Collaborative Decision Making For Site Development Analysis

Collaborative Decision Making For Site Development Analysis

3.0 Methodology
The main aim of this study are to evaluate, develop and propose alternative mechanism to support the collaboration process in decision making that utilize spatial and non-spatial data. The question of interactivity between man-man and man-data are considered the main basis of importance.

This study adopted the exploratory and development approach in its research framework. Through this approach the phenomena during the process of decision making was studied and an alternative model for the proposed methodology formed and its effectiveness analysed. Qualitative and quantitative methods were employed in the research design. In the quantitative method primary and secondary data were collected, processed and analysed and used in the formation of the model and prototype. The ensuing design was the analysed qualitatively to suit the needs and stages in decision making. Hence the methodology of the study focused on aspects of exploration, document and development to suit the various stages in the study that is collection, data processing, development of alternative model and development of experimental prototype.

In the first stage, exploratory aspects were used to seek primary data from respondents feedback by using the stratified random sampling method. Here the practical method adopted include support instruments, procedures, decision makers and data including general criteria used when making certain group decision making involving spatial data were collected. Personal interviews and questionnaires were conducted involving respondents like EPU (Economic Planning Unit), UPEN (State Economic Planning Unit), statutory bodies and local councils. Through this approach, settlement procedures, relevant parties, support instruments and agency roles in the processes can be identified. Data were recorded in the database and categorically prioritise.

In the second stage, alternative mechanism were outlined and formed to suit the study needs. This mechanism covers various aspects of data management, processing, output, sharing and data manipulation. The hardware, software and implementation procedures were amalgamated and developed into a system.

In the third stage, case study were conducted to test the proposed mechanism. Specific data were collected by digitizing, keyboarding and the transformation process conducted for consistency in interfacing, from various relevant agencies to suit the referenced cases.

In the fourth stage, the qualitative evaluation effectiveness to three aspects were analysed. The aspects are; the interaction capability with data, interaction capability among decision makers during the process of decision making and the capability of processing proposal and concluding the finding with respect to the method used.

A multi-station method is used in the design where decision makers from different locations are connected in a cyber environment. Three main questions in the decision making such as iterative, interactive and participative were considered in the methodology development to support the interactive issue.

A case study namely SKOLA (Collaborative Systems) with motto “cyber society of decision makers” was undertaken to evaluate the proposed concept. The term KOLA was a short form from word ‘collaborative’ which mean a collective effort in making decision. Motto used is in-line with the collectively approach used by decision maker from various agencies in a cyber environment to share a common data using server-client concept (Refer to Diagram 3.1). Visual Basic Script (VBS) programming language is used in designing web page at interaction center. VBS is being used widely in the cyber environment and supported by Microsoft Corporation. Cyber environment will create a collaborative interaction among decision makers and interaction can take place without time, place and other constraints.

Diagram 3.1 Interface Design Between Decision Makers
To promote interaction, field design introduced by Shy (1994) was used. He introduce this approach while designing a City of Music as a center of interaction among multi-racial community. In this approach, all decision making activities are made through central debate arena which is equipped with decision making tools and the facilities is attractive, easy-to-use, freely communicate and can be use at any time. A Heuristics concept is being introduced as a decision making mainframe. Meanwhile BORDA, MCE, AHP and SWOT concepts were used to facilitate decision analysis.

In this case study, consideration will be given to the requirement of decision makers and surrounding environment of MPSP while approving a proposed development plan. Decision making procedures by MPSP was used as a case study due to the similarity in the decision making concept in this research and the availability of digital spatial and non-spatial data. Many related agencies were involved in the process of decision making in MPSP. This study analysed on the flood impact of the proposed development project. The impact analysis involved with spatial and non-spatial data and requirement of other parties. The proposed methodology is shown in Diagram 3.2.

The study is focusing on the issues on the approval of the proposed development site on Lot 2703 Mukim Seberang Perai Selatan (Diagram 3.3). As the study area is not directly affected by the flood, therefore the probability to flood became dominant. Pertaining to this study, only geographical characteristics will be focused.

Data were collected at the central station and GIS is used to manipulate spatial and non-spatial information. Several processing procedures need to be conducted in advance to establish a uniform and consistent database to suit the study requirement.

Diagram 3.2 Proposed design model for MPSP decision maker in approviing proposed development.

Diagram 3.3 Proposed development site
Three agencies related with flood issues were selected to analyse relevant characteristics pertaining to flood impacts. Seventeen (17) characteristics were selected to be used in the regional and local analysis. Decision makers are required to select six main characteristics only. Selection can be made through web site at the interaction center arena. BORDA method is being used in this stage and Table 3.1 shows the finding.

Table 3.1: Characteristics Selection by Decision makers

Diagram 3.4 shows the combined diagrams used in the flood risk analysis based on the selected characteristics. Drainage flow analysis is used to identify alternative drainage network to cater overflow flood water and site level analysis is used to define development risks at certain ground level.

Diagram 3.4 Analysed Site Plans
Usually, any land development site below two (2) meters A.M.S.L (above mean sea level) are at high risk. However the safe level for land development is also based on other factors such as transportation networks and topographical conditions can become a retaining wall to flood. Flood location and topographical slopes in the surrounding area is analysed to get the latest and future risks. Slope direction which can trap rain water and flow it to a common direction will result to the higher flood risk rather than scattered slopes. It is clear that this issues are related to each other and complex.

Table 3.2 MCE Analysis Result

ID	Site Criteria	Loc_Criteria	Alt_a	Alt_b	AV_L	AV_R	AV_T	Num	Skor_a	Skor_b
1	Site Layout	Site location w.r.t. flood area	6.3	3.6	3.3	3.3	6.6	0.38	2.39	1.37
2	Slope Direction of Catchment Area	Topography of catchment area	5.0	5.0	3.3	2.3	5.6	0.33	1.65	1.65
3	Development features in the river basin	Site location w.r.t. river	3.3	6.7	1.0	4.0	5.0	0.29	0.96	1.94
	Total						17.2	1.00	5.00	4.96

Diagram 3.5 Internet Display for MCE Analysis
MCE method is used to allow selected panels to give their evaluation on the flood risk level at the location. Panel will do their evaluation through internet display at their own station (Diagram 3.5). Panel preferences is translated into a weightage and scores for the alternatives as shown in Table 3.2.

Analysis result shown that Skor_a is higher than Skor_b. This means that alternative ‘not agree” is more dominant. However to make the decision making process much harmony, SWOT (Strength, Weakness, Opportunity, Threat) approach was used. SWOT components is used as a characteristics and ‘agree’ and ‘not agree’ alternative is a function of aim (matlamat) and combined together in the AHP analysis. Result from this combination analysis showing that ‘not agree’ alternative is still dominant and the comparison result being enhanced.

Diagram 3.6 Results of AHP analysis

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