Information Technology Reference
In-Depth Information
Araujo and Araujo (2003) classified risks taken in EC transactions into two categories. Technology
related risk that includes security, privacy, and integrity and business related risk that include misuse
of personal information and incorrect fulfilment of transactions. Interface web design and usability
and ease of navigation have also been found to influence user behaviour and trust towards EC websites
(Basso et al, 2001; Hu et al, 2004; Riegelsberger & Sasse, 2001). Web retailers use eye-catching graph-
ics not only to grab a user's attention but also to convey competence and professionalism. A model
developed by Matthew and Turban (2001) acknowledges the importance of both network technology
and other parameters such as merchant factor and third party certification factor. Meanwhile, Cheung,
Lee and Matthew (2000) recognize the legal framework role in creating a trusted environment in the
EC setting. They also recognize the role of individual trust propensity in determining the level of trust
required before someone is ready to commit in a trust relationship. This trust propensity is influenced
by individual personality traits, culture and experience (Jarvenpaa, Tranctinsky, & Vitale, 2000). Fuzzy
logic is used to model and evaluate trust in EC and some systems will be summarised in the following
subsection.
f uzzy Logic in electronic Commerce
Akhter et al. (2005) developed a fuzzy logic based system for assessing the level of trust in B2C EC.
In their model, trust (T) is composed of three variables which are security (S), familiarity (F) and the
Website's design layout (D) hence T = f(S, F, D). In addition, they have also used competitiveness (C)
in the evaluation of the business transaction. Hence the business transaction is a function of trust and
competitiveness and formulated as L B2C =g(T, C). However, in their model they are not clear on what
factors they use to evaluate each of the three variables S, F and D. They assume that users by just using
a Website can decide if the trust is high, average or low with regards to these three variables. Studies
on the use of Websites design for example to convey trust are well documented and the characteristics
well defined (Basso et al., 2001; Hu et al., 2004; Riegelsberg & Sasse, 2001).
Manchala (2000) proposes a model for the measurement of trust variables and the fuzzy verifica-
tion of EC. He highlights the fact that trust can be determined by evaluating the factors that influence
it, namely risk. He defines cost of transaction, transaction history, customer loyalty, indemnity, and
spending patterns as the trust variables. Each variable is measured using semantic labels. His notation is
focused on defining when two trust variables are related by an EC trust relationship (ECTR). Using this
ECTR, a trust matrix is constructed between the two variables and a trust zone is established. He also
describes a method for trust propagation and the construction of a single trust matrix between vendor
and customer that governs the transaction. The problem with Manchala's model is that it is (1) unclear,
which variables should be used by default for the best results; (2) if it is actually possible for a computer
to automatically establish that two variables are related by an ECTR. In his definition, he mentions a
semantic relationship between the variables, but neglects to mention how this fact will be specified to the
computer so that evaluation can be automated; and (3) if ECTR merging will scale in the face of large
trust matrices. These concerns are all related to the viability of implementing his model. These models
do not support a theoretic approach to trust and they are not suitable for e-commerce (Tyrone, 2003).
Fuzzy logic was also used for product classification in EC (Mohanty & Bhasker, 2005). When faced
with a choice of many products, users need to make a decision on which product to purchase. Taking
the case of a car purchase, the authors used five variables which are the cost, re-sale value, mileage,
comfort, and maintenance cost. A typical statement would then be to purchase a car with a price around
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