scholarly journals Optimization-Based TOPSIS Method with Incomplete Weight Information under Nested Probabilistic-Numerical Linguistic Environment

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Yan Deng ◽  
Xinxin Wang ◽  
Chao Min
Keyword(s):  
Decision Making ◽  
Health Assessment ◽  
Quantitative Information ◽  
Distance Measures ◽  
Topsis Method ◽  
Uncertain Environments ◽  
Attribute Weight ◽  
Complex Decision Making ◽  
Incomplete Weight ◽  
The Impact

With the development of the economic and technology, decision-making problems are more and more complex and uncertain. Experts have difficulty in expressing evaluation information because of different research background and insufficient cognition of knowledge structure. Attribute weight information has been often incomplete in decision-making problems. Considering that nested probabilistic-numerical linguistic term sets (NPNLTSs) are flexible to express qualitative and quantitative information, in this paper, we firstly establish an optimization model based on distance measures to obtain the attribute weight. Combined with a classical decision-making method, an optimization-based TOPSIS method with NPNLTSs is proposed to deal with complex decision-making problems. After that, a case study about the river health assessment is given to show the effectiveness and practicability of the proposed method. Finally, some comparative analysis and discussion are provided from three aspects, including the impact for the results without weight optimization, the impact for the results under other uncertain environments, and the impact for the results using other decision-making methods. As a result, the proposed optimization-based TOPSIS method is effective and reliable. The optimization-based TOPSIS method proposed in this paper provides a new way to deal with uncertain and practical problems, which makes a technically sound contribution to the decision-making field.

Abstract TP310: Effect of an Extended Treatment Window on Transfer Times in Patients With Stroke

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Dawn K Beland ◽  
Ilene Staff ◽  
Jenna Beckwith ◽  
Amre Nouh
Keyword(s):  
Decision Making ◽  
Process Of Care ◽  
Patient Demographics ◽  
Complex Decision Making ◽  
Complex Decision ◽  
Stroke Type ◽  
Comprehensive Stroke Center ◽  
Stroke Center ◽  
The Impact ◽  
Transfer Times

STK-OP-1 examines transfer times for patients going to a higher level of care. Known as door in, door out or DIDO, certified stroke centers are required to report times for both ischemic and hemorrhagic stroke patients transferred to a Primary or Comprehensive Stroke Center (CSC). Purpose: Barriers to time-sensitive transfer and complex decision making are common. As a result, Hartford Healthcare (HHC) began a QI initiative to measure DIDO times while introducing advanced CTP imaging and treatment in the extended window, April 2018. This project evaluates the impact on DIDO. Methods: This multi-center QI project evaluated data pre and post implementation for stroke transfers to the CSC. Pre-implementation was May 2017 to April 2018, post-implementation May 2018 to March 2019. Patient and process of care data abstracted from Epic was entered into Excel. The main analysis compared median DIDO times using Wilcoxon Ranked Sum. Results: Data were collected on hospital, stroke type/severity and treatments administered; patient demographics, and key timing variables of door in/door out, EMS and CT. While there is no universal criterion for DIDO, 60 minutes is often the ultimate goal with 90 or 120 minutes as intermediate goals. Pre and post implementation median DIDO times for all hospitals were 117 and 139 minutes (p = 0.02), for HHC hospitals 115 and 137 minutes (p = 0.027) and for non-HHC hospitals 118 and 140.5 minutes (p = 0.423). Of the pre-implementation group, 7.8% had CTP imaging prior to transfer compared with 9.3% post. Extended times post-implementation include factors such as complex decision making, patient eligibility or hospital capacity issues. A new transfer algorithm was implemented April 2019. Future analyses will correlate DIDO with patient, stroke and treatment categories to better define delays and barriers. Relevance: A JC directive to CSCs are to develop supportive relationships with referring hospitals to facilitate efficient care. As decision making becomes more complex, the process for transfer needs to improve. DIDO goals need to be realistic to prevent secondary imaging at the CSC, i.e. the tradeoff for an extra 15 or 20 minutes should translate into shorter door to puncture times. Reducing the time to treatment may help improve patient outcomes.

scholarly journals Supporting surgeons in patient-centred complex decision-making: a qualitative analysis of the impact of a perioperative physician clinic

BMJ Open ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. e033277
Author(s):  
Clarabelle T Pham ◽  
Catherine L Gibb ◽  
Robert A Fitridge ◽  
Jon Karnon ◽  
Elizabeth Hoon
Keyword(s):  
Decision Making ◽  
High Risk ◽  
Elective Surgery ◽  
Structured Interviews ◽  
Complex Patients ◽  
Complex Decision Making ◽  
Complex Decision ◽  
Additional Value ◽  
The Impact ◽  
High Risk Clinic

ObjectivePatients with comorbidities can be referred to a physician-led high-risk clinic for medical optimisation prior to elective surgery at the discretion of the surgical consultant, but the factors that influence this referral are not well understood. The aims of this study were to understand the factors that influence a surgeon’s decision to refer a patient to the clinic, and how the clinic impacts on the management of complex patients.DesignQualitative study using theoretical thematic analysis to analyse transcribed semi-structured interviews.SettingInterviews were held in either the surgical consultant’s private office or a quiet office/room in the hospital ward.ParticipantsSeven surgical consultants who were eligible to refer patients to the clinic.ResultsWhen discussing the factors that influence a referral to the clinic, all participants initially described the optimisation of comorbidities and would then discuss with examples the challenges with managing complex patients and communicating the risks involved with having surgery. When discussing the role of the clinic, two related subthemes were dominant and focused on the management of risk in complex patients. The participants valued the involvement of the clinic in the decision-making and communication of risks to the patient.ConclusionsThe integration of the high-risk clinic in this study appears to offer additional value in supporting the decision-making process for the surgical team and patient beyond the clinical outcomes. The factors that influence a surgeon’s decision to refer a patient to the clinic appear to be driven by the aim to manage the uncertainty and risk to the patient regarding surgery and it was seen as a strategy for managing difficult and complex cases.

scholarly journals Drought Hazard Modelling of Klaten Regency Central Java Using AHP and TOPSIS Method

2021 ◽  
Vol 936 (1) ◽  
pp. 012043
Author(s):  
Meiga Nugrahani ◽  
Purnama Budi Santosa
Keyword(s):  
Decision Making ◽  
High Risk ◽  
Geographical Information Systems ◽  
Public Works ◽  
Disaster Mitigation ◽  
Geographical Information ◽  
Topsis Method ◽  
Drought Vulnerability ◽  
Central Java ◽  
The Impact

Abstract According to information of areas at high risk of drought provided by Central Java disaster risk assessment in 2016 - 2020, Klaten Regency is in the top ten at high risk of drought in Central Java. Drought is an annual disaster in this region, which usually occurs during the dry season. The impact of the drought has caused some areas to experience a lack of clean water. For the purpose of disaster mitigation in anticipating and minimizing drought disasters losses, it is necessary to analyze the level of drought with a decision-making system by comparing two methods, namely the AHP with TOPSIS. Both methods are decision-making methods that are composed of various criteria to obtain an alternative sequence of choices. Both the AHP and TOPSIS methods produces weight values and a positive ideal solution value, respectively. These are used as input data in the mapping of drought vulnerability analysis with Geographical Information Systems (GIS). The results of the analysis are visualized with a map that shows the level of drought vulnerability. AHP and TOPSIS method decision making generates the order of the drought classes in predicting the distribution of areas experiencing drought. To validate the model, the authors compare the results of the analysis of drought vulnerability of the two methods with drought data from BPBD (Local Agency for Disaster Prevention) and DPUPR (Public Works and Public Housing Department). The results show that AHP provides better results than TOPSIS based on results validation with BPBD and DPUPR data. By comparing the two models with BPBD data, the results show that the percentage of AHP suitability is higher than TOPSIS at 47,619% and 19,048% respectively.

Extended topsis method based on Pythagorean cubic fuzzy multi-criteria decision making with incomplete weight information

2020 ◽  
Vol 38 (2) ◽  
pp. 2285-2296 ◽  
Author(s):  
Muhammad Sajjad Ali Khan ◽  
Faisal Khan ◽  
Joseph Lemley ◽  
Saleem Abdullah ◽  
Fawad Hussain
Keyword(s):  
Decision Making ◽  
Multi Criteria Decision Making ◽  
Topsis Method ◽  
Incomplete Weight ◽  
Incomplete Weight Information

Examining the Impact of Training and Feedback on Visualization-Supported Decision Making under Uncertainty

2018 ◽  
Vol 62 (1) ◽  
pp. 1449-1453
Author(s):  
Jihye Song ◽  
Olivia B. Newton ◽  
Stephen M. Fiore ◽  
Jonathan Coad ◽  
Jared Clark ◽  
...  
Keyword(s):  
Decision Making ◽  
Ecological Validity ◽  
Critical Role ◽  
Decision Making Under Uncertainty ◽  
Cognitive Efficiency ◽  
Training Interventions ◽  
Complex Decision Making ◽  
Complex Decision ◽  
Task Training ◽  
The Impact

Empirical evaluations of uncertainty visualizations often employ complex experimental tasks to ensure ecological validity. However, if training for such tasks is not sufficient for naïve participants, differences in performance could be due to the visualizations or to differences in task comprehension, making interpretation of findings problematic. Research has begun to assess how training is related to performance on decision-making tasks using uncertainty visualizations. This study continues this line of research by investigating how training, in general, and feedback, in particular, affect performance on a simulated resource allocation task. Additionally, we examined how this alters metacognition and workload to produce differences in cognitive efficiency. Our results suggest that, on a complex decision-making task, training plays a critical role in performance with respect to accuracy, subjective workload, and cognitive efficiency. This study has implications for improving research on complex decision making, and for designing more efficacious training interventions to assess uncertainty visualizations.

scholarly journals Foreign direct investment in the G-20: to what extent do institutions matter?

2018 ◽  
Vol 53 (3) ◽  
pp. 404-421
Author(s):  
Jurema Tomelin ◽  
Mohamed Amal ◽  
Nelson Hein ◽  
Andreia Carpes Dani
Keyword(s):  
Decision Making ◽  
Foreign Direct Investment ◽  
Direct Investment ◽  
Global Financial Crisis ◽  
Economic Factor ◽  
Topsis Method ◽  
Firm Level ◽  
Content Type ◽  
Governance Indicators ◽  
The Impact

Purpose This study aims to identify to what extent the economic factor effect is more salient in shaping inward foreign direct investment (IFDI) than are institutional factors in G-20 inflow patterns. Design/methodology/approach Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was applied using the World Bank Governance and Development Indicators, followed by a panel data technique over the period 2005-2015 to estimate the connections between the different dimensions of economics, institutions and IFDI in the G-20. Findings Results showed that countries with better economic performance contrasting with the governance indicators are more effective at attracting IFDI. However, the correlation between FDI intensity and governance indicators has been found relatively weak, which may suggest a more controversial role of institutions as determinants of IFDI. Research limitations/implications This quantitative approach uses a country-level set of variables; therefore, the authors suggest the development of more firm-level analysis of the impact of institutions. Also, the limitation of the TOPSIS method itself is based on heuristic assumptions. Practical implications The main findings point to a relatively low impact of institutions on IFDI. The authors suggest that the global financial crisis has changed the rationale of decision-making by multinational companies. Originality/value The originality of the present study was to apply a multi criteria decision-making technique on FDI’s analysis combined with institutional data.

scholarly journals Reflections on science advisory systems in Canada

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Remi Quirion ◽  
Arthur Carty ◽  
Paul Dufour ◽  
Ramia Jabr
Keyword(s):  
Decision Making ◽  
Scientific Evidence ◽  
Scientific Development ◽  
Recent Experience ◽  
Science Advisory ◽  
Science Advice ◽  
Complex Decision Making ◽  
Solid Foundation ◽  
Advisory Systems ◽  
The Impact

Abstract As the evolution of our world has triggered complexity and technological sophistication, it is now essential to consider sound scientific evidence as an integral element of decision-making. Science advisers or chief scientists have to take into account many factors in giving advice. Depending on the nature and level of advice, factors such as the ideology of the governing body, the state of the social, economic and scientific development in the country or region, potential impacts on the health, environment and security of the community, the balance of risk and reward in various options, must all be considered. Canada has lived through a few of these issues in its recent experience with science advice and advisory systems. This article will elaborate on the impact and influence of changes in science advisory bodies at the federal and Quebec government levels and will provide a perspective on their impact. It examines the historical evolution of the advisory apparatus for science throughout Canada’s history and underscores some of their successes and failures under different regimes. The conclusion drawn in this article is that science and science advisory systems in Canada have lacked continuity and a solid foundation thus weakening efforts to enable sound science-based policy into decision-making. The article argues for a more institutionalized and pluralistic approach to ensuring that evidence and science advice can endure—both at the federal and provincial levels. In many ways, the experience with these advisory mechanisms suggests a growing need to ensure sound advice within increasingly complex decision-making as well as a demand by citizens to have scientific evidence considered more carefully in public policy and for the public interest. This article is published as part of a collection on scientific advice to governments.

scholarly journals How Does Part-Time Farming Affect Farmers’ Adoption of Conservation Agriculture in Jianghan Plain, China?

2020 ◽  
Vol 17 (16) ◽  
pp. 5983
Author(s):  
Xin Yang ◽  
Yiming Sang
Keyword(s):  
Decision Making ◽  
Conservation Agriculture ◽  
Positive Influence ◽  
Jianghan Plain ◽  
The Sustainable Development ◽  
Multivariate Logistic Model ◽  
Part Time ◽  
Complex Decision Making ◽  
Complex Decision ◽  
The Impact

Part-time farming has been suggested by scholars to play an important part in farmers’ decision making, but seldom empirical evidence has been done on the field of conservation agriculture (CA) technology adoption worldwide. Based on the field survey data of 433 farmers in Jianghan Plain, China, this paper estimate the impact of part-time farming on farmers’ adoption of CA technology by applying the multivariate logistic model. The results show that 91.92% of the farmers adopted CA technology. Part-time farming had a highly significant positive influence on the likelihood of adoption. Moreover, the impact degree increased along with the deepening of part-time farming. In addition, farmers’ adoption behaviors were affected by gender, contracted land area, economic welfare cognition and social welfare cognition. Our results help to understand farmers’ complex decision-making on farmland and to promote the sustainable development of agriculture in Jianghan Plain. A somewhat targeted approach to design policies to support technological, policy and institutional interventions to encourage farmers to engage in part-time farming are recommended, especially in areas that share similar edaphic and climatic characteristics with Jianghan Plain.

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