Uncertain Alternatives Research Articles

Human Rights Education: Exploring the Safety of Teachers in South African Secondary Public Schools

This paper examined the extent and nature of safety for teachers in their different school settings and further underscored the importance of safety for teachers in the school context. The current school environment is violent owing to the increasing lack of teachers’ ability to maintain order in schools due to the uncertain alternatives to corporal punishment. This creates a hostile learning environment that weakens the teachers’ position of power and prohibits them from using their authority and fulfilling their duty to provide learners with compassionate monitoring. A qualitative interpretivist research paradigm was used in this study employing Critical Emancipatory Research (CER) as a research framework. A CER framework aims to strengthen the liberating, enlightening, emancipating, and empowering democratic values of equality and justice among the researcher and the participants in the research setting. A team of four teachers, a principal, and the School Governing Body (SGB) member from each school were purposively sampled to apply the principles of PAR in Lejweleputswa District in the Free State Province in South Africa. A focused group was employed to answer the following questions: What are the perceptions of secondary school teachers regarding their safety in the school setting? To what extent does learners’ violent behaviour threaten teachers’ safety at schools? And, how can teachers be assisted to change their minds regarding Human Rights Education as a tool for peaceful education? Data was analysed thematically. The findings of this research showed that teachers do not feel safe at their workplace, they fear both learners and parents who most of the time come to humiliate them physically and emotionally in front of their learners. The study contributes to a debate on the safety of teachers in schools for professional development. Keywords: Human Rights Education, Teacher-Learner Relationships, Teachers’ Safety, Parental Involvement.

A Special Tribunal for the Crime of Aggression?

Abstract The Russian Federation is currently in the second phase of what appears to be a war of aggression against Ukraine. While Russia’s invasion is widely thought to satisfy the threshold of the crime of aggression, the routes to accountability for this crime are unclear: The International Criminal Court lacks jurisdiction and domestic courts offer an uncertain alternative. Therefore, Ukraine and a chorus of others are advocating the creation of a special tribunal. This piece explores the options as well as the arguments that speak in favour and against establishing such a special tribunal for the crime of aggression.

Assessment of uncertain alternatives for co-located aquaculture and offshore wind farm in tasmania

This study investigated a set of 36 alternatives of co-located aquaculture and an offshore wind farm in three potential sites across Tasmania. We assessed the alternatives against technological aspects, environmental aspects, and site-selection factors through the development of a Bayesian network and an influence diagram such that the uncertainties of each possible vector of consequences were effectively assessed for each alternative. We structured the consequence space as a three-level hierarchical tree and constructed the multi-attribute utility function under various independence conditions. We described in detail the assessment of the scaling constants in the multi-attribute utility function. The analysed alternatives were ranked based on the maximum expected utility rule to outline the best one. We performed one-dimensional and multi-dimensional sensitivity analyses, to test how the solution is impacted by the subjectively assessed five-dimensional utility function and showed that the constructed function is rather robust within a very wide range of values. Finally, we outlined some future aspects of development and implementation for the Bayesian-network-influence diagram based multi-attribute analysis as a decision-support system tool for offshore Blue Growth projects with different types of production systems.

Phishing for (Quantum-Like) Phools—Theory and Experimental Evidence

Quantum-like decision theory is by now a theoretically well-developed field (see e.g., Danilov, Lambert-Mogiliansky & Vergopoulos, 2018). We provide a first test of the predictions of an application of this approach to persuasion. One remarkable result entails that, in contrast to Bayesian persuasion, distraction rather than relevant information has a powerful potential to influence decision-making. We first develop a quantum decision model of choice between two uncertain alternatives. We derive the impact of persuasion by means of distractive questions and contrast them with the predictions of the Bayesian model. Next, we provide the results from a first test of the theory. We conducted an experiment where respondents choose between supporting either one of two projects to save endangered species. We tested the impact of persuasion in the form of questions related to different aspects of the uncertain value of the two projects. The experiment involved 1253 respondents divided into three groups: a control group, a first treatment group and the distraction treatment group. Our main result is that, in accordance with the predictions of quantum persuasion but in violation with the Bayesian model, distraction significantly affects decision-making. Population variables play no role. Some significant variations between subgroups are exhibited and discussed. The results of the experiment provide support for the hypothesis that the manipulability of people’s decision-making can to some extent be explained by the quantum indeterminacy of their subjective representation of reality.

Probabilistic planning of electric vehicles charging stations in an integrated electricity-transport system

One of the most important aspects of the development of Electric Vehicles (EVs) is the optimal sizing and allocation of charging stations. Due to the interactions between the electricity and transportation systems, the key features of these systems (such as traffic network characteristics, charging demands and power system constraints) should be taken into account for the optimal planning. This paper addressed the optimal sizing and allocation of the fast-charging stations in a distribution network. The traffic flow of EVs is modeled using the User Equilibrium-based Traffic Assignment Model (UETAM). Moreover, a stochastic framework is developed based on the Queuing Theory (QT) to model the load levels (EVs’ charging demand). The objective function of the problem is to minimize the annual investment cost, as well as the energy losses that are optimized through chance-constrained programming. The probabilistic aspects of the proposed problem are modeled by using the point estimation method and Gram-Charlier expansion. Furthermore, the probabilistic dominance criteria are employed in order to compare the uncertain alternatives. Finally, the simulation results are provided for both the distribution and traffic systems to illustrate the performance of the proposed problem.

A Heuristic Approach to Explore: The Value of Perfect Information

How do people choose in a dynamic stochastic environment when they face uncertainty about the return of their choices? There is a growing literature that investigates the validity of boundedly rational models in this type of environment. In this research, we contribute to this literature by proposing a new heuristic decision process called Myopic-VPI, which extends the Value of Perfect Information (VPI) idea first proposed by Howard (1966) and Dearden et al. (1998, 1999) in engineering and computer science. This approach provides an intuitive and computationally tractable way to capture the value of exploring uncertain alternatives. In our approach, a decision-maker investigates the benefits of a subset of information, which can improve her myopic decision outcome. More specifically, the Myopic-VPI approach only involves ranking the alternatives and computing a one-dimensional integration to obtain the expected future value of exploration. In terms of computational costs, we show that Myopic-VPI is very attractive compared with dynamic programming, Index Strategy, and other heuristics, although its performance in accumulated rewards is not the strongest. Using individual-level scanner data, we find evidence that Myopic-VPI is able to capture actual consumers’ choices very well compared with other models under consideration (it provides the best in-sample fit, and very competitive out-of-sample fit). Our simulation and estimation results suggest that although consumers sacrifice some accumulated rewards by adopting Myopic-VPI, it allows them to save in cognitive costs. We argue that practitioners should consider Myopic-VPI as a serious alternative “as if” consumer model because of its relatively superior empirical performance in capturing actual consumer choice, and low implementation cost.

Egalitarianism under Severe Uncertainty

In the spring of 2009, a novel strain of the H1N1 influenza virus, containing a never before witnessed combination of gene segments from human influenza, two forms of swine influenza, and avian influenza, 1 was declared a global pandemic. The UK Government had to decide whether to undertake, at a cost of £1.2 billion (USD 1.9 billion at the time, equivalent to 1 percent of that year’s health budget), an extensive set of preparatory measures, including the purchase of both antiviral medication and a novel vaccine in quantities sufficient to cover the entire UK population, or whether instead to take substantially less costly measures, which would involve having only a limited supply of these medicines and vaccines at hand.2 The possible.

Multicriteria Decision Integrated Prospective Theory Applied at Engineering Services' Company

This paper proposes a model integrates future scenario planning techniques, based on the Multicriteria Decision Aid (MCDA) approach, which can be used as a tool for attending companies' strategic planning, applying it to an engineering company services, located in the State of Rio de Janeiro, Brazil. The motivation of the studied theme is the possibility of applying MCDA techniques added to the future scenario concepts planning as a tool for strategic (and progress) planning. Thus, the usefulness of the proposed model was proven, since it enabled the manager to analyse investment alternatives in the light of the future prospecting conducted. Recent discussions suggest the use of resources in an optimized way due to the increasing scarcity. This fact makes decision-making and strategic planning based on future scenarios a complex task, since it has multiple and uncertain alternatives. A bibliographic review was performed to identify methods are more applicable to the problems. An innovative proposal is made to unite prospective with multicriteria in a compensatory problem; proposing a methodology with six steps.

Development of a scenario prospecting model with the use of multicriteria decision aiding: Importance of environmental variables

The significance of using resources optimally comes from its increasingly present scarcity, whether they are related to the environment, term, financial resources, and political or legal difficulties. This study proposes the use of prospective scenarios, considering multiple and uncertain alternatives. It can be an essential tool for the strategic planning process of organizations. The motivation of the subject studied is the possibility to contribute to the expansion of the corporate strategic planning vision and towards social welfare, related to the commitment of companies to society, since it proposes a model for prospecting scenarios supported by multicriteria decision aiding (MDA) approach, necessarily considering variables related to Corporate Social Responsibility and its nuances. As a result, it is expected to fill the identified gap, which places prospecting scenarios as an empirical tool that deals only with economics and a single future possibility. For further research the application of the model in an actual case is suggested, still raising important questions such as: is there a real contribution with the application of prospective scenarios? Is this tool applicable to any type of company? Who are the stakeholders and how do you measure the effectiveness of this tool?

Framing of Decisions: Effect on Active and Passive Risk Avoidance

ABSTRACTDecision makers intending to avoid risk in a decision situation can choose a less risky alternative (passive risk avoidance) or intervene actively in an alternative applying a risk‐defusing action (active risk avoidance). In Experiment 1 (64 participants), we compared active and passive risk defusing in two framing conditions. In the negative frame, in the uncertain alternative, a change to the worse was possible; in the positive frame, a change to an improvement was possible. Each participant decided in both framing conditions. As expected, active risk avoidance behavior for preventing a negative outcome (i.e., in the negative frame) was more likely than for promoting a positive one (i.e., in the positive frame). If decision makers did not or could not actively defuse the risk, they chose in correspondence to the classical pattern: risk avoidance in the positive frame and risk seeking in the negative one. We replicated the latter result in a second experiment (32 participants). The classical framing pattern in passive risk avoidance in both experiments is remarkable, because participants were not presented or did not search for exact probabilities. Copyright © 2014 John Wiley & Sons, Ltd.

Rapid decisions from experience

In many everyday decisions, people quickly integrate noisy samples of information to form a preference among alternatives that offer uncertain rewards. Here, we investigated this decision process using the Flash Gambling Task (FGT), in which participants made a series of choices between a certain payoff and an uncertain alternative that produced a normal distribution of payoffs. For each choice, participants experienced the distribution of payoffs via rapid samples updated every 50ms. We show that people can make these rapid decisions from experience and that the decision process is consistent with a sequential sampling process. Results also reveal a dissociation between these preferential decisions and equivalent perceptual decisions where participants had to determine which alternatives contained more dots on average. To account for this dissociation, we developed a sequential sampling rank-dependent utility model, which showed that participants in the FGT attended more to larger potential payoffs than participants in the perceptual task despite being given equivalent information. We discuss the implications of these findings in terms of computational models of preferential choice and a more complete understanding of experience-based decision making.

Compliance for uncertain inventories via probabilistic/fuzzy comparison of alternatives

A direct comparison among highly uncertain inventories of emissions is inadequate and may lead to paradoxes. This issue is of particular importance in the case of greenhouse gases. This paper reviews the methods for the comparison of uncertain inventories in the context of compliance checking. The problem is treated as a comparison of uncertain alternatives. It provides a categorization and ranking of the inventories which can induce compliance checking conditions. Two groups of techniques to compare uncertain estimates are considered in the paper: probabilistic and fuzzy approaches. They show certain similarities which are revealed and stressed throughout the paper. The group of methods most suitable for the compliance purpose is distinguished. They introduce new conditions for fulfilling compliance, depending on inventory uncertainty. These new conditions considerably change the present approach, where only the reported values of inventories are accounted for.

The Influence of Adaptation on Skewness Seeking

A large body of literature has shown that adaptation in the form of experiential learning and competitive selection can lead to risk averse behavior by individuals. Recently, however, it has been noted that this behavioral pattern is not necessarily consistent if the uncertain alternative is negatively skewed. In such a case, risk-seeking behavior can emerge. This would imply that some patterns of adaptation imply skewness-avoiding behavior. Prior studies have examined attitudes towards risk in the form of variance and skewness in a combined fashion. Using a novel approach, we separate the two concepts and investigate the attitude towards skewness implied by each of the two behavioral patterns when controlling for effects of variance. We find in our model that experiential learning indeed implies weak skewness-avoiding behavior. However, competitive selection leads to a preference for positively skewed alternatives. The results further the understanding of adaptation. Particularly, they highlight the differences between the two most prominent modes of adaptation, learning and competitive selection.

Shunning uncertainty: The neglect of learning opportunities

Financial, managerial, and medical decisions often involve alternatives whose possible outcomes have uncertain probabilities. In contrast to alternatives whose probabilities are known, these uncertain alternatives offer the benefits of learning. In repeat-choice situations, such learning brings value. If probabilities appear favorable (unfavorable), a choice can be repeated (avoided). In a series of experiments involving bets on the colors of poker chips drawn from bags, decision makers often prove to be blind to the learning opportunities offered by uncertain probabilities. They forgo significant expected payoffs when they shun uncertain alternatives in favor of known ones. Worse, when information is revealed, many make choices contrary to learning. Priming with optimal strategies offers little improvement. Such decision makers violate identified requirements for making rational decisions.

“Stormy waters ahead”: global emergence of carbapenemases

Carbapenems, once considered the last line of defense against of serious infections with Enterobacteriaceae, are threatened with extinction. The increasing isolation of carbapenem-resistant Gram-negative pathogens is forcing practitioners to rely on uncertain alternatives. As little as 5 years ago, reports of carbapenem resistance in Enterobacteriaceae, common causes of both community and healthcare-associated infections, were sporadic and primarily limited to case reports, tertiary care centers, intensive care units, and outbreak settings. Carbapenem resistance mediated by β-lactamases, or carbapenemases, has become widespread and with the paucity of reliable antimicrobials available or in development, international focus has shifted to early detection and infection control. However, as reports of Klebsiella pneumoniae carbapenemases, New Delhi metallo-β-lactamase-1, and more recently OXA-48 (oxacillinase-48) become more common and with the conveniences of travel, the assumption that infections with highly resistant Gram-negative pathogens are limited to the infirmed and the heavily antibiotic and healthcare exposed are quickly being dispelled. Herein, we provide a status report describing the increasing challenges clinicians are facing and forecast the “stormy waters” ahead.

Sustaining inertia?

PurposeHumans tend to rely on beliefs, assumptions and cognitive rules‐of‐thumb for making judgments and are biased against taking more uncertain alternatives. Such inertia has implications for client organizations' decision making about innovations, which are inherently more uncertain than conventional alternatives. The purpose of this paper is to contribute to furthering the understanding of barriers to overcoming inertia in client decision making in new‐build.Design/methodology/approachA descriptive behavioural decision‐making perspective is combined with an organizational information‐processing perspective. To identify and discuss individual and organizational barriers that potentially distort clients' decision making on innovation, the analysis addresses aggregated data from four studies. The analysis focuses on inferences and interpretations made by decision makers in Swedish client organizations, their information‐processing practices and the subsequent impacts on perceived meanings and judgments about industrialized multi‐storey, timber‐framed building innovations, which are perceived by Swedish clients as new and different building alternatives.FindingsCognitive and organizational barriers maintain status‐quo decisions. Clients are inclined to make biased judgments about industrialized‐building alternatives because non‐applicable cognitive rules‐of‐thumb, based on their experiences of conventional‐building alternatives, are used. Furthermore, client organizations' information‐processing practices do not allow different meanings to surface, interact and potentially suggest different conclusions, at odds with established beliefs.Originality/valueThe paper's conclusions highlight how inertia is sustained in client decision making in new‐build. They illustrate the limitations of a common engineering approach, i.e. supporting decision making about innovations by focusing on providing more information to the decision maker in order to reduce uncertainty, as well as managing multiple meanings by reductionism.

Research on the Method of Equipment Maintenance Support Simulation Experiment Based on Exploratory Analysis

Aiming at the character of complexity and uncertainty on equipment maintenance support system, a method named equipment maintenance support simulation experiment was brought forward to study maintenance support problem based on exploratory analysis, which was applied to support decision-making about uncertain support scheme alternatives. The main characteristics of EMSSE were analyzed in detail, and the working flow was designed. Finally, in an example about warship maintenance support system simulation model which was set up, the optimal scheme of various storehouse inventory distributions for spare part was gotten. The optimization result was consistent with the basic principle under the three-echelon maintenance support pattern, and validates that EMSSE is feasible and reasonable to supply uncertain decision assistance for equipment support.

Research on Warship Maintenance Support Simulation System Based on the Method of Equipment Maintenance Support Simulation Experiment

Equipment maintenance support simulation experiment (EMSSE) is a method of studying maintenance support problem about decision-making about uncertain support scheme alternatives. Aiming at the character of complexity and uncertainty on the warship equipment maintenance support system, a type of structure applied to the warship equipment maintenance support simulation system was brought forward to support EMSSE based on the functional demand of system, and the interface layer, running-time layer, and data layer were analyzed in detail , and the executing process was designed. Finally, a warship maintenance support simulation system (WMSSS) which was developed and realized based on system design, which was used to make an experiment. The result of simulation experiment validates that WMSSS is feasible and reasonable to supply uncertain decision assistance for warship maintenance equipment support.

Behavioral assumptions for a class of utility theories: A program of experiments

An outline is given of the behavioral properties (axioms) that have been proposed, and to some extent empirically evaluated, concerning uncertain (often risky) alternatives, the joint receipt of alternatives, and possible linking properties. Recent theoretical work has established the existence of three inherently distinct risk types of people—risk seeking, risk neutral, and risk averse—and so evaluations of theories must take respondent type into account. A program of experiments is sketched making clear exactly which empirical studies need to be repeated with respondents partitioned by risk type.

Cumulative distribution functions, p-boxes and decisions under risk

Our concern is with the problem of decision making in the face of incomplete or imprecise probabilistic information. We particularly focus on the use of the Cumulative Distribution Function (CDF) and the related idea of a p-box. After first describing the CDF we consider the problem of choosing between two uncertain alternatives based on their representation using CDFs. We introduce the idea of dominance as a primary rule for choosing between CDFs. Since this condition is often not satisfied, we provide a rule based on a comparison of the integrals of the CDF. We show how this is related to the expected value. The p-box, which is seen as an imprecise CDF, is introduced. We then consider the problem of choosing between alternatives whose payoffs are represented as p-boxes.