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

Recent E-Commerce Research

E-commerce continues to face the challenges posed by immature technologies and the absence of
necessary standards. Still, the Internet promises significant improvements in performance for
companies. A company who is first in its industry to deploy cutting edge technology and innovative
business practice will enhance the probability of its success. Moreover, beyond the enterprise of a
single company, business partnerships and alliances can be formed to collaborate on the design,
engineering, production, delivery, and maintenance of products and services. Sadeh and Lee (2000)
explored the usage of middleware to facilitate the decision-making process for virtual companies.
They conclude technology can improve business performance, although it takes time for the benefits
of such technology to take effect.

Lee and Benbasat (2003) investigate the effects of image size, fidelity, and motion on
attention and memory. They applied Reeves and Nass’ studies on human-media interaction to the Web,
using empirical data to validate the theory. A laboratory experiment was conducted to test the
influence of three Web design features — image size, fidelity (clarity of an image), and motion.
They found that the higher visual fidelity of an image, the greater attention users give to it.
Fidelity, or clarity of image, then is especially important for pictures of products. Lee and
Benbasat also discovered that motion on a Web interface creates greater user attention than a
static Web interface. They conclude that an interface with a combination of higher fidelity and
motion leads to a greater attention span than an interface with only one of these characteristics.
Finally, the size of the image has an impact on memory. Practically, getting customers’ attention
and then keeping it has an impact on memory of the Web site, and perhaps ultimately on purchase
behavior.

Stylianou et al. (2003) explore the relatively under-researched country – China. With its
booming economic development, China will likely become the largest Internet and telecommunications
market. By developing a descriptive profile of Chinese business managers with respect to their
awareness of the technological infrastructure as well as their perceptions and attitudes regarding
e-commerce, they provide insight into the future of e-commerce in China. However, the current
Chinese e-commerce infrastructure presents a barrier against its development, and software
development is far behind that in the US. China’s e-commerce has its own characteristics. For
example, COD is the most common method of payment in China, whereas in the US payments are rendered
in the form of credit cards, debit cards or via a third party.

In addition to the quantitative analysis of e-commerce, some researchers use qualitative
methods to evaluate e-commerce. Iivari and Janson (2003) investigate four aspects of e-commerce in
the automobile industry: strategic understanding of electronic commerce (e-commerce), technological
understanding of e-commerce, maturity of the Web site supporting e-commerce, and e-commerce
developmental strategy. Their work supports the conjecture that both strategic understanding and
technological understanding influence developmental strategy and Web site maturity.

Web design has been examined from the perspective of consumer and organizational buying
decision processes. Huarng (2003) suggests that understanding the consumer buyer decision process
and organizing e-commerce sites to support this decision-making process could increase purchase
potential. Pandya and Arenyeka-Diamond (2002) perform a SWOT analysis on e-tailing and identified
key success factors. For the B2B decision-making process, Sadeh and Lee (2003) investigate e-supply
chain effectiveness. Pandya, Hackney et al. (2002) studied how electronic commerce revolutionizes
organizations’ business models by its impact on the value chain. Kendall and Kendall (2001) discuss
the potential for e-commerce to be a profitable and sustainable business model.

Trust as a dimension of e-commerce is of particular interest to researchers because trust is
such a significant factor in consumer behavior and in business relationships. Research has
demonstrated that online purchase intention is positively correlated with trust. Four factors
relate to trust in the virtual marketplace: perceived market orientation, site quality, technical
trustworthiness, and the extent of the user’s Web experience. Perceived site quality is positively
correlated with perceived market orientation and trustworthiness towards e-commerce (Corbitt et
al., 2003). Trust and risk are negatively associated so effective risk reduction tactics improve
trust. Positive word-of-mouth, money-back warranties and relationships with well-known business
partners are effective in reducing perceived risk. They improve trust, and hence strengthen
customer loyalty.

Whitworth and Moor (2003) take the concept of cyber-trust even further. They argue that
“legitimacy” is a necessary condition for trust, and that “trust is necessary for productive
community interactions like e-commerce.” Whitworth and Moor assert that legitimacy depends on a
property analysis — who owns what in IS design. Such a systematic “legitimacy” analysis could apply
to a wide variety of social software, they suggest, from chat rooms to virtual realities. It could
lead to future global standards for virtual social environment design, standards that are perhaps
necessary for the emergence of a global online community.

Technology Acceptance Model (TAM)

The most influential research model used in technology
adoption is the technology acceptance model (TAM) developed by Davis (1986). The original TAM model
consists of three constructs: perceived ease of use, perceived usefulness and attitude. Later Davis
et al. (1989) expanded Davis’s original TAM to include external variables as antecedents of
perceived ease of use and perceived usefulness, and attitude and intention as mediator variables of
actual use. TAM posits the following relationships: perceived ease of use is positively related to
perceived usefulness; perceived usefulness is positively related to usage; perceived ease of use is
positively related to usage. Researchers have validated TAM in various technological settings and
concluded that TAM is a valid model in explaining users’ behavior and predicting users’ attitude
toward a technology. (See
Figure
12-1.)

Figure 12-1: Technology
acceptance model (TAM)

Major Findings with TAM

Gefen (2003) examined habit as another variable that contributes to online shopping
intention. He confirmed the TAM model and concluded habit alone can explain a large proportion of
the variance of continued use of a Web site. Heijden (2003) empirically investigates an extension
of the TAM model to explain individual acceptance and usage of Web sites, specifically, perceived
ease-of-use, usefulness, enjoyment, and their impact on attitude towards using, intention to use
and actual use. A new construct, “perceived visual attractiveness” of the Web site influences
usefulness, enjoyment, and ease-of-use.

Chau and Lai (2003) examine the factors contributing to a consumer’s adoption of Internet
banking. They found that personalization, alliance services, task familiarity, and accessibility
have significant influence on perceived usefulness and perceived ease of use, which, in turn, were
found to be important factors in fostering a positive attitude toward accepting the
services.

O’Cass and Fenech (2003) use key consumer characteristics such as opinion leadership,
impulsiveness, Web shopping compatibility, Internet self-efficacy, perceived Web security,
satisfaction with Web sites, and shopping orientation to understand the adoption of Web retailing
by Internet users. They found that Internet users’ perceived usefulness and perceived ease of use
are affected in various degrees by opinion leadership, Web shopping compatibility, Internet
self-efficacy, perceived Web security, impulsiveness, satisfaction with Web sites, and shopping
orientation. Zhang and Prybutok’s (2003) work further confirms the validity of TAM in an online
context. By extending and applying TAM to consumer Web shopping experience, they find that TAM is a
generic model and can be used to predict consumer behavior. Legris et al. (2003) conclude that TAM
is a useful model, but that still other important factors need to be identified and added into the
model. They cite in particular variables related to social and human changes.

Online Marketing

Marketing concepts and strategies are as important for e-commerce as for any other business
model. The goals remain the same: a Web site must capture the attention of potential customers and
then convert viewers into buyers. Research confirms the importance of basic marketing tactics.
DiClemente and Hantula (2003), for example, confirm the positive effect of discounts in an online
shopping mall. There is one major area of difference, however, between online and traditional
commerce: a heightened concern for privacy. Byrne (2003) proposes the importance of seeking
permission from Web site visitors before sending personal or promotional packages in online
marketing. Milne and Rohm (2003) suggest that managers need to be reminded that consumer privacy
concerns associated with the mobile Internet and mobile commerce are different from those in the
traditional and online marketing contexts.

Consumers dislike pop-up advertisements and other intrusive and annoying marketing
solicitations. Consumers also want to control their personal information. These two marketing
elements, the use of customer information and the use of intrusive promotions, are related in the
consumer’s mind. Consumers feel their privacy is violated by unsolicited marketing communications,
especially product offers, and they feel the same about the collection and use of information that
identifies them personally. They fear that their personal information will be misused. Thus, online
marketing needs to respect consumers’ concern and protect consumers’ interests. One alternative
would enable consumers to opt out of future marketing activities. Such an option might build trust
and ease consumer’s worries. It could also generate positive word of mouth, which in turn reduces
perceived risk and builds trust.