Introducing the metalog distributions Nestler, Scott; Keelin, Tom
Significance (Oxford, England),
December 2022, 2022-12-01, 20221201, Letnik:
19, Številka:
6
Journal Article
Scott Nestler and Tom Keelin provide an overview of a new family of distributions, originally developed for the decision analysis field, that may have virtually unlimited applicability in any field
...Scott Nestler and Tom Keelin provide an overview of a new family of distributions, originally developed for the decision analysis field, that may have virtually unlimited applicability in any field
Multi‐criteria decision analysis (MCDA) is a method to support decision‐making, by exploring the balance between the pros and cons of different alternatives to accomplish a specific goal. It assists ...in framing decision problems, illustrating the performance of alternatives across criteria, exploring trade‐offs, formulating a decision and testing its robustness. This paper provides a structured review of empirical applications of MCDA to nature conservation published in the scientific literature over the last 20 years. The paper aims at taking stock of past experiences, and comparing them with best practices and common pitfalls identified in the literature, to provide recommendations for better MCDA application to conservation.
The review follows the structure of a generalized MCDA process consisting of three key stages: (1) decision context and problem structuring, (2) analysis and (3) decision.
The search identified 86 papers that describe MCDA applications to a range of topics, including conservation prioritization and planning; protected areas management and zoning; forest management and restoration; and mapping of biodiversity, naturalness and wilder. The results show that, concerning problem structuring, a small percentage of the reviewed MCDA engaged stakeholders other than the authors in identifying alternatives and formulating criteria (15% and 35% respectively). Concerning the analysis, criteria assessment was adequately justified by the authors (47%), at times also by involving other stakeholders (22%). Weighting was performed in almost all applications, whereas criteria aggregation was mostly based on the weighted linear combination (63%). Sensitivity analysis was largely overlooked (57%). Concerning decision, 45% of the articles provided only an overall ranking or suitability of alternatives, while 22% included additional rankings according to specific criterion, and 8% further analyses and clustering of stakeholders’ preferences.
The paper concludes by suggesting key elements of successful MCDA applications, including clear construction of the decision context; collaborative identification of alternatives and criteria that reflect the values at stake; adequate justification and communication of the methods for criteria assessment and weighting; reasoned choice of the criteria aggregation method, and comprehensive sensitivity analysis.
Multi-criteria decision analysis (MCDA) methods have become increasingly popular in decision-making for sustainable energy because of the multi-dimensionality of the sustainability goal and the ...complexity of socio-economic and biophysical systems. This article reviewed the corresponding methods in different stages of multi-criteria decision-making for sustainable energy, i.e., criteria selection, criteria weighting, evaluation, and final aggregation. The criteria of energy supply systems are summarized from technical, economic, environmental and social aspects. The weighting methods of criteria are classified into three categories: subjective weighting, objective weighting and combination weighting methods. Several methods based on weighted sum, priority setting, outranking, fuzzy set methodology and their combinations are employed for energy decision-making. It is observed that the investment cost locates the first place in all evaluation criteria and CO
2 emission follows closely because of more focuses on environment protection, equal criteria weights are still the most popular weighting method, analytical hierarchy process is the most popular comprehensive MCDA method, and the aggregation methods are helpful to get the rational result in sustainable energy decision-making.
Chemoradiation followed by esophagectomy is a standard treatment option for patients with locally advanced esophageal cancer (LAEC). Esophagectomy is a high-risk procedure, and recent evidence ...suggests select patients may benefit from omitting or delaying surgery. This study aims to compare surgery versus active surveillance for LAEC patients with complete clinical response (cCR) after neoadjuvant chemoradiotherapy (nCRT).
Decision analysis with Markov modeling was used. The base case was a 60-year-old man with T3N0M0 esophageal cancer with cCR after nCRT. The decision was modeled for a 5-year time horizon. Primary outcomes were life-years and quality-adjusted life-years (QALY). Probabilities and utilities were derived through the literature. Deterministic sensitivity analyses were performed using ranges from the literature with consideration for clinical plausibility.
Surgery was favored for survival with an expected life-years of 2.89 versus 2.64. After incorporating quality of life, active surveillance was favored, with an expected QALY of 1.70 versus 1.56. The model was sensitive to probability of recurrence on active surveillance (threshold value 0.598), probability of recurrence being resectable (0.318), and disutility of previous esophagectomy (−0.091). The model was not sensitive to perioperative morbidity and mortality.
Our study finds that surgery increases life expectancy but decreases QALY. Although the incremental change in QALY for either modality is insufficient to make broad clinical recommendations, our study demonstrates that either approach is acceptable. As probabilities of key factors are further defined in the literature, treatment decisions for patients with LAEC and a cCR after nCRT should consider histology, patient values, and quality of life.
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•A bibliometric based survey on AHP and TOPSIS methods has been conducted.•Scopus database was employed to retrieve the required data for this analysis.•Assessment of quantitative and qualitative ...bibliometric indicators was obtainable.•Efficacy of these methods promotes the development of related research.•More scientific research interests will be devoted to these methods in the future.
In recent years, the employment of multiple criteria decision analysis (MCDA) techniques in solving complex real-world problems has increased exponentially. The willingness to build advanced decision models, with higher capabilities to support decision making in a wide range of applications, promotes the integration of MCDA techniques with efficient systems such as intelligence and expert systems, geographic information systems, etc. Amongst the most applied MCDA techniques are Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The development of a comprehensive perspective on research activities associated with the applications of these methods provides insights into the contributions of countries, institutes, authors and journals towards the advancements of these methods. Furthermore, it helps in identifying the status and trends of research. This in turn will help researchers in shaping up and improving future research activities and investments. To meet these aims, a bibliometric analysis based on data harvested from Scopus database was carried out to identify a set of bibliometric performance indicators (i.e. quantitative indicators such as productivity, and qualitative indicators such as citations and Hirsch index (h-index)). Additionally, bibliometric visualization maps were employed to identify the hot spots of research. The total research output was 10,188 documents for AHP and 2412 documents for TOPSIS. China took a leading position in AHP research (3513 documents; 34.5%). It was also the leading country in TOPSIS research (846 documents; 35.1%). The most collaborated country in AHP research was the United States, while in case of TOPSIS it was China. The United States had gained the highest h-index (78) in AHP research, while in TOPSIS it was Taiwan with h-index of 46. Expert Systems with Applications journal was the most productive journal in AHP (204; 2.0%) and TOPSIS research (125; 5.2%), simultaneously. University of Tehran, Iran and Islamic Azad University, Iran were the most productive institutions in AHP (173; 1.7%) and TOPSIS (115; 4.8%) research, simultaneously. The major hot topics that utilized AHP and will continue to be active include different applications of geographic information systems, risk modeling and supply chain management. While for TOPSIS, they are supply chain management and sustainability research. Overall, this analysis has shown increasing recognition of powerful of MCDA techniques to support strategic decisions. The efficacy of these methods in the previous context promotes their progress and advancements.
Z-numbers are efficient tools to represent uncertain information through restriction and reliability measurement. Z-numbers and their variants have been integrated with diverse decision-analysis ...methods to solve practical decision-making problems. To make researchers understand the research status and challenges in this area, this paper provides an overview of publications related to Z-number-based decision analysis methods and applications. Firstly, a bibliometric analysis is conducted to present the trends and hotspots in this research domain. To uncover theoretical developments of Z-numbers, concepts and operation rules of Z-numbers and their variants are then recalled. Furthermore, decision analysis methods regarding multiple criteria decision analysis, optimization, prediction, and reasoning within the context of Z-numbers are summarized. Applications of Z-number-based decision analysis methods are categorized into six different fields including business and financial management, industrial engineering and management, energy management, medical and healthcare management, environment and sustainable development, and others. Findings, challenges, and future research directions are further discussed. It is hoped that this paper can provide insights for scholars and practitioners in the fields of Z-number-based decision analysis and applications.
Many multiple attribute decision analysis problems include both quantitative and qualitative attributes with various kinds of uncertainties such as ignorance, fuzziness, interval data, and interval ...belief degrees. An evidential reasoning (ER) approach developed in the 1990s and in recent years can be used to model these problems. In this paper, the ER approach is extended to group consensus (GC) situations for multiple attributive group decision analysis problems. In order to construct and check the GC, a compatibility measure between two belief structures is developed first. Considering two experts’ utilities, the compatibility between their assessments is naturally constructed using the compatibility measure. Based on the compatibility between two experts’ assessments, the GC at a specific level that may be the attribute level, the alternative level, or the global level, can be constructed and reached after the group analysis and discussion within specified times. Under the condition of GC, we conduct a study on the forming of group assessments for alternatives, the achievement of the aggregated utilities of assessment grades, and the properties and procedure of the extended ER approach. An engineering project management software selection problem is solved by the extended ER approach to demonstrate its detailed implementation process, and its validity and applicability.
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