Pulyamon Vihakapirom , School of Computer Science and Software Engineering Monash University , Melbourne, 3800. Email: yuipulyamon@hotmail.com
Dr. Raymond Koon-Ying Li, School of Multimedia Systems, Monash University, Melbourne, 3800. Email: Raymond.li@infotech.monash.edu.au
Globalization has brought changes to our business environment. Corporate business decision making now often involves groups that are dispersed globally. Traditional face-to-face meetings are costly and are not a practical means of multiple site organization. This research examines an alternative approach to support dispersed group decision making processes utilizing Internet technology. This paper outlines a framework to guide the development of a Multiple Criteria Group Decision Support System that can provide a synchronized meeting to geographically dispersed decision makers. A prototype, called Web-CDMS, was implemented to demonstrate how the framework should be applied and to highlight some issues that need to be addressed during the implementation.
Over the last decade, globalization has brought about changes in our business environment. Organizations must now often deal with multiple sites and geographically dispersed business associates and partners (Consejero, 1999). The corporate decision makers can be dispersed across multiple local offices as well as offices in different countries. Gathering decision makers from multiple places to join in a face-to-face meeting can be very costly. Costs include not only travel expenses, but also lost productivity (Drake et al., 1992).
Complicated business decisions often involve a number of conflicting alternatives evaluated against multiple criteria (Tabucanon, 1988). Globalization adds another layer of difficulty to the top of the already complex multi-criteria decision making problem. Fortunately, emerging technology, such as the Internet, is now mature enough to provide a solution. This paper is to present a framework, using web technology, designed to provide a real-time collaboration among dispersed groups to handle their multiple criteria decision making (MCDM) problems. The framework could be used to guide the development of a multi criteria decision making system supporting distributed decision makers (DGDSS).
Existing literature was surveyed to establish a clear definition for the DGDSS, the MCDM method to be adopted and salient features that are required for the DGDSS to facilitate its usability. The findings were then used to develop the presented framework. A prototype called Web-CDMS was developed to demonstrate the application of the framework and to highlight some of the issues that needed to be addressed during the implementation of the required system.
Decision Support Systems (DSS) emerged in the 1970s and is a computer-based system designed to actively interact with an individual decision maker in order to assist her/him to make better decisions based on information obtained (Keen & Scott-Morton, 1978; Sprague & Carlson, 1982). Group Support System (GSS), which are closely related to DSS, are computer-based information systems employed to facilitate collaborative work within groups (Jessup & Valacich, 1993).
In the early 1980s, Group DSS (GDSS) was developed to support the group decision making process (Gray, 1987). It amalgamates techniques from both DSS and GSS. GDSS is a combination of communication, computer software, decision support technologies and structure group techniques (e.g. normal group and Dephi techniques) to assist decision makers in formulating and generating the optimal solution for their unstructured problems. (See Figure 1) (DeSanctis & Gallupe, 1987).
Distributed Group Decision Support System (DGDSS) are GDSS designed to facilitate decision making amongst dispersed groups. According to Tung & Turban (1998), there are two types of Distributed Group Support System (GSS): synchronous DGSS and asynchronous DGSS. Similarly, there are two types of DGDSS: synchronous DGDSS and asynchronous DGDSS. This paper focuses on the synchronous DGDSS in which all distributed group members can interact with each other in real time mode.
The development and delivery platforms of DSS/GDSS are now shifting to the Web environment (Dennis & et al., 1996; Shim & et al, 2002). A Web-based GDSS refers to a computerized system that provides decision tools and decision support information to its users who are accessing it via a Web browser (e.g. Netscape Navigator or Internet Explorer). The salient benefits of a Web-based environment for GDSS are the reduction of geographical barriers, improved delivery processes, and reductions to operating cost. As the focus of this research is a synchronous DGDSS, a web-based approach is the logical choice for implementing such a system.
Business decisions are regularly complex. There are often a set of alternatives that needed to be evaluated against a set of sometimes conflicting criteria to determine an optimal solution. Such a decision making process can be referred to as Multi-Criteria Decision making (MCDM). As the aim of the proposed DGDSS is to assist business executives in their joint decision making, the system therefore should support MCDM.
The problem that the Multi-criteria Decision Making process aims to solve is evaluating a set of alternatives in terms of a number of criteria which is conflicting in nature. According to Triantaphyllou ( 2000), although this is a practice problem, there are a few methods available and “their quality is hard to determine”. The MCDM methods that authors have considered are Simple Multi-Attribute Rating Technique (SMART), Multiple Attribute Utility Theory (MAUT), and Analytic Hierarchy Process (AHP).
AHP was chosen for its ease of use and its successful track records in Industries. MAUT required a decision maker to specify the best and worse case for each criterion in order to generate the utility function (Olson 1996). SMART is a simplified form of MAUT (Edwards and Newman, 1982) and the decision maker has to follow the same procedure as in MAUT. AHP uses a simple method of pair-wise comparison of alternatives against criterion. AHP is widely applied successfully in a variety of industries. Examples include location planning of airport facilities and international consolidation terminals (Min 1994a, 1994b), large and complex project such as the “Silverlake Project” (Bauer, et al. 1992) and software development (Finnie et al., 1992; Partovi amd Hopton 1994).
The Analytic Hierarchy Process (AHP) was developed in the early 1970s by Thomas L. Saaty (Saaty, 1980). It provides decision makers with a method to indicate his/her decisions by weighing the evaluation criteria and making pair-wise judgments of a set or subset of alternatives (Hanne, 2001). AHP can be used to handle complex situations (tangible, intangible, quantitative, and qualitative factors) within a multiple criteria decision problem. AHP can also support a group of decision makers. Geometric means of individual judgments can be used to aggregate group preferences. AHP has successfully been applied in a range of fields, such as a plan to allocate energy to industries; designing a transport system for the Sudan; and designing future scenarios for higher education in the United States (Saaty, 1990).
A decision maker will start by brainstorming to find out all the related criteria, as well as all the alternatives, in order to structure the decision hierarchy. Both quantitative and qualitative criteria are handled. The pair-wise comparison technique utilizing a 9 points scale will assist the user to rank his preferences between two objects within each level of the hierarchy. The 9-point rating scale is easy to understand and easy to deploy in making decisions (Saaty, 1995). Since the 9-point scale can be interpreted as a linguistic sentence, it is therefore easier for decision makers to weight the importance objectively between two considered objects. The consistency of the judgment can also be validated by calculating the consistency ratio (C.R.) and the inconsistency index. The final priorities can then be calculated and the result will provide the ranking of the alternatives. AHP is very easy to use and a powerful MCDM technique. The main merit of AHP is that the users do not have to understand the intricacy of the complex mathematics behind the technique before they can use it. AHP has therefore been adopted as the MCDM technique behind the system
The literature survey conducted by the authors revealed that there are two areas of interest that are unique to web-based DGDSS and they are anonymity (Gavish & Gerdes, 1998) and mediator (Clawson & et al., 1993).
According to Er & Ng, (1995), anonymity is one of the most widely discussed issues of GDSS, with specific emphasis on its effect on group decision outcomes (Er & Ng, 1995). They have identified the following advantages and disadvantages of anonymity for group meetings.
Advantages of anonymity for group meetings are:
Disadvantages of anonymity for group meetings are:
The above disadvantages are related to the undesirable behaviours and selfishness of team members thereby contributing to lengthening the decision making process. The advantages, on the other hand, are related to the fact that they can contribute to the quality of the decision. The authors believe that the quality of the outcome is more important and, therefore, anonymity is an important consideration to be taken into account when implementing a DGDSS. When a web-based approach is used, anonymity will be relatively easy to be incorporate into the system.
According to Bui (1987), types of GDSS based on DSS-user interactions can be classified into six possible types (See figure 2).
Type 6 architecture represents “distributed problem solving” (Bui, 1987: p41) or decentralized group decision making, where all group members are probably dispersed in different locations. It is therefore the typology that is appropriate to this research. Within the proposed system, there are a system mediator and a human mediator.
The system mediator provides two functions. Firstly, it support the control structure (i.e. the connection of an individual DSS) and process (i.e. how individuals communicate with each other) of communications. Secondly, it facilitates the human mediators to gather and synchronize results, identify individual dissimilarities as well as common interests, and to create new issues and alternatives. The system mediator provides assistance to a “human mediator” (Bui, 1987: p45) to evaluate the group decision situation and to monitor the GDSS. The human mediator can remain neutral while assisting the group to resolve an argument, but can also make a judgment in any conflict among decision makers. A GDSS mediator should have planning and designing skills, communication skills, and the ability to be flexible. Furthermore, he should be able to select, prepare, and deploy appropriate support technologies (Clawson & et al., 1993).
Fuller & Trower (1994) summarized the socio-technical roles of a human mediator as: Initiator / contributor, recorder, opinion seeker, harmonizer, Information giver, compromiser, elaborator, gatekeeper, coordinator, standard setter, observer / commenter, evaluator / critic, Follower, Energizer and Procedural technician.
The objective of this research to develop a framework to guide the development of a Distributed Multiple Criteria Decision Support Systems in which communication within a distributed group is synchronous and distributed (“Same Time” and “Different Place”).
The framework proposes system architecture derived from the GDSS type 6 of Bui (1987). AHP is the adopted technique used to support the decision making process. Once participants contribute their pair-wise judgement for a current decision issue, all individual judgements will be automatically aggregated as the group judgement. When all decision issues are resolved, group judgements accumulated will be automatically synthesized to provide the final ranking for all alternatives under consideration. Anonymity and system mediator are the embedded features of the system. The system requires a human mediator as operator.
Technically, the proposed framework outlines a web-based system that is based on client-server architecture (see figure 3). The major components of the system are:
The features embedded within the framework are derived from the discussions on DGDSS, AHP and web-based systems in previous sections. Real time collaboration on a web-based system requires real-time control and monitoring facilities. A system mediator (locking mechanism) is included to provide the control facility. A hierarchical decision model, pairwise comparison techniques, and aggregated overall group preference are features that have been adopted from the underlying principles of AHP discussed in the previous section. To enhance the quality of the decision outcomes, anonymity is provided for decision makers.
The monitoring feature provides the display of all judgments submitted by group members in real time. Conferencing services (e.g. Netmeeting) can be used to provide a real-time discussion among group members to supplement the display function. These factors allow group members to obtain feedback, clarifications, and commitment from other group members on their judgments. The proposed system, however, can still be used when the conferencing services are not available. When conferencing services are used, the server providing the services must be capable of maintaining the anonymity of the users.
Although there are some drawbacks to anonymity, it can encourage group members to make their decisions without worrying about political ramifications.
Ensuring collaboration among participants is a major concern for all synchronous meetings. In Face-to-Face meetings, human facilitators using visual cues are able to control the decision process. However, in the online meeting environment, human facilitators cannot use visual cue to make sure that all participants are working together. Therefore, a locking feature is required on the system to prevent a participant from moving on to the next step before all decision makers have agreed on the current step. Once everyone agrees with the current judgment, the system should then allow all participants to move to the next step in the decision making process together.
The major benefit of having a human in a synchronous meeting, (Face-to-Face and Distributed meetings), is the increase in the effectiveness of a meeting session. Online meetings relying solely on a system mediator to provide the control function, may involve an unnecessarily long waiting time before the whole group can advance together to the next stage in the decision making process. A system mediator may also not have the intelligence capabilities that a human has to make judgements to interrupt and restart the current stage of the process. A human mediator helps to avoid or resolve these issues. The human mediator can also provide conflict resolution, a gatekeeper function and policing duties.
The system utilizes AHP to help users to handle their decision making in a systematic way. Within the system, the group can define their problem as a hierarchical structure of criteria and alternatives. Using a 9-point scale, criteria are first compared in pairs and then by comparing each pair of alternatives against a criterion. Geometric mean is used to aggregate the overall group preferences from preferences of each group member. The Eigen vector method is employed to synthesise all group preferences to arrive at the final decision.
The following are the major benefits of the proposed framework:
There are some limitations and they are:
This session presents a prototype called Web-CDMS, implemented based on the proposed framework (Vihakapirom, 2002).
The implementation of Web-CDMS is based on client-server architecture. Macromedia Cold Fusion (Forta & et al, 1998), a web application development tool, is employed to develop the prototype.
As shown in figure 4, there are three categories of users in Web-CDMS:
The system flow chart of Web-CDMS is illustrated in figure 5. Web-CDMS allows users to participate in two modes of decision making: individual decision mode and group decision mode. The group mode and individual mode share the basic decision making module. Additional processes for group decision mode are shown in figure 8 and are indicated by the broken-arrows. The system will aggregate all decisions from participants to arrive at group decisions or overall preferences.
The user interface of Web-CDMS is designed to support collaboration among participants and assist users to carry out pairwise comparisons simultaneously. There are three key areas within the user interface design:
The major function of the monitoring panel is to broadcast current statuses related to the current pairwise comparison decision in real-time.
The benefits of the monitoring panel are as follows:
The pairwise comparison panel employs a slide bar and an inverted button to allow users to enter their decision values. The slide bar provides a good way to allow users to enter “rating scale value” and the inverted button enables only integer numbers to be entered. The pairwise comparison entry panel and the monitoring panel must operate together (See figure 7). Participants use the 9 rating scale to enter their pairwise comparison judgments. As soon as participants input their decision value, the updated decision value will be shown on the Monitoring Panel. Since cooperation among participants is a major concern, the system automatically locks the screen in order to prevent any participant from moving to the next issue independently. When all participants have confirmed their judgments, the final status of the monitoring panel can be changed to “Yes” by the human mediator. All participants are then allowed to move to the next pairwise comparison by clicking the refresh button followed by the next button.
The human mediator has the responsibility of coordinating and facilitating the interactions between participants thereby enhancing the performance of group decision making. The mediator’s panel has two extra features (See figure 8). When all participants confirm and agree in their decisions, the mediator uses the final button to change the final status field of the monitoring panel to “Yes”. This will unlock the system from the current pair-wise comparison process. Participants are then allowed to move on. The second feature is provided to allow resetting of all the current values, and the mediator will use this function at the beginning of the decision session or when all participants want to restart.
This section demonstrates a hypothetical case on how to deploy Web-CDMS for group decision-making. The scenario is to select a new store site for an ice-cream company. Decision makers consist of three managers who are currently in different states. There are three alternative locations. The three managers jointly agreed that the criteria are: Visibility, Competitors, Customers, and Rental.
Decision Model: Select the best site for a new ice-cream store (See Figure 9).
The example scenario has both qualitative (visibility competitors, and customers) and quantitative (rental) criteria. There are a total of 19 pairwise comparisons for each participant in this decision model. The following are screen snapshots of the pairwise comparisons between customers and rental criteria (see figure 9).
The decision makers in this model are John (the mediator) Amy and Peter. Figure 10 shows all participants’ decision values. Figure 11 shows that John has made the group judgment final by pressing the final button. It can be seen that the final status field in the monitoring panel now became “Yes”.
Figure 12 presents the overall group preferences of three managers. The overall group preferences show that location 1 is the first priority location; location 2 is the second, and location 3 is last.
The above example demonstrates that the proposed framework can be implemented.
In the new global economy, decision making will occur across multiple physical locations more frequently than ever before. Such decision making is inherently difficult. Specifically, there are three main difficulties: interactions amongst multiple decision makers; dealing with decisions under multiple criteria; and involving decision makers who are physically located in different sites.
This research presents a framework that can be used to guide the development of a system which can address all of these difficulties simultaneously. The concepts supporting the proposed framework are derived from research into three disciplines: GDSS, MCDM, and Web-based System. AHP, a well-known MCDM method, was chosen for this framework. The architecture of the proposed framework, together with its features, were presented. Benefits and limitations of the framework were discussed.
A prototype system, called Web-CDMS, exhibiting all of the key components of the framework was developed and demonstrated. The purpose of developing Web-CDMS is not only to prove that the framework can be implemented, but also to illustrate some issues that need to be considered during the implementation of such a system.
Due to time and resource constraint, this research, however, does not attempt to validate the framework. It is therefore proposed that the Web-CDMS should be tested in a real business setting. The feedback and experimental results should be collected and used to provide suggestions on how to improve the framework. In addition, the following are areas within the proposed framework that can be improved or extended.
A number of research studies (Hackman & Vidmar, 1970; Marsden & Mathiyalakan, 1999) attempted to determine the optimum number of group members that would bring about maximum effectiveness (i.e. achieve the consensus) and efficiency (i.e. time spent). Marsden & Mathiyalakan (1999) suggested an optimum group size of five, using decision quality, decision time, productivity, participation, and alternatives generated and alternatives discussed as the five indicators. Literature surveys indicate that there are no research projects aimed at determining the optimal group size for virtual group decision making. The system developed using the proposed framework could be used to facilitate research in this area.
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