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300,173 result(s) for "Decision Analysis"
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Are MCDM methods useful? A critical review of Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP)
Although Multi Criteria Decision Making (MCDM) methods have been applied in numerous case studies, many companies still avoid employing these methods in making their decisions and prefer to decide intuitively. There are studies claiming that MCDM methods provide better rankings for companies than intuitive approaches. This study argues that this claim may have low validity from a company's perspective. For this purpose, it focuses on one of the MCDM methods referred to as the Analytic Hierarchy Process (AHP) and shows that AHP is very likely to provide a ranking of options that would not be acceptable by a rational person. The main reason that many companies do not rely on current MCDM methods can be due to the fact that managers intuitively notice ranking errors. Future studies should end the promotion of outdated approaches, pay closer attention to the deficiencies of the current MCDM processes, and develop more useful methods.
Key management ratios : the 100+ ratios every manager needs to know
Business ratios are the figures that provide management with targets and standards for their organisation. From earnings per share and cash flow to return on investment and sales to fixed assets ratios, this book guides managers through the key ratios at the heart of business practice.
The use of multi-criteria decision-making methods in project portfolio selection: a literature review and future research directions
In most project portfolio selection (PPS) situations, the presence of multiple attributes and decision-maker preference is inevitable. As Multi-criteria Decision Analysis (MCDA) methods provide a framework well-suited to deal with these challenges in PPS problems, the use of MCDA methods in real-life PPS problems has increased in recent years. This paper provides a comprehensive literature review of the use of different MCDA methods and their individual or combined utilization with other modeling techniques to support PPS problems. First, we summarize how MCDA methods are used in different modeling approaches. Second, we examine the mathematical models that are generally used to combine MCDA with mathematical programming techniques to solve PPS problems with resource constraints. Third, we present the drawbacks of combined utilization and discuss recent advances. Finally, we visualize the summary of the reviewed papers as a decision tree to assist researchers and practitioners in the use of MCDA methods in a specific PPS context and propose some future research directions.
Comparison of GIS-based AHP and fuzzy AHP methods for hospital site selection: a case study for Prayagraj City, India
Identification of hospital sites and their ranking is important for the planning and development of any country's health infrastructure. The site selection problem is a typical multi-criteria decision making problem involving multiple stakeholders and their interests. Multi-Criteria Decision Analysis (MCDA) is a promising approach to solve a location-based problem due to the constitution of various criteria involved in decision making. In this research, eleven criterion are chosen which are classified under three main criteria; socio-economic, geographical and environmental. This research aims to identify the appropriate MCDA method for the selection of a new hospital sites. Here, two MCDA methods named Analytical Hierarchy Process (AHP) and Fuzzy AHP (FAHP) are used. Further, Geographical Information System (GIS) based MCDA methodology is proposed in this paper. The results obtained with both AHP and FAHP methods are compared. This comparison is based on criterion rankings, proposed hospital locations and sensitivity analysis. The main difference in results is shown in the result of sensitivity analysis in which constant variation in site ranking is obtained when weight change analysis is performed using AHP. The FAHP result shows only one variation in site ranking after a change in weight from +10 to +20%. The result suggests that FAHP may be a better approach to the hospital site selection problem.
Applications of management science
'Applications of Management Science' focuses on the application of management science to multiple criteria decision making, data envelopment analysis, and managerial applications.
Multicriteria decision analysis (MCDA) in health care: a systematic review of the main characteristics and methodological steps
Background The health area is one of the most affected systems on the perspective of decision-making with multiobjectives, thus becoming prone to errors in the final solution, however, multicriteria decision analysis (MDCA) appears as an aid tool for this process decision-making. Therefore,the present study aims to analyze and synthesize articles found in the literature, involing MCDA in health care, evaluating general issues and methodological aspects, structuring them in a single work. Methods Surveys in the bibliographic databases SCOPUS and PUBMED indicated 1852 documents on the subject, however after a careful verificatios, 66 studies were selected to be analyzed completely. The data extracted from the included articles were organized into a spreadsheet for the preparation of analysis, and the technique used was descriptive statistics. Results It was possible to identify a growth trend in the application of the MCDA in the health area, but no dominance was identified in relation to the authors of the publication and the periodicals where they are published, but some countries stood out in terms of the number of published researches, such as: Canada and Turkey. In defining the decision problem, and in defining criteria, the “literature” presented the greatest demand for those who wish to structure their decision problem. Finally, it was verified by the analysis of the problem, that the MCDA to solve the problems of ranking has comprehensive application and that there is a greater incidence in the use of the AHP and Logic methods Fuzzy. Conclusion With this, it is possible to observe, through the data of this review, that more than the multicriteria methods, the multicriteria decision model has been highlighted, also in the health area. In addition, the study can guide new applications and techniques using MCDA in the health care.
Norwegian offshore wind power—Spatial planning using multi-criteria decision analysis
The Norwegian government recently agreed on the goal 30by40, which involves opening Norwegian offshore areas to host 30 GW of installed wind power by 2040. We address this goal by presenting a first mapping of wind power suitability scores (WPSS) for the entire Norwegian economic zone (NEZ) using a multi-criteria decision analysis framework (MCDA), namely, the analytical hierarchical process (AHP) approach. We obtain WPSS considering relevant criteria like wind resources, techno-economic aspects, social acceptance, environmental considerations, and met-ocean constraints such as wind and wave conditions. The results starts with a baseline scenario, where the criterion importance is pairwise compared in the context of balancing economic incentives and conflicting interests. Additionally, to reveal regions that are robust to changes in criterion importance, we carry out a sensitivity analysis by introducing three additional scenarios. These scenarios represent stereotypical actors with distinct preferences for siting of wind farms: the investor, the environmentalist, and the fisherman. The results show that the southern part of the NEZ is the most suitable and robust region for offshore wind power deployment. This region receives the highest suitability category (“very high” suitability for wind power application) throughout all the scenarios. Areas in the Norwegian part of the Barents Sea and the near-coastal areas outside mid-Norway are also well suited regions, but these are more sensitive to the choice of criterion importance. The use of AHP within the framework of MCDA is shown to be a promising tool for pinpointing the best Norwegian offshore areas for wind power application.