Public Policy Group Support Systems Part 2

2. System Design

This -'Public Policy Making Group Support System”, from a system and pragmatic perspective, is a modular design concept, integration the design process and illustrating of each hierarchy module.

(1)Modular Concept

This so-called module design is a top-down design method, whereby the system's functions are categorized. Initially, the system is divided into several major categories, then, these major categories are further divided into smaller modular functions, meticulously dividing into ever-finer utilities until every module has been broken down into its most simple and pure form. After completing this division process, all segments are linked together according to a hierarchy functional relationship forming a hierarchy diagram. The modular design concept of this "Public “Policy Making Group Support System" can be seen in diagram 7.

(2) Group Inference Engine Design

The inference engine comprises of numerous operating rules and principles, capable of inferring a rational conclusion from knowing how to make use of the knowledge base and from the data and knowledge extracted from the knowledge base The inference engine is a rules translator, it helps allocate the extracted knowledge to solving the problem. The following steps were adopted in the design of this group inference engine:

1. Coding experts and their disciplines

2. Selecting suitable experts:
Based on contents of the policy issue, select suitable experts to carry out-group inference

3. Collecting expert listed data: After choosing suitable experts from the above tw individual experts' political ideas and compile stati identical to "Policy Delphi", the most important par of experts' opinions.

(3) Group Decision System Design
1. Analytic Hierarchy Process:
The main purpose of this analytic hierarchy process is the solving of complex policy problems, for operations flow diagram see diagram 8

2. Producing Policy Alternative
After AHP analysis, calculate the standard policy decision priority vectors, and determine the overall priority vector. If the policy decision problem is relatively complex, establish several goals and criteria at different levels under the policy decision objective. First, make use of AHP to ascertain individual and overall standard policy decision priority vectors, and, after deliberation, propose policy alternatives, proceeding with multi-attribute utility analysis (MAUT) to find the optimal policy alternative. When making policy decisions, this becomes the recommended policy alternative.

4, Conclusion

1. Research

The most important objective of this entire research project was to utilize information technology to support group experts in their public policy decision-making, and combining group support systems, expert systems and artificial knowledge to establish a "Public Policy Group Support System". Ultimately, the conceived system assists in case analysis and the searching out of a policy issue to implement hands-on policy decision simulation, as well as providing a detailed explanation of the system's operating procedure, testing and verifying feasibility Moreover, me system's internal sequential recorder is capable of recording even process in the operation, which can be play back later, providing users a review on every process in its policy making decisions.

In the design of this system, apart from using the concept of modularization and consideration of the system's later functional expansion, thought was also given to the user-friendliness of the operating interface. The system was, therefore, programmed for use in MS-Windows, using a diverse selection of data to display a variety of graphs, text, sound, images, etc. allowing users to easily and quickly understand the operating procedure. Therefore, this system has flexibility in its functional expansion capabilities, as well as being extremely user-friendly.

2. Major Contribution

(1) Introducing the concept of a group support system (GSS) to the public policy domain;
(2) Establishing a "Public Policy Making Public Policy Making Group Support System" theoretical model;
(3) Synchronous integration of GSS, ES and AI Information Technology to support public policy making;
(4) Introducing monitoring and learning concept to a system

3. Recommendations on Future Research Developments

(1) Information Technology

1. In pace with the growing worldwide internet and national information infrastructure technology, there’s a huge potential to develop and bring into full play the maximum utilization of Group Support Systems.

2. Research on interface technology and attentive development on "hand-writing recognition systems" and "speech input" to assist in the operation of group support systems.

3. Integration of expert systems and group knowledge bases to group support systems.

4. Artificial intelligence will be one of the future major industries, and its development will assist in strengthening the learning ability of group support systems

2) Establishing Experimental and Control Groups

1. Examining discrepancy between use and non-use of a group support system. Decision quality, policy efficiency, benefit-cost analysis, cost-effectiveness, member satisfaction, degree of communication and information sharing, etc. are all worthy of further research.

2. Influence of group size to group support systems

(3) Public Policy Aspect

1.Establish public policy Thinks

2.Provide new insights into traditional policy making processes,
rebuilding the policy-making procedure.

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