scholarly journals How much evidence is in evidence-based policymaking: a case study of an expert group of the European Commission

2020 ◽  
Vol 16 (1) ◽  
pp. 45-63
Author(s):  
Jean Philippe Pierre Décieux
Keyword(s):  
Decision Making ◽  
European Commission ◽  
Qualitative Content Analysis ◽  
Real Life ◽  
Evidence Based ◽  
Expert Group ◽  
Documentary Analysis ◽  
Life Problems ◽  
The Right

Knowledge co-production is a solution-oriented approach to analysing real-life problems such as making the right decision in a given scenario. The most popular examples come from evidence-based policymaking contexts. Political decisions made in this way rely on specialist expertise co-produced in organisations that can be characterised as Hybrid Fora. However, despite the rise in popularity of Hybrid Fora and evidence-based policymaking processes, there are only a few studies that analyse the influencing factors of knowledge co-production in these contexts. The case study presented here addresses this new area of research through a documentary analysis and 11 expert interviews, both analysed via qualitative content analysis. First, the study reconstructs how knowledge is produced within an Expert Group of the European Commission. Second, it reflects how the produced knowledge is de facto included as “evidence” into the decision-making processes of the relevant policy area. The results of this study show that in this expert group, pragmatic and extra-scientific criteria such as specific stakes and interests as well as the group hierarchy controlled the process of knowledge co-production. Moreover, it also seems that knowledge produced by the interaction of experts within the examined Expert Group has a more symbolic, policy-orientated function, rather than being specifically used as decision-making evidence.

scholarly journals Desenvolvimento e Avaliação de uma Plataforma Colaborativa Digital para Educação e Tomada de Decisão Médica Baseada em Evidências

2019 ◽  
Vol 43 (1 suppl 1) ◽  
pp. 513-524
Author(s):  
Álisson Oliveira dos Santos ◽  
Alexandre Sztajnberg ◽  
Tales Mota Machado ◽  
Daniel Magalhães Nobre ◽  
Adriano Neves de Paula e Souza ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Clinical Decision Making ◽  
Real Life ◽  
Evaluation Process ◽  
Clinical Decision ◽  
Medical Decision ◽  
Alternative Form ◽  
Evidence Based ◽  
Life Problems

ABSTRACT The medical education for clinical decision-making has undergone changes in recent years. Previously supported by printed material, problem solving in clinical practice has recently been aided by digital tools known as summaries platforms. Doctors and medical students have been using such tools from questions found in practice scenarios. These platforms have the advantage of high-quality, evidence-based and always up-to-date content. Its popularization was mainly due to the rise of the internet use and, more recently, of mobile devices such as tablets and smartphones, facilitating their use in clinical practice. Despite this platform is widely available, the most of them actually present several access barriers as costs, foreign language and not be able to Brazilian epidemiology. A free national platform of evidence-based medical summaries was proposed, using the crowdsourcing concept to resolve those barriers. Furthermore, concepts of gamification and content evaluation were implemented. Also, there is the possibility of evaluation by the users, who assigns note for each content created. The platform was built with modern technological tools and made available for web and mobile application. After development, an evaluation process was conducted by researchers to attest to the valid of content, usability, and user satisfying. Consolidated questionnaires and evaluation tools by the literature were applied. The process of developing the digital platform fostered interdisciplinarity, from the involvement of medical and information technology professionals. The work also allowed the reflection on the innovative educational processes, in which the learning from real life problems and the construction of knowledge in a collaborative way are integrated. The assessment results suggest that platform can be real alternative form the evidence-based medical decision-making.

scholarly journals ACO with Intuitionistic Fuzzy Pheromone Updating Applied on Multiple-Constraint Knapsack Problem

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1456
Author(s):  
Stefka Fidanova ◽  
Krassimir Todorov Atanassov
Keyword(s):  
Decision Making ◽  
Knapsack Problem ◽  
Propositional Logic ◽  
Optimization Problems ◽  
Real Life ◽  
Combinatorial Optimization Problems ◽  
Intuitionistic Fuzzy ◽  
Life Problems ◽  
Multiple Constraint

Some of industrial and real life problems are difficult to be solved by traditional methods, because they need exponential number of calculations. As an example, we can mention decision-making problems. They can be defined as optimization problems. Ant Colony Optimization (ACO) is between the best methods, that solves combinatorial optimization problems. The method mimics behavior of the ants in the nature, when they look for a food. One of the algorithm parameters is called pheromone, and it is updated every iteration according quality of the achieved solutions. The intuitionistic fuzzy (propositional) logic was introduced as an extension of Zadeh’s fuzzy logic. In it, each proposition is estimated by two values: degree of validity and degree of non-validity. In this paper, we propose two variants of intuitionistic fuzzy pheromone updating. We apply our ideas on Multiple-Constraint Knapsack Problem (MKP) and compare achieved results with traditional ACO.

What is a Culture of Evidence? How do you Get One? and … Should you Want One?

2014 ◽  
Vol 116 (3) ◽  
pp. 1-27 ◽  
Author(s):  
Charles A. Peck ◽  
Morva A. Mcdonald
Keyword(s):  
Decision Making ◽  
Teacher Education ◽  
Organizational Factors ◽  
Outcome Data ◽  
Evidence Based ◽  
Retrospective Case ◽  
Large Measure ◽  
Culture Of Evidence ◽  
Evidence Based Decision Making

Background/Context Contemporary state and national policy rhetoric reflects increased press for “evidence-based” decision making within programs of teacher education, including admonitions that programs develop a “culture of evidence” in making decisions regarding policy and practice. Recent case study reports suggest that evidence-based decision making in teacher education involves far more than access to data—including a complex interplay of motivational, technical, and organizational factors. Purpose In this paper we use a framework derived from Cultural Historical Activity Theory to describe changes in organizational practice within two teacher education programs as they began to use new sources of outcome data to make decisions about program design, curriculum and instruction. Research Design We use a retrospective case study approach, drawing on interviews, observations and documents collected in two university programs undergoing evidence-based renewal. Conclusions We argue for the value of a CHAT perspective as a tool for clarifying linkages between the highly abstract and rhetorically charged concept of a “culture of evidence” and concrete organizational practices in teacher education. We conclude that the meaning of a “culture of evidence” depends in large measure on the motivations underlying its development.

Introduction and Historical Background

2019 ◽  
pp. 1-26
Keyword(s):  
Decision Making ◽  
Historical Development ◽  
Real Life ◽  
Literature Survey ◽  
Historical Background ◽  
Simultaneous Occurrence ◽  
Special Interests ◽  
Life Problems ◽  
Complex Decision Making ◽  
Complex Decision

This chapter describes the evolution of different multi-objective decision-making (MODM) models with their historical backgrounds. Starting from MODM models in deterministic environments along with various solution techniques, the chapter presents how different kinds of uncertainties may be associated with such decision-making models. Among several types of uncertainties, it has been found that probabilistic and possibilistic uncertainties are of special interests. A brief literature survey on different existing methods to solve those types of uncertainties, independently, is discussed and focuses on the need of considering simultaneous occurrence of those types of uncertainties in MODM contexts. Finally, a bibliographic survey on several approaches for MODM under hybrid fuzzy environments has been presented. Through this chapter the readers can be able to get some concepts about the historical development of MODM models in hybrid fuzzy environments and their importance in solving various real-life problems in the current complex decision-making arena.

An integrated machine learning: Utility theory framework for real-time predictive maintenance in pumping systems

2020 ◽  
pp. 095440542097051
Author(s):  
Raghad M Khorsheed ◽  
Omer Faruk Beyca
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Utility Theory ◽  
Predictive Maintenance ◽  
Manufacturing Operations ◽  
Pumping Stations ◽  
Bearing Failures ◽  
Temperature Levels ◽  
The Right

Bearings are the most widely used mechanical parts in rotating machinery under high load and high rotational speeds. Operating continuously under such harsh conditions, wear and failure are imminent. Developing defects give rise to even-higher vibration and temperature levels. In general, mechanical defects in a machine cause high vibration levels. Therefore, bearing fault identification and early detection enables the maintenance team to repair the problem before it triggers catastrophic failure in the bearing. Machine downtime is thus avoided or minimized. This paper explores the use of Machine Learning (ML) integrated with decision-making techniques to predict possible bearing failures and improve the overall manufacturing operations by applying the correct maintenance actions at the right time. The accuracy of the Predictive Maintenance (PdM) module has been tested on real industrial production datasets. The paper proposes an effective PdM methodology using different ML algorithms to detect failures before they happen and reduce pump downtime. The performance of the tested ML algorithms is based on five performance indicators: accuracy, precision, F-score, recall, and an area under curve (AUC). Experimental results revealed that all tested ML algorithms are successful and effective. Furthermore, decision making with utility theory has been employed to exploit the probability of failures and thus help to perform the appropriate maintenance interventions. This provides a logical framework for decision-makers to identify the optimum action with the maximum expected benefit. As a case study, the model is applied on forwarding pumping stations belonging to the Sewerage Treatment Company (STC), one of the largest sewage stations in Qatar.

scholarly journals A Novel Hybrid Fuzzy Grey TOPSIS Method: Supplier Evaluation of a Collaborative Manufacturing Enterprise

2019 ◽  
Vol 9 (18) ◽  
pp. 3770 ◽  
Author(s):  
Yixiong Feng ◽  
Zhifeng Zhang ◽  
Guangdong Tian ◽  
Amir Mohammad Fathollahi-Fard ◽  
Nannan Hao ◽  
...  
Keyword(s):  
Decision Making ◽  
Comprehensive Evaluation ◽  
Real Life ◽  
Fuzzy Topsis ◽  
Supplier Evaluation ◽  
Manufacturing Enterprise ◽  
Collaborative Manufacturing ◽  
Life Problems ◽  
Order Preference ◽  
The Difference

Recently, there is of significant interest in developing multi-criteria decision making (MCDM) techniques with large applications for real-life problems. Making a reasonable and accurate decision on MCDM problems can help develop enterprises better. The existing MCDM methods, such as the grey comprehensive evaluation (GCE) method and the technique for order preference by similarity to an ideal solution (TOPSIS), have their one-sidedness and shortcomings. They neither consider the difference of shape and the distance of the evaluation sequence of alternatives simultaneously nor deal with the interaction that universally exists among criteria. Furthermore, some enterprises cannot consult the best professional expert, which leads to inappropriate decisions. These reasons motivate us to contribute a novel hybrid MCDM technique called the grey fuzzy TOPSIS (FGT). It applies fuzzy measures and fuzzy integral to express and integrate the interaction among criteria, respectively. Fuzzy numbers are employed to help the experts to make more reasonable and accurate evaluations. The GCE method and the TOPSIS are combined to improve their one-sidedness. A case study of supplier evaluation of a collaborative manufacturing enterprise verifies the effectiveness of the hybrid method. The evaluation result of different methods shows that the proposed approach overcomes the shortcomings of GCE and TOPSIS. The proposed hybrid decision-making model provides a more accurate and reliable method for evaluating the fuzzy system MCDM problems with interaction criteria.

scholarly journals Outsourcing energy retrofitting of hotel buildings: the decision-making process

2019 ◽  
Vol 266 ◽  
pp. 01016 ◽  
Author(s):  
M.F.F. Fasna ◽  
Sachie Gunatilake
Keyword(s):  
Decision Making ◽  
Energy Performance ◽  
Decision Making Process ◽  
Existing Buildings ◽  
Energy Retrofit ◽  
Energy Efficiency Improvement ◽  
Adoption And Implementation ◽  
Energy Service ◽  
The Right

Poor energy performance of existing buildings worldwide has led to a crucial need to retrofit existing buildings to minimise energy consumption. Among the existing buildings, hotels use as much as 50% of their total expenses on energy and offer significant opportunities for energy efficiency improvement. Yet, comparatively the level of implementation of energy retrofits found to be low, which has attributed to, inter alia, the absence of a clearly defined process for ensuring the delivery of energy retrofit projects and lack of proactive guidance for project teams to ensure that they make the right decisions at the right time to achieve the desired outcomes. Since many energy retrofit projects in existing hotels are carried out with the involvement of an external contractor, or an Energy Service Company (ESCO), this study focuses on investigating the decision-making process in implementing energy retrofits when the project is outsourced to an external party. An in-depth case study is used to obtain insights into the critical decisions to be taken and key activities to be performed throughout the decision-making process. The findings are used to propose a step-by-step decision-making process comprising of three key phases: i.e., pre-retrofit, retrofit implementation and post-retrofit. It is hoped that the decision-making process developed in this study will serve as a roadmap for the effective adoption and implementation of energy retrofits in existing hotel buildings when an external contractor is involved.

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