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Collaborative Decision Making For Site Development Analysis
Assoc. Prof. Dr. Zakaria Mat Arof & Hamlussalam Md. Dali
Department Survey Science and Geomatics
Faculty of Architecture, Planning and Surveying
University Technology MARA, Arau Campus, Perlis, Malaysia
Ph: (04) – 9874251, Fax: (04) – 9874241,
Email: salam@perlis.uitm.edu.my
Collaborative Decision Making For Site Development Analysis
Assoc. Prof. Dr. Zakaria Mat Arof & Hamlussalam Md. Dali
Department Survey Science and Geomatics
Faculty of Architecture, Planning and Surveying
University Technology MARA, Arau Campus, Perlis, Malaysia
Ph: (04) – 9874251, Fax: (04) – 9874241,
Email: salam@perlis.uitm.edu.my
Abstract
Decision making can be defined as a process of selecting the best approach of doing things. The decision making stage become an important agenda in any development project and is normally executed through integration and collaboration among individuals, organisations or agencies. During the process all relevant information, either spatial or textual, digital or analogue irrespectively of their locations and custodian, will be analysed based on defined parameters such as costs and impacts toward the best decision. A positive impact means prosperity and a negative impact means otherwise. The impact of decision making which involve spatial data are not generic. It may be minimum at a particular geography but may be beyond prediction at other sites and hence the risk could be higher. This paper attemps to discuss an alternative approach to support the collaboration process in decision making that utilise spatial information, in particular for land development site analysis.
The capability of the Geographical Information System software together with a high-speed intenet infrastructure, spatial and non-spatial data located at different agencies can be analysed. Decision maker may utilise the combination of several processing concepts such as Multi-Criteria Evaluation (MCE), Analytical Hierarchy Process (AHP) together with SWOT concept have been used in the computer developed system by the name of SISTEM KOLA. The result shows that the elements of collaborative decision making of iterative, interactive and participative have been improved.
1.0 Introduction
Decision making is a process. It has been practiced by many organizations with different scales to solve different problems. Several approaches have been used to suit with the local needs, requirements and surrounding conditions and limitation.
The main issue in the decision making process is basically towards the definition and classification of characteristics (Janskowski, 1995). Group discussions become a common practice in decision making. It seems that direct interaction among group members are very significant towards a harmonic and balance solutions. Group interactions are sometimes become not effective due to several human constrains such as status-quo, administrative post, bureaucracy, office location and self interest among the group member. Thus personal jurisdictions can sometimes play a dominant role in decision making.
Spatial information are gathered from analogue maps. Problems are sometimes arise from the maps itself as some maps content are good while others were compiled from a poor sources. Lack of map interpretation skill and the ability to understand map content will further worsening the situation. Due to the lack of skill in map interpretation, it will take longer time to collect and analyse the information presented. This problem will become more complex while dealing with maps with different theme, sources, scales and projections. These weaknesses will limit the capability of gathering and integrating valuable information thus affecting the efficiency of decision makers.
Drastic and tremendous development in information technology especially in Geographical Information System (GIS) has consequently become a useful intellectual resources to support decision making. However GIS is just an application tool to support spatial and non-spatial data handling with action-oriented database concept and need to be customized to become more specific towards the need of the customers (Mahindar, 1994). GIS can provide a greater impact to the decision making process which are becoming more challenging with the advent of modern technology.
Spatial Decision Support System (SDSS) which has been developed by integrating GIS and DSS (Decision Support System) is a good example of a tailored application development. This paper intend to study and evaluate the integration concept between GIS and DSS and introduce the KOLA Systems as an effective tool in the decision making process involving spatial data in Malaysia utilizing group or collaborative approaches.
2.0 A Collaborative Decision Making
Generally decision making can be defined as a systematic process towards a result which can be referred to certain standards. Harris (1998) defined the decision making as a study to identify and evaluate alternatives based on values and priorities to be inline with the goal of the decision maker. Every decision has their own risks and decision maker is responsible to minimize it.
Ander (1998) defines collaborative as a borderless working environment. It was characterized by the ability to share information and discussions through computer networking connected to group members. However Tinzmann et al. (1990) wrote that collaborative means a fair two way communication and is open towards objectives with support by the facilitator. Basically collaborative group appreciates similarity, involvement from the group member, working together, knowledge and expert sharing within a borderless working environment. Members will have an active interaction along the process of decision making with some little assistance from facilitator.
Meanwhile Nutt (1989) described four methods of decision making i.e Heuristic, Systematic, Speculative and Judicial. Heuristic method is categorized as supporting qualitative approach. Systematic method is in opposite approach of heuristic method. It gives priority to quantitative approach with a great consideration to gain and loss factors. Speculative method uses logical approach to estimate priorities of the result. On the other hand judicial method is based on the requirement set by group members.
Decision making requires large amount of data. Latest and updated spatial data are not presented in a proper manner and thus fully utilized. GIS technology together with a comprehensive hardware and software has the capability to handle this kind of spatial data. Data can be manipulated and organized in a structured form to be used with other sources.
In GIS environment data are displayed in a layer and every layer represent a theme. Each theme will be represented graphically in computer digital form supported by descriptive information of entity and these groups of data are sometimes called spatial data. Non-spatial data or textual data are considered as general information or attributes.
Generally there are two types of data being used in GIS systems, namely raster and vector. Raster data are represented by pixel. The quality of raster data is determined by pixel size where smaller pixel give better resolution. Graphical analysis is done by manipulating the attribute of the pixel. Raster data requires higher disk space for storage and large memory to support processing. Vector data are represented by point, line and area (polygon) and it is also supported by descriptive information.
GIS system has the capability to perform spatial analysis in three main classifications namely locality, neighborhood and regional. In a locality classification, analysis will be focused to the entities of the object without any consideration to the relationship factors which is practiced in the neighborhood classification. In regional classification, object entity or the entity itself is being modified to suit with the regional phenomenon (Ruslan, 1991). Comprehensive analysis to entities can be done through four processes namely re-classification, overlay, proximity and neighborhood. Re-classification process allows displayed objects to be re-modified to suit with analysis requirements. In the overlay process, entities can be separated or merged. Distance between entity is calculated in the proximity analysis while to identify the surrounding entity within define distance, a neighborhood analysis can be carried out.
As mentioned earlier, SDSS is the integration between GIS and DSS systems. When this systems being used in conjunction with collaborative approach, it can be called a Collaborative Spatial Decision Support System (CSDSS). The role of map is not just to serve theme information but as interface between spatial and non-spatial databases. Therefore many issues pertaining to map could be organized and presented. With the existence of informationt communication technology (ICT), map information can be shared through electronic line from different administrative sites. This technology assists the process of visual thinking in a collaborative decision making.
Diagram 2.1 Generalised Model for decision making in approving proposed governmental public sector development plan.
The decision making procedures practiced by government department, agencies and local authorities in approving land developmental plan are quite similar. Diagram 2.1 intends to explain the generalized model of said decision making procedures. The process starts with developer submitting the proposal to land development agency. A technical committee is established to assist the local authority to evaluate the proposal. For example in the case of MPSP (The Seberang Perai Municipal Council), the similar approach is being practiced. MPSP Town Planning Division usually being appointed as a secretariat to the committee to coordinate activities pertaining to project approval.
Separate analysis can be carried out by group members at their own office premises utilizing source data provided by project proposer or from their own database. Digital data are usually in the form of textual, graphical or tabular which have been loaded to the proposed layout plan together with technical report which basically presented in analogue or hardcopy. Data can be categorized into three, namely coverage, area and site information. Additional data are sometimes required to support the analysis which can be gathered from other related agencies through secretariat.
After a comprehensive and thorough evaluation, group member should finally be able to select which decision is the best. If more than one objective to be evaluated, usually the secretariat will arrange them according to the most basic principle that is cost. Although the evaluation is done based on the specific approach utilizing their own professionalism and expertise, it is a common practice to apply SWOT (Strength, Weakness, Opportunity and Threat) concept to the selected decision. Early conclusion should be recorded into a written document and submitted to secretariat for the purpose of compilation, official record and references.
At this stage, the final decision is being decided collectively among group members in a round table discussion. Public protests together with analysis findings will be tabled and presented to Chairman or Secretary of the town council for approval. At this level all comments and proposal from related divisions will be discuss with consideration to technical aspects, sosio-economic, environmental and ecological impacts. In some cases the decision made at this level will be brought to the higher administrative level such as State Assembly or Ministry for further debate and approval.
In the decision making process, it sometimes happen that a very limited interaction between decision maker, proposer and secretariat occur due to limitation of time and distance apart. Thus accessibility to information becomes restricted due to the limited amount of data supplied by proposer. Due to these constraints and limitation, the decision maker may make their own approach based on their experiences and expertise. Decision makers are sometimes taking a simplest approach by just applying the existing standards and rules. Consequently this will worsen the situation as they will keep aside important parameters including impact and site analysis. There are also cases where the decision is being made based on political pressures.
Although the method used is having similarities but it does not meet the requirements set by the collaborative approach. Decision made is very subjective to the personal jurisdiction, paper works, bureaucracy and limited information.
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
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
4.0 Analysis
All the three panels are required to express their level of acceptance to the system protocol with references to main decision making terms shown in the questionnaires form for factor analysis either as iterative, interactive or participative. Forms are circulated after each panel explore the KOLA Systems.
The form has been divided into three column i.e panel dimension, continuous scale and proportionate reason. In the panel dimension column question pertaining to theme has been outlining. In the scale column five interval at rate 1-5 is stated, i.e 1: FULLY SATISFIED, 2: SATISFIED, 3: FAIR, 4: NOT SATISFIED, 5: FULL UNSATISFIED. Fully unsatisfied means that panel has the opinion that the method used is not capable to help decision making process as required. While fully satisfied means otherwise. In the proportionate reason column panel is allow to explain the meaning of their weightage.
Basic statistics method such as mean, sum, min, max, variance and standard deviation are used in this analysis. This functions are used to show the characteristics of the collected data and further more to study the effectiveness and capability of the methodology. Table 4.1 shows the result of the questionnaires.
Table 4.1 Data from the Questionnaires
S,K & R represent group of question for analysed facts. S is for iterative, K for interactive and R for participative. Panels background such as age, sex and computer knowledge are located at the first column of the table while the secretariat requirements is placed at the last column.
First analysis is shown through inferences result from panel evaluation towards all factors including their own secretariat. (Table 4.2)
Table 4.2 Statistics on panel acceptance towards all facts
Analysis result showing that first panel giving a higher rate for all three factors with average 4.03, meanwhile second panel giving a medium rate at average 3.83 and third panel giving the lowest score with average 2.26. First panel give rating 5 to the requirement of secretariat while second and third panel give 4 and 3 respectively.
From the analysis, it is found that similarity exists in the standard deviation among the panel. In overall, these values are close to zero even though range between high and low is remarkable. This shown that all panel have given almost the same rating for variables except for the isolated cases. First panel fully agreed with the capability of the proposed methodology supporting decision making, while second panel is quiet moderate as the rating given closely to the capable category. The third panel clearly stated that the system is less capable. Although their background are almost similar, but their perception to the system are different. However if all results are averaged, a moderate status can be achieved as a general statement. On the other hand, all parties agreed with the existence of secretariat as a facilitator, though first panel categorized it as very needed.
Second analysis is done based on inferences to the acceptance factors by the three panels. Summary of the analysis can be shown in Table 4.3.
Table 4.3 Acceptable Inferences factors and Secretariat Need by panels
This analysis shows that iterative and interactive factors are getting average of 10.45 and 10.57 respectively. While participative factor averaged 9.80. This figure shows that iterative and interactive factors are more acceptable than participative.
Meanwhile the evaluation for interactive factor is much stable compare with the other, as the standard deviation is closer to 1. Differences in perception among panels are quite significant while evaluating iterative and participative factors.
It is clear that all panels fully agreed with the existence of secretariat as a facilitator to the decision making process. Although there are dissimilarity exist among the panels, generally they agreed with the proposed methodology to be used to support interaction in the collaborative decision making.
5.0 Comment and Conclusion
This research is focused to interactive issues which applied through three main activities in decision making process namely iterative, interactive and participative between human-data and human-human as a decision makers referring to the same field. Data can be manipulate into information and information can be further enhanced to support decision making.
This research has shown an alternative mechanism in decision making based on systematic and scientific methods to support collaborative decision making although they are in a separate locations. All three outlined objective have been achieved successfully. Analysis from the first objective showing that there are almost similar sequences being used in the proposed development approval procedures in the governmental agencies. Through second objective, a decision making concept using cyber society of decision maker has been introduced. In the third objective, the previous concept has been translated into a computer system utilizing internet as a medium of interaction. Finding shows that proposed mechanism is capable to support iterative, integrative and interactive decision making utilizing the same source of spatian and non-spatial data.
The created field is refereed to Cyber Society of Decision Makers motto. Through this motto, similarity and fairness will be priorities in the design. Decision makers have been virtually gathered through a common field and they can be interacted among themselves with the assistance of a developed KOLA System.
The main obstacle in the decision making process is too much paper works, limited access to information, time constraint, complex spatial issues due to unstructured system, bureaucracy in every stages and personal discretion can be minimized. Methodology transparencies allow discussion and can be conducted at any time without having to gather in physical. It is predicted that the time duration in decision making can be minimized.
Decision are decided together collectively following similar weightage or based on individual priority of decision maker. This flexibility can be easily accepted by the decision makers as their requirement is fulfilled.
Although there are several shortcomings in the acceptance of the system, the proposed methodology have the potential to be expanded and developed in the decision making application especially in the public sectors in-line with requirement and competition in a cyber world. A capable system in terms of its hardware and software is urgently required to manage spatial and non-spatial data in a huge volumes to be used by consumers from different locations efficiently and systematically.
References
Decision making can be defined as a process of selecting the best approach of doing things. The decision making stage become an important agenda in any development project and is normally executed through integration and collaboration among individuals, organisations or agencies. During the process all relevant information, either spatial or textual, digital or analogue irrespectively of their locations and custodian, will be analysed based on defined parameters such as costs and impacts toward the best decision. A positive impact means prosperity and a negative impact means otherwise. The impact of decision making which involve spatial data are not generic. It may be minimum at a particular geography but may be beyond prediction at other sites and hence the risk could be higher. This paper attemps to discuss an alternative approach to support the collaboration process in decision making that utilise spatial information, in particular for land development site analysis.
The capability of the Geographical Information System software together with a high-speed intenet infrastructure, spatial and non-spatial data located at different agencies can be analysed. Decision maker may utilise the combination of several processing concepts such as Multi-Criteria Evaluation (MCE), Analytical Hierarchy Process (AHP) together with SWOT concept have been used in the computer developed system by the name of SISTEM KOLA. The result shows that the elements of collaborative decision making of iterative, interactive and participative have been improved.
1.0 Introduction
Decision making is a process. It has been practiced by many organizations with different scales to solve different problems. Several approaches have been used to suit with the local needs, requirements and surrounding conditions and limitation.
The main issue in the decision making process is basically towards the definition and classification of characteristics (Janskowski, 1995). Group discussions become a common practice in decision making. It seems that direct interaction among group members are very significant towards a harmonic and balance solutions. Group interactions are sometimes become not effective due to several human constrains such as status-quo, administrative post, bureaucracy, office location and self interest among the group member. Thus personal jurisdictions can sometimes play a dominant role in decision making.
Spatial information are gathered from analogue maps. Problems are sometimes arise from the maps itself as some maps content are good while others were compiled from a poor sources. Lack of map interpretation skill and the ability to understand map content will further worsening the situation. Due to the lack of skill in map interpretation, it will take longer time to collect and analyse the information presented. This problem will become more complex while dealing with maps with different theme, sources, scales and projections. These weaknesses will limit the capability of gathering and integrating valuable information thus affecting the efficiency of decision makers.
Drastic and tremendous development in information technology especially in Geographical Information System (GIS) has consequently become a useful intellectual resources to support decision making. However GIS is just an application tool to support spatial and non-spatial data handling with action-oriented database concept and need to be customized to become more specific towards the need of the customers (Mahindar, 1994). GIS can provide a greater impact to the decision making process which are becoming more challenging with the advent of modern technology.
Spatial Decision Support System (SDSS) which has been developed by integrating GIS and DSS (Decision Support System) is a good example of a tailored application development. This paper intend to study and evaluate the integration concept between GIS and DSS and introduce the KOLA Systems as an effective tool in the decision making process involving spatial data in Malaysia utilizing group or collaborative approaches.
2.0 A Collaborative Decision Making
Generally decision making can be defined as a systematic process towards a result which can be referred to certain standards. Harris (1998) defined the decision making as a study to identify and evaluate alternatives based on values and priorities to be inline with the goal of the decision maker. Every decision has their own risks and decision maker is responsible to minimize it.
Ander (1998) defines collaborative as a borderless working environment. It was characterized by the ability to share information and discussions through computer networking connected to group members. However Tinzmann et al. (1990) wrote that collaborative means a fair two way communication and is open towards objectives with support by the facilitator. Basically collaborative group appreciates similarity, involvement from the group member, working together, knowledge and expert sharing within a borderless working environment. Members will have an active interaction along the process of decision making with some little assistance from facilitator.
Meanwhile Nutt (1989) described four methods of decision making i.e Heuristic, Systematic, Speculative and Judicial. Heuristic method is categorized as supporting qualitative approach. Systematic method is in opposite approach of heuristic method. It gives priority to quantitative approach with a great consideration to gain and loss factors. Speculative method uses logical approach to estimate priorities of the result. On the other hand judicial method is based on the requirement set by group members.
Decision making requires large amount of data. Latest and updated spatial data are not presented in a proper manner and thus fully utilized. GIS technology together with a comprehensive hardware and software has the capability to handle this kind of spatial data. Data can be manipulated and organized in a structured form to be used with other sources.
In GIS environment data are displayed in a layer and every layer represent a theme. Each theme will be represented graphically in computer digital form supported by descriptive information of entity and these groups of data are sometimes called spatial data. Non-spatial data or textual data are considered as general information or attributes.
Generally there are two types of data being used in GIS systems, namely raster and vector. Raster data are represented by pixel. The quality of raster data is determined by pixel size where smaller pixel give better resolution. Graphical analysis is done by manipulating the attribute of the pixel. Raster data requires higher disk space for storage and large memory to support processing. Vector data are represented by point, line and area (polygon) and it is also supported by descriptive information.
GIS system has the capability to perform spatial analysis in three main classifications namely locality, neighborhood and regional. In a locality classification, analysis will be focused to the entities of the object without any consideration to the relationship factors which is practiced in the neighborhood classification. In regional classification, object entity or the entity itself is being modified to suit with the regional phenomenon (Ruslan, 1991). Comprehensive analysis to entities can be done through four processes namely re-classification, overlay, proximity and neighborhood. Re-classification process allows displayed objects to be re-modified to suit with analysis requirements. In the overlay process, entities can be separated or merged. Distance between entity is calculated in the proximity analysis while to identify the surrounding entity within define distance, a neighborhood analysis can be carried out.
As mentioned earlier, SDSS is the integration between GIS and DSS systems. When this systems being used in conjunction with collaborative approach, it can be called a Collaborative Spatial Decision Support System (CSDSS). The role of map is not just to serve theme information but as interface between spatial and non-spatial databases. Therefore many issues pertaining to map could be organized and presented. With the existence of informationt communication technology (ICT), map information can be shared through electronic line from different administrative sites. This technology assists the process of visual thinking in a collaborative decision making.
Diagram 2.1 Generalised Model for decision making in approving proposed governmental public sector development plan.
The decision making procedures practiced by government department, agencies and local authorities in approving land developmental plan are quite similar. Diagram 2.1 intends to explain the generalized model of said decision making procedures. The process starts with developer submitting the proposal to land development agency. A technical committee is established to assist the local authority to evaluate the proposal. For example in the case of MPSP (The Seberang Perai Municipal Council), the similar approach is being practiced. MPSP Town Planning Division usually being appointed as a secretariat to the committee to coordinate activities pertaining to project approval.
Separate analysis can be carried out by group members at their own office premises utilizing source data provided by project proposer or from their own database. Digital data are usually in the form of textual, graphical or tabular which have been loaded to the proposed layout plan together with technical report which basically presented in analogue or hardcopy. Data can be categorized into three, namely coverage, area and site information. Additional data are sometimes required to support the analysis which can be gathered from other related agencies through secretariat.
After a comprehensive and thorough evaluation, group member should finally be able to select which decision is the best. If more than one objective to be evaluated, usually the secretariat will arrange them according to the most basic principle that is cost. Although the evaluation is done based on the specific approach utilizing their own professionalism and expertise, it is a common practice to apply SWOT (Strength, Weakness, Opportunity and Threat) concept to the selected decision. Early conclusion should be recorded into a written document and submitted to secretariat for the purpose of compilation, official record and references.
At this stage, the final decision is being decided collectively among group members in a round table discussion. Public protests together with analysis findings will be tabled and presented to Chairman or Secretary of the town council for approval. At this level all comments and proposal from related divisions will be discuss with consideration to technical aspects, sosio-economic, environmental and ecological impacts. In some cases the decision made at this level will be brought to the higher administrative level such as State Assembly or Ministry for further debate and approval.
In the decision making process, it sometimes happen that a very limited interaction between decision maker, proposer and secretariat occur due to limitation of time and distance apart. Thus accessibility to information becomes restricted due to the limited amount of data supplied by proposer. Due to these constraints and limitation, the decision maker may make their own approach based on their experiences and expertise. Decision makers are sometimes taking a simplest approach by just applying the existing standards and rules. Consequently this will worsen the situation as they will keep aside important parameters including impact and site analysis. There are also cases where the decision is being made based on political pressures.
Although the method used is having similarities but it does not meet the requirements set by the collaborative approach. Decision made is very subjective to the personal jurisdiction, paper works, bureaucracy and limited information.
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.
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.
| 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.
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Abbreviations (alternatives) :
A : Agree
B : Disagree
Abbreviations (criteria) :
a : Weakness
b : Strength
c : Opportunity
d : Threat
Results of evaluation by a decision making body
| | A B
a | 32.1 | 17.9 82.1
b | 15.8 | 22.3 77.7
c | 17.2 | 87.4 12.6
d | 35.0 | 7.6 92.4
Final results: 22.7 77.3
Scale parameter used for calculating the weight of the criteria : 0.347
Scale parameter used for calculating the weight of the alternatives : 0.693
4.0 Analysis
All the three panels are required to express their level of acceptance to the system protocol with references to main decision making terms shown in the questionnaires form for factor analysis either as iterative, interactive or participative. Forms are circulated after each panel explore the KOLA Systems.
The form has been divided into three column i.e panel dimension, continuous scale and proportionate reason. In the panel dimension column question pertaining to theme has been outlining. In the scale column five interval at rate 1-5 is stated, i.e 1: FULLY SATISFIED, 2: SATISFIED, 3: FAIR, 4: NOT SATISFIED, 5: FULL UNSATISFIED. Fully unsatisfied means that panel has the opinion that the method used is not capable to help decision making process as required. While fully satisfied means otherwise. In the proportionate reason column panel is allow to explain the meaning of their weightage.
Basic statistics method such as mean, sum, min, max, variance and standard deviation are used in this analysis. This functions are used to show the characteristics of the collected data and further more to study the effectiveness and capability of the methodology. Table 4.1 shows the result of the questionnaires.
S,K & R represent group of question for analysed facts. S is for iterative, K for interactive and R for participative. Panels background such as age, sex and computer knowledge are located at the first column of the table while the secretariat requirements is placed at the last column.
First analysis is shown through inferences result from panel evaluation towards all factors including their own secretariat. (Table 4.2)
Analysis result showing that first panel giving a higher rate for all three factors with average 4.03, meanwhile second panel giving a medium rate at average 3.83 and third panel giving the lowest score with average 2.26. First panel give rating 5 to the requirement of secretariat while second and third panel give 4 and 3 respectively.
From the analysis, it is found that similarity exists in the standard deviation among the panel. In overall, these values are close to zero even though range between high and low is remarkable. This shown that all panel have given almost the same rating for variables except for the isolated cases. First panel fully agreed with the capability of the proposed methodology supporting decision making, while second panel is quiet moderate as the rating given closely to the capable category. The third panel clearly stated that the system is less capable. Although their background are almost similar, but their perception to the system are different. However if all results are averaged, a moderate status can be achieved as a general statement. On the other hand, all parties agreed with the existence of secretariat as a facilitator, though first panel categorized it as very needed.
Second analysis is done based on inferences to the acceptance factors by the three panels. Summary of the analysis can be shown in Table 4.3.
This analysis shows that iterative and interactive factors are getting average of 10.45 and 10.57 respectively. While participative factor averaged 9.80. This figure shows that iterative and interactive factors are more acceptable than participative.
Meanwhile the evaluation for interactive factor is much stable compare with the other, as the standard deviation is closer to 1. Differences in perception among panels are quite significant while evaluating iterative and participative factors.
It is clear that all panels fully agreed with the existence of secretariat as a facilitator to the decision making process. Although there are dissimilarity exist among the panels, generally they agreed with the proposed methodology to be used to support interaction in the collaborative decision making.
5.0 Comment and Conclusion
This research is focused to interactive issues which applied through three main activities in decision making process namely iterative, interactive and participative between human-data and human-human as a decision makers referring to the same field. Data can be manipulate into information and information can be further enhanced to support decision making.
This research has shown an alternative mechanism in decision making based on systematic and scientific methods to support collaborative decision making although they are in a separate locations. All three outlined objective have been achieved successfully. Analysis from the first objective showing that there are almost similar sequences being used in the proposed development approval procedures in the governmental agencies. Through second objective, a decision making concept using cyber society of decision maker has been introduced. In the third objective, the previous concept has been translated into a computer system utilizing internet as a medium of interaction. Finding shows that proposed mechanism is capable to support iterative, integrative and interactive decision making utilizing the same source of spatian and non-spatial data.
The created field is refereed to Cyber Society of Decision Makers motto. Through this motto, similarity and fairness will be priorities in the design. Decision makers have been virtually gathered through a common field and they can be interacted among themselves with the assistance of a developed KOLA System.
The main obstacle in the decision making process is too much paper works, limited access to information, time constraint, complex spatial issues due to unstructured system, bureaucracy in every stages and personal discretion can be minimized. Methodology transparencies allow discussion and can be conducted at any time without having to gather in physical. It is predicted that the time duration in decision making can be minimized.
Decision are decided together collectively following similar weightage or based on individual priority of decision maker. This flexibility can be easily accepted by the decision makers as their requirement is fulfilled.
Although there are several shortcomings in the acceptance of the system, the proposed methodology have the potential to be expanded and developed in the decision making application especially in the public sectors in-line with requirement and competition in a cyber world. A capable system in terms of its hardware and software is urgently required to manage spatial and non-spatial data in a huge volumes to be used by consumers from different locations efficiently and systematically.
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