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 it

is 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: wang@robots.ox.ac.uk (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 decision

resources on the Web?

†

How can consumers or decision-makers find and access

their 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 and

providers. 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 standard

format 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 to

allow 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 forward

two-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 presented

this 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 decision

resource 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 supports

group 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): It

supports 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): Decision

resources 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 extend

and 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 and

server. 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 open

network 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 advanced

browser/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, update

and withdraw their decision resources.

(2)

Electronic markets allow decision-makers to search, list

and 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 back

their 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 resources

must 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 in

Section 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 of

the 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 model

comes 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 calls

for 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 the

requirements.

(4)

The decision-maker pays for the bid and gets the

corresponding 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 Dc1

and Dc2.

Y. Xie et al. / Knowledge-Based Systems 18 (2005) 309–319318

†

EZ fEm;Ec1;Ec2g,where Em is the municipality electronic

market 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 resources

providers 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 some

midterm 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 and

calls for models and data to make the education plan for

the municipality.

(2)

Bidding: Many bidders including Pm, Pc1, Pc2 submit

their 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 time

and 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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