Expanding the role of social science in conservation through an engagement with philosophy, methodology, and methods. 25], focus groups [e.g. the Multi Criteria Decision Analysis (MCDA), widely utilized in a range of applications such as combined cooling, heating and power systems [6], solar projects [7] and national scale application for the selection of the most suitable renewable energy system [8–10] for their energy supply market. Any queries (other than missing content) should be directed to the corresponding author for the article. International Journal of Geographical Information Science. 82], and finally, 5% of the reviewed articles applied some ad hoc rules [e.g. The second stage is the actual analysis, broadly consisting of: criteria assessment, weighting, criteria aggregation and sensitivity analysis (see Belton & Stewart, 2002; Munda, 1995; Roy, 1996). To this end, their main results consisted of spatial clusters identifying areas with high biodiversity based on a set of criteria which were then crosschecked to see whether they overlap with existing protected areas in the region. In a situation where multiple criteria are involved confusion can arise if a logical, well-structured decision-making process is not followed. The review was carried out based on the generalized MCDA process described in Section 2. Belton and Stewart (2002) present a detailed analysis of the theoretical foundations of different MCDA approaches as well as their comparative strengths and weaknesses. Insights from an Italian case study. 51]. In total, the articles covered 41 countries; the most represented countries being Italy (thirteen articles), UK (seven articles), USA (six articles), followed by Iran (five articles), Australia, Mexico and Spain (four articles each), and Finland, France and Sweden (three articles each), and the remaining 31 countries covered by one or two articles. 46; 49]. About criteria selection, in 49% of the MCDA the authors formulated the criteria without input from stakeholders (see Figure 5 and Supporting Information). 27; 46] and SMART [e.g. Criteria aggregation refers to the application of a rule (e.g. Most of the articles addressed forest management and restoration (25%), conservation prioritization and planning (24%), and protected area planning and management (21%), while fewer dealt with mapping of biodiversity, wilderness and naturalness (8%). a Multi-Criteria Decision Making (MCDM), called the Simple Additive Weighting (SAW) method. In the following section, the articles are referenced with square brackets according to their numbering in the Supporting Information. MULTI-CRITERIA DECISION ANALYSIS FOR THE APPRAISAL OF MEDICAL NEEDS: A PILOT STUDY . ScienceDirect ® is a registered trademark of Elsevier B.V. ScienceDirect ® is a registered trademark of Elsevier B.V. Multicriteria decision-making and probabilistic weighing applied to sustainable assessment of beef life cycle. Multi‐criteria decision analysis ultimately aims to assist people in making decisions related to the objectives of the specific case study. Problem Structuring ☺ 3. Department of Mechanical Engineering, Faculty of Engineering, Delta State University, Abraka, Oleh Campus, 331107, Nigeria. In 20% of the MCDA, alternatives were designed by the authors, applying: spatial MCDA to identify restoration sites [e.g. We specifically aimed at identifying a set of studies classified by their own authors as explicitly addressing nature and biodiversity conservation. For example, to derive weights, Ianni and Geneletti (2010) applied a 3‐point scale pairwise comparison, which means that each criterion can be equally important, slightly more important or strongly more important than the criterion it is being compared to. Optimization of regional forest planning with multiple decision-makers. 2 = Weighting performed by the authors through multiple weight sets; 3 = Weighting performed by involving experts or representatives of stakeholders; 4 = Multiple weighting performed by involving experts or representatives of stakeholders. Objectives and criteria, often organized in a hierarchical or network structure called value or decision tree, have to be complete, concise, operational, independent and understandable (see Gregory et al., 2012; Keeney, 1992). 11; 12]; while 22% also included partial rankings or suitability [e.g. Multi-criteria decision method: Commitment: Is there commitment to action? Planning for Ecosystem Services in Cities. Multi-criteria decision analysis (MCDA) methods are extremely valuable, especially in the case of decision making for sustainable energy, because of their ability to incorporate multiple criteria that aren’t restricted to economics alone.12 Compared to previously used single criteria approaches Use of Multi-Criteria Decision Analysis for Energy Planning 2 ABSTRACT This paper uses a Multi-Criteria Decision Analysis (MCDA) to examine tradeoffs in electricity generation technologies on the basis of cost, greenhouse gas emissions, water consumption, and land use. Multi-Criteria Decision Analysis. In this respect, it is worth noticing that existing frameworks, such as the Common International Classification of Ecosystem Services (Haines‐Young & Potschin, 2013), could help to structure the objectives during or after an initial round of stakeholder involvement to define the problem. Weighting was not considered by 2% of the MCDA [e.g. An Example to Select the best mobile phone from many alternative Therefore, in the review, we searched for such information as a proxy of the actual decision, investigating how decisions could be made based on the MCDA results, regardless of their quality and of their actual implementation (Keeney, 2002). Figure 5 summarizes the analysis in the reviewed articles (see also the Supporting Information). Nevertheless, it could be argued that most approaches involve the three main stages of the generalized MCDA process shown in Figure 1 (based on Geneletti & Ferretti, 2015; Kiker, Bridges, Varghese, Seager, & Linkov, 2005), in which a key aspect is the involvement of different actors providing different types of input to the process. The basic idea of MCDA methods is to evaluate the performance of alternative courses of action (e.g. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Several different techniques can be applied to obtain ordinal or cardinal weights, based on the judgements and perception about the relevance of the different issues at stake. 26; 80; 83]. The first stage of the MCDA process aims to establish a shared understanding of the decision context, and to structure the problem. Independently of the weighting technique considered, the most important evaluation criteria identified for orphan drugs were: "disease severity", "unmet needs" and "comparative effectiveness", while the "size of the population" had the lowest relevance for decision making. Among the others, the sensitivity analysis was mostly applied to the weights (19%) [e.g. Some contributions to theory about the Analytical Hierarchy Process (AHP) are challenged. MSU-NCRST-SEPP MEMPHIS-IN-MAY WORKSHOP May 6th –8th , 2009 Memphis-TN UNDERSTANDING SPATIAL MULTI‐CRITERIA DECISION MAKING an analytical … The Supporting Information provides details on the search queries. 1 = Yes. Among these, Ferretti and Comino (2015) noted that independence between attributes should be fulfilled, and checked it with participants in a focus group. It may not be possible to complete all tasks for each tool due to a lack of available information, the task not applying to the tool, etc. It is most applicable to solving problems that are characterized as a choice among alternatives. The Supplementary Information is archived in IRIS (see http://hdl.handle.net/11572/184016)—the Research Registry of the University of Trento—an Open Access institutional archive, whose full‐text files are disseminated on the web and, following the publishers’ policies in terms of Open Access, are freely accessible by web users (as well as specialized harvesters) without any password or other types of identification. In the following sub‐section, we discuss our findings in the light of MCDA best practices and common pitfalls, providing recommendations for more effective applications in conservation. Thus, they proposed a rather transparent approach to explicitly avoid undesired trade‐offs. 28; 73], the aggregation rule (3%) [e.g. Tversky & Kahneman, 1981). Examining the results of a MCDA in the light of its initial purpose is perhaps the most important step to assist people in making decisions. Multi-Criteria Decision Analysis, or MCDA, is a valuable tool that we can apply to many complex decisions. They may comprise, for example, different locations and design for natural parks or restoration areas (Uribe, Geneletti, del Castillo, & Orsi, 2014; Van Elegem, Embo, Muys, & Lust, 2002), options for ecosystem management (Cordingley, Newton, Rose, Clarke, & Bullock, 2016; Jalilova, Khadka, & Vacik, 2012), plant species for reforestation (Reubens et al., 2011) or wildlife management units (García‐Marmolejo, Escalona‐Segura, & Van Der Wal, 2008). 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