
of PBC
Since
there has
the early days of TPB, the nature of PBC. surrounding
nature and measurement
been
some
ambiguity its questions regarding a lot of attention attracting (e.g.,
Recently,
have been
Ajzen 2002b; Trafimow et al. 2002). In particular, empirical findingshave cast doubt on Ajzen's (1991) original assertion that is a unitary
PBC
construct,
suggesting
instead
that PBC
two
has
distinctdimensions: self-efficacy(SE) and controllability.5 While the conceptualization there is an emerging
of SE and controllability is still controversial, consensus that the two are the underlying
dimensions of PBC. We offerthefollowingdefinitions:
is thus expected.
Self-Efficacy: Following Bandura (1986), we define SE as individual
Perceived Behavioral
Control
see Trafimow
et al. 2002).
This paper
dimensions
capabilities SE
a
to perform
describes
to get product
consumers' information
sheds
lighton thenatureand role ofPBC by (1) clarifyingitsrole inTPB, (2) describing its underlying dimensions, and (3) proposing a model that integrates its underlying parsimonious their antecedents into a coherent model.
of a person's to e-commerce,
Applied judgments of their own capabilities and purchase products online.
PBC is a topic thathas been debated in the social psychology literature (for a review,
judgments
behavior.
We
Controllability:
follow Ajzen
(2002b)
to define
as individual judgments about the availability controllability of resources and opportunities toperform the behavior. Applied to e-commerce, describes consumers' percep controllability
and
tions of whether
getting information and purchasing products is completely of the availability of up to them because resources and opportunities.
online
The Role of PBC PBC
is defined
inTPB
as a person's
of how
perception
easy
or difficult
it
would be to carryout a behavior (Ajzen 1991). To differentiate PBC fromattitude, Ajzen (2002b) emphasized thatPBC denotes a subjective
of control over
degree
of a behavior
the performance
and
not the perceived likelihood thatperformingthe behavior will a given outcome. produce read as perceived control
that PBC "should be suggested the performance of a behavior" ease PBC is the consumer's (2002b, p. 668). Therefore, perceived or difficulty of getting product information from a vendor's website and purchasing
a product
Ajzen over
from aWeb
vendor,
respectively.
In general, PBC plays a dual role in TPB. First, along with attitude and SN, it is a co-determinant of intention. Second, together with of behavior. for the role of intention, it is a co-determinant Support
PBC on intention and behavior isprovidedbyMathieson (1991) and Taylor and Todd (1995b). We thussuggest H3a:
PBC
over
getting
information
from
a Web
vendor
positively influences (1) intention and (2) actual behavior
toward
that Web
vendor.
getting
product
information
The Nature of Perceived Despite
evidence
empirical
Behavioral Control that SE
and
controllability
can
be
manipulated differentlyand can be reliably distinguishedacross behaviors (e.g., Cheng and Chan 2000), Ajzen (2002b, p. 696) maintains that"the fact that it is possible to reliably distinguish between twodifferenttypesofPBC?SE and controllability?does not invalidate
the unitary nature of the [PBC] construct." To bridge a two-level hierarchical this inconsistency, he proposes to model describe PBC as an "overarching, construct" (p. 697). superordinate or
Hierarchical interrelations grative coherent
latent
are used to explain models higher-order an lower-order factors that constitute
among
the inte
construct.
description
a more models Higher-order provide of multiple facets of a complex phenomenon
thatcould be described by a unitaryfactor(Law et al. 1998). The between relationships oxformative.
reflective
lower While
and higher order constructs reflective structures assume
can
be
that the
from the SE and controllability differ in their predictive validity (e.g., and Armitage 1998), there is no evidence to support the common view that SE reflects internal factors whereas controllability reflects beliefs While
H3b:
PBC
over
product
purchasing
from
a Web
vendor
positively influences (1) intention and (2) actual
Conner
about external factors (Ajzen 2002b).
MIS QuarterlyVol. 30 No. 1/March 2006
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119
the TPB
& Fygenson/Extending
Pavlou
Jfc
fW\
Beliefs_|
H_l^^^-^-^^^
Normative
/[.
-^
j !
CONTROL
PERCEIVED
BELIEFS
Figure 2. The Proposed
order construct
assume
Extension
causes
(for a review,
--'"''"
^_'
v. j4j
BEHAVIORAL
of the Theory
see Edwards
is caused
I ^ j-~~~ f"*" j
'
- - -?'- -
by the
2001).
and controllability. for a formative
and controllability traits. As dynamic be manipulated PBC Hence,
are dynamic concepts,
model
is based
on the notion
that SE
1986), not stable concepts (Bandura are to likely change over time and they
et al. 2002). differently by other factors (Trafimow cause cannot and SE thus controllability, equally
in since a change unlikely. Moreover, rendering a reflective model one of the lower-order factors does not necessarily imply an equal in the other, a formative model is deemed more change likely.
for
its two underlying dimensions, of attitude.
to eliciting
in addition
the antecedent
includes
normative,
three
and control.
categories These
of
external
beliefs:
are scenario
beliefs
and a
We
cannot
conducted
questionnaire, to freely elicit
120
a belief
elicitation
open-ended using The aim was procedure. and control beliefs, which
study
(2002a) following Ajzen's themost salient attitudinal
an
a
convenience staff, and
faculty, States. Their
a 20 percent
responses
2 and
(Tables
then chose
the
cutoff, as prescribed
by
3).
frequency
of 56 sample of a major are sorted based on
students We
and characteristics, characteristics, (5) product technological were on skills. These derived based (6) consumer categories literature grounding and practical For getting empiricism. infor : (1) the attitudinal beliefs are trust, perceived mation usefulness and (4)
beliefs
beliefs are trust, ease of use, time (2) the controllability download and (3) the SE delay, and website navigability; are ease of use and skills. For purchasing: (1) the attitudinal
beliefs
are trust, usefulness,
of use;
(2) the controllability resources, the SE
of purchasing, and product value; are trust, ease of purchasing, monetary and information protection; and diagnosticity,
product beliefs are ease
can aggregate
of use
and
skills.
Figure
3 depicts
our
beliefs
to create measures
of attitude,
SN,
and
(Ajzen and Fishbein 1980). This aggregation has been
behavior create
ease
beliefs
model.
criticized
one for each new behavior, be generalized. Hence, that are identify five to nine salient beliefs for each behavior context and population 1980). specific (Ajzen and Fishbein
priori must
a
range of characteristics, span a wide resulting set of beliefs we grouped into six categories for better exposition: (1) trust consumer inWeb resources, vendor, (2) technology acceptance, (3)
PBC
attitudinal, specific
1). Normative that SN has
The
TPB
HHBHI^H
(Table showed
which
proposed
TPB
Construct
Ajzen and Fishbein (1980, p. 68) (presented inbold in the tables).
(3)
Eliciting External Beliefs
from
included
that exceeded
resources,
beliefs
behavior
in the United university the frequency mentioned
ease
to comprehensively predict the two key e-commerce TPB extension allows for a thorough the proposed and their of PBC dimensions through its underlying a parsimonious while maintaining view of antecedents, elicits the antecedents PBC section of following through
each which
participants,
In our endeavor
respective PBC. The
Second-Order
weak role inonline behaviors (George 2002). We solicited thekey
behaviors, prediction
Construct 1 First-Order
1 . y\_I i_I
to specific open-ended correspond questions beliefs were not elicited since prior studies
beliefs rationale
I
_
Behavior
drivers
The
Behavior
-j^
-
|--r^--~~" I Perceived Behavioral
of Planned
our proposed of TPB with PBC viewed extension factor formed by the first-order dimensions of SE
Figure 2 depicts as a second-order
Intentions
-^^^fc
'_'
CONTROL
the first order factors, formative order construct
that the second
first order factors
Subjective Norm
Self-Efficacy K*~
I-"
^
Beliefs
j_j-1 Controllability \ j _ V[_
r
Self-EfficacyU-?| Beliefs !
\jR
latent second
\f.
|
I I r? Controllability Beliefs \ VW
structures
Attjtude I
Attitudinal _J
identifying specific factors that might predict a itmay and Todd and for the biases 1995a)
for not
(e.g., Taylor (e.g., Karahanna
be decomposed
et al.
1999).
intomultidimensional
The
idea that TPB
constructs
beliefs
has been
can
credited
toTaylor and Todd (1995b), who introducedthedecomposed TPB (DTPB). While we stayfaithfultoTPB, we decompose thederived
beliefs behavior.
following
DTPB
In doing
to provide a better understanding of each aim not only to assure high explanatory but also to select managerially amenable
so, we
and predictive validity, factors. We also use another
variation
MIS QuarterlyVol. 30 No. 1/March2006
This content downloaded from 130.63.180.147 on Thu, 05 Mar 2015 21:08:15 UTC All use subject to JSTOR Terms and Conditions
of TPB
to permit
cross-over
Pavlou & Fygenson/ExtendingtheTPB
1. Questionnaire
Table
for Eliciting
External
Salient
Beliefs
1. Getting informationabout this particular product from thisvendor's website 1a What do you beNeve are the advantages of doing this? ^k what do you believe are the disadvantages?
Attitudinal Beliefs
(Getting Information)
inthe next 30 days:
2' Anvtnin9 e,se y?u associate with your getting informationabout this product fromthisvendor's website? 3. What factors or circumstances would enable you toget informationabout this product fromthis vendor's website?
Control Beliefs
4. What factors or circumstances would make itdifficultforyou toger informationabout this product from this vendor's website?
(Getting Information)
5 Are tnere any 0tner jssues (barriers or facilitatingconditions) thatcome tomind when you think about getting informationabout this product from thisvendor's website? 6. Purchasing the particular product from thisWeb vendor inthe next 30 days: 6a_ What do you believe are the advantages of doing this? 6b. What do you believe are the disadvantages?
Attitudinal Beliefs
7. Anything else you associate with your purchasing this product from thisWeb vendor? 8. What factors or circumstances would enable you topurchase 9. What factors or circumstances would make
Control Beliefs
this product from thisWeb
vendor?
(Purchasing)
Table
this product from thisWeb vendor?
itdifficultforyou topurchase
^q Are tnere any 0tner issues (barriers or facilitatingconditions) thatcome tomind when you think this product from thisWeb _about your purchasing vendor?_
2. Frequency
of Elicited
Beliefs
Attitudinal Beliefs Trust - Getting Information Perceived Perceived
Ease
Frequency
Information) Control Beliefs
(%)
37 (66%)
of Getting Info
33 (59%)
of Getting
25 (45%)
Usefulness Info
Download
(Getting
Perceived Trust -
14 (25%)
Delay
Perceived Risk ofGetting Information
Time
Perceived Enjoyment
5 (8%)
Website
Product Variety
5 (8%) 2
Getting
Website
30 (54%)
Information Delay 21
24 (43%) (38%)
Resources 18(32%) Navigability 12
(21%)
Features (e.g., search engine, _FAQ)_
(4%)_Website
(%)
31(55%)
Ease of Getting Info
Download
6 (11%)
Instant Gratification_
Frequency
Getting Information Skills
Personalization_
7 (13%)
3 (5%)
MIS QuarterlyVol. 30 No. 1/March 2006
This content downloaded from 130.63.180.147 on Thu, 05 Mar 2015 21:08:15 UTC All use subject to JSTOR Terms and Conditions
121
Pavlou
& Fygenson/Extending
the TPB
3. Frequency
of Elicited
Table
Beliefs
Attitudinal Beliefs Perceived
of
Usefulness
(Purchasing)
32 (57%) 17 (30%)
Product Diagnosticity Perceived Ease of Purchasing
Purchasing Ease of Purchasing Trust - Purchasing
ProductValue |
14(25%)
_ProductDiagnosticity
13(23%)
Perceived Risk of Purchasing
7(13%) 2 (4%)
Product Quality
8(14%)
Product Variety
~~Z^+ \___ \T^
PU ofGetting Info PEOU ofGetting Info
Download Delay .-.
I-1
Website Navigability
Information Skills Getting
MonetaryResources
122
18(32%)
3 (5%)
\\ -V^^
I I^^-^^"^ k^
-\>l
Research
Attitudetoward Getting Info
.
-
Intentionto -^ Get lnfo m
^
/
^^ .i Jt^
^^
(Getting
)
Getting Info Behavior
PBC '' j
Info)
M' j j
PERCEIVED BEHAVIORAL CONTROL (GETTING INFORMATION)
(PURCHASING)
Vol. 30 No.
|
Gratification3(5%) Quick Pay Availability (e.g., oneclick pay)
!^! Self-Efficacy (Getting lnfo)^^
^^^^
^\ \
^---^\ '
Information Protection
Quarterly
[
Skills12(21%) Purchasing
Controllability / j ^^ / (GettingInfo) ^.
_
\
Diagnosticity-V?^
3. The Proposed
MIS
p4
^^\^-JjJ
EXTERNAL BELIEFS
Trust Purchasing 22(39%) Information Protection
V.
Z\Jk>LiJ
