761 resultados para Decision Making Support


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This article extends the traditions of style-based criticism through an encounter with the insights that can be gained from engaging with filmmakers at work. By bringing into relationship two things normally thought of as separate: production history and disinterested critical analysis, the discussion aims to extend the subjects which criticism can appreciate as well as providing some insights on the creative process. Drawing on close analysis, on observations made during fieldwork and on access to earlier cuts of the film, this article looks at a range of interrelated decision-making anchored by the reading of a particular sequence. The article examines changes the film underwent in the different stages of production, and some of the inventions deployed to ensure key themes and ideas remained in play, as other elements changed. It draws conclusions which reveal perspectives on the filmmaking process, on collaboration, and on the creative response to material realities. The article reveals elements of the complexity of the process of the construction of image and soundtrack, and extends the range of filmmakers’ choices which are part of a critical dialogue. Has a relationship to ‘Sleeping with half open eyes: dreams and realities in The Cry of the Owl’, Movie: A Journal of Film Criticism, 1, (2010) which provides a broader interpretative context for the enquiry.

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Demands for thermal comfort, better indoor air quality together with lower environmental impacts have had ascending trends in the last decade. In many circumstances, these demands could not be fully covered through the soft approach of bioclimatic design like optimisation of the building orientation and internal layout. This is mostly because of the dense urban environment and building internal energy loads. In such cases, heating, ventilation, air-conditioning and refrigeration (HVAC&R) systems make a key role to fulfill the requirements of indoor environment. Therefore, it is required to select the most proper HVAC&R system. In this study, a robust decision making approach for HVAC&R system selection is proposed. Technical performance, economic aspect and environmental impacts of 36 permutations of primary and secondary systems are taken into account to choose the most proper HVAC&R system for a case study office building. The building is a representative for the dominant form of office buildings in the UK. Dynamic performance evaluation of HVAC&R alternatives using TRNSYS package together with life cycle energy cost analysis provides a reliable basis for decision making. Six scenarios broadly cover the decision makers' attitudes on HVAC&R system selection which are analysed through Analytical Hierarchy Process (AHP). One of the significant outcomes reveals that, despite both the higher energy demand and more investment requirements associated with compound heating, cooling and power system (CCHP); this system is one of the top ranked alternatives due to the lower energy cost and C02 emissions. The sensitivity analysis reveals that in all six scenarios, the first five top ranked alternatives are not changed. Finally, the proposed approach and the results could be used by researchers and designers especially in the early stages of a design process in which all involved bodies face the lack of time, information and tools for evaluation of a variety of systems.

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This study investigates the impact of experience upon trained behaviours in real estate investment decisionmaking. In a controlled experiment design, two groups of subjects, experts and novices, conduct an evaluation and reach a decision about two investment options. Using a process‐tracing technique, each subject’s behaviour is observed and recorded. Differences between the groups are discovered in relation to some behaviour characteristics, but experience appears not to impact all behaviours. These findings are discussed in relation to the current absence of a universal normative model of real estate investment decisionmaking. In an associated component of the study, the belief that monetary compensation is needed in order to render valid results from studies such as this is tested. We find this not to be the case.

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Conventional economic theory, applied to information released by listed companies, equates ‘useful’ with ‘price-sensitive’. Stock exchange rules accordingly prohibit the selec- tive, private communication of price-sensitive information. Yet, even in the absence of such communication, UK equity fund managers routinely meet privately with the senior execu- tives of the companies in which they invest. Moreover, they consider these brief, formal and formulaic meetings to be their most important sources of investment information. In this paper we ask how that can be. Drawing on interview and observation data with fund managers and CFOs, we find evidence for three, non-mutually exclusive explanations: that the characterisation of information in conventional economic theory is too restricted, that fund managers fail to act with the rationality that conventional economic theory assumes, and/or that the primary value of the meetings for fund managers is not related to their investment decision making but to the claims of superior knowledge made to clients in marketing their active fund management expertise. Our findings suggest a disconnect between economic theory and economic policy based on that theory, as well as a corre- sponding limitation in research studies that test information-usefulness by assuming it to be synonymous with price-sensitivity. We draw implications for further research into the role of tacit knowledge in equity investment decision-making, and also into the effects of the principal–agent relationship between fund managers and their clients.

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We examined the maturation of decision-making from early adolescence to mid-adulthood using fMRI of a variant of the Iowa gambling task. We have previously shown that performance in this task relies on sensitivity to accumulating negative outcomes in ventromedial PFC and dorsolateral PFC. Here, we further formalize outcome evaluation (as driven by prediction errors [PE], using a reinforcement learning model) and examine its development. Task performance improved significantly during adolescence, stabilizing in adulthood. Performance relied on greater impact of negative compared with positive PEs, the relative impact of which matured from adolescence into adulthood. Adolescents also showed increased exploratory behavior, expressed as a propensity to shift responding between options independently of outcome quality, whereas adults showed no systematic shifting patterns. The correlation between PE representation and improved performance strengthened with age for activation in ventral and dorsal PFC, ventral striatum, and temporal and parietal cortices. There was a medial-lateral distinction in the prefrontal substrates of effective PE utilization between adults and adolescents: Increased utilization of negative PEs, a hallmark of successful performance in the task, was associated with increased activation in ventromedial PFC in adults, but decreased activation in ventrolateral PFC and striatum in adolescents. These results suggest that adults and adolescents engage qualitatively distinct neural and psychological processes during decision-making, the development of which is not exclusively dependent on reward-processing maturation.

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Currently researchers in the field of personalized recommendations bear little consideration on users' interest differences in resource attributes although resource attribute is usually one of the most important factors in determining user preferences. To solve this problem, the paper builds an evaluation model of user interest based on resource multi-attributes, proposes a modified Pearson-Compatibility multi-attribute group decision-making algorithm, and introduces an algorithm to solve the recommendation problem of k-neighbor similar users. Considering the characteristics of collaborative filtering recommendation, the paper addresses the issues on the preference differences of similar users, incomplete values, and advanced converge of the algorithm. Thus the paper realizes multi-attribute collaborative filtering. Finally, the effectiveness of the algorithm is proved by an experiment of collaborative recommendation among multi-users based on virtual environment. The experimental results show that the algorithm has a high accuracy on predicting target users' attribute preferences and has a strong anti-interference ability on deviation and incomplete values.

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We systematically explore decision situations in which a decision maker bears responsibility for somebody else's outcomes as well as for her own in situations of payoff equality. In the gain domain we confirm the intuition that being responsible for somebody else's payoffs increases risk aversion. This is however not attributable to a 'cautious shift' as often thought. Indeed, looking at risk attitudes in the loss domain, we find an increase in risk seeking under responsibility. This raises issues about the nature of various decision biases under risk, and to what extent changed behavior under responsibility may depend on a social norm of caution in situations of responsibility versus naive corrections from perceived biases. To further explore this issue, we designed a second experiment to explore risk-taking behavior for gain prospects offering very small or very large probabilities of winning. For large probabilities, we find increased risk aversion, thus confirming our earlier finding. For small probabilities however, we find an increase of risk seeking under conditions of responsibility. The latter finding thus discredits hypotheses of a social rule dictating caution under responsibility, and can be explained through flexible self-correction models predicting an accentuation of the fourfold pattern of risk attitudes predicted by prospect theory. An additional accountability mechanism does not change risk behavior, except for mixed prospects, in which it reduces loss aversion. This indicates that loss aversion is of a fundamentally different nature than probability weighting or utility curvature. Implications for debiasing are discussed.

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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.

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This study surveys parents with children who are deaf or hard of hearing from one private school in St. Louis, Missouri. The issue of stress and time pressure on decision making is addressed and the importance of how stress and time pressure effect parents’ decisions regarding their children who are deaf and hard of hearing.

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Dissertação apresentada ao Programa de Pós-graduação em Administração - Mestrado da Universidade Municipal de São Caetano do Sul

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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.

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Vague words and expressions are present throughout the standards that comprise the accounting and auditing professions. Vagueness is considered to be a significant source of inexactness in many accounting decision problems and many authors have argued that the neglect of this issue may cause accounting information to be less useful. On the other hand, we can assume that the use of vague terms in accounting standards is inherent to principle based standards (different from rule based standards) and that to avoid vague terms, standard setters would have to incur excessive transaction costs. Auditors are required to exercise their own professional judgment throughout the audit process and it has been argued that the inherent vagueness in accounting standards may influence their decision making processes. The main objective of this paper is to analyze the decision making process of auditors and to investigate whether vague accounting standards create a problem for the decision making process of auditors, or lead to a better outcome. This paper makes the argument that vague standards prompt the use of System 2 type processing by auditors, allowing more comprehensive analytical thinking; therefore, reducing the biases associated with System 1 heuristic processing. If our argument is valid, the repercussions of vague accounting standards are not as negative as presented in previous literature, instead they are positive.