EURO Journal on Decision Processes最新文献

An experiment was set up to determine whether some short, focused training could influence decision makers to take a more structured and process-based approach to project decision-making. The experiment also investigated the impact on project decision-making of the way a decision is framed by an authority figure, i.e. how a decision is influenced by an authority figure advocating a process-driven, neutral or an opinion/schedule-driven approach. The experiment was set up so that half of the participants watched three 15-min training videos before answering questions on decision-making scenarios for projects, and the other half just answered questions on the decision-making scenarios. 40% of participants (split across those who watched the training videos and those that only answered the decision-making scenario questions) had undergone some prior training on decision making. The results demonstrate that watching the training videos has an impact. The impact is greater when there has been no prior training; however, there is still impact in each case, albeit small for some. This implies that the benefits of 1 h of training prior to project decision-making is more valuable for those with no prior training, but still worthwhile for those with prior training. The results showed that framing by an authority figure has a strong influence on the participants’ responses, in terms of whether a process-based, neutral or opinion/intuition-based response was given.

With the proliferation of information and communication technologies, especially with recent developments in Artificial Intelligence, social robots at home and the workplace are no longer being treated as lifeless and emotionless, leading to proposals which aim at incorporating affective elements within agents. Advances in areas such as affective decision-making and affective computing drive this interest. Our motivation in this paper is to use affection as a basic element within a decision-making process to facilitate robotic agents providing more seemingly human responses. We use earlier research in cognitive science and psychology to provide a model for an autonomous agent that makes decisions partly influenced by affective factors when interacting with humans and other agents. The factors included are emotions, mood, personality traits, and activation sets in relation with impulsive behavior. We describe several simulations with our model to study and compare its performance when facing various types of users. Through them, we essentially showcase that our model allows for a powerful agent design mechanism regulating its behavior and provides greater decision-making adaptivity when compared to emotionless agents and simpler emotional models. We conclude describing potential uses of our model in several application areas.

This paper analyzes the labor–employer relations during conditions that lead to strike using an evolutionary game and catastrophe theory. During a threat to strike, the employers may accept the whole or only a part of the demands of labors and improve the work conditions or decline the demands, and each selected strategies has its respective costs and benefits. The threat to strike action causes the formation of a game between the strikers and employers that in which, as time goes on, different strategies are evaluated by the players and the effective variables of strike faced gradual and continuous changes, which can lead to a sudden jump of the variables and push the system to very different conditions such as dramatic increase or decrease in the probability of selecting strategies. So the alliance between labors could suffer or reinforce. This discrete sudden change is called catastrophe. In this study after finding evolutionary stable strategies for each player, the catastrophe threshold analyzed by nonlinear evolutionary game and the managerial insight is proposed to employers to prevent the parameters from crossing the border of the catastrophe set that leads to a general strike.

In this paper, we analyze and discuss the optimization challenges and opportunities raised by the decision of building an automated clinical laboratory in a hospital unit. We first describe the general decision setting from a strategic, tactical and operational perspective. We then focus on the analysis of a practical case, i.e., the Central Laboratory of a large urban academic teaching hospital in the North of Italy, the ‘Spedali Civili’ in Brescia. We will describe the present situation and the research opportunities related to the study of possible improvements of the management of the laboratory.

The objective of the present work is twofold. First, Pythagorean fuzzy ordered weighted averaging (PFOWA) aggregation operator is introduced along with its desirable properties, namely commutatively, idempotency, boundedness and monotonicity. Finally, the proposed operator is applied to decision making problems to show the validity, practicality and effectiveness of the new approach. The main advantage of using the proposed method is that this method gives more accurate results as compared to the existing methods.

Resilience management aims to increase the ability of the system to respond to adverse events. In this study, we develop and apply a structured framework for assessing the resilience of the decision-making process related to reservoir (or lake) regulation with the resilience matrix approach. Our study area is Finland, where the initiatives for the regulation have typically been hydro power production or flood prevention, but nowadays recreational and environmental issues are also increasingly considered. The main objectives of this study are twofold. First, it aims to provide support for reservoir operators and supervisors of the water course regulation projects in their work for identifying the possible threats and actions to diminish their consequences. Second, it studies the applicability of the resilience matrix approach in a quite specifically defined operational process, as most of the earlier applications have focused on a more general context. Our resilience matrix was developed in close co-operation with reservoir operators and supervisors of regulation by means of two workshops and a survey. For the practical application of the matrix, we created an evaluation form for assessing the resilience of a single dam operation process and for evaluating the cost efficiency of the actions identified to improve the resilience. The approach was tested on a dam controlling the water level of a middle-sized lake, where it proved to be a competent way to systematically assess resilience.

Transport decision processes have traditionally applied cost–benefit analysis (CBA) with benefits mainly relating to time-savings, and costs relating to infrastructure and maintenance costs. However, a shift toward more sustainable practices was initiated over the last decades to remedy the many negative impacts of automobility. As a result, decision processes related to transport projects have become more complex due to the multidimensional aspects and to the variety of stakeholders involved, often with conflicting points of view. To support rigourous decision-making, multicriteria decision analysis (MCDA) is, in addition to CBA, often used by governments and cities. However, there is still no consensus in the transport field regarding a preferred method that can integrate sustainability principles. This paper presents a descriptive literature review related to MCDA and CBA in the field of transport. Among the 66 considered papers, we identified the perceived strengths and weaknesses of CBA and MCDA, the different ways to combine them and the ability of each method to support sustainable transport decision processes. We further analysed the results based on four types of rationality (objectivist, conformist, adjustive, and reflexive). Our results show that both methods can help improve the decision processes and that, depending on the rationality adopted, the perceived strengths and weaknesses of MCDA and CBA can vary. Nonetheless, we observe that by adopting a more global and holistic perspective and by facilitating the inclusion of a participative process, MCDA, or a combination of both methods, emerge as the more promising appraisal methods for sustainable transport.

Our society is facing serious environmental challenges related to climate change, pollution, diminishing resources, and biodiversity loss. Such problems are often ill-defined and are characterized by high uncertainty. Environmental decisions have strong impacts on society and demand clear and transparent trade-offs across values and priorities of stakeholder groups. This Feature Issue on Environmental Decisions includes papers focused on important environmental applications approached through various disciplinary backgrounds. The papers highlight advanced–often interdisciplinary–methodological approaches and include the perspectives of different stakeholders in the process of environmental decision-making. A wide range of methods are explored, ranging from a comprehensive review (for sustainable transport by Marleau Donais et al.) to an opinion paper proposing the use of Records of Engagement and Decision-making (RoED; by Cockerill et al.). Stakeholder engagement and preference elicitation required the development of new aggregation models for Multi-Criteria Decision Analysis (MCDA; by Reichert et al.). The integration of Cost-Benefit Analysis (CBA) with MCDA was found to be necessary in practice (by Liu et al.; Marleau Donais et al.). MCDA was extended to include the spatial dimension by integrating Geographic Information Systems (GIS; by Guay et al.; Schito et al.). The importance of considering the resilience of systems to better respond to and recover from unpredictable risks was emphasized (by Leyerer et al.; Mustajoki and Marttunen). These papers demonstrate the richness of approaches to environmental decision-making. Environmental issues offer ample exciting research opportunities to a broader scientific community. We encourage the readers of this Feature Issue—and of EJDP—to engage in environmental decision-making projects to support emerging societal needs.

We propose creating and maintaining records of engagement and decision-making (RoED) to help us and our communities better understand ourselves, our goals, our decisions, and the dynamic systems in which we all live. The purpose of RoED is to go well beyond noting that dialogue occurred or a decision was reached. The records should, in ways appropriate to the context and participants, document interactions and note biases, beliefs, emotions, behaviors, norms, and values. These crucial aspects are generally absent in academic papers and formal reports, yet they always play a role in decision-making processes. While not a panacea for addressing critical biophysical and social challenges, we propose that a comprehensive framework for promoting realistic, legitimate and inclusive engagement could enhance trust, establish institutional memory, and when and where appropriate, ensure greater transparency. The aim is to create and maintain RoED to collect significant information and share insights from multi-stakeholder decision-making processes from diverse institutions, contexts, and disciplinary domains. In the long-term RoED could promote more effective adaptive management or governance approaches. This paper describes an exploratory phase intended to catalyze collaborative efforts worldwide.

Decisions about urban space and especially regarding power transmission lines are of great public interest, because their visibility affects citizens for decades. With citizens’ increasing awareness, they expect to be transparently informed, their concerns to be taken seriously and that decision-makers base their decisions rationally on facts and laws. In this paper, we present a 3D Decision Support System (3D DSS) that tackles this issue and allows decision-makers to find an optimal transmission line corridor on such rational basis and by considering stakeholder’s preferences regarding multiple criteria. We examined its reliability regarding the ability of predicting transmission line corridors realistically—as stakeholders would expect them—by carrying out a study in central Switzerland with 10 grid planning experts and government representatives. Moreover, we investigated the extent to which graphic representations may support decision-makers firstly in evaluating a transmission line corridor modeled by the 3D DSS, secondly in considering and improving a human-defined scenario for transmission line planning, and thirdly in changing their opinion about a human-defined path. For this, a questionnaire was statistically evaluated by means of exploratory analysis, correlation analysis, and regression analysis. The results on the investigated visual analytics approach showed that it supports the evaluation of the corridor modeled by the 3D DSS as well as of the scenario defined by the stakeholders. As our new approach allows stakeholders to evaluate a transmission line path they consider to be optimal for land and population, it has a high potential for supporting rational group decision-making when considering different opinions.