George Kontolemakis, Marisa Masvoula, Panagiotis Kanellis, Drakoulis Martakos
Department of Informatics & Telecommunications
National and Kapodistrian University of Athens
University Campus, Athens 15771
Abstract: If effectively utilized, modern technologies such as ontologies and software agents hold the potential to
inform the design of the next generation of E-Hubs. In terms of their evolution, we argue that taxonomies
as tools hold the danger of stifling innovation as they may implicitly impose boundaries on the problem
domain. We proceed to use one that is well-referenced in the literature and identify a number of issues that
can be seen as limiting factors, proposing a generic and agent-mediated architecture that holds the potential
of addressing them.
E-Hubs bring together buyers and sellers in real-time
trading communities at relatively low cost (Rosson,
2000). Taxonomies are classification systems that
allow one to uniquely identify something. One of the
best known examples is the science of systematics
which classifies animals and plants into groups
showing the relationship between each (Bishop et
al., 1995). Any classification should be presented in
such a form that stakeholders can use to specify the
identity of the system they seek as a solution to a
problem and to prescribe the base functionality that
will guide the design. But taxonomies can also stifle
innovation by limiting the views of the stakeholder,
imposing boundaries through categorization
schemes and levels of abstraction that can and must
be challenged. In this work we take as a starting
point a well-referenced taxonomy for E-Hubs
(Kaplan et al., 2000) and identify a number of issues
that demand our attention.
The next section contains the issues that drive our
h towards the proposition of a generic E-Hub
architecture which is presented in the third section.
The paper concludes by presenting the next steps in
our research endeavors.
Regarding the taxonomy in (Kaplan and Sawhney,
2000), we have put forward four issues that can be
used for arguing against the underlying assumptions
behind it and in effect question any claims to future
applicability that it may have. Issue 1:
(2000), states that E-Hubs are not as open as they
could or should be. Every company has different
types of products and services and a different
customer base to deal with. Even if they have the
same product categories, they may present them
differently to their clients emphasizing on special
attributes that they only amongst the other hub
participants choose to provide. In addition, the
particular taxonomy differentiates E-Hubs to those
that deal with manufacturing and to those that deal
with operating products. Simply stated, if a
company transcends these categories in the physical
world, it cannot do it in the virtual. Issue 2:
Virtually every hub or marketplace created focuses
on either B2B or B2C business transactions. An
integration of both categories would yield a generic
e-hub made for all stakeholders across the process
flows and covering every step of the way from
production to consuming. It is important to note that
the taxonomy proposed by Kaplan and Sawhney
only covers B2B E-Hubs. Issue 3a:
Categorizing E-
Hubs as in the particular taxonomy may strip away
any flexibility that a prospective participant could
have used in order to evaluate his options to engage
or not. In systematic sourcing the conditions are not
favorable for small participants since they cannot
achieve the same terms and discounts as large users
who buy large quantities through the E-Hub. In spot
sourcing the conditions are not favorable for large
clients since even if they buy a lot from the E-Hub
they sometimes during the auction may end up
buying to a steeper price than a small business.
Accordingly, an E-Hub offering both spot and
systematic sourcing may help to avoid the
Kontolemakis G., Masvoula M., Kanellis P. and Martakos D. (2005).
In Proceedings of the Seventh International Conference on Enterprise Information Systems, pages 297-300
DOI: 10.5220/0002539202970300
appearance of phenomena that relate to the ‘chicken-
and-egg’ problem. Issue 3b:
Long-term contracts in
current E-Hub systems are negotiated on fixed
product prices. The negotiation schemes of E-Hub
architectures offer no allowances regarding the
users’ wish and freedom in generating a new offer or
have any influence over the “game rules”. Again, an
integration of both categories can help the user to be
flexible to market dynamics and either harden or
soften his/her negotiation stance to his advantage.
Issue 4:
According to (Kaplan et al., 2000), E-Hubs
can be either neutral or biased. In the physical world
there exists no such distinction. A business can be
neutral to some and biased to others. Buyers as well
as suppliers are needed for the system to function
and neutrality can be decided according to the
chosen tactics and strategies.
In the next section we propose a prototype of a
generic and agent-mediated E-Hub architecture that
was designed so as to confront the above issues
perceived as impediments to the evolution of open
and truly flexible E-Hubs. What we imply is that
our research path followed probes us to question the
applicability of existing taxonomies and revisit their
underlying assumptions.
To be effective in achieving their set objectives, E-
Hub users must analyze a wealth of information,
negotiate over multiple contracts, and execute a lot
of complex transactions on the Internet
(Kontolemakis et al., 2004). To this end, agents play
a significant role and many systems such as those
proposed by Debenham (2000) and Shen et al.
(2002) are beginning to incorporate them in their
Agents are clearly identifiable solving entities with
well-defined boundaries and interfaces and have
evolved from Multi-Agent Systems (MAS).
The main areas related to E-Hubs where agent-based
functionality can be applied are ontologies, advising
services and negotiation. By ontology we mean the
specification of the knowledge structures used to
define concepts and the relationship among those.
The primary focus when designing the ontology
model of an E-Hub is to satisfy those design
requirements that will enable its extension, share and
reusability both within and outside the boundaries of
the hub infrastructure (Albers et al., 1999). The
advising service an agent is to deliver requires the
consideration of a multiplicity of design issues and
parameters such as intent (the goal of the advising
agent), timing (when the agent generates advice),
intrusiveness (how proactive the agent is in
interrupting the user's workout), presentation (how
the advice is displayed to the user), and content (the
information the advice contains) (Chin-Ming Fu,
1997). Negotiation is the process by which a group
of agents come to a mutually acceptable agreement
(Jennings et al., 2001). In Figure 1, we show how
the three basic components of an E-Hub come
together and interact defining as a whole the
functionality of the system. The first component is
the Generic Product Ontology which is created so as
to cover every possible product or input
combinations which can be stored in the systems
database. The second is the Negotiation Agent, who
is responsible for managing the negotiation process
between the buyer and seller using ontology
attributes and for reaching a mutually acceptable
promise which is then fulfilled through the logistics
services. The third one is the Advising Agent, who
uses the ontology to help the user to accomplish a
specific task, keeping track of user movements and
bringing together users that share common interests
according to their profile.
A flexible and generic E-Hub architecture can
mutate from one taxonomy classification to another.
We have expanded and build upon the model
presented in (Albers et al., 1999) so as to cover
every aspect of a modern electronic hub whilst
striving to keep it as simple and hence as reusable as
Figure 1: A Generic and Agent-Mediated E-Hub Architecture
Buyer (Or group of buyers) Seller (Or group of sellers)
Product Ontology
Figure 2: Generic Product Ontology
In Figure 2 the expanded product model is depicted.
The Identifier is the ID along with some details for
recognition of the product. The Physical property
corresponds to a single material when we talk about
manufacturing inputs or to a collection of raw
materials or other products so that when synthesized
an operating input is created. So both manufacturing
and operating products are supported by the
ontology (issue 1). The Functional property refers
to the possible applications of the product. The
Presentational property is related to the way in
which the product is represented to the user (Albers
et al., 1999). As described in (Niem, 1999), the latter
is accomplished by creating a 3D model from
images taken as inputs. The Product Category
property provides the vendor with the ability to
classify his product into a broader category. Each
category is assigned with specific properties called
Special Attributes. The Special Attributes property
includes alternate characteristics or meta-attributes
of a product. This property contributes to producing
a flexible system since additional product attributes
are not predefined by the ontology, but can be
created at run-time by appropriately configuring the
Product Category. In conjunction with the physical
property it provides the flexibility to the user to
promote his product or service in any way that he
sees fit (issue 1). Strategy is a property that helps
the user to define his deal-making tactics based on
the products’ negotiable attributes. Profiling is a
property that allows one to define the characters of
the people for whom the product will most likely
have greater appeal.
According to the proposed architecture buyers can
be sellers and vice versa as shown in Figure 1 by the
fact that both buyers and sellers are part of the E-
Hub. This means that an industry can buy raw
material from the same hub that it later sells the final
product. This integrates B2B and B2C E-Hubs in an
open and generic platform that everyone can
participate (issue 2). Taking into account that in
manufacturing inputs quantity determines price, the
ontology offering the Special Attributes property can
accept ranged space attributes other than price, here
quantity. In this way the E-hub supports both
vertical and horizontal business purchases (issue 1).
With the help of the Profiling attribute of the
ontology and the agent implementing it, the spot
sourcing oriented E-Hub can easily be mutated into
systematic sourcing for a specific buyer (issue 3a,
4). This, for example, can be accomplished when
the customer buys a lot from a) a specific seller that
can provide him with better terms relating, for
example, to price, and b) from not a specific seller
but from the same hub where for example having
met predefined sales levels, better prices quotes can
be offered regarding fulfilment services, etc.
The advising agent keeps track of the buyers’
movements and for the first case it informs the seller
for the specific customer and proposes him to
contract the customer with better terms. If the seller
agrees, the discount is applied every time the two
sides come to a mutually accepted agreement
through negotiation (issue 4). This mechanism
favours the vendor in the sense that he receives all
the orders and the buyer in the sense that he enjoys
better terms. If the contracts that take place consider
a discount percentage on the upper or lower limit of
the negotiation ranged space attributes and the
negotiation is still used then the buyer will still
receive lower prices. But if something unexpected
happens causing the product’s negotiable attribute
(usually price) to rise, then the seller would have a
chance to apply hard utility factors and functions on
the product that will enable him not to loose money
and to keep his client happy since he will still buy
cheaper than the others (issue 3b
For the second case, the advising agent informs the
corresponding logistics department for the discount
in shipping fees (sending them the reduced fee that
should be retrieved from his/her account) as well as
the buyer for the discount taken place. This favours
the buyers since the E-Hub lowers its
transaction/fulfilment costs. Sellers can also be
favoured in this E-Hub. The advising agent keeping
track of all the transactions within the marketplace
can also decide whether a specific seller can enjoy a
reduction in the rental space of the marketplace. This
decision is taken by considering not only the value
of the goods sold but also the frequency of sales. If
Used For
3D Representation
User VS Product
Special Attributes
User-Defined attributes
Product Category
Product Belongs To
Tactics & Scores
the reduction is decided, the seller is informed and a
new contract must be signed for the changes to take
effect. So the proposed architecture could prompt us
to classify it as neutral but offering at the same time
the flexibility to become either forward, reverse and
biased (issue 4).
Last but not least, the ontology of this E-Hub
employs the ability of Reverse Aggregation since
many buyers can join together as one, to accomplish
better terms. We believe that when only reverse
aggregation is employed by an E-Hub it is unlikely
to have all buyers as possible customers. With the
architecture mentioned above, even if Reverse
Aggregation is employed, large purchasers can enjoy
better terms on their own without having to ally with
other smaller purchasers. The element client (C) is
embodied in the hub without any vitiation of the
B2B procedure (issue 2). So, everyone can
participate in this E-Hub (issue 2). This can be again
accomplished by the advising agent, who can match
sellers or buyers according to their profile and bring
them together to form a group of sellers or a group
of buyers. If this group is formed, it is then treated as
a single buyer or seller and can enjoy better terms
according to the aforementioned contracts.
Taxonomies are tools that can be used to classify
objects and thus, implicitly or explicitly, impose a
frame around the problem domain addressed by
research. We argue that although such framing can
be useful for guiding research by narrowing the
boundaries of the domain, they should also be
approached with caution since any such restrictions
may stifle innovation. Taking such a taxonomy as a
starting point, we have identified a set of issues that
to our opinion are obstacles to the evolution of
modern E-Hubs and proposed an architecture that
addresses them.
Our research falls under the design-science
paradigm in information systems research where
knowledge and understanding of a problem domain
and its solution are achieved by engaging in the
actual process of building the desired artifact and
applying or putting it into use.
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