Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game

Probabilistic hydro-meteorological forecasts have over the last decades been used more frequently to communicate forecastuncertainty. This uncertainty is twofold, as it constitutes both an added value and a challenge for the forecaster and the user of the forecasts. Many authors have demonstrated the added (economic) value of probabilistic over deterministic forecasts across the water sector (e.g. flood protection, hydroelectric power management and navigation). However, the richness of the information is also a source of challenges for operational uses, due partially to the difficulty to transform the probability of occurrence of an event into a binary decision. This paper presents the results of a risk-based decision-making game on the topic of flood protection mitigation, called “How much are you prepared to pay for a forecast?”. The game was played at several workshops in 2015, which were attended by operational forecasters and academics working in the field of hydrometeorology. The aim of this game was to better understand the role of probabilistic forecasts in decision-making processes and their perceived value by decision-makers. Based on the participants’ willingness-to-pay for a forecast, the results of the game show that the value (or the usefulness) of a forecast depends on several factors, including the way users perceive the quality of their forecasts and link it to the perception of their own performances as decision-makers.

Shared decision-making in mental health care : a user perspective on decisional needs in community-based services

BACKGROUND: Shared decision-making (SDM) is an emergent research topic in the field of mental health care and is considered to be a central component of a recovery-oriented system. Despite the evidence suggesting the benefits of this change in the power relationship between users and practitioners, the method has not been widely implemented in clinical practice. OBJECTIVE: The objective of this study was to investigate decisional and information needs among users with mental illness as a prerequisite for the development of a decision support tool aimed at supporting SDM in community-based mental health services in Sweden. METHODS: Three semi-structured focus group interviews were conducted with 22 adult users with mental illness. The transcribed interviews were analyzed using a directed content analysis. This method was used to develop an in-depth understanding of the decisional process as well as to validate and conceptually extend Elwyn et al.'s model of SDM. RESULTS: The model Elwyn et al. have created for SDM in somatic care fits well for mental health services, both in terms of process and content. However, the results also suggest an extension of the model because decisions related to mental illness are often complex and involve a number of life domains. Issues related to social context and individual recovery point to the need for a preparation phase focused on establishing cooperation and mutual understanding as well as a clear follow-up phase that allows for feedback and adjustments to the decision-making process. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: The current study contributes to a deeper understanding of decisional and information needs among users of community-based mental health services that may reduce barriers to participation in decision-making. The results also shed light on attitudinal, relationship-based, and cognitive factors that are important to consider in adapting SDM in the mental health system.

Shared-decision making in designing new healthcare environments : ready to take off for improved quality

Background Successful implementation of new methods and models of healthcare to achieve better patient outcomes and safe, person-centered care is dependent on the physical environment of the healthcare architecture in which the healthcare is provided. Thus, decisions concerning healthcare architecture are critical because it affects people and work processes for many years and requires a long-term financial commitment from society. In this paper, we describe and suggest several strategies (critical factors) to promote shared-decision making when planning and designing new healthcare environments. Discussion This paper discusses challenges and hindrances observed in the literature and from the authors extensive experiences in the field of planning and designing healthcare environments. An overview is presented of the challenges and new approaches for a process that involves the mutual exchange of knowledge among various stakeholders. Additionally, design approaches that balance the influence of specific and local requirements with general knowledge and evidence that should be encouraged are discussed. Summary We suggest a shared-decision making and collaborative planning and design process between representatives from healthcare, construction sector and architecture based on evidence and end-users’ perspectives. If carefully and systematically applied, this approach will support and develop a framework for creating high quality healthcare environments.

A BDI-based approach for the assessment of driver's decision-making in commuter scenarios

The rapid growth of urban areas has a significant impact on traffic and transportation systems. New management policies and planning strategies are clearly necessary to cope with the more than ever limited capacity of existing road networks. The concept of Intelligent Transportation System (ITS) arises in this scenario; rather than attempting to increase road capacity by means of physical modifications to the infrastructure, the premise of ITS relies on the use of advanced communication and computer technologies to handle today’s traffic and transportation facilities. Influencing users’ behaviour patterns is a challenge that has stimulated much research in the ITS field, where human factors start gaining great importance to modelling, simulating, and assessing such an innovative approach. This work is aimed at using Multi-agent Systems (MAS) to represent the traffic and transportation systems in the light of the new performance measures brought about by ITS technologies. Agent features have good potentialities to represent those components of a system that are geographically and functionally distributed, such as most components in traffic and transportation. A BDI (beliefs, desires, and intentions) architecture is presented as an alternative to traditional models used to represent the driver behaviour within microscopic simulation allowing for an explicit representation of users’ mental states. Basic concepts of ITS and MAS are presented, as well as some application examples related to the subject. This has motivated the extension of an existing microscopic simulation framework to incorporate MAS features to enhance the representation of drivers. This way demand is generated from a population of agents as the result of their decisions on route and departure time, on a daily basis. The extended simulation model that now supports the interaction of BDI driver agents was effectively implemented, and different experiments were performed to test this approach in commuter scenarios. MAS provides a process-driven approach that fosters the easy construction of modular, robust, and scalable models, characteristics that lack in former result-driven approaches. Its abstraction premises allow for a closer association between the model and its practical implementation. Uncertainty and variability are addressed in a straightforward manner, as an easier representation of humanlike behaviours within the driver structure is provided by cognitive architectures, such as the BDI approach used in this work. This way MAS extends microscopic simulation of traffic to better address the complexity inherent in ITS technologies.

Better than my pride is your misfortune: the impact of schadenfreude on decision-making

Investigações anteriores relacionadas ao schadenfreude concentraram-se nos fatores que provocam o prazer no infortúnio do outro. A presente pesquisa tem como objetivo investigar o impacto do schadenfreude na tomada de decisão. Dois estudos (um em laboratório e uma em campo) abordam o impacto do schadenfreude em decisões realizadas no passado e no futuro em eventos desportivos. O primeiro estudo confronta sentimentos de orgulho em uma vitória do time favorito contra os sentimentos de perda schadenfreude de uma equipe rival. Os resultados mostraram que as pessoas preferiam enviar notícias sobre a vitória da equipe favorita (orgulho) ao invés da perda do time rival (schadenfreude) quando as diferenças de pontuação no jogo eram pequenas (por exemplo: time favorito 1 x 0 outro, contra, o time rival 0 x 1 favorito). No entanto, as pessoas eram mais propensas a fazer a escolha schadenfreude (por exemplo, escolher o envio de uma notícia sobre a derrota de um time rival) quando o resultado era alto (por exemplo, time favorito 5 x 0 rival, contra, time rival 0 x 5 favorito). O segundo estudo no campo examina como schadenfreude influencia a vontade de apostar contra um time rival. Para responder a esse problema, a preferência da equipe do participante é avaliada (Participantes que apoiam time alvo contra os que apoiam o rival). Uma manipulação de louvor é adicionada, tal que os consumidores vejam ou não um elogio à equipe alvo enquanto eles estão fazendo uma aposta sobre o resultado da partida. Os resultados mostram que os torcedores do time alvo não foram influenciados pela manipulação de louvor. No entanto, torcedores do time rival aumentaram sua probabilidade de aposta contra o time alvo (ou seja, mostraram um comportamento que envolve o schadenfreude) quando esta foi elogiada antes do jogo.

Winning in Brazil: how institutional voids affect the entry decision making process of foreign venture capital firms coming to Brazil

The master thesis for the achievement of the academic status master of science in international management (MPGI) will aim to solve the research question of how institutional voids affect the entry decision-making process of foreign venture capital firms coming to Brazil. This is a timely matter since in the past years there has been a sudden eruption of foreign VC involvement in Brazil. Based on the actionable framework by Khanna and Palpeu (2010) we conducted quantitative as well as qualitative research with two sets of interview partners in a two-phase analysis. We interviewed experts from VC firms, foreign VC firms based in Brazil and perspective VC firms that are looking to come to Brazil. We started with the former, derived lessons learned and analyzed how they affect the latter in reaching a decision. As we expected we found that depending on the industry that ventures are in, institutional voids can either pose an opportunity or a threat and hence attract or push away potential VC firms entering Brazil. Opportunities exist especially when exploiting institutional voids, for example through ventures in the marketplace efficiency. Threats are posed by investments in for instance hard infrastructure, where the economic, political and judicial systems as well as corruption and bureaucracy play demanding roles.

The combination of neural estimates in prediction and decision problems

In this dissertation, different ways of combining neural predictive models or neural-based forecasts are discussed. The proposed approaches consider mostly Gaussian radial basis function networks, which can be efficiently identified and estimated through recursive/adaptive methods. Two different ways of combining are explored to get a final estimate – model mixing and model synthesis –, with the aim of obtaining improvements both in terms of efficiency and effectiveness. In the context of model mixing, the usual framework for linearly combining estimates from different models is extended, to deal with the case where the forecast errors from those models are correlated. In the context of model synthesis, and to address the problems raised by heavily nonstationary time series, we propose hybrid dynamic models for more advanced time series forecasting, composed of a dynamic trend regressive model (or, even, a dynamic harmonic regressive model), and a Gaussian radial basis function network. Additionally, using the model mixing procedure, two approaches for decision-making from forecasting models are discussed and compared: either inferring decisions from combined predictive estimates, or combining prescriptive solutions derived from different forecasting models. Finally, the application of some of the models and methods proposed previously is illustrated with two case studies, based on time series from finance and from tourism.

Increase in Hippocampal Theta Oscillations during Spatial Decision Making

The processing of spatial and mnemonic information is believed to depend on hippocampal theta oscillations (5–12 Hz). However, in rats both the power and the frequency of the theta rhythm are modulated by locomotor activity, which is a major confounding factor when estimating its cognitive correlates. Previous studies have suggested that hippocampal theta oscillations support decision-making processes. In this study, we investigated to what extent spatial decision making modulates hippocampal theta oscillations when controlling for variations in locomotion speed. We recorded local field potentials from the CA1 region of rats while animals had to choose one arm to enter for reward (goal) in a four-arm radial maze. We observed prominent theta oscillations during the decision-making period of the task, which occurred in the center of the maze before animals deliberately ran through an arm toward goal location. In speed-controlled analyses, theta power and frequency were higher during the decision period when compared to either an intertrial delay period (also at the maze center), or to the period of running toward goal location. In addition, theta activity was higher during decision periods preceding correct choices than during decision periods preceding incorrect choices. Altogether, our data support a cognitive function for the hippocampal theta rhythm in spatial decision making

The influence of the scout upon the decision-making process of recruited workers in three Acromyrmex species (Formicidae : Attini)

We examined how the information communicated by a scout worker influences the plant species transported by recruited workers in Acromymex balzani, Acromyrmex rugosus, and Acromyrmex crassispinus, three species of leaf-cutting ant that have different substrate and habitat preferences. We verified that certain plant species were more likely to be transported than others and that recruitment occurs. We found that recruited workers were more likely to transport non-preferred plant species when they were recruited to these by scout workers. The results suggest that the scout worker can communicate information about plant identity to recruited workers, but that recruited workers integrate the information communicated with their own experience during the decision-making process. (C) 2004 Published by Elsevier B.V.

Decision-Making Tool for Knowledge-Based Projects in Offshore Production Systems

The development of an offshore field demands knowledge of many experts to choose the different components of an offshore production system. All the specialized parts of this knowledge are intrinsically related. The aim of this paper is to use Fuzzy Sets and knowledge-based systems to describe and formalize the phases of development of an offshore production system project, in order to share and to manage the required knowledge for carrying out a project, while at the same time proposing alternatives for the oil field configuration.

Information Visualization to support decision making in the context of distance learning: A study with VLE TelEduc

Digital data sets constitute rich sources of information, which can be extracted and evaluated applying computational tools, for example, those ones for Information Visualization. Web-based applications, such as social network environments, forums and virtual environments for Distance Learning, are good examples for such sources. The great amount of data has direct impact on processing and analysis tasks. This paper presents the computational tool Mapper, defined and implemented to use visual representations - maps, graphics and diagrams - for supporting the decision making process by analyzing data stored in Virtual Learning Environment TelEduc-Unesp. © 2012 IEEE.

Emergetic ternary diagrams: five examples for application in environmental accounting for decision-making

In a recent paper, "A combined tool for environmental scientists and decision makers: ternary diagrams and emergy accounting." [Giannettti BF, Barrella FA, Almeida CMVB. A combined tool for environment scientists and decision makers: ternary diagrams and emergy accounting. J Clean Prod, in press http://dx.doi.org/10.1016/j.jclepro.2004.09.002] Ternary diagrams were proposed as a graphical tool to assist emergy analysis. The graphical representation of the emergy accounting data makes it possible to compare processes and systems with and without ecosystem services, to evaluate improvements and to follow the system performance over time. The graphic tool is versatile and adaptable to represent products, processes, systems, countries, and different periods of time.The use and the versatility of ternary diagrams for assisting in performing emergy analyses are illustrated by means of five examples taken from the literature, which are presented and discussed. It is shown that emergetic ternary diagram's properties assist the assessment of the system of the system efficiency, its dependance upon renewable and non-renewable inputs and the environmental support for dilution and abatement of process emissions. With the aid of ternary diagrams, details such as the interaction between systems and between systems and the environment are recognized and evaluated. Such a tool for graphical analysis allows a transparent presentation of the results and can serve as an interface between emergy scientists and decision makers, provided the meaning of each line in the diagram is carefully explained and understood. (c) 2005 Elsevier Ltd. All rights reserved.

Effects of age on aerobic capacity in heart failure patients under beta-blocker therapy: Possible impact in clinical decision-making?

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Decision making in the product portfolio: methods adopted by Brazil?s innovative companies

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)