Web Systems Design and Online Consumer Behavior [Electronic resources] نسخه متنی

Literature Review

In this section, different theoretical perspectives on user acceptance of IS/Web site are
first reviewed. They are followed by reviewing literature on dimensions of IS success model
including ServQual and trust that may quantify various quality attributes of Web sites.

Theoretical Perspectives on User Acceptance of IS/Web
Site

Many researches address the issues of IT design and evaluation to enhance usability and
acceptance and try to identify the determinants of IT use and acceptance (Davis et al., 1989). User
acceptance is a critical factor to determine the success of a Web design project. Both
practitioners and researchers have a strong interest in understanding how people accept e-commerce
Web sites so that better methods can be employed to design and evaluate Web sites and predict
customers’ response. The acceptance theory seeks to extend the model of customer/user-centered
design, which is advocated in usability approaches (Nielsen, 2000), from interface improvement to
predictions of likely usage (Dillon & Morris, 1996). To enhance our understanding of the
determining variables to explain the level of Web site acceptance, it is necessary to review
different perspectives that touch on this issue: Theory of Reasoned Action, Technology Acceptance
Model, and Human-Computer Interface/Usability Theory.

Theory of Reasoned Action (TRA)

TRA defines the relationships among beliefs, attitudes, norms, intentions, and behavior
(Fishbein & Ajzen, 1975). TRA assumes that human beings are basically rational and make
systematic use of information available to them when making decisions. TRA also assumes that the
behavior being studied is under total volitional control of the performer (Chang, 1998). However,
the prediction of behavior from intention is problematic because a variety of factors in addition
to one’s intention determine whether the behavior is performed.

TRA is a general model and may provide a common frame of reference within which to integrate
various lines of inquiry. A substantial body of empirical data in support of TRA has accumulated
(Bang et al., 2000; Chang, 1998; Jackson et al., 1997). TRA has broad applicability that spans
behaviors in many fields including using a computer. The theory has gone through rigorous testing
that shows its robustness in predicting a person’s intention and behavior under volitional control
(Bagozzi, 1992; Davis et al., 1989).

However, TRA has some boundaries: (1) The behavior should be under volitional control; (2)
Intent does not change prior to the performance of the behavior; (3) Intention measures should
correspond to the behavioral criterion in terms of action, target, context, and time (Liker &
Sindi, 1997). Free from these boundaries, TRA can be adapted to study e-commerce Web site design
because most e-commerce Web site users are under volitional control and without influence from
other factors such as supervisor’s impact.

Technology Acceptance Model (TAM)

TAM of Davis (1989) is the most widely cited theory in the studies on user acceptance of
technology. The goal of TAM is to predict the system acceptance and diagnose the design problems
before users experience the system. TAM predicts that the user acceptance of a system is determined
by two factors: (1) perceived usefulness and (2) perceived ease of use. Perceived usefulness is the
degree to which a person believes that use of the system will enhance his or her performance.
Perceived ease of use is the degree to which a person believes that use of the system will be free
from efforts.

Since Davis’s elucidation of TAM, numerous researchers have discovered that TAM yields
consistently high-explained variance for why users use/accept systems. An adaptation of TRA, TAM is
specifically tailored for modeling user acceptance of IS. Being parsimonious and theoretically
justified, it provides a general justification for the determinants of computer acceptance and is
capable of explaining user behavior across a range of end-user computing technologies. In contrast
to TRA, in which the beliefs are considered idiosyncratic to a specific context, TAM’s perceived
usefulness and perceived ease of use are meant to be fairly general determinants of user
acceptance. Therefore, TAM is more applicable to studying the user acceptance of an e-commerce Web
site than TRA because Web site design is one kind of IT project which is always carried out in a
specific context. Studies on the acceptance of Web sites using TAM theory and its
refinement/extension are accumulating (Eighmey & McCord, 1998; Liu & Arnett, 2000;
Mathieson et al., 2001).

Human-Computer Interaction (HCI) and Usability
Engineering

HCI examines all aspects of user-interface design from the high-level concerns of
organizational context and system requirements to the conceptual, semantic, syntactic, and lexical
levels. HCI research concentrates heavily on the concept of usability. The usability of an
application refers to the effectiveness, efficiency, and satisfaction with which specific users who
are performing specific tasks in specific environments can use the application. Two major
characteristics of usability engineering are prototyping and redesign in seeking to maximize the
usability throughout the whole product development process. Nielsen (2000) provides a large number
of related usability attributes: learnability, efficiency, memorability, errors, and
satisfaction.

HCI/Usability theory is the most applicable to the Web site interface design (Behbunan-Fich,
2001; Gary, 1999; Nielsen, 2000; Smith et al., 1997). The usability of a Web site is about ease to
use and usefulness. For example, it answers the question — does the audience think the site is easy
to use? From the perspective of usability theory, a Web site has to be developed as friendly as
possible, or customers will go elsewhere. Today’s Internet users are savvier than ever, and a Web
site needs to impress them if the site wants to keep them around. What impresses customers is not
fancy presentation but the functionality. Such questions should be asked when developing a Web
site, for example: Can users find what they need quickly and easily? Is there a site map or an
index? Do pages load quickly? Is the Web site easy to navigate?

Dimensions of IS Success Model Including ServQual and
Trust

IS Success

Many researchers attempt to identify IS success factors. Among them, the dimensions suggested
by Delone and McLean (1992) receive the most attention. Based on Shannon and Weaver (1949) and
Mason (1987), they postulate a multidimensional model of IS success. Shannon and Weaver (1949)
define three communication levels: technical, semantic, and effectiveness (on the receiver). Mason
(1978) re-labels it as production, product, and influence on recipient. By surveying 180 articles
on IS success, Delone and McLean (1992) propose that existing measures be classified into six major
dimensions: systems quality, information quality, use, user satisfaction, individual impact, and
organizational impact.

The first four metrics of Delone and McLean’s IS success model can be employed to evaluate
the quality and usability of an e-commerce Web site. Systems quality means availability, response
time, and usability. Information quality is completeness, relevance, and ease of understanding of
information. Use means the number of site visits and the number of transactions executed. User
satisfaction can be assessed as repeat purchases and repeat visits. The last two metrics refers to
the impact of IS on employees and firms, which may not be useful to evaluate outside customers’
perceptions on the Web site.

ServQual

The above discussed dimensions include only the system aspect of IS success but overlook the
human interaction aspect (Li, 1997). This deficiency can be supplemented by the factor of service
quality. Pitt et al. (1995) note that most IS effectiveness measures focus on the products rather
than the services and IS effectiveness will be mismeasured if IS service quality is not included.
Recently, most researchers agree that a service quality measure should be a part of IS success
(Kettinger & Lee, 1995; Li, 1997; Delone & McLean, 2003).

Service quality is commonly defined as the extent to which a delivered service level matches
customer expectations (Parasuraman et al., 1985). Parasuraman et al. (1985) identify ten dimensions
of service quality, and these dimensions are then reduced to five dimensions (i.e., reliability,
responsiveness, assurance, empathy, and tangibles), which are called the ServQual instrument
(Parasuraman et al., 1988). The ServQual instrument assesses the gap between what is expected and
what is delivered. Pitt et al. (1995) argue that ServQual is an appropriate instrument for
measuring service quality. Van Dyke et al. (1997) question the application of ServQual to IS
service quality. They argue that the instrument for service perception is better than that for the
difference score of the perception-minus-expectation. They propose it is preferable to use a
perceptions-only method.

The ServQual instrument has been tested in IS context (Pitt et al., 1995). The instrument
uses dimensions of tangibles (e.g., up-to-date hardware and software), reliability (i.e.,
dependable), responsiveness (i.e., prompt service to users), assurance (i.e., knowledge to do the
job well), and empathy (i.e., IS has users’ best interest at heart). There are some overlaps in the
conceptual domains of service and system quality. In the e-commerce context, service quality covers
assurance, reliability, and empathy while system quality covers tangibles and
responsiveness.

Trust

In the e-commerce context, the reliability dimension of ServQual can also be explained or
replaced by the critical concept of trust. Trust is crucial in the transactional buyer-seller
relationship of customers and e-vendors because of the risk and uncertainty in the online
environment (Reichheld & Schefter, 2000). Trust is the expectation that e-vendors will not
behave opportunistically by taking the advantage of the situation (Gefen et al., 2003). It is
customers’ beliefs that e-vendors will behave in a reliable/dependable, ethical, and socially
appropriate manner (Hosmer, 1995; Zucker, 1986).

Trust is defined as the subjective probability that customers believe that an e-vendor’s
technology infrastructure is capable of supporting transactions (Pavlou, 2001). Pavlou (2001)
posits that digital economy encourages the creation of institutional provisions to support
transactions among entities that lack the traditional face-to-face context. There are many
trust-building assurances provided by e-vendors, such as certification, https, guarantees, and
policies. Such trust provides favorable impersonal conditions conducive to transactional success
(Zucker, 1986). Gefen et al. (2003) believe that trust is critical because of the absence of proven
guarantees that e-vendors will not engage in opportunistic behaviors such as unfair pricing,
conveying inaccurate information, violations of privacy, and unauthorized use of credit card
information.