Difference between revisions of "Decision support tools"

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A look at the '''decision support tools''' and their component parts that are available to decision makers and policy makers.
 
  
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==Terminology==
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This article gives a short introduction to the '''decision support systems''' and their component parts, the '''decision support tools''' that are available to decision makers and policy makers. It is partially based on [https://www.academia.edu/1865329/Nostrum-Dss_Guidelines_for_the_development_of_Decision_support_System_in_Integrated_Water_Resources_Management_in_the_Mediterranean_Area Nostrum DSS Guidelines].
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The terms '''Decision Support Tools''' or '''Decision Support Systems (DSS)''' refer to a wide range of computer-based tools (simulation models, and/or techniques and methods) developed to support decision analysis and participatory processes. A DSS consists of a database, different coupled hydrodynamic and socio-economic models and is provided with a dedicated interface in order to be directly and more easily accessible by non-specialists (e.g. policy and decision makers). DSS have specific simulation and prediction capabilities but are also used as a vehicle of communication, training and experimentation <ref>Welp M. (2001). The use of decision support tools in participatory river basin management. ''Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere'', '''26''' 7-8, 535-539.</ref>. Principally, DSS can facilitate dialogue and exchange of information thus providing insights to non-experts and support them in the exploration of policy options.
 
  
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==DSS Components==
 
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'''A Database Management System (DBMS)''': a DBMS collects, organizes, and processes data and information.
 
  
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'''Models''': different hydrodynamic and socio-economic models are integrated in a DSS to perform optimization, forecasting/prediction, statistical functions. The type of models included defines the type of support provided and the area of application of a DSS (i.e. [[erosion]] or shoreline management, [[pollution]], etc.).
 
  
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'''Users’ interface''': helps the users to interact with the system and to analyse its results. Important features of a DSS interface should be its user friendliness meaning its simplicity, flexibility, and capability of presenting data and model output. An effective user’s interface facilitates the communication and increases the acceptability of the tool by intended users (e.g. Coastal Zone Managers as well as Policy and Decision Makers).
+
==Decision Support Systems==
 +
Decision Support Systems (DSS) are the combination of computer-based Decision Support Tools (DSTs) designed to assist in decision-making related to environmental problem management and long-term planning. Decision support systems also serve in participatory processes by facilitating dialogue and exchange of information to provide insights to non-experts and support them in exploring policy options. Decision support systems further assist in documenting the decision-making process that leads to the choice of a particular option, contributing to its increasing transparency and fairness.
  
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'''Other components''': [[GIS|Geographic Information Systems]] (GIS) play a significant role in ''Spatial Decision support systems'' (SDSS) in which they organise, present and compare data and information on a visualisation map; ''Web-Based DSS'' which are computerised systems that deliver decision support information to managers  using a Web browser <ref>Bhargava H. K., D. J. Power and D. Sun (2007). Progress in Web-based decision support technologies. ''Decision Support Systems'', '''43''' 4, 1083.</ref>, ''Group Decision Support System (GDSS)'' are common computer tools or networks used to enable collaboration between people to solve complex decision making;
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Decision support systems typically consist of a database, different coupled simulation models and a dedicated interface in order to be directly and more easily accessible by non-specialists (e.g. policy and decision makers). The simulation models are designed to provide information on the physical, ecological, economic and social consequences of alternative policies, strategies, plans and interventions under different scenarios. Decision support systems have specific simulation and prediction capabilities but are also used as a means of communication, training and experimentation <ref>Welp M. (2001). The use of decision support tools in participatory river basin management. ''Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere'', '''26''' 7-8, 535-539.</ref>. Decision support systems are primarily a data-based and model-based approach to help managers organize and analyze a large amount of pertinent spatial information assisted by analytical or predictive models. However, decision support systems are not restricted to handling quantitative environmental or economic data, but can also incorporate other considerations such as the values, preferences, and experiences of decision-makers, communities, and other stakeholders.
  
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==DSS Classification==
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Examples for the use of decision support systems are:
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See Power (2003)<ref name="Power">Power D. J. (2003). A Brief History of Decision Support Systems DSS. Resources.COM, World Wide Web, version 2.8, May 31, 2003.</ref>
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*[[Integrated Coastal Zone Management (ICZM)]]
 +
*The development of [[Climate adaptation policies for the coastal zone|policies]] and [[Climate adaptation measures for the coastal zone|strategies for adaptation to climate change]]
 +
*The development of coastal and marine [[Spatial planning|spatial plans]]
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*The development of a [[Governance policies for a blue bio-economy|blue economy]]<ref>Turschwell, M.P., Hayes, M.A., Lacharite, M., Abundo, M., Adams, J., Blanchard, J., Brain, E., Buelow, C.A., Bulman, C., Condie, S.A., Connolly, R.M., Dutton, I., Fulton, E.A., Gallagher, S., Maynard, D., Pethybridge, H., Plaganyi, E., Porobic, J., Taelman, S.E., Trebilco, R., Woods, G. and Brown, C.J. 2022. A review of support tools to assess multi-sector interactions in the emerging offshore Blue Economy. Environmental Science and Policy 133: 203–214</ref>
  
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* '''model-driven DSS''' emphasizes access to and manipulation of a statistical, financial, optimization, or simulation model. Model-driven DSS use data and parameters provided by users to assist decision makers in analyzing a situation; they are not necessarily data intensive.
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==DSS for risk assessment==
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Decision support systems are often used for risk assessment, for example, to specify and prioritize vulnerable locations and risk areas based on multiple criteria or to support the development of flood and salt intrusion management under scenarios of climate change. Decision support systems for risk management often use Decision Support Indices (DSIs), index-based approaches to assess combinations of multiple environmental and socioeconomic dimensions of vulnerability, risk and resilience. Different types of decision support indices can be distinguished<ref>Barzehkar, M., Parnell, K.E., Soomere, T., Dragovich, D. and Engstrom, J. 2021. Decision support tools, systems and indices for sustainable coastal planning and management: A review. Ocean and Coastal Management 212, 105813</ref>:
 +
*Coastal Vulnerability Index (CVI) indicates the extent to which a system is susceptible to, and unable to cope with, adverse effects. It provides quantitative analysis for ranking vulnerabilities of coastal sections and helps identify the vulnerable areas that require protection measures.
 +
*Coastal exposure index (CEI) evaluates the likelihood of socioeconomically valuable features such as infrastructure and urban areas being adversely affected by a hazard, such as a flood.
 +
* Coastal Risk Index Maps (CRI) are derived from the CVI and CEI to identify coastal sectors affected by natural hazards. The maps can help develop plans for coastal protection against climate-induced hazards.
 +
* Coastal Area Index (CAI) is used in spatial planning strategies to identify priority areas for coastal protection in regions experiencing economic development.
 +
*Coastal Resilience Index (CoRI) is used to estimate the ability of the coastal area to respond to hazards in a way that reduces their impact. Important factors influencing resilience are distance from the shoreline, elevation changes and human activities.
  
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* '''communication-driven DSS''' supports more than one person working on a shared task.  
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Decision support systems focused on risk assessment generally require accurate data at a small grid cell scale to accurately identify the spatial distribution of vulnerability at the local level and to identify suitable buffer zones for coastal protection and infrastructure development.
  
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* '''data-driven DSS''' or data-oriented DSS emphasizes access to and manipulation of a time series of internal company data and, sometimes, external data.
 
  
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* '''document-driven DSS''' manages, retrieves and manipulates unstructured information in a variety of electronic formats.
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==Categories of Decision Support Tools (DSTs)==
 +
Different types of Decision Support Tools can be distinguished<ref name="Power">Power D. J. (2003). A Brief History of Decision Support Systems DSS. Resources.COM, World Wide Web, version 2.8,  May 31, 2003</ref><ref>Bhargava H. K., D. J. Power and D. Sun (2007). Progress in Web-based decision support technologies. ''Decision Support Systems'', '''43''' 4, 1083</ref>:
 +
* '''Model-driven DSTs''' use data and parameters provided by users to assist decision makers in analyzing a situation. They can include physical, ecological and economic simulation and optimization models, to be used in interactive mode in the decision-making process. They help in the analysis of possible trade-offs, in the development of 'What if …?' scenarios and in conflict situations for the identification of the most suitable solutions.
 +
*'''Users’ interface''' helps the users to interact with the Decision Support System and to analyze its results. Important features of a DSS interface are its user friendliness, meaning its simplicity, flexibility, and capability of presenting data and model output. An effective user’s interface facilitates the communication and increases the acceptability of the tool by intended users (e.g. Coastal Zone Managers, Policy and Decision Makers and other stakeholders).
 +
* '''Communication support DSTs''' allow divers groups of people to participate in decision-making processes and to work on a shared task. Tools include groupware, bulletin boards, audio and videoconferencing and other (web-based) systems to support collaborative decision making. They help multidisciplinary teams involved in the analysis of a coastal problem to establish a 'common language' and think in a structured way. Criteria, objectives and constraints about the problem become more explicit through the shared decision-making process.
 +
* '''Data-driven DSTs''' or data-oriented decision support systems enable access to and manipulation of spatial geo-referenced data (actual and historical) and time series data. The graphic features support communication between stakeholders with different backgrounds. Visual aids are important for audiences that are composed not only by experts but also by the general public.
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* '''Document-driven DST''' or '''Database Management System (DBMS)''' manages, retrieves and manipulates unstructured information in a variety of electronic formats. It enables integration of different types of knowledge (e.g. local and expert knowledge), disciplines and perspectives. A search engine is an important support tool.
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* '''Knowledge-driven DST''' provides specialized problem solving expertise stored as facts, rules, procedures, or otherwise.
  
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* '''knowledge-driven DSS''' provides specialized problem solving expertise stored as facts, rules, procedures, or in similar structures.
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Two important tools are MCDA and GIS.
  
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==Practical application==
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===Multi-Criteria Decision Analysis (MCDA)===
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The '''database management system''' component allows the organisation, facilitates access to and the elaboration of time series of raw data. 
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[https://en.wikipedia.org/wiki/Multiple-criteria_decision_analysis MCDA] is a tool for benchmarking and ranking different policy or management options based on estimates of their various impacts. These estimates can be provided by models, but can also incorporate knowledge, experience, expectations, interests and concerns of experts and stakeholders, thereby overcoming some of the issues associated with using a realist, quantitative approach to a problem that also has non-quantifiable dimensions. MCDA thus supports decision-making in which widely differing objectives are weighed up against each other. This aspect is particularly important for coastal management planning, which may require the simultaneous consideration of economic, social, cultural and ethical values.  
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* The '''integration''' of different type of knowledge (e.g. local and expert knowledge), disciplines and perspectives in the development of effective and sustainable water policies can find extremely useful support by the participatory development and implementation of DSS;
 
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* DSS helps multidisciplinary team involved in the analysis of a water problem to establish a ''common language'' and think in a structured way. Criteria, objectives and constraints about the problem become more explicit through the whole process of development and application of a decision support system.
 
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* The graphical features of a DSS '''support communication''' between stakeholders with different backgrounds. Visual aids in DSS also become more and more important when audiences are composed not only by policy makers but also by citizens.  
 
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* Communication capabilities help in '''fostering public participation''' are particularly developed in Deliberation Support Tools. For instance Group Decision Support Systems support collaborative decision making;
 
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* '''Optimisation and simulation capabilities''' of the integrated help in the analysis of possible trade-offs and conflict situation for the identification of the most suitable within a set of alternative options  integrated in the DSS help through the development of “''What if…?''” ''scenarios''.
 
  
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Specific techniques can be integrated in DSS to help for the selection (“''What is best/ what is good enough …?''”). For instance '''multi-criteria decision making''' for the [[evaluation]], benchmarking and raking of the different options identified. Optimisations models integrated in the systems help to identify the best between the generated alternatives.
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Multi-criteria decision analysis typically includes the following main steps:
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# Primary problem analysis
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# Development of the options to be assessed
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# Identification of objectives and associated criteria against which to test options
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# Construction of the performance profile of each option
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# Scoring of impacts of each option
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# Weighting of criteria
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# Combination of scores and weights
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# Sensitivity analysis
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# Presentation of the results of the MCA exercise as a support for the final decision-making
  
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The use of [[GIS]] in '''Spatial Decision Support Systems''' allows for the definition hydrological and socio-economic maps that help in the multi-criteria analysis of the problem at hand. [[GIS]] components helps in the visualisation of the location of measures and impacts and facilitate the problem assessment by providing important information for the allocation of water management infrastructures.  
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The simplest and most often used MCDA consists of adding the outcome (for example: large negative impact/very poor performance=-2, negative impact/poor performance=-1, no impact/acceptable performance=0, positive impact/good performance=1, large positive impact/very good performance=2) of all considered criteria, each multiplied by a weight defined by the participants in the decision-making process. However, proper selection of criteria and weights is crucial. Inconsistencies and errors may arise due to mutual dependence of criteria and double counting, to incorrect weighting  and to unsound rules to combine scores and weights<ref>Dean, A. 2022. A Practical Guide to Multi-Criteria Analysis. Bartlett School of Planning, University College London. https://www.researchgate.net/publication/358131153_A_Practical_Guide_to_Multi-Criteria_Analysis</ref>. 
 +
===Geographic Information Systems (GIS)===
 +
[[GIS]] is a powerful DST for storing, displaying, and analyzing large amounts of spatial data from different sources. Its flexibility for controlling spatial data has made it a cost-effective technique for long-term planning of coastal adaptation. Various [[GIS]] components help in the visualization of the location of measures and the environmental and socio-economic impacts. As such they facilitate the problem assessment by providing key information for coastal management infrastructure planning. GIS can be integrated in MCDA for determining priorities by allocating values and weights to maps. It can be used to calculate a Coastal Vulnerability Index (CVI) and to identify vulnerable coastal areas by combining map layers. It is also an effective tool for the analysis of coastal resilience, integrating and then mapping resilience parameters and calculating a Coastal Resilience Index (CoRI). GIS can be used as an engagement tool by providing output maps accessible to both coastal managers and non-specialists.  
  
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A DSS help in ''documenting'' the decision process that leads to the choice of a particular option thus contributes to its increasing transparency and fairness.
 
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In particular, COASTAL ZONE MANAGEMENT DSS are developed to help in the investigation of existing gaps on physical processes in coastal zones and their relationships to socio-economic demands and needs.  They also support:
 
  
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* Water quality management (i.e. [[pollution]] control strategies, [[eutrophication]] management, salt intrusion and surface water quality).  
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The article [[Stakeholder analysis]] describes the ''Quasta'' tool. This tool can be considered as a qualitative decision support tool, aimed to involve stakeholders in a decision-making process. It is not an optimization tool, but primarily a deliberation support tool.
  
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* Erosion management: management of dams and reservoirs operation and forecasting.
 
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* Identification of the location of physical structures (water treatment plants; dams; weirs; uptakes; monitoring stations; ...).
 
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* Risk assessment: flood forecasting, travel-time computations in Early-warning systems in the event of accidental [[pollution]]. Floods and drought management under scenarios of [[climate change]]. Drought mitigation measures during planning and operation of water systems.
 
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* Enforcement of laws (i.e. the [[Water Framework Directive]] – WFD): specifically tailored DSS can help with the implementation of water legislation and guide stakeholders to check on the authority’s performance and agenda management.
 
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* Assessment of the cost-effectiveness, the possible social impacts of the alternatives considered as well as the sustainability of water management measures.
 
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In the [[Stakeholder analysis]] section, the ''Quasta'' tool is described. This tool can be considered as a qualitative decision support tool, aimed to involve stakeholders in a decision-making process. It is not an optimisation tool, but has a rather deliberative design.
 
  
 
==Links to web resources==  
 
==Links to web resources==  
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* '''mDSS''' (Multi-sectoral Integrated and Operational decision support system for sustainable use of water resources at the catchment scale) - MULINO EU project
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* '''SPICOSA SAF''' (System Approach Framework)  A self-evolving, operational research approach framework for the assessment of policy options for the sustainable management of coastal zone systems   http://www.spicosa.eu/
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: http://www.netsymod.eu/mDSS/
 
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* '''OPTIMA DSS''' (Optimisation for Sustainable Water Management) - OPTMA EU project
 
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: http://www.ess.co.at/OPTIMA/
 
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* '''WMSS''' (Water Management Support System) Integrated and problem oriented water management system at catchment scale for coastal water resources. - MEDITATE EU project
 
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: http://www.meditate.hacettepe.edu.tr/prjdesc/objectives.htm
 
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* '''SPICOSA SAF''' (System Approach Framework)  A self-evolving, operational research approach framework for the assessment of policy options for the sustainable management of coastal zone systems.  
 
  
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: http://www.spicosa.eu/
 
  
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==Related articles==
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==See also==
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:[[Integrated Coastal Zone Management (ICZM)]]
 
:[[Decision Support Systems for coastal risk assessment and management]]
 
:[[Decision Support Systems for coastal risk assessment and management]]
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:[[Vulnerability and risk]]
 
:[[Policy instruments for integrated coastal zone management]]
 
:[[Policy instruments for integrated coastal zone management]]
 +
:[[Multicriteria techniques]]
 +
:[[Input-output matrix]]
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<references/>
 
<references/>
  
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This a revised extract from the Nostrum DSS Guidelines. Please refer to the Nostrum DSS Guidelines for a complete overview.
 
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http://www.feem-web.it/nostrum/doc/d5-2.pdf
 
  
  
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{{author
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{{2Authors
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|AuthorID=12523
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|AuthorID1=12523
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|AuthorName=Margaretha
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|AuthorName1=Margaretha
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|AuthorFullName=Margaretha Breil}}
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|AuthorFullName1=Margaretha Breil
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|AuthorID2=120
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|AuthorFullName2=Job Dronkers
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|AuthorName2=Dronkers J
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}}
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[[Category:Integrated coastal zone management]]
 
[[Category:Integrated coastal zone management]]
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[[Category:Evaluation and assessment in coastal management]]

Latest revision as of 19:16, 18 September 2023

This article gives a short introduction to the decision support systems and their component parts, the decision support tools that are available to decision makers and policy makers. It is partially based on Nostrum DSS Guidelines.


Decision Support Systems

Decision Support Systems (DSS) are the combination of computer-based Decision Support Tools (DSTs) designed to assist in decision-making related to environmental problem management and long-term planning. Decision support systems also serve in participatory processes by facilitating dialogue and exchange of information to provide insights to non-experts and support them in exploring policy options. Decision support systems further assist in documenting the decision-making process that leads to the choice of a particular option, contributing to its increasing transparency and fairness.

Decision support systems typically consist of a database, different coupled simulation models and a dedicated interface in order to be directly and more easily accessible by non-specialists (e.g. policy and decision makers). The simulation models are designed to provide information on the physical, ecological, economic and social consequences of alternative policies, strategies, plans and interventions under different scenarios. Decision support systems have specific simulation and prediction capabilities but are also used as a means of communication, training and experimentation [1]. Decision support systems are primarily a data-based and model-based approach to help managers organize and analyze a large amount of pertinent spatial information assisted by analytical or predictive models. However, decision support systems are not restricted to handling quantitative environmental or economic data, but can also incorporate other considerations such as the values, preferences, and experiences of decision-makers, communities, and other stakeholders.

Examples for the use of decision support systems are:

DSS for risk assessment

Decision support systems are often used for risk assessment, for example, to specify and prioritize vulnerable locations and risk areas based on multiple criteria or to support the development of flood and salt intrusion management under scenarios of climate change. Decision support systems for risk management often use Decision Support Indices (DSIs), index-based approaches to assess combinations of multiple environmental and socioeconomic dimensions of vulnerability, risk and resilience. Different types of decision support indices can be distinguished[3]:

  • Coastal Vulnerability Index (CVI) indicates the extent to which a system is susceptible to, and unable to cope with, adverse effects. It provides quantitative analysis for ranking vulnerabilities of coastal sections and helps identify the vulnerable areas that require protection measures.
  • Coastal exposure index (CEI) evaluates the likelihood of socioeconomically valuable features such as infrastructure and urban areas being adversely affected by a hazard, such as a flood.
  • Coastal Risk Index Maps (CRI) are derived from the CVI and CEI to identify coastal sectors affected by natural hazards. The maps can help develop plans for coastal protection against climate-induced hazards.
  • Coastal Area Index (CAI) is used in spatial planning strategies to identify priority areas for coastal protection in regions experiencing economic development.
  • Coastal Resilience Index (CoRI) is used to estimate the ability of the coastal area to respond to hazards in a way that reduces their impact. Important factors influencing resilience are distance from the shoreline, elevation changes and human activities.

Decision support systems focused on risk assessment generally require accurate data at a small grid cell scale to accurately identify the spatial distribution of vulnerability at the local level and to identify suitable buffer zones for coastal protection and infrastructure development.


Categories of Decision Support Tools (DSTs)

Different types of Decision Support Tools can be distinguished[4][5]:

  • Model-driven DSTs use data and parameters provided by users to assist decision makers in analyzing a situation. They can include physical, ecological and economic simulation and optimization models, to be used in interactive mode in the decision-making process. They help in the analysis of possible trade-offs, in the development of 'What if …?' scenarios and in conflict situations for the identification of the most suitable solutions.
  • Users’ interface helps the users to interact with the Decision Support System and to analyze its results. Important features of a DSS interface are its user friendliness, meaning its simplicity, flexibility, and capability of presenting data and model output. An effective user’s interface facilitates the communication and increases the acceptability of the tool by intended users (e.g. Coastal Zone Managers, Policy and Decision Makers and other stakeholders).
  • Communication support DSTs allow divers groups of people to participate in decision-making processes and to work on a shared task. Tools include groupware, bulletin boards, audio and videoconferencing and other (web-based) systems to support collaborative decision making. They help multidisciplinary teams involved in the analysis of a coastal problem to establish a 'common language' and think in a structured way. Criteria, objectives and constraints about the problem become more explicit through the shared decision-making process.
  • Data-driven DSTs or data-oriented decision support systems enable access to and manipulation of spatial geo-referenced data (actual and historical) and time series data. The graphic features support communication between stakeholders with different backgrounds. Visual aids are important for audiences that are composed not only by experts but also by the general public.
  • Document-driven DST or Database Management System (DBMS) manages, retrieves and manipulates unstructured information in a variety of electronic formats. It enables integration of different types of knowledge (e.g. local and expert knowledge), disciplines and perspectives. A search engine is an important support tool.
  • Knowledge-driven DST provides specialized problem solving expertise stored as facts, rules, procedures, or otherwise.

Two important tools are MCDA and GIS.

Multi-Criteria Decision Analysis (MCDA)

MCDA is a tool for benchmarking and ranking different policy or management options based on estimates of their various impacts. These estimates can be provided by models, but can also incorporate knowledge, experience, expectations, interests and concerns of experts and stakeholders, thereby overcoming some of the issues associated with using a realist, quantitative approach to a problem that also has non-quantifiable dimensions. MCDA thus supports decision-making in which widely differing objectives are weighed up against each other. This aspect is particularly important for coastal management planning, which may require the simultaneous consideration of economic, social, cultural and ethical values.

Multi-criteria decision analysis typically includes the following main steps:

  1. Primary problem analysis
  2. Development of the options to be assessed
  3. Identification of objectives and associated criteria against which to test options
  4. Construction of the performance profile of each option
  5. Scoring of impacts of each option
  6. Weighting of criteria
  7. Combination of scores and weights
  8. Sensitivity analysis
  9. Presentation of the results of the MCA exercise as a support for the final decision-making

The simplest and most often used MCDA consists of adding the outcome (for example: large negative impact/very poor performance=-2, negative impact/poor performance=-1, no impact/acceptable performance=0, positive impact/good performance=1, large positive impact/very good performance=2) of all considered criteria, each multiplied by a weight defined by the participants in the decision-making process. However, proper selection of criteria and weights is crucial. Inconsistencies and errors may arise due to mutual dependence of criteria and double counting, to incorrect weighting and to unsound rules to combine scores and weights[6].

Geographic Information Systems (GIS)

GIS is a powerful DST for storing, displaying, and analyzing large amounts of spatial data from different sources. Its flexibility for controlling spatial data has made it a cost-effective technique for long-term planning of coastal adaptation. Various GIS components help in the visualization of the location of measures and the environmental and socio-economic impacts. As such they facilitate the problem assessment by providing key information for coastal management infrastructure planning. GIS can be integrated in MCDA for determining priorities by allocating values and weights to maps. It can be used to calculate a Coastal Vulnerability Index (CVI) and to identify vulnerable coastal areas by combining map layers. It is also an effective tool for the analysis of coastal resilience, integrating and then mapping resilience parameters and calculating a Coastal Resilience Index (CoRI). GIS can be used as an engagement tool by providing output maps accessible to both coastal managers and non-specialists.


The article Stakeholder analysis describes the Quasta tool. This tool can be considered as a qualitative decision support tool, aimed to involve stakeholders in a decision-making process. It is not an optimization tool, but primarily a deliberation support tool.


Links to web resources

  • SPICOSA SAF (System Approach Framework) A self-evolving, operational research approach framework for the assessment of policy options for the sustainable management of coastal zone systems http://www.spicosa.eu/


Related articles

Integrated Coastal Zone Management (ICZM)
Decision Support Systems for coastal risk assessment and management
Vulnerability and risk
Policy instruments for integrated coastal zone management
Multicriteria techniques
Input-output matrix


References

  1. ↑ Welp M. (2001). The use of decision support tools in participatory river basin management. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, 26 7-8, 535-539.
  2. ↑ Turschwell, M.P., Hayes, M.A., Lacharite, M., Abundo, M., Adams, J., Blanchard, J., Brain, E., Buelow, C.A., Bulman, C., Condie, S.A., Connolly, R.M., Dutton, I., Fulton, E.A., Gallagher, S., Maynard, D., Pethybridge, H., Plaganyi, E., Porobic, J., Taelman, S.E., Trebilco, R., Woods, G. and Brown, C.J. 2022. A review of support tools to assess multi-sector interactions in the emerging offshore Blue Economy. Environmental Science and Policy 133: 203–214
  3. ↑ Barzehkar, M., Parnell, K.E., Soomere, T., Dragovich, D. and Engstrom, J. 2021. Decision support tools, systems and indices for sustainable coastal planning and management: A review. Ocean and Coastal Management 212, 105813
  4. ↑ Power D. J. (2003). A Brief History of Decision Support Systems DSS. Resources.COM, World Wide Web, version 2.8, May 31, 2003
  5. ↑ Bhargava H. K., D. J. Power and D. Sun (2007). Progress in Web-based decision support technologies. Decision Support Systems, 43 4, 1083
  6. ↑ Dean, A. 2022. A Practical Guide to Multi-Criteria Analysis. Bartlett School of Planning, University College London. https://www.researchgate.net/publication/358131153_A_Practical_Guide_to_Multi-Criteria_Analysis


The main authors of this article are Margaretha Breil and Job Dronkers
Please note that others may also have edited the contents of this article.
Citation: Margaretha Breil; Job Dronkers; (2023): Decision support tools. Available from http://www.coastalwiki.org/wiki/Decision_support_tools [accessed on 22-11-2024]
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