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Transcript of A research framework for Web-based open decision support systems
A research framework for Web-based open decision support systems
Yong Xiea, Hongwei Wanga,*, Janet Efstathioub
aInstitute of Systems Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinabManufacturing Systems Group, Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
Received 28 October 2002; accepted 1 December 2004
Available online 15 December 2004
Abstract
With the prevalence of the Web, most decision-makers are likely to use the Web to support their decision-making. Web-based
technologies are leading a major stream of researching decision support systems (DSS). In this paper, we propose a formal definition and a
conceptual framework for Web-based open DSS (WODSS). The formal definition gives an overall view of WODSS and creates a uniform
research framework for various decision support systems. The conceptual framework based on browser/broker/server computing mode
employs the electronic market to mediate decision-makers and providers, and facilitate sharing and reusing of decision resources. We also
analyze the basic functions and develop an admitting model, a trading model and a competing model of electronic market in WODSS based
on market theory in economics. These models reveal the key mechanisms that drive WODSS function efficiently. Finally, an illustrative
example is studied to support the proposed ideas.
q 2004 Published by Elsevier B.V.
Keywords: Decision support systems; Electronic market; Decision resources; Web-based DSS
1. Introduction
Although it appeared many years ago, the development
and application of decision support system (DSS) is rather
limited. The main factors that cause this situation are:
†
095
doi
*
Poor maintainability: A decision-maker must take
pains and time maintaining the DSS instead of
concentrating on decision problems. Measures should
be taken to shield decision-makers from burdensome
maintenance.
†
Poor flexibility: DSS are often application-specific, and itis difficult to update the DSS according to decision-
makers’ needs. Because of the lack of flexibility, the
application of DSS is greatly restricted.
†
Less reusability: Due to the restrictions of the frame-work, many existing DSS resources such as data, model
and knowledge are unable to be reused by decision-
makers. Developers have to spend much money and
0-7051/$ - see front matter q 2004 Published by Elsevier B.V.
:10.1016/j.knosys.2004.12.001
Corresponding author.
E-mail address: [email protected] (H. Wang).
human resources in repeated work. It is important to
make decision resources reusable in order that all
potential decision-makers share decision resources
conveniently.
The increasing use of the Web in DSS is providing an
attractive framework to overcome the current limitations.
As the Web becomes more and more popular, many
researchers and organizations are beginning to focus on
applying Web technologies to enhance DSS applications
[2,4,12]. On the other hand, the enriched decision resources
such as decision models, On-line Analysis Process (OLAP)
tools and data mining tools are bringing enormous business
opportunities to DSS developers. They can benefit from
publishing and sharing their decision resources on the
Internet. Apart from simple information, decision resources
will be able to assist users to solve some complex
problems. Because of the heterogeneousness of various
decision resources, it is greatly necessary to describe them
in open standard format such as Extensible Markup
Language (XML) that is commonly used on the Web,
which facilitates easier searching and management of
decision resources. In order to investigate the viability of
Knowledge-Based Systems 18 (2005) 309–319
www.elsevier.com/locate/knosys
Y. Xie et al. / Knowledge-Based Systems 18 (2005) 309–319310
Web-based DSS, we should focus on the following
questions:
†
What is the appropriate research framework for Web-based DSS?
†
How can providers publish and share their decisionresources on the Web?
†
How can consumers or decision-makers find and accesstheir preferred decision resources to assist them to solve
decision problems?
To address the above problems, we propose a research
framework for Web-based open decision support systems
(WODSS). In this framework, we design an electronic
market for decision resources that consists of four
components: consumer, electronic market, provider and
decision resources provided by provider. The electronic
market offers infrastructure services to help providers
register decision resources and facilitate consumers to
search and utilize decision resources to solve problems. We
choose the Web and browser/broker/server computing mode
as the platform of WODSS because they are valuable and
viable for performing rapid and flexible access to infor-
mation for both consumers and providers. The major
innovation of our work is that we present a formal definition
and a new research framework based on browser/broker/
server computing mode for WODSS. We also develop an
admitting model, a trading model and a competing model of
electronic market in WODSS and reveal the mechanisms
that drive WODSS function efficiently.
The rest of the paper is organized as follows. First, we
take an overview of some related work in Section 2. Then
we propose a formal definition of WODSS and compare it
with the conventional DSS in Section 3. In Section 4, we
give a new research framework based on browser/broker/
server computing mode and design an electronic market to
mediate decision-makers and decision resource providers.
We also analyze the transaction process of WODSS in
Section 5. In Section 6, we introduce the three models of
electronic market in WODSS. We also present an
illustrative example to clarify the ideas discussed in the
above sections in Section 7. Finally, we conclude with a
summary and future research directions in Section 8.
2. Literature review
Before we discuss our work, we need to review the
related literature to give an overview of Web-based DSS. It
can be traced back to 1995, a series of papers on using the
Web and Internet for decision support were presented at the
third international Conference of ISDSS (the International
Society for Decision Support Systems) in Hong Kong. In the
next year, a DSS/WWW Workshop was held as part of the
IFIP Working Group 8.3 Conference on ‘Implementing
Systems for Supporting Management Decisions: Concepts,
Methods and Experiences’ in London [12]. From then on,
many researchers and organizations were engaged in Web-
based DSS and made a lot of achievements. The famous
known works are DecisionNet by Bhargava [1] and Open
DSS by M.Goul [6]. DecisionNet aims to establish an
electronic market for decision technology that consists of
consumers, providers and brokers mediating consumers and
providers. The market helps to bring together and provide
services for matching consumers, providers and decision
technology. Goul et al. proposed a set of protocols called
Open DSS Protocols for DSS deployment on the Internet. In
contrast to DecisionNet, it connects consumers and
providers via the open DSS protocols instead of broker in
DecisionNet. As for the decision resources concerned, Web-
based DSS are to provide data services [10] and computing
services or model services [3]. Jeusfeld et al. [5] advanced
this idea to decision components on the Internet and
designed a script language to connect the distributed
decision components. Additionally, a few researchers pay
attention to the Web support mechanisms for DSS. Power
[4] investigates the support mechanisms and identifies five
types of them: data-driven, model-driven, knowledge-
driven, document-driven and communication-driven. Srid-
har [7] focused on the data-dialog-model framework of DSS
and explored in detail how Web technologies can improve
the functions of the three components, respectively. He then
presents taxonomy of major types of Web-based decision
support. Ba et al. [8] designed a client–broker–server
framework to achieve information integration in Web-based
DSS. Kersten [11] developed the INSPIRE prototype to
study and conduct negotiation via the Web in DSS. The
above researches reveal that many researchers set forth their
work about Web-based DSS from different points of view.
We prefer to present a fundamental research approach of
WODSS and propose a formal definition and new frame-
work. Based on this framework, we also bring forward some
key issues about WODSS.
3. The main ideas and formal definition of WODSS
3.1. Main ideas and some definitions
There is no commonly accepted definition about Web-
based DSS now. Power gave a definition of Web-based DSS
[4]. The main ideas are that decision support systems are
services on the Web. These services could be accessible to
anyone with a problem and an Internet connection.
Decision-makers only use ‘thin’ client browsers such as
Internet explorer to support decision-making. Some
researchers prefer that Web-based DSS are DSS
implemented on the Web. We propose Web-based open
DSS with two core ideas: ‘electronic market’ and ‘open’. An
electronic market for decision resources acts as an
intermediary between decision-makers and providers. It
helps providers register decision resources to the electronic
Y. Xie et al. / Knowledge-Based Systems 18 (2005) 309–319 311
market and facilitate consumers to search and utilize
decision resources to solve problems. An electronic market
offers a good platform for sharing and reusing decision
resources, and it also provides planning and executing
services, which shield decision-makers from troublesome
maintenance.
‘Open’ is another key idea of WODSS. Viewed from
system theory, a system should be open for getting new
information from the environment in order to evolve into
new states. ‘Open’ in WODSS has the three meanings as
follows:
(1)
Electronic markets are open to decision-makers andproviders. They can apply for legal users of electronic
markets easily. This makes it more convenient for users
to share their decision resources.
(2)
Decision resources are described in open standardformat such as DC (Dublin Cores) and XML [20],
which facilitates easier search for users or software
agents.
(3)
Environment of electronic markets is open in order toallow more electronic markets to join it.
Some terms such as decision resources, electronic market
have been used in previous sections, but now we need to
precisely define them in order to elucidate Web-based open
DSS expediently.
Definition 1 (Decision resources) Decision resources are all
information resources that can support decision-making.
They help users to solve some problems or make decision.
For simplicity, we identify four types of decision resources
in this paper: database, models, knowledge and documents.
Definition 2 (Consumer or decision-maker) A consumer or
decision-maker is a user who needs and wants to use certain
decision resources to help him to solve problems or make
decision. Decision-maker can benefit from applying
decision resources to support decision-making.
Definition 3 (Provider) A provider is a user who offers
decision resources and publishes them to attract decision-
makers for using the decision resources. Provider can
benefit from offering decision resources to decision-makers.
Definition 4 (Electronic market) An electronic market is a
market infrastructure on the Internet where providers
register and publish their decision resources and decision-
makers search and acquire decision resources supporting
decision-making. Electronic market acts as the intermediary
to match decision-makers and providers and offers a good
platform for them to share and transact decision resources.
3.2. Formal definition of WODSS
With the main ideas and some useful terms defined
above, we then propose a formal definition of WODSS.
Definition 5 (WODSS)WODSS is a seven-tuple of the form:
WODSS Z hP; S; x;E; d;D; li (1)
where
P is a set of providers, PZ fPijiZ1; 2;.; ng.
S is a set of decision resources. Four types of decision
resources: database (DBS), models (MS), knowledge
(KS) and documents (DS) are usually concerned by
researchers. This causes the appearance of multiple-
bases system framework for DSS.
E is a set of electronic market, EZ fEijiZ1; 2;.; kg. In
general, electronic markets are organized to form
marketplace in order to extend and enhance the functions
of one electronic market. Two forms can be applied to
organize electronic markets, peer-to-peer and hierarch-
ical, which are described in detail in Section 4.3.
D is a set of decision-makers, DZ fDijiZ1; 2;.;mg.
Different kinds of decision-makers require different
supporting mode and user interface for DSS. This is
the user operating mode research framework for DSS
explained in the next section.
x: P!S/2E is a registering function that shows
providers P registering their decision resources S to the
electronic market environment E. Where P!S is the
Cartesian product of P and S, 2E is the power set of E.
d: E!S/2D is a utilizing function that manifests
decision-makers D querying, searching, integrating and
utilizing decision resources S from electronic markets
environment E to solve decision problems.
l: D/P is a feedback function. It represents that
decision-makers feed back their suggestions to providers
in order that they improve the quality of their decision
resources. The feedback function makes WODSS a
closed-loop system, which adapts it to the decision-
makers’ various needs.
3.3. Advantages of WODSS
Compared with the traditional DSS infrastructure, the
formal definition of WODSS creates a uniform research
framework for decision support systems. The traditional
research work about DSS developed in two ways: resources
organizing mode and user operating mode. The former
emphasizes the elements and structure of decision support
systems, focusing on ‘system’. But the latter pays more
attention to the user interface of decision support systems,
focusing on ‘support’ for decision-makers. The comparison
between traditional DSS and WODSS is shown in Table 1.
Resources organizing mode includes three kinds of
research framework:
(1)
Multi-base systems (MBS): Spargue brought forwardtwo-base system framework for DSS [14] in 1980,
which consists of a database and its management
Table 1
WODSS comparison with traditional DSS
Traditional
DSS
WODSS
P D S E x d l
Resources
organization
mode
MBS Multiple resources base Multiple resources base
integration
KBS Problem-solving knowledge
base
Reasoning and problem-sol-
ving
DSC High-level
decision-makers
Decision resources center,
experts group
Centralized problem-sol-
ving, experts cooperation
User operat-
ing mode
GDSS Group users Group management and
communication
Group cooperation and
decision-making
ODSS Organization users Organization management
and communication
Organization coordination
and decision-making
DDSS Distributed users Distributed management and
communication
Distributed problem-solving
ADSS Various users User knowledge base User interest and pattern
learning
Message feedback
Y. Xie et al. / Knowledge-Based Systems 18 (2005) 309–319312
system, a model base and its management system, and
user interface system. Based on this framework, many
researchers extended the two-base framework to
multiple bases, such as knowledge base, method base,
document base etc. As WODSS are concerned, the set
of decision resources S consists of multiple decision
resources, while d should support integration of them.
(2)
Knowledge-based systems (KBS): Bonczek presentedthis framework in 1981 [13]. It focuses on the knowl-
edge base of system and draws on reasoning and
problem-solving technology in artificial intelligence to
decision support systems. Then a new branch of DSS—
intelligent DSS(IDSS) came into being. To realize KBS
in WODSS, S should include problem-solving knowl-
edge, while d must support reasoning and problem
solving.
(3)
Decision support centers (DSC): It is a decisionresource center with a group of experts to aid high-
level decision-makers to make emergent or momentous
decisions [15]. It adopts centralized approach that is
different from distributed DSS.
User operating mode pays more attention to user
‘support’ interface for DSS. It includes four kinds of
research framework:
(1)
Group decision support systems (GDSS): It supportsgroup users to cooperate and make decisions. GDSS
provides a communicative and interactive platform for
individual members that need to work in a group to
reach a decision.
(2)
Organization decision support systems (ODSS): Itsupports organization users to coordinate and make
decisions. ODSS provides an organization-wide plat-
form to enhance and facilitate the decision process for
organization members by network and communication
technologies. Especially in ODSS, related decisions are
made among organization decision-makers according to
their roles and responsibilities in the organization.
(3)
Distributed decision support systems (DDSS): It sup-ports distributed decision-makers to cooperate and
make distributed problem solving. In DDSS, decision-
makers are distributed physically in different hosts.
They make decentralized decision to some extent and
communicate through network.
(4)
Adaptive decision support systems (ADSS): Decisionresources S includes a knowledge base about decision-
makers’ interests, while d supports decision-makers’
interests learning and l feeds back decision-makers’
suggestions to providers who offer customized decision
resources thereafter.
From the above analysis, we can find that WODSS is a
general framework for DSS. Different kinds of traditional
DSS research branches can be realized by instantiating
WODSS in a certain way, as shown in Table 1.
Additionally, WODSS explicitly demonstrates the entities
and their relationship and establishes a useful foundation for
further work.
4. A proposed research framework of WODSS
4.1. Computing mode evolution of DSS
As the design objective of WODSS is to enable decision
resources shareable and accessible on the Web [9], it is very
important for WODSS to be with an open and flexible
framework. The computing mode plays a great role in the
framework [22]. In general, a typical DSS application can
be divided into three logic layers: user logic, business logic
and data logic, as shown in Fig. 1. As the three sub-system
framework for DSS is concerned, the dialog sub-system
manages user logic and man–machine conversation. The
model sub-system deals with business logic and fulfills
Fig. 1. The logic layer for a DSS application.
Fig. 2. Computing mode evolution of DSS.
Y. Xie et al. / Knowledge-Based Systems 18 (2005) 309–319 313
business tasks such as computing, reasoning, problem
solving, etc. The data sub-system deals with data logic. It
stores related dada in database for the other two sub-systems
and provides data access interface for them. The three logic
layers are often in different distribution ways, which forms
the computing mode of a DSS application.
In general, the evolution of computing mode in DSS
comes through four stages: single, client/server, browser/
server and browser/broker/server, as shown in Fig. 2. They
are described in detail respectively as follows:
(1)
Single: It is an isolated mode that is difficult to extendand integrate new resources, and the three layers are
integrated closely and centralized in a single host.
(2)
Client/server: It is a closed mode including client andserver. It runs in two ways: thin-client/fat-server and
fat-client/thin-server. Unlike single mode, the three
layers are distributed in client and server side in
client/server mode in order to enhance the flexibility
and extensibility of DSS application. When user logic
resides in client, business logic and data logic reside in
server side, it is termed thin-client/fat-server mode.
When user logic and business logic reside in client, but
Fig. 3. A framework for W
only data logic resides in server side, it is termed fat-
client/thin-server mode. Client connects with server via
specified network protocol. So those clients that are
incompatible with the network protocol cannot access
the server.
(3)
Browser/server: It is a less open mode based on opennetwork platform via the Web. It is a special thin-
client/fat-server mode with standard client—browser,
which facilitates decision-makers to apply decision
resources expediently without any other specific client
software. But in this mode, the browser should ‘know’
explicitly where the server is, namely, the IP address of
the server.
(4)
Browser/broker/server: It is an open and advancedbrowser/server mode with a broker to match browsers
and servers. In this mode, the browser need not ‘know’
explicitly where the server is because the broker does it
automatically. When a new server is created, every
browser will ‘know’ it from the broker as long as it
registers to the broker. So it is easier to integrate new
decision resources and extend to a more powerful
system in this mode. It is the right computing mode that
is fit for WODSS.
4.2. A research framework for WODSS
According to the formal definition introduced above, we
design a framework based on browser/broker/server com-
puting mode. It is shown in Fig. 3. The system consists of
four components: decision-makers, electronic markets,
decision resources and providers which respectively corre-
spond to the entities in the formal definition, and that the
relationships between these components manifest the
functions in the formal definition (all notations in Fig. 3
have the same meaning as that in the formal definition). The
key component of the system is the electronic market. It
serves as the broker between decision-makers and providers
and assists them to trade decision resources. Decision-
makers only use ‘thin’ client browsers to access decision
resources, while providers put their decision resources on
the server side and register them in electronic markets so
that decision-makers search and access them easily.
ODSS.
Fig. 4. Organizing mode of electronic markets.
Y. Xie et al. / Knowledge-Based Systems 18 (2005) 309–319314
We identify some basic functions of the electronic market
and describe them in detail as follows:
(1)
Electronic markets allow providers to register, updateand withdraw their decision resources.
(2)
Electronic markets allow decision-makers to search, listand select their appropriate decision resources.
Additionally, in order to offer transparent decision
support services to decision-makers, it is necessary for
electronic markets to provide planning and executing
services [10]. The planning services aim to employ
decision resources to make problem-solving plans for
decision-makers, and the executing services helps those
who have no necessary computing platform to execute
the plan on the remote platform.
(3)
Electronic markets allow decision-makers to feed backtheir suggestions to providers by e-mail, message board,
etc.
4.3. Organizing mode of electronic markets in WODSS
We have noted that the key component of WODSS is
electronic market (EM), but one market has some
limitations in scalability and serving for multiple users. So
extensibility is an important goal for the design of electronic
markets [10]. Two forms can be applied to organize
electronic markets, peer-to-peer and hierarchical, as
shown in Fig. 4. The electronic markets with a certain
organizing mode form a marketplace.
The two forms of segmented electronic markets over-
come the above limitations to a certain degree. In peer-to-
peer electronic markets, every market plays the same role.
Fig. 5. Sequence diagram for a tran
When a new electronic market joins, it will have the same
authority as others. In hierarchical electronic markets, on
the other hand, the market holds distinguished status
according to the hierarchy it belongs to. There is a child–
parent relationship between an electronic market and the
electronic market authorizing its admittance. Marketplaces
become a tree with a center market as the root node and the
others as offspring, just like Domain Name servers (DNS)
on the Internet. Once a new market joins the marketplace, it
will inherit the services of its parent with possible
extensions.
5. Transaction process of WODSS
The framework describes the structure of WODSS. In
this section, we also explore the dynamic characters of
WODSS and illustrate how it runs as expected. Dynamic
characters can be described as transaction processes. All
components in the framework are involved in a process, and
transaction series are described in a sequence diagram that is
shown in Fig. 5.
A whole transaction cycle consists of seven phases as
follows:
saction
Providers create or update decision resources.
Decision resources are registered in electronic markets
after standardization.
Decision-makers search their favorite decision
resources from electronic markets.
Electronic markets return searching results to
decision-makers.
Decision-makers access the appropriate decision
resources according to the returned results in .
Electronic markets will then make a problem-solving
plan. It can be executed remotely and the results are
returned to decision-makers. Alternatively, decision-
makers may also download decision resources and
execute the plan on their local machines.
Decision-makers feed back their suggestions to
providers by e-mail or message board after they
process of WODSS.
Table
Basic
WODS
d
x
l
P and
Y. Xie et al. / Knowledge-Based Systems 18 (2005) 309–319 315
employ the decision resources so that providers
improve their decision resources according to
decision-makers’ needs.
6. Some functions and models of electronic markets
in WODSS
6.1. Fundamental functions of electronic markets in WODSS
The former definition and framework describe the
structure of WODSS. In the following subsections, we
will analyze the function models of WODSS based on its
structure. As the electronic markets play an important role
in WODSS, most functions of the WODSS are related to
them. We identify the basic functions of electronic markets
in WODSS that are shown in Table 2.
6.2. Some models of electronic markets in WODSS
In order to explore the decision resources trade process
between decision-makers and providers, and to analyze the
markets mechanisms in WODSS, it is necessary to create a
model that enables efficient functioning of the electronic
markets. We draw on market theory in economics [17,21]
and create three models: admitting model, trading model
and competing model. The admitting model describes the
required qualification of the entities to participate in the
electronic markets environment. The trading model illus-
trates how providers and decision-makers trade decision
resources via electronic markets. The competing model
reveals the profit mechanisms that drive the electronic
markets to function efficiently. The following subsections
discuss the three models in detail respectively.
6.2.1. Admitting model
The admitting model aims to check and ratify the entities
applying to participate in the electronic markets environ-
ment. The entities include providers, decision-makers,
decision resources and electronic markets, just as mentioned
2
functions of electronic markets in WODSS
S Functions Meanings
Search Search the ex
List Look over th
Select Select the ap
Plan Make a probl
Execute Provide a pla
Export Providers reg
Withdraw Providers ret
Update Providers upd
Feedback Decision-mak
D Register D and P regi
Deregister D and P dere
Authorize D and P are
in the formal definition of WODSS. We have earlier noted
that WODSS are open systems for different entities, but they
do not mean that any entity is allowed to join the electronic
market environment without any restriction. A series of
rules are needed to direct the actions of an entity. So we
provide the admitting model to meet the requirements. It can
be studied from the following three aspects:
(1)
pecte
e list
propr
em-s
tform
ister
ract d
ate d
ers f
ster t
giste
autho
Users admittance: Providers and decision-makers must
be identified by electronic markets and must promise to
comply with the market rules before they are legal users
of electronic markets and acquire services from them.
Those who are bankrupt in reputation will be eliminated
from electronic markets.
(2)
Decision resources admittance: Decision resourcesmust be described in an open standard format such as
RDF/XML that is commonly accepted on the Web [18,
19]. A standard description about decision resources
facilitates easier searching and management. It is
necessary to note that Resources Description Frame-
work (RDF) is very useful for the representation of
metadata in the form of XML documents. RDF is a
common infrastructure to encode, exchange and reuse
structured descriptions of decision resources on the
Web, which results in semantic integration of decision
resources even though they are heterogeneous at the
physical level.
(3)
Electronic markets admittance: As introduced inSection 4.3, WODSS can be viewed as the federated
electronic market systems organized in term of peer-to-
peer or hierarchical mode. When a new market applies
to join the system, it will be granted a certain authority
according to its grade and the organizing mode of
electronic markets.
6.2.2. Trading model
If we regard the admitting model as creating rules of
electronic markets, then trading model depicts the trading
process between providers and decision-makers. It consists
of two sub-models: trade driving model and trade matching
d decision resources according to the related keywords
of registered decision resources
iate decision resources from list or the searching results
olving plan according to the certain decision resources
for decision-makers to execute the plan
and publish decision resource on electronic markets
ecision resources from electronic markets
ecision resource according to decision-makers’ suggestions
eed back their suggestions to providers by e-mail, etc.
o electronic markets to be legal users
r from electronic markets
rized by electronic markets to access the appropriate resources
Y. Xie et al. / Knowledge-Based Systems 18 (2005) 309–319316
model. Any trading model is derived from the two sub-
models.
(1)
Tabl
Com
Driv
mod
Pull
Push
Trade driving model: It specifies the promoter who
initiates the trade. If decision-makers initiate the trade,
then it is called a pull model. If providers initiate the
trade, it is called a push model. Now most of applications
on the Web follow the pull model. Decision-makers must
spend much time searching appropriate resources to
meet their demands. Correspondingly, the push model is
more convenient for decision-makers because providers
actively push the right resources to decision-makers
according to their interests.
(2)
Trade matching model: The matching function is one ofthe most important functions of electronic markets [21,
23]. It describes the bilateral relationship between
providers and decision-makers. When a trade starts,
providers and decision-makers compete and pursue their
private utility. There are four possible ways that elec-
tronic markets can match providers and decision-
makers:
(1) One-to-one: One decision-maker to one provider. It
serves for a decision-maker to make simple decision.
The decision-maker only needs decision resource
from one provider to support decision-making.
(2) One-to-many: One decision-maker to many provi-
ders. It serves for a decision-maker to make complex
decision. The decision-maker needs different
decision resources from more than one provider to
support decision-making.
(3) Many-to-one: Many decision-makers to one provider.
It serves for many decision-makers with a decision
resource center that is regarded as the provider.
Decision support center (DSC) runs in this way.
(4) Many-to-many: Many decision-makers to many
providers. It serves for GDSS, ODSS, and DDSS,
etc.
e 3
paris
ing
el
mode
mod
(3)
Some popular trading models: A certain trading modelcomes into being when the driving model and matching
model are decided. Liang gave six popular trading
models in the electronic trading [16]. These trading
models are barter, bargaining, bidding, auction, clearing
and contract. We analyze these models and obtain the
comparison results shown in Table 3.
With bidding as an example, it is a pull trade model that
involves a decision-maker and many potential providers.
ons of six popular trading models in WODSS
Matching model
1 to 1 1 to N N to 1 M to N
l Barter,
bargaining
Bidding Clearing,
contract
el Barter,
bargaining
Auction Clearing,
contract
The decision-maker compares the received bids and chooses
the best. A typical bidding process includes:
(1)
The decision-maker broadcasts his demands and callsfor bidding after specifying the detailed criteria.
(2)
Many bidders submit their bids according to the criteria.(3)
The decision-maker chooses the best bid that meets therequirements.
(4)
The decision-maker pays for the bid and gets thecorresponding decision resources to support his
decision-making.
6.2.3. Competing model
As the key component of WODSS, electronic markets
play an important role in facilitating the exchange of
decision resources, information and payments. The behavior
of decision-makers, providers and electronic markets is
motivated by their desire to maximize their private utility.
But in order to make electronic markets run normally, it is
necessary to rationalize profit and loss of everyone.
Competing model can archive this goal and motivate
WODSS to function efficiently via three objectives.
(1) Decision-makers utility maximization. It is important
to meet decision-makers’ demands and find the most
appropriate decision resources to maximize his utility. It
will attract more and more decision-makers to register to
electronic markets and stimulate the market demands. The
mathematical model is
UDjZ
Xk
iZ1
½UiðSiÞKPiðSiÞO0 (2)
where UDjis the utility of decision-makers Dj. iZ1,2,.,k is
the number of decision resources that Dj needs to support his
decision-making. Si is an item of decision resources. Ui(Si)
is the utility of Si for Dj, Pi(Si) is the price that Dj must pay
for employing Si. It is required that UDjbe greater than zero,
which guarantees the basic satisfaction of decision-maker
with his utility. Obviously, the greater the UDjis, the better it
is for the decision-maker. In real-life situation, it is a
decision-makers’ utility maximizing problem. The decision-
maker should make choice whether to buy a decision
resource or not according to its price and expected value.
When the expected value is higher than the price, he will
buy the decision resource, or else, he will not. This is the
decision rule of decision-maker in real situation. This model
stimulates the demands for decision resources.
(2) Providers satisfaction. In order to stimulate providers
to create and publish their decision resources on electronic
markets, it is required that providers benefit from the
decision resources offered by them. The model can be
described as
UPjZ
Xk
iZ1
½PiðSiÞKCiðSiÞO0 (3)
Fig. 6. The hierarchical structure of education institution in China.
Y. Xie et al. / Knowledge-Based Systems 18 (2005) 309–319 317
where UPjis the utility of provider Pj, iZ1,2,.,k is the
number of decision resources that Pj provides, Si is an item
of decision resources, Pi(Si) is the selling price for Si, Ci(Si)
is the cost for creating Si. In this model, UPjmust be greater
than zero, which guarantees provider satisfaction with his
utility. This model stimulates the supply of decision
resources. In real-life situation, it is a decision resources
pricing problem. Provider should decide the price of his
decision resource according to its creating cost and market
demands. Creating cost is the reserve price, the decided
price should not be lower than this price and it also
should not be too high. The price is also affected by the
decision-makers’ demands and their expected utility of the
decision resource. If the price is too high to exceed
the decision-maker’s expected utility, he will not buy the
decision resource, and then both the provider and the
decision-maker will obtain zero profit. This is an unfavor-
able outcome for both of them. But we should indicate that
for the same decision resource, different decision-maker
may have different expected utility, in this situation,
discriminatory pricing strategy is a good choice and
available method to decide the price of decision resource
[24]. Actually, most providers register their decision
resources to electronic markets and offer free use for a
specified period. This measure facilitates decision-makers
to know clearly about the decision resource without paying
any cost, which makes for attracting more and more
decision-makers. On the other hand, it facilitates providers
to acquire decision-makers’ demand preferences and
actualize discriminatory pricing strategy by collecting
their accessing record and suggestions. The feedback
function in WODSS plays a great role in realizing these
functions.
(3) Electronic markets satisfaction. Without electronic
markets, the previous two objectives cannot be achieved. On
the other hand, electronic markets will not function
efficiently without the participation of providers and
decision-makers. In order to promote the creation of
electronic markets, it is also necessary to guarantee the
profit of these intermediaries. The model can be described as
UEkZ
Xm
iZ1
CDiC
Xn
jZ1
CPjC
Xq
lZ1
UðSlÞKCkðEkÞO0 (4)
where UEkis the utility of electronic market Ek, CDi
and CPj
are membership fees for decision-makers and providers,
respectively, U(Sl) is the services charge for trading decision
resource Sl, Ck(Ek) is the cost for creating electronic market
Ek. In real-life situation, it is a membership-registering
problem. It is obvious that the more registered providers and
decision-makers there are in Ek, the more profit it will gain.
Additionally, the increase of trading volume will also
contribute to more profit for electronic market Ek. UEkis
greater than zero, which guarantees electronic markets
satisfaction with their profit. This model stimulates the
creation of electronic markets and attracts them to join
the electronic markets environment. We also show from the
model that electronic markets should improve their service
quality to attract more and more users and take measures to
motivate them to trade more. This will provide much benefit
to electronic markets as well as to providers and decision-
makers.
In the above three objectives, the first one is the most
important because it is the engine for electronic markets in
WODSS, many DSS applications are driven by decision-
makers’ demands. In general, a pull model is fit for this kind
of electronic markets and the appropriate trading model is
bidding. As the second model is concerned, a push model
such as auction is the best for providers’ satisfaction. The
electronic market helps to achieve the first two goals and
benefits from the trading services that it offers for decision-
makers and providers, which guarantees its private profit as
described in the third model.
7. An illustrative example
To clarify the ideas discussed in the previous sections,
we give an illustrative example that the WODSS framework
is exploited to support national education planning in China.
The design objective of the project is to provide the Ministry
of Education (MOE) with a good platform to make long-
term education development plan in China. In this project,
the hierarchical markets organizing mode is adopted to suit
the natural structure of education institutions in China as
shown in Fig. 6.
For the convenience of depiction, we choose a scenario
with one municipality decision-maker and two county
decision-makers to illustrate how they cooperate to make
an education development plan for the municipality. In the
scenario, the municipality decision-maker Dm and the two
county decision-makers Dc1, Dc2 form a cooperative decision
group. Dm makes his decision on the basis of data or decision
plans from Dc1 and Dc2. He has two choices to achieve his
goal, makes the plan directly from the basic data or exploits a
uniting model to sum up the finished plans from Dc1, Dc2 and
forms the municipality plans indirectly. Firstly, we should
identify the components of WODSS in this scenario
according to the formal definition in formula (1):
†
DZ fDm;Dc1;Dc2g, where Dm holds higher status than Dc1and Dc2.
Y. Xie et al. / Knowledge-Based Systems 18 (2005) 309–319318
†
EZ fEm;Ec1;Ec2g,where Em is the municipality electronicmarket and Ec1, Ec2 are the county electronic markets,
respectively. They are physically distributed and serve the
users in different levels.
†
PZ fPm;Pc1;Pc2g, where Pm is the decision resourcesproviders of the municipality electronic market and Pc1,
Pc2 are providers of the county electronic markets,
respectively.
†
S includes data (basic data for education plan and somemidterm data for finished plan stored in database), models
(uniting model for summing up the finished plans and
forecasting models for students, teachers, schools,
education outlay, etc.) and help documents. The finished
plans derive from basic data and forecasting models.
Then according to the transaction process introduced in
Section 5, providers register decision resources to the
corresponding electronic markets, and the decision
resources distribution status in electronic markets can be
described as follows:
In Em: Uniting model Mu, forecasting models
Mf Z fMf _stu;Mf _tea;Mf _sch;Mf _outg, where Mf_stu, Mf_tea,
Mf_sch, Mf_out, are forecasting models for students,
teachers, schools, education outlay respectively, help
documents DSm. They are all provided by Pm.
In Ec1: Forecasting models Mf 1Z fMf _stu;Mf _tea;Mf _sch;
Mf _outg that have the same schemes but different
parameters with that in Em, basic data DBb1 and midterm
data DBm1 of county, help documents DS1. They are all
provided by Pc1.
In Ec2: Forecasting models Mf 2Z fMf _stu;Mf _tea;Mf _sch;
Mf _outg that have the same schemes but different
parameters with that in Em, basic data DBb2 and midterm
data DBm2 of county, help documents DS2. They are all
provided by Pc2.
From the above introduction, we can find that the
demands for education plan of Dm drive the trade process
and many providers as well as Dc1, Dc2 take part in the trade.
Because Dc1, Dc2 also provide finished education plans of
the counties, they hold the dual roles of both decision-
makers and providers. Bidding model is the best trading
model to fit the scenario. So in the following, we focus on
how the bidding model facilitates Dm to make an education
plan for the municipality.
(1)
Announcing: Dm broadcasts his demands on Em andcalls for models and data to make the education plan for
the municipality.
(2)
Bidding: Many bidders including Pm, Pc1, Pc2 submittheir bids according to the criteria. The uniting model
Mu and forecasting models Mf from Pm can achieve the
goals of Dm. But on Em, there are neither necessary
finished plans for Mu nor necessary basic data for Mf to
complete the plan. So the new bids are produced and
transferred to Ec1, Ec2. On Ec1, Ec2, midterm data DBm1,
DBm2 that represent finished plans fit the uniting model
Mu, basic data DBb1, DBb2 are summed up to be the
basic data for Mf. So Dm is faced with two choices to
make the education plan for the municipality. One is
applying Mu to sum up the two finished counties plans
DBm1, DBm2, and the other is exploiting Mf to make the
plan based on basic data directly.
(3)
Awarding: Dm evaluates the two approaches with timeand cost to pursue maximal profit as in formula (2)
before he makes the choice. Finally, he chooses Mu to
sum up the finished plans DBm1, DBm2 and forms the
education plan for the municipality because this
approach is more time-saving and cost-saving.
(4)
Paying: Dm pays for Mu and the finished plans DBm1,DBm2 and gets the corresponding decision resources to
make the education plan for the municipality.
From the above scenario, we can find that WODSS
liberates decision-makers from weary maintenance and
offers a good platform for decision-makers and providers to
trade decision resources for their private profit. We also see
that it is very convenient to establish GDSS or DDSS based
on WODSS infrastructure.
8. Concluding remarks and future work
The technology underlying the Web is fast evolving. It
creates a major opportunity to improve the research of DSS
technology. Decision-makers are likely to use the Web to
support their decision-making. On the other hand, the
emergence of electronic markets for decision technology
also has a strong impact on the DSS theory and applications.
In this paper, we propose a new research framework for DSS
using Web technology (WODSS) and bring up many key
issues related to it.
The main contributions and highlights of this research
are: (1) It proposes a formal definition and a conceptual
framework of WODSS. The formal definition creates a
uniform research framework for various decision support
systems. And the conceptual framework based on browser/
broker/server computing mode employs the electronic
market to mediate decision-makers and providers, and
provides a good platform to facilitate sharing and reusing of
decision resources. (2) It develops an admitting model, a
trading model and a competing model of electronic market
in WODSS based on market theory in economics. These
models reveal the key mechanisms that direct WODSS
function efficiently and show how decision-makers and
providers make deal and benefit via WODSS.
The research provides guidelines for designing and
developing DSS on the Web. It is, of course, not without
limitations. Further efforts are needed to describe decision
resources in standard format for easier search and manage-
ment. How to integrate heterogeneous decision resources
Y. Xie et al. / Knowledge-Based Systems 18 (2005) 309–319 319
and make a problem-solving plan for decision support? How
to trade decision resources employing market competition
mechanism between providers and decision-makers in
electronic markets? All these issues are very important for
WODSS and worthy of deep investigations. We hope that
this paper will further increase interest in this important
topic.
Acknowledgements
The research was supported by the Teaching and
Research Award Fund for Outstanding Young Teachers in
Higher Education Institutions of Ministry of Education
(MOE), China.
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