Decision support systems for forest management: a comparative analysis and assessment

dc.contributor.affiliationFacultad de Administración y Dirección de Empresas
dc.contributor.affiliationDepartamento de Estadística e Investigación Operativa Aplicadas y Calidad
dc.contributor.affiliationCentro de Gestión de la Calidad y del Cambio
dc.contributor.authorSegura Maroto, Marinaes_ES
dc.contributor.authorRay, Duncanes_ES
dc.contributor.authorMaroto Álvarez, Mª Concepción
dc.contributor.funderEuropean Commission
dc.contributor.funderEuropean Cooperation in Science and Technologyes_ES
dc.contributor.funderMinisterio de Ciencia e Innovaciónes_ES
dc.date.accessioned2016-03-11T14:30:00Z
dc.date.available2016-03-11T14:30:00Z
dc.date.issued2014-02
dc.descriptionSupplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.compag.2013. 12.005.es_ES
dc.description.abstract[EN] Decision Support Systems (DSS) are essential tools for forest management practitioners to help take account of the many environmental, economic, administrative, legal and social aspects in forest management. The most appropriate techniques to solve a particular instance usually depend on the characteristics of the decision problem. Thus, the objective of this article is to evaluate the models and methods that have been used in developing DSS for forest management, taking into account all important features to categorize the forest problems. It is interesting to know the appropriate methods to answer specific problems, as well as the strengths and drawbacks of each method. We have also pointed out new approaches to deal with the newest trends and issues. The problem nature has been related to the temporal scale, spatial context, spatial scale, number of objectives and decision makers or stakeholders and goods and services involved. Some of these problem dimensions are inter-related, and we also found a significant relationship between various methods and problem dimensions, all of which have been analysed using contingency tables. The results showed that 63% of forest DSS use simulation modelling methods and these are particularly related to the spatial context and spatial scale and the number of people involved in taking a decision. The analysis showed how closely Multiple Criteria Decision Making (MCDM) is linked to problem types involving the consideration of the number of objectives, also with the goods and services. On the other hand, there was no significant relationship between optimization and statistical methods and problem dimensions, although they have been applied to approximately 60% and 16% of problems solved by DSS for forest management, respectively. Metaheuristics and spatial statistical methods are promising new approaches to deal with certain problem formulations and data sources. Nine out of ten DSS used an associated information system (Database and/or Geographic Information System - GIS), but the availability and quality of data continue to be an important constraining issue, and one that could cause considerable difficulty in implementing DSS in practice. Finally, the majority of DSS do not include environmental and social values and focus largely on market economic values. The results suggest a strong need to improve the capabilities of DSS in this regard, developing and applying MCDM models and incorporating them in the design of DSS for forest management in coming years.en_EN
dc.description.accrualMethodSes_ES
dc.description.bibliographicCitationSegura Maroto, M.; Ray, D.; Maroto Álvarez, MC. (2014). Decision support systems for forest management: a comparative analysis and assessment. Computers and Electronics in Agriculture. 101:55-67. https://doi.org/10.1016/j.compag.2013.12.005es_ES
dc.description.sponsorshipThe authors acknowledge the support received from European Cooperation in Science and Technology (COST Action FP0804 - Forest Management Decision Support Systems "FORSYS"), the Ministry of Economy and Competitiveness through the research project Multiple Criteria and Group Decision Making integrated into Sustainable Management, Ref. ECO2011-27369 and Ministry of Education (Training Plan of University Teaching). We also thank the editor and reviewers for their suggestions to improve the paper.
dc.description.upvformatpfin67es_ES
dc.description.upvformatpinicio55es_ES
dc.description.volume101es_ES
dc.identifier.doi10.1016/j.compag.2013.12.005
dc.identifier.issn0168-1699
dc.identifier.urihttps://riunet.upv.es/handle/10251/61746
dc.languageIngléses_ES
dc.publisherElsevieres_ES
dc.relation.ispartofComputers and Electronics in Agriculturees_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/COST//FP0804/EU/Forest Management Decision Support Systems (FORSYS)/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MICINN//ECO2011-27369/ES/TECNICAS MULTICRITERIO Y TOMA DE DECISIONES PARTICIPATIVA PARA UNA GESTION SOSTENIBLE/es_ES
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.compag.2013.12.005es_ES
dc.relation.senia262643es_ES
dc.rightsReconocimiento - No comercial - Sin obra derivada (by-nc-nd)es_ES
dc.rights.accessRightsAbiertoes_ES
dc.subjectDecision support systemses_ES
dc.subjectForest managementes_ES
dc.subjectMultiple criteria decision makinges_ES
dc.subjectGroup decision makinges_ES
dc.subjectOptimizationes_ES
dc.subjectSimulationes_ES
dc.subject.classificationESTADISTICA E INVESTIGACION OPERATIVAes_ES
dc.titleDecision support systems for forest management: a comparative analysis and assessmentes_ES
dc.typeArtículoes_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
dspace.entity.typePublication
person.identifier3188
person.identifier.orcid0000-0001-8512-3197
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relation.isAuthorOfPublication.latestForDiscoveryc9ea63e6-dd80-4c7e-a018-fbfe06863425
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upv.uuid5d52fa43-9a7d-44b9-b235-c84849454814es_ES

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